BIOLOGICAL processes are governed through specific interactions of macromolecules. The three-dimensional structural information of the macromolecules is necessary to understand the basis of molecular recognition. A large number of protein structures have been determined at a high resolution using various experimental techniques such as X-ray crystallography, NMR, electron microscopy and made publicly available through the Protein Data Bank. In the recent years, comprehending function by studying a large number of related proteins is proving to be very fruitful for understanding their biological role and gaining mechanistic insights into molecular recognition. Availability of large-scale structural data has indeed made this task of predicting the protein function from three-dimensional structure, feasible. Structural bioinformatics, a branch of bioinformatics, has evolved into a separate discipline to rationalize and classify the information present in three-dimensional structures and derive meaningful biological insights. This has provided a better understanding of biological processes at a higher resolution in several cases. Most of the structural bioinformatics approaches so far, have focused on fold-level analysis of proteins and their relationship to sequences. It has long been recognized that sequence-fold or fold-function relationships are highly complex. Information on one aspect cannot be readily extrapolated to the other. To a significant extent, this can be overcome by understanding similarities in proteins by comparing their binding site structures. In this thesis, the primary focus is on analyzing the small-molecule ligand binding sites in protein structures, as most of the biological processes ranging from enzyme catalysis to complex signaling cascades are mediated through protein-ligand interactions. Moreover, given that the precise geometry and the chemical properties of the residues at the ligand binding sites dictate the molecular recognition capabilities, focusing on these sites at the structural level, is likely to yield more direct insights on protein function. The study of binding sites at the structural level poses several problems mainly because the residues at the site may be sequentially discontinuous but spatially proximal. Further, the order of the binding site residues in primary sequence, in most of cases has no significance for ligand binding. Compounding these difficulties are additional factors such as, non-uniform contribution to binding from different residues, and size-variations in binding sites even across closely related proteins. As a result, methods available to study ligand-binding sites in proteins, especially on a large-scale are limited, warranting exploration of new approaches. In the present work, new methods and tools have been developed to address some of these challenges in binding site analysis. First, a novel tool for site-based function annotation of protein structures, called PocketAnnotate was developed ( http://proline.biochem.iisc.ernet. in/pocketannotate/). PocketAnnotate, detects the putative binding sites from a given protein structure and compares them to known binding sites in PDB to derive functional annotation in terms of ligand association. Since the tool derives functional annotation at the level of binding sites, it has an advantage over other methods that solely utilize fold or sequence information. This becomes even more important for cases where there is no detectable homology with entries in existing databases, as Pocket Annotate does not depend on evolutionary based information for annotation. Second, a web-accessible tool for in silico almandine scanning mutations of binding site residues called ABS-Scan has been developed ( http://proline.biochem.iisc.ernet.in/abscan/). This tool helps in assessing the contribution of the individual residues of binding sites in the protein towards ligand recognition. All residues, one at a time, in a binding site are mutated systematically to an alanine and the ability of the corresponding mutant to bind a given ligand is analyzed. The contribution of each residue towards ligand binding is calculated through a G value derived by comparing the binding affinity to the wild-type protein-ligand complex. Third, a database called Protein-Ligand Interaction Clusters (PLIC) has been developed to identify and analyze the information of similarity across binding sites in PDB, which has been provided in the form of a web-accessible database ( http://proline.biochem.iisc.ernet/ PLIC). Protein-ligand interactions are primarily explored using three different computational approaches - (i) binding site characteristics including pocket shape, nature of residues and interaction profiles with different kinds of chemical probes, (ii) atomic contacts between protein and ligands (iii) binding energetics involved in interactions derived from scoring functions developed for docking. The information on variations in these features derived from different computational tools is also included in the database for enabling the characterization of the binding sites. As a case study to demonstrate the usefulness of these tools, they have been applied to decipher the complexity of S-adenosyl methionine interactions with the protein. Around 1,213 binding sites of SAM or SAM-like compounds could be extracted from the PLIC database. The SAM or SAM-like compounds were observed to interact with ∼18 different protein-fold types. The variations in different protein-ligand contacts across fold types were analyzed. The fold-specific interaction properties and contribution of individual residues towards SAM binding are identified. The tools developed and example analyses using them are described in Chapter 2. Chapter 3 describes a large-scale pocketome analysis from structural complexes in PDB, in an effort to characterize the known pocket space of protein-ligand interactions. Tools devel-opted as described in Chapter 2 are used for this. A set of 84,846 binding sites compiled from PDB, have been comprehensively analyzed with an objective of obtaining (a) classification of binding sites, (b) sequence-fold-site relationships among proteins, (c) a minimal set of physicochemical attributes sufficient to explain ligand recognition specificity and (d) site-type specific signatures in terms of physicochemical features. A new method to describe binding sites was developed in the form of BScIds such that the structural fold information is well captured. Binding sites and similarities among them were abstracted in the form of networks where each node represents a binding site and an edge between two nodes represents significant similarity between the sites at the structural level. Pocketome networks were constructed from the large-scale information on protein-ligand interactions in the PLIC database. The large pocketome network was then studied to derive relationships between protein folds and chemical entities they interact with. A classification of the binding pockets was achieved by analyzing the pocketome network using graph theoretical approaches combined with clustering methods. 10,858 clusters were identified from the network, each indicating a site-type. Thus, it can be said that there are about 10,858 site-types. Classification of ligand associations into specific site-types helps greatly in resolving the complex relationships by yielding specific site-type ligand associations. The observed classification was further probed to understand the basis of ligand recognition by representing the pockets through feature vectors. These features capture a wide range of physicochemical properties that can be used to derive site-type specific signatures and explore the pocket-space of protein-ligand interactions. A principal component analysis of these features reveals that binding site feature space is continuous in the entire PDB and minor changes in specific features can give rise to significant differences in ligand specificity, consequently defining their distinct functional roles. The weights were also derived for these features through the use of different information theoretic approaches to explain the multiple-specificity of protein-ligand interactions. Analysis of binding sites arising from contribution of residues from different protein fold-types revealed increasing diversity of physicochemical properties at the site, supporting the hypothesis that combination of folds could give rise to new binding sites. Given that a finer appreciation of the molecular mechanisms within the cell is possible only with the structural information, the next objective was to explore if a structural view of an entire proteome can be obtained and if a pocketome could be constructed and analyzed. With this in mind, the causative agent of tuberculosis - Mycobacterium tuberculosis (Mtb) was chosen. Mtb is also being studied in the laboratory from a systems biology perspective, which enabled exploration of how systems and the structural perspectives could be combined and applied for drug discovery. Chapters 4 to 6 describe this effort. The genome sequence of Mycobacterium tuberculosis (Mtb) H37Rv, indicates the presence of ∼4,000 protein coding genes, of which experimentally determined structures are available for ∼300 proteins. Further, advances in homology modeling methods have made it feasible to obtain structural models for many more proteins in the proteome. Chapter 4 describes the efforts for obtaining the Mtb structural proteome, through which the three-dimensional struc-tures were derived for ∼70% of the proteins in the genome. Functional annotation of each protein was derived based on fold-based functional assignments, binding-site comparisons and consequent ligand associations. PocketAnnotate, a site-based function annotation pipeline was utilized for this purpose and is described in Chapter 2. Besides these, the annotation covers detection of various sequence and sub-structural motifs and quaternary structure predictions based on the corresponding templates. The study provides a unique opportunity to obtain a global perspective of the fold distribution in the genome. The annotation indicates that cellular metabolism can be achieved with only 219 unique folds. New insights about the folds that predominate in the genome, as well as the fold-combinations that make up multi-domain proteins are also obtained. 1,728 binding pockets have been associated with ligands through binding site identification and sub-structure similarity analyses, yielding a list of ligands that can participate in various biochemical events in the mycobacterial cell. A web-accessible database MtbStructuralproteome has been developed to make the data and the analyses available to the community, ( http://proline.physics.iisc.ernet.in/Tbstructuralannotation). The resource, being one of the first to be based on structure-based functional annotations at a genome scale, is expected to be useful for better understanding of tuberculosis and for application in drug discovery. The reported annotation pipeline is fairly generic and can be applied to other genomes as well. Chapter 5 describes the characterization of the Mtb pocketome. For the structural models of the Mtb proteome described in chapter 4, a genome-scale binding site prediction exercise was carried out using three different computational methods and subsequently obtaining consensus predictions. The three methods were independent and were based on considering geometry, inter-molecular energies with probes and sequence conservations in evolutionarily related proteins respectively. In all, 13,858 consensus binding pockets were predicted in 2,877 proteins. The pocket space within Mtb was then explored through systematic all-pair comparisons of binding sites. The number of site-types within Mtb was found to be 6,584, as compared to the ∼400 structural folds and 1,831 unique sequence families. This reveals that the pocket space is larger than the sequence or fold-space, suggesting that variations at the site-level contribute significantly to functional repertoire of the organism. By comparing the pockets with the PDB sites enclosing known ligands, around 6906 binding sites were observed to exhibit significant similarity in the entire pockets to some or the other known binding site in PDB. 1,213 metabolites could be mapped onto 665 enzymes covering most of the metabolic pathways. The identified ligands serve as a predicted metabolome for unit abundances of the proteins. A list of proteins containing unique pockets is also identified. The binding pockets, similarities they share within Mtb and the ligands mapped onto them are all made available in a web-accessible database at http://proline.biochem.iisc.ernet.in/mtbpocketome/. The availability of structural information of the pocketome at a genome-scale opens up several opportunities in drug discovery. They can be directly applied for understanding mechanism of drug action, predicting adverse effects and pharmacodynamics of a drug. Moreover, it enables exploration of new ideas in drug discovery. Polypharmacology is a new concept that aims at modulating multiple drug targets through a single chemical entity. Currently, there are no established approaches to either select appropriate target sets or design polypharmacological drugs. In this study, a structural-proteomics approach is explored to first characterize the pocketome and then utilize it to identify similar binding sites. The knowledge of similarity relationships between the binding sites within the genome can be used in identifying possible polypharmacological drug targets. A pocket similarity based clustering of binding site residues resulted in identification of binding site sets, each having a theoretical potential to interact with a common ligand. A polypharmacological index was formulated to rank targets by incorporating a measure of drug ability and similarity to other pockets within the proteome. By comparing with known drug binding sites from databases such as the Drug Bank, the study has yielded a ready shortlist that includes sets of promising drug targets with polypharmacological possibilities and at the same time has identified possible drug candidates either directly for repurposing or at the least as significant lead clues that can be used to design new drug molecules against the entire group of proteins in each set. This analysis presents a rational approach to identify targets with polypharmacological potential, clues about lead compounds and a list of candidates for drug repurposing. This thesis demonstrates the feasibility of utilizing the structural bioinformatics approaches at a genome-scale. The tools developed for analyzing large-scale data on protein-ligand inter-actions could be applied to characterize the pocket-space of protein-ligand interactions. The network theory approaches applied in this work, make large-scale data tractable and enable binding-site typing. The binding site analysis at a genome-scale for Mtb is first of its kind and has provided novel insights into the pocket space. The binding site analysis performed on a genome-scale for Mtb provided an opportunity to rationalize the polypharmacological target selection and explore drugs for repurposing in TB. In the larger context, structural modelling of a proteome, mapping the small-molecule binding space in it and understanding the determinants of small-molecule recognition forms a major step in defining a proteome at higher resolution. This in turn will serve as a valuable input towards the emerging field of structural-systems biology, which seeks to understand the biological models at a systems level without compromising on the resolution of the study.

As ligações de hidrogênio (LH), fundamentais na determinação da estrutura da água, proteínas, etc., são muito importantes no reconhecimento molecular e nos mecanismos de reações enzimáticas. A determinação da energia das LHs intramoleculares em proteínas e intermoleculares entre uma proteína e o solvente água, porque fornece informações sobre a estrutura secundária, terciária e quaternária das proteínas. Um método para quantificar e qualificar as LHs foi desenvolvido utilizando critérios de distância, geométricos e energéticos a partir das trajetórias obtidas por simulações de dinâmica molecular. O método foi testado com o monômero de uma fosfolipase A2 homodimérica, sem atividade catalítica, isolada do veneno da Bothrops asper(BaspMT-II). No dímero, a análise das LHs mostrou que elas são também essenciais na manutenção da estrutura quaternária. Essa análise permitiu identificar movimentos do tipo dobradiça acompanhados da formação transitória, na interface dimérica, de LHs controladas pelo triptofano na posição 77. Esses movimentos podem estar associados à ação danosa às membranas, uma vez que podem promover a inserção da região C-terminal na membrana. Estudos prévios mostraram que o peptídeo sintético (3Y codificado pelos aminoácidos 115-129 da BaspMT-II) apresenta atividade bactericida e citolítica. Um outro peptídeo (3W), mutante de 3Y, no qual três resíduos tirosina são substituidos por triptofano, apresenta um aumento do dano às membranas e do efeito miotóxico. Os mecanismos de ação desses peptídeos e as suas estruturas foram estudados por dinâmica molecular, dicroísmo circular (DC), microscopia de fluorescência e monocamadas de Langmuir (Mlang). As adsorções dos peptídeos em monocamadas de ácido dimiristoil fosfatídico (DMPA) e dimiristoilfosfatidilcolina (DMPC) se processam por mecanismos diferentes ocasionados pelas diferentes naturezas físico-químicas dos resíduos tirosina e triptofano. A microscopia de fluorescência acoplada a Mlang de DMPA com 3W adsorvido mostra um aumento da fluidez da monocamada, enquanto que o 3Y modifica os domínios do DMPA para pequenas estruturas circulares. Foram realizadas simulações dos peptídeos 3Y e 3W em meio aquoso e nas regiões interfaciais água/n-hexano e água/bicamadas de DMPC. Os resultados confirmam os obtidos por Mlang, demonstrando que os peptídeos interagem diferentemente com as membranas por adotar conformações alternativas definidas previamente. Essas conformações, diferentes das observadas em meio aquoso, dependem da natureza da interface. As estruturas encontradas no final das simulaçoes corroboram o mecanismo proposto por Mlang, assim como as estruturas sugeridas por DC. Isso sugere que a atividade biológica reduzida do peptídeo 3Y ocorre porque os seus dois resíduos Leu se adsorvem na interface sem penetrá-la. Ao contrário de 3W, os resíduos carregados do peptídeo 3Y não estão localizados corretamente para promover uma interação suficientemente atrativa para permitir a sua inserção na membrana celular. / Hydrogen bonds (HB) are highly important in the determination of the structure of the water and proteins. They also play a important role in molecular recognition and in enzyme reaction mechanisms. The determination of protein/water intermolecular and protein intramolecular HB energies provide information with respect to the formation and stabilization of secondary, tertiary and quaternary protein structure. A method that quantifies and qualifies the properties of HB was developed using distance, geometric and energy criteria as applied to data obtained from the atomic trajectories generated by molecular dynamics simulations. The method was tested with a monomer of a catalytically inactive homodimeric phospholipase A2 from Bothrops asper(BaspMT-II) venom. HBs at dimmer interface are essential for maintaining the quaternary structure, and are highly conserved during hinge-like movements of the dimmer. HB formed by tryptophan residue at position 77 controls this movement. These motions can be associated to the membrane damaging action since they facilitate the insertion of the C-terminus into the cellular membrane. Previous studies have shown that synthetic peptide (3Y, coding the amino acids 115-129 of BaspMT-II ) presents bactericidal and cytolitic activities. A peptide variant ( 3W ), in which tyrosine residues were substituted by tryptophan residues, presents an enhanced membrane damaging activity increased miotoxic effect. The mechanism of action of the peptides and their structures were studied by molecular dynamics simulations, circular dichroism (CD), fluorescence microscopy and Langmuir monolayers (Mlang). The adsorption of the peptides on a monolayer composed of dimiristoyl phosphatidic acid (DMPA) and dimiristoylphosphatidyl choline (DMPC) occurs through different processes due to the differences in the physic-chemical nature of the tyrosine and tryptophan residues. Fluorescence microscopy together with Mlang of DMPA with adsorbed 3W indicates an increase of the membrane fluidity while small circular domains are formed with DMPA. Simulations were conducted with the 3Y and 3W peptides in aqueous media, is a water/n-hexane and water/DMPC bilayers. The results confirm the Mlang results, showing that the peptides interact differently with the membranes by adopting alternative previously defined conformations. These two conformations, both of which are different to those observed in water, are dependent of the nature of the interfaces. The final simulated configurations confirm the mechanism proposed by Mlang and the structures proposed by CD. It is suggest that the reduced biological activity of the 3Y peptide is due to the two Leu residues that only adsorb to the cellular membrane without penetrating the bilayer. In contrast to the 3W peptide, no charged residue is correctly located to promote the interaction and insertion of the 3Y peptide into the membrane.

Mycobacterium tuberculosis (M.tb), the causative agent of tuberculosis (TB), has remained the largest killer among infectious diseases for over a century. The increasing emergence of drug resistant varieties such as the multidrug resistant (MDR) and extremely drug resistant (XDR) strains are only increasing the global burden of the disease. Available statistics indicate that nearly one-third of the world’s population is infected, where the bacteria remains in the latent state but can reactivate into an actively growing stage to cause disease when the individual is immunocompromised. It is thus immensely important to rethink newer strategies for containing and combating the spread of this disease. Extraction of iron from the host cell is one of the many factors that enable the bacterium to survive in the harsh environments of the host macrophages and promote tuberculosis. Host–pathogen interactions can be interpreted as the battle of two systems, each aiming to overcome the other. From the host’s perspective, iron is essential for diverse processes such as oxygen transport, repression, detoxification and DNA synthesis. Infact, during infection, both the host and the pathogen are known to fight for the available iron, thereby influencing the outcome of the infection. It is of no surprise therefore, that many studies have investigated several components of the iron regulatory machinery of M.tb and the host. However, very few attempts have been made to study the interactions between these components and how such interactions lead to a better adapted phenotype. Such studies require exploration at multiple levels of structural and functional complexity, thereby necessitating the use of a multiscale approach. Systems biology adopts an integrated approach to study and understand the function of biological systems. It involves building large scale models based on individual biochemical interactions, followed by model validation and predictions of the system’s response to perturbations, such as a gene knock-out or exposure to drug. In multiscale modeling, an approach employed in this thesis, a particular biological phenomenon is studied at different spatiotemporal levels. Studying responses at multiple scales provides a broader picture of the communications that occur between a host and pathogen. Moreover, such an analysis also provides valuable insights into how perturbation at a particular level can elicit responses at another level and help in the identification of crucial inter-level communications that can possibly be hindered or activated for a desired physiological outcome. The broad objectives of this thesis was to obtain a comprehensive in silico understanding of mycobacterial iron homeostasis and metabolism, the influence of iron on host-pathogen interactions, identification of key players that mediate such interactions, determination of the molecular consequences of inhibiting the key players and finally the global response of M.tb to altered iron concentration. Perturbation of iron homeostasis holds a strong therapeutic potential, given its essentiality in both the host and the pathogen. Understanding the workings of iron metabolism and regulation in M.tb has been a main objective, so as to ultimately obtain insights about specific therapeutic strategies that capitalize on the criticality of iron concentration. An in-depth study of iron metabolism and regulation is performed at different levels of temporal and spatial scales using diverse methods, each appropriate to investigate biological events associated with the different scales. The specific investigations carried out in the thesis are as follows, a) Reconstruction of a host-pathogen interaction (HPI) model, with focus on iron homeostasis. This study represented the inter-cellular level analysis and was crucial for the identification of key players that mediate communication between the host and pathogen. Additionally, the model also provided a mathematical framework to study the effect of perturbations and gene knock-outs. b) Understanding the influence of iron on IdeR, an iron-responsive transcription factor, also identified as a key player in the HPI model. The study was carried out at the molecular level to identify atomistic details of how IdeR senses iron and the resulting structural modifications, which finally enables IdeR-DNA interaction. The study enabled identification of residues for the functioning of IdeR. c) Genome scale identification of genes that are regulated by IdeR to obtain an overview of the various biological processes affected by changing iron concentrations and IdeR mutation in M.tb. d) To understand the direct and indirect influences of iron and IdeR on the M.tb proteome using large scale protein-protein interaction network. The study enabled identification of highest differentially regulated genes and altered activity of the different biological processes under differing iron concentrations and regulation. e) Systems level analysis of the M.tb metabolome to investigate the metabolic re-adjustments undertaken by M.tb to adapt to altered iron concentration and regulation. The conceptual details and the background of each of the methods used to study the specific aims are provided in the Methodology chapter (Chapter 2). Construction of the host-pathogen interaction (HPI) model and the insights obtained from this study are presented in Chapter 3. A rule based HPI model was built with a focus on the iron regulatory mechanisms in both the host and pathogen. The model consisted of 194 rules, of which 4 rules represented interactions between the host and pathogen. The model not only represented an overview of iron metabolism but also allowed prediction of critical interaction that had the potential to form bottleneck in the system so as to control bacterial proliferation. Infact, model simulation led to the identification of 5 bottlenecks or chokepoints in the system, which if perturbed, could successfully interfere with the host-pathogen dynamics in favour of the host. The model also provided a framework to test perturbation strategies based on the bottlenecks. The study also established the importance of an iron responsive transcription factor, IdeR for regulating iron concentration in the pathogen and mediating host-pathogen interactions. Additionally, the importance of mycobactin and transferrin as key molecular players, involved in host-pathogen dynamics was also determined. The model provided a mathematical framework to test TB pathogenesis and provided significant insights about key molecular players and perturbation strategies that can be used to enhance therapeutic strategies. Given the importance of IdeR in HPI, its molecular mechanism of activation and dimerization was explored in Chapter 4. The main objective of the study was to explore the structural details of IdeR and its iron sensing capacity at the molecular level. A combination of molecular dynamics and protein structure network (PSN) were used to analyse IdeR monomers and dimers in the presence and absence of iron. PSNs used in this thesis are based on non-covalent interactions between sidechain atoms and are quite efficient in identifying iron induced subtle conformational variations. The study distinctly indicated the role of iron in IdeR stability. Further, it was observed that IdeR monomers can take up two major conformations, the ‘open’ and ‘close’ conformation with the iron bound structure preferring the ‘close’ conformation. Major structural changes, such as the N-terminal folding and increased propensity for dimerization were observed upon iron binding. Interestingly, careful analysis of structure suggests a role of these structural modifications towards DNA binding and has been tested in the next chapter. Overall, the results clearly highlight the influence of iron on IdeR activation and dimerization. The predisposition of IdeR to bind to DNA in the presence of metal is clearly visible even when the simulations are performed solely on protein molecules. However, to confirm the conjectures proposed in this chapter and to obtain the atomistic details of IdeR-DNA interactions, the IdeR-DNA complex was investigated. Chapter 5 focuses on the mechanistic details of IdeR-DNA interactions and the influence of iron on the same. IdeR is known to bind to a specific stretch of DNA, known as the ‘iron-box’ motif to form a dimer-of-dimer complex. Molecular dynamics followed by protein-DNA bipartite network analysis was performed on a set of four IdeR-DNA complexes to obtain a molecular level understanding of IdeR-DNA interactions. A striking observation was the dissociation of IdeR-DNA complex in the absence of iron, undoubtedly establishing the importance of iron for IdeR-DNA binding. At the residue level, hydrogen bond and non-covalent interactions clearly established the importance of N-terminal residues for DNA binding, thereby confirming the conjecture put forth in the previous chapter. An important aspect studied in this chapter is the allosteric nature of IdeR-DNA binding. Recent years have witnessed a paradigm shift in the understanding of allostery. Unlike the classical definition of allostery that was based on static structures, the newer definition is based on the conformational ensemble as represented by the shift in the energy landscape of the protein. The allosteric nature of IdeR-DNA complex was probed using simulated trajectories and indeed they suggest iron to be an allosteric regulator of the protein. Finally, based on the known experimental data and observations presented in Chapters 4 and 5, a multi-step model of IdeR activation and DNA binding has been proposed. In chapter 6, a global perspective of IdeR regulation in M.tb was obtained. This was important to gain insights about the influences of iron and its regulation at the M.tb cellular level. A genome scale identification of all possible IdeR targets based on the presence of ‘iron-box’ motif in the promoter region of the genes was carried out. An interesting aspect of this study was the use of energetic information from previous molecular dynamics study as an input for generation of the motif. A total of 255 such IdeR targets were identified and converted into an IdeR target network (IdeRnet). Along with IdeRnet, an unbiased systems level protein-protein interaction network was also generated. To study the response of the pathogen to external perturbations, iron-specific gene expression data was integrated into the network as node weights and edge weights. Analysis of IdeRnet provides interesting associations between fatty acid metabolism and IdeR regulations. Specific genes such as fadD32, DesA3 or lppW have been found to be affected by IdeR mutation. While IdeRnet discusses the direct associations, the global level responses are monitored by analysing pathways for the flow of information in the protein-protein interaction network (PPInet). Comparisons of the PPInets under conditions such as altering iron concentrations and lack of iron homeostasis led to the identification of the ‘top-most’ active paths under the different conditions. The study clearly suggests a halt in the protein synthesis machinery and decreased energy consumption under iron scarcity and an uninhibited consumption of energy when iron homeostasis is perturbed. In the final chapter (Chapter 7), flux balance analyses has been used to investigate the influence of iron on M.tb metabolism. The importance of iron for metabolic enzymes has already been established in the previous chapter. Additionally, M.tb is known to produce siderophores, an important metabolite that requires amino acids as its precursors, for iron extraction. All this, together highlighted the importance of iron and its regulation of M.tb metabolism. Flux balance analysis has been used previously to study the metabolic alterations that occur in an organism under different conditions. For this study, iron specific gene expression data was also incorporated into the model as reaction bounds and the flux values so obtained were compared in different environmental conditions. The study provided valuable insights into the metabolic adjustments taken up by M.tb under iron stress conditions and correlates well with the responses observed from the interactome as well as experimental observations. Most significantly, changes were observed in the energy preferences of the cell. For instance, it was noted that while the wild type strain of M.tb prefers synthesis of ATP via glycolysis, the IdeR mutant strain preferred oxidative phosphorylation. The picture becomes clearer when one accounts for the uncontrolled utilization of energy and rapid activation of protein synthesis machinery in the IdeR mutant strain. Biological systems are inherently multiscale in nature and therefore for a successful drug target regime, analysis of the genome to the phenome, which captures interactions at multiple levels, is essential. In this thesis, a detailed understanding of iron homeostasis and regulation in M.tb at multiple levels has been attempted. More importantly, insights obtained from one level, formed questions in the next level. The study was initiated at the inter-cellular level, where the influence of iron on HPI was modeled and analysed. From this study, IdeR, an iron-responsive transcription factor was identified as a key player that had the potential to alter host-pathogen interactions in the favour of the host. For a complete understanding of how IdeR regulates iron homeostasis, it was imperative to obtain a molecular level insight of its mechanism of action. Finally, the various aspects of IdeR regulation were investigated at the cellular level by analysing direct and indirect influences of IdeR on M.tb proteome and metabolome. The study suggests certain therapeutic interventions, such as 1) reduction in the concentration of free transferrin various, 2) mutations at the N-terminal sites of IdeR, 3) regulation of proteins involved in production of mycolic acids by iron and 4) perturbation of altering energy sources, which capitalize on iron and should be investigated in detail. In summary, the consequences of iron on TB infection were studied by threading different levels. This is based on the belief that most biological functions involve multiple spatio-temporal levels with frequent cross talks between the different levels, thereby making such multiscale approaches very useful.

The selection of the forcefield is a crucial issue in any MD related work and there is no clear indication as to which of the many available forcefields is the best for protein analysis. Many recent literature surveys indicate that MD work may be hindered by two limitations, namely conformational sampling and forcefields used (inaccuracies in the potential energy function may bias the simulation toward incorrect conformations). However, the advances in computing infrastructures, theoretical and computing aspects of MD have paved the way to carry out a sampling on a sufficiently longtime scale, putting a need for the accuracies in the forcefield. Because there are established differences in MD results when using forcefields, we have sought to ask how we could assess common mobility segments from a protein by analysis of trajectories using three forcefields in a similar environment. This is important because, disparate fluctuations appear to be more at flexible regions compared to stiff regions; in particular, flexible regions are more relevant to functional activities of the protein molecule. Therefore, we have tried to assess the similarity in the dynamics using three well-known forcefields ENCAD, CHARMM27 and AMBERFF99SB for 61 monomeric proteins and identify the properties of dynamic residues, which may be important for function. The comparison of popular forcefields with different parameterization philosophy may give hints to improve some of the currently existing agnostics in forcefields and characterization of mobile regions based on dynamics of proteins with diverse folds. These may also give some signature on the proteins at the level of dynamics in relation to function, which can be used in protein engineering studies. Nanosecond level MD simulation(30ns) on 61 monomeric proteins were carried out using CHARMM and AMBER forcefields and the trajectories with ENCAD forcefield obtained from Dynameomics database. The trajectories were first analyzed to check whether structural and dynamic properties from the three forcefields similar choosing few parameters in each case. The gross dynamic properties calculated (root mean square deviation (RMSD), TM-score derived RMSD, radius of gyration and accessible surface area) indicated similarity in many proteins. Flexibility index analysis on 17 proteins, which showed a notable difference in the flexibility, indicated that tertiary interactions (fraction of nonnative stable hydrogen bonds and salt bridges) might be responsible for the difference in the flexibility index. The normalized subspace overlap and shape overlap score taken based on the covariance matrices derived from trajectories indicated that majority of the proteins show a range between 0.3-0.5 indicating that the first principal components from these proteins in different combinations may not match well. These results indicate that although dynamic properties in general are similar in many proteins. However, flexibility index and normalized subspace overlap score indicate that subspaces on the first principal component in many proteins may not match completely. The number of proteins showing a better correlation is higher in CHARMM-AMBER combinations than the other two. The structural features from trajectories have been computed in terms of fraction of secondary structure, hydrogen bonds, salt bridges and native contacts. Although secondary structures and native contacts are well preserved during the simulations, the tertiary interactions (hydrogen bonds) are lost in many proteins and may be responsible for the difference in the some of properties among forcefields. Comparison of simulation results to experimental structures in terms of Root mean square fluctuations, Accessible surface area and radius of gyration indicates that the simulations results are on par with the ones derived from experimental structures. We have tried to assess the flexibility in the proteins using normalized Root mean square fluctuations (nRMSF), which for a residue is the ratio of RMSF from simulation to that of crystal structure. We have selected a threshold for this nRMSF to indicate the mobile regions in a protein based on secondary structure analysis. Based on the threshold of nRMSF and conformational properties (deviation in the dihedral angles), we have classified the residue and evaluated the properties of rigid hinge residues and corresponding mobile residues in terms of residue propensity, secondary structure preference and accessible surface area ranges. Since the rigid dynamic residues represent the inherent mobility, they might be important for function. Therefore, we have tried to assess the functional relevance considering the dynamic mobile residues from each protein from each forcefield simulation with the residues important for the function (taken from literature and databases). It is observed that some residues found to be mobile from the simulation are found to match with the experimental ones, although in many cases the number of these mobile residues is higher compared to the experimental ones. In summary, an analysis of protein simulation trajectories using three forcefields on a set of monomeric protein has shown that the gross structural properties and secondary structures from many proteins remain similar, but there are differences as may be seen from flexibility index. However correlation in parameters from CHARMM and AMBER force field is better compared to other two combinations. The differences seen in some of structural properties may arise mainly due to the loss of few tertiary interactions as indicated by the fraction of native hydrogen bonds and salt bridges. Based on the nRMSF, mobile segments obtained from the simulations were identified, and some of the mobile segments are found to match the functionally important residues from the experimental ones. Our work indicates that there are still some differences in the properties from the simulations, which indicates that care must be exercised when choosing a forcefield, especially assessing the functionally relevant residues from the simulations.

The conversion of the native monomeric cellular prion protein (PrPC) into an aggregated pathological β-oligomeric (PrPβ) and an infectious form (PrPSc) is the central element in the development of prion diseases. The structure of the aggregates and the molecular mechanisms of the conformational change involved in this conversion are still unknown. My research hypothesis was that a specific structural rearrangement of normal PrPC monomers leads to the formation of new inter-subunit interaction interfaces in the prion aggregates, leading to aggregation. My approach was to use constraints obtained by structural proteomic methods to create a 3D model of urea-acid induced recombinant prion oligomers (PrPβ). My hypothesis was that this model would explain the mechanism of the conformational change involved in the conversion, the early formation of the β-structure nucleation site, and would describe the mode of assembly of the subunits within the oligomer. I applied a combination of limited proteolysis, surface modification, chemical crosslinking and hydrogen/deuterium exchange (HDX) with mass spectrometry for the differential characterization of the native and the urea-acid converted prion β-oligomer structures to get an insight into the mechanism of the conversion and aggregation. Using HDX, I detected a region of the protein in which backbone amides become more protected from exchange in PrPβ compared to PrPC. In order to obtain the inter-residue distance constraints to guide the assembly of the oligomer model, I then applied zero-length and short-range crosslinking to an equimolar mixture of 14N/15N-metabolically labeled β-oligomer thereby enabling the classification of the crosslinks as either intra-protein or inter-protein. Working with the Dokholyan group at the University of North Carolina at Chapel Hill, I was able to assemble a structure of the β-oligomer based on the combination of constraints obtained from all methods. By comparing the structures before and after the conversion, I was able to deduce the conformational change, that occurs during the conversion as the rearrangement and disassembly of the beta sheet 1– helix 1 – beta sheet 2 (β1-H1-β2) region from the helix 2 – helix 3 (H2-H3) core, forming new β-sheet nucleation site and resulting in the exposure of hydrophobic residues patches leading to formation of inter-protein contacts within aggregates. / Graduate / 2018-06-14

Proteins orchestrate a number of cellular processes either alone or in concert with other biomolecules like nucleic acids, carbohydrates, and lipids. They exhibit an intrinsic ability to fold de novo to their functional states. The three–dimensional structure of a protein, dependent on its amino acid sequence, is important for its function. Understanding this sequence– structure–function relationship has become one of the primary goals in biophysics. Various experimental techniques like X–ray crystallography, Nuclear Magnetic Resonance (NMR), and site–directed mutagenesis have been used extensively towards this goal. Computational studies include mainly sequence based, and structure based approaches. The sequence based approaches such as sequence alignments, phylogenetic analysis, domain identification, statistical coupling analysis etc., aim at deriving meaningful information from the primary sequence of the protein. The structure based approaches, on the other hand, use structures of folded proteins. Recent advances in structure determination and efforts by various structural consortia have resulted in an enormous amount of structures available for analysis. Innumerable observations such as the allowed and disallowed regions in the conformations of a peptide unit, hydrophobic core in globular proteins, existence of regular secondary structures like helices, sheets, and turns and a limited fold space have been landmarks in understanding the characteristics of protein structures. The uniqueness of protein structure is attained through non–covalent interactions among the constituent amino acids. Analyses of protein structures show that different types of non–covalent interactions like hydrophobic interactions, hydrogen bonding, salt bridges, aromatic stacking, cation–π interactions, and solvent interactions hold protein structures together. Although such structure analyses have provided a wealth of information, they have largely been performed at a pair–wise level and an investigation involving such pair–wise interactions alone is not sufficient to capture all the determinants of protein structures, since they happen at a global level. This consideration has led to the development of graphs/networks for proteins. Graphs or Networks are a collection of nodes connected by edges. Protein Structure Networks (PSNs) can be constructed using various definitions of nodes and edges. Nodes may vary from atoms to secondary structures in Synopsis proteins, and the edges can range from simple atom–atom distances to distance between secondary structures. To study the interplay of amino acids in structure formation, the most commonly used PSNs consider amino acids as nodes. The criterion for edge definition, however, varies. PSNs can be constructed at a course grain level by considering the distances between Cα/Cβ atoms, any side–chain atoms, or the centroids of the amino acids. At a finer level, PSNs can be constructed using atomic details by considering the interaction types or by computing the extent of interaction between amino acids. Representation of proteins as networks and their analyses has given us a unique perspective on various aspects such as protein structure organization, stability, folding, function, oligomerization and so on. A variety of network properties like the degree distribution, clustering coefficient, characteristic path lengths, clusters, and hubs have been investigated. Most of these studies are carried out on protein structures alone. However, the interaction of proteins with other biopolymers like nucleic acids is vital for many crucial biological processes like transcription and translation. In this thesis, we have attempted to address this problem by constructing and analyzing combined graphs of the structures of protein and DNA. Also, in almost all of the PSN studies, the connections have been made solely on the basis of geometric criteria. In the later part of the thesis, we have taken PSN a step further by defining the non–covalent connections based on chemical considerations in the form of the energies of interactions. The thesis contains two sections. The first part mainly involves the construction and application of PSNs to study DNA binding proteins. The DNA binding proteins are involved in several high fidelity processes like DNA recombination, DNA replication, and transcription. Although the protein– DNA interfaces have been extensively analyzed using pair–wise interactions, we gain additional global perspective from network approach. Furthermore, most of the earlier investigations have been carried out from the protein point of view (protein centric) and the present network approach aims to combine both the protein centric and the DNA centric view points by construction and analyses of protein–DNA graphs. These studies are described in Chapters 3 and 4. The second part of the thesis discusses the development, characterization, and application of protein structure networks based on non– covalent interaction energies. The investigations are presented in chapters 5 and 6. Chapter 3 discusses the development of Protein–DNA Graphs (PDGs) where the protein–DNA interfaces are represented as networks. PDG is a bipartite network in which amino acids form a set of nodes and the nucleotides form the other set. The extent of interaction between the two diverse types of biopolymers is normalized to define the strength of interaction. Edges are then constructed based on the interaction strength between amino acids and nucleotides. Such a representation, reported here for the first time, provides a holistic view of the interacting surface. The developed PDGs are further analyzed in terms of clusters of interacting residues and identification of highly connected residues, known as hubs, along the protein–DNA interface and discussed in terms of their interacting motifs. Important clusters have been identified in a set of protein–DNA complexes, where the amino acids interact with different chemical components of DNA such as phosphate, deoxyribose and base with varying degrees of connectivity. An analysis of such fragment based PDGs provided insights into the nature of protein–DNA interaction, which could not have been obtained by conventional pair–wise analysis. The predominance of deoxyribose–amino acid clusters in beta–sheet proteins, distinction of the interface clusters in helix–turn–helix and the zipper type proteins are some of the new findings from the analysis of PDGs. Additionally, a potential classification scheme has been proposed for protein–DNA complexes on the basis of their interface clusters. This classification scheme gives a general idea of how the proteins interact with different components of DNA in various complexes. The present graph–based method has provided a deeper insight into the analysis of the protein–DNA recognition mechanisms from both protein and DNA view points, thus throwing more light on the nature and specificity of these interactions (Sathyapriya, Vijayabaskar et al. 2008). Chapter 4 delineates the application of PSN to an important problem in molecular biology. An analysis of interface clusters from multimeric proteins provides a clue to the important residues contributing to the stability of the oligomers. One such prediction was made on the DNA binding protein under starvation from Mycobacterium smegmatis (Ms–Dps) using PSNs. Two types of trimers, Trimer A (tA) and Trimer B (tB) can be derived from the dodecamer because of the inherent three fold symmetry of the spherical crystal structure. The irreversible dodecamerization of these native Ms--Dps trimers, in vitro, is known to be directly associated with the bimodal function (DNA binding and iron storage) of this protein. Interface clusters which were Synopsis identified from the PSNs of the derived trimers, allowed us to convincingly predict the residues E146 and F47 for mutation studies. The prediction was followed up by our experimental collaborators (Rakhi PC and Dipankar Chatterji), which led to the elucidation of the molecular mechanism behind the in vitro oligomerization of Ms--Dps. The F47E mutant was impaired in dodecamerization, and the double mutant (E146AF47E) was a native monomer in solution. These two observations suggested that the two trimers are important for dodecamerization and that the residues selected are important for the structural stability of the protein in vitro. From the structural and functional characterizations of the mutants, we have proposed an oligomerization pathway of Ms–Dps (Chowdhury, Vijayabaskar et al. 2008). The second part of the thesis involves the development, characterization (Chapter 5) and application (Chapter 6) of Protein Energy Networks (PENs). As mentioned above, the PSNs constructed on the geometric basis efficiently capture the topology and associated properties at the level of atom–atom contact. The chemistry, however, is not completely captured by these network representations, and a wealth of information can be extracted by incorporating the details of chemical interactions. This study is an advancement over the existing PSNs, in terms of edges being defined on the basis of interaction energies among the amino acids. This interaction energy is the resultant of various types of interactions within a protein. Use of such realistic interaction energies in a weighted network captures all the essential features responsible for maintaining the protein structure. The methodology involved in representing proteins as interaction energy weighted networks, with realistic edge weights obtained from standard force fields is described in Chapter 5. The interaction energies were derived from equilibrium ensembles (obtained using molecular dynamics simulations) to account for the structural plasticity, which is essential for function elucidation. The suitability of this method to study single static structures was validated by obtaining interaction energies on minimized crystal structures of proteins. The PENs were then characterized using network parameters like edge weight distributions, clusters, hubs, and shortest paths. The PENs exhibited three distinct behaviors in terms of the size of the largest connected cluster as a function of interaction energy; namely, the pre–transition, transition, and post transition regions, irrespective of the topology of the proteins. The pre– transition region (energies<–20 kJ/mol) comprises smaller clusters with mainly charged and polar residues as hubs. Crucial topological changes take place in the transition region (–10 to –20 kJ/mol), where the smaller clusters aggregate, through low energy van der Waals interactions, to form a single large cluster in the post–transition region (energies>–10 kJ/mol). These behaviors reinforce the concept that hydrophobic interactions hold together local clusters of highly interacting residues, keeping the protein topology intact (Vijayabaskar and Vishveshwara 2010). The applications of PENs in studying protein organization, allosteric communication, thermophilic stability and the structural relation of remote homologues of TIM barrel families have been outlined in Chapter 6. In the first case, the weighted networks were used to identify stabilization regions in protein structures and hierarchical organization in the folded proteins, which may provide some insights into the general mechanism of protein folding and stabilization (Vijayabaskar and Vishveshwara 2010). In the second case the features of communication paths in proteins were elucidated from PENs, and specific paths have been extensively discussed in the case of PDZ domain, which is known to bring together protein partners, mediating various cellular processes. Changes in PEN upon ligand binding, resulting in alterations of the shortest paths (energetically most favorable paths) for a small fraction of residues, indicated that allosteric communication is anisotropic in PDZ. The observations also establish that the shortest paths between functionally important sites traverse through key residues in PDZ2 domain. Furthermore, shortest paths in PENs provide us the exact pathways of communication between residues. Although the communication in PDZ has been extensively investigated, detailed information of pathways at the energy level has emerged for the first time from the present study from PEN analysis (Vijayabaskar and Vishveshwara 2010). In the third case, a set of thermophilic and mesophilic proteins were compared to determine the factors responsible for their thermal stability from a network perspective using PENs. The sub– graph parameters such as cluster population, hubs and cliques were the prominent contributing factors for thermal stability. Also, the thermophilic proteins have a better–packed hydrophobic core. The property of thermophilic protein to increase stability by increasing the connectivity but retain conformational flexibility is discussed from a cliques and communities (higher order inter–connection of residues) perspective (Vijayabaskar and Vishveshwara 2010). Finally, the remote homologues from the TIM barrel fold have been analyzed using PENs to identify the interactions responsible for the maintenance of the fold despite low sequence similarity. A study of conserved Synopsis interactions in family specific PENs reveals that the formation of the central beta barrel is vital for the TIM barrel formation. The beta barrel is being formed by either conserved long range electrostatic interactions or by tandem arrangement of low energy hydrophobic interactions. The contributions of helix–sheet and helix–helix interactions are not conserved in the families. This study suggests that the sequentially near residues forming the helix–sheet interactions are common in many folds and hence formed despite non– conservation, whereas formation of beta barrel requires long range interactions, thus more conserved within the families. The thesis also consists of an appendix in which a web–tool, developed to express proteins as networks and analyze these networks using different network parameters is discussed. The web based program–GraProStr allows us to represent proteins as structure graphs/networks by considering the amino acid residues as nodes and representing non–covalent interactions among them as edges. The different networks (classified based on edge definition) which can be obtained using GraProStr are Protein Side–chain Networks (PScNs), Cα/Cβ distance based networks (PcNs) and Protein– Ligand Networks (PLNs). The parameters which can be generated include clusters, hubs, cliques (rigid regions in proteins) and communities (group of cliques). It is also possible to differentiate the above mentioned parameters for monomers and interfaces in multimeric proteins. The well tested tool is now made available to the scientific community for the first time. GraProStr is available online and can be accessed from http://vishgraph.mbu.iisc.ernet.in/GraProStr/index.html. With a variety of structure networks, and a set of easily interpretable network parameters GraProStr can be useful is analyzing protein structures from a global paradigm (Vijayabaskar, Vidya et al. 2010). In summary, we have extensively studied DNA binding proteins using side– chain based protein structure networks and by integrating the DNA molecule into the network. Also, we have upgraded the existing methodology of generating structure networks, by representing both the geometry and the chemistry of residues as interaction energies among them. Using this energy based network we have studied diverse problems like protein structure formation, stabilization, and allosteric communication in detail. The above mentioned methodologies are a considerable advancement over existing structure network representations and have been shown in this thesis to shed more light on the structural features of proteins.

The last few decades have witnessed an upsurge in the availability of large-scale data on genomes and genome-scale information. The development of methods to understand the trends and patterns from large scale data promised potentially to unravel the mechanisms responsible for the enormous diversity observed in biological systems. Of the many mechanisms adopted, protein-protein interactions represent one of the commonly adopted mechanisms to achieve functional diversity using a limited genetic repertoire. Protein-proteins interactions bring about several fundamental cellular processes and also modulate regulation at the cellular level. Different types of protein-protein interactions have evolved to carry out myriad functions in a cell. Mainly, interactions can be permanent or transient in nature, depending on the duration of interaction. In terms of affinity ,they are classified as obligate or non-obligate interactions. Structural studies on the various kinds of complexes have enabled the identification of the distinctive features characterizing the different types of complexes. Further, identifying the mechanisms involved in the evolution of protein-protein interactions are important in understanding the forces involved in their maintenance. Such studies also provide clues for the development of methods to predict protein-protein interactions from the large repertoire of sequence and structural data available. In spite of significant understanding of various aspects of protein-protein interactions, several questions still remain unanswered. The work embodied in this thesis studies two main aspects of protein-protein interactions for various types of complexes: structural and evolutionary features. The first part of the thesis(comprising of chapters 2,3,4 and 5) involves structural studies on the following features of protein-protein interactions: structural change, flexibility, symmetry, and residue conservation. The second part of the thesis(comprising of chapters 6,7,8 and 9) involves study of evolutionary aspects of protein-protein interactions, based on both large-scale data as well as case studies. Chapter1 provides a background and literature survey of the area of protein-protein interactions. The different classification schemes commonly used for describing the various protein-protein interactions are outlined. The key small-scale and large-scale experimental methods used for the identification of protein-protein interactions are described along with the details of the databases storing such experimentally derived information. Further, a comprehensive account of structural and evolutionary studies performed so far using the available data is provided. The computational(prediction)methods developed to address various aspects of protein-protein interactions are also outlined. In addition, the importance of protein-protein interactions in the context of diseases and the development of methods used to inhibit these interactions are discussed. Finally, the efforts towards design of protein-protein interactions based on the understanding of the principles governing their formation are outlined. Chapter 2 and chapter 3 describe different aspects of transient protein-protein interactions, which form an important subset of interactions, and are mainly involved in the regulation of Cellular processes. In chapter 2, the structural changes occurring upon complex formation are described. In chapter 3, roles of interface residues in the unbound form are described. In chapter 2, the nature, extent and location of structural changes upon binding is analyzed using a non-redundant and curated dataset of 77 structures of protein-protein complexes available in both bound and unbound forms. Structural change has been captured using two metrics: protein blocks and root mean square deviation of Cα positions. The relevance of the structural changes observed in protein-protein complexes is established by comparison with a control dataset of proteins not bound to any small or macromolecule. Results indicate that the observed changes are much larger than those observed due to random fluctuations. Given this background, the following observations were made on the nature, extent and location of structural changes in protein-protein complexes.(i) The nature of structural changes occurring at the interface is largely conformational with few rigid-body movements.(ii)The interfaces in the dataset are segregated into three types based on the extent of structural changes at the interface. A significant fraction of the interfaces are ‘pre-made’(almost in variant interface) or‘ induced-fit’(interface with large structural changes), while the rest are interfaces with moderate structural changes(‘others’). Analysis of structural changes using protein blocks reveals that pre-made interfaces are not completely invariant and are characterized by conformational changes of small magnitude. Pre-made interfaces are also observed to bind preferentially to‘ induced fit ’or‘ other’ interfaces. These observations implicate that non-obligate interactions possess in-built regulatory mechanisms in terms of conformational features to control the timely association-dissociation of transiently interacting proteins. (iii) Interestingly, significant structural changes away from the interface were observed in almost one-half of the complexes in the dataset. The analysis of these changes forms a major focus of this chapter. Crystallographic temperature factors, crystal packing, and normal mode analysis of these regions were studied to analyze the structural changes in these regions. Normal mode analysis along with literature survey indicates that most of the structural changes observed in non-interacting surface regions may be functionally relevant, with many of them corresponding to allosteric transitions. The majority of these changes occur in signaling proteins. The chapter summarizes that these observations suggest a much higher prevalence of allostery caused due to protein binding than appreciated before. The data set generated in this chapter can serve as a starting point to uncover potentially new allosteric modulators in signaling systems. In chapter 3, the question‘ Do residues at the interface of transient protein-protein interactions have any role in the unbound form?’ has been investigated. A high resolution, non-redundant and functionally diverse dataset of 67 proteins with known structures available both in the form of protein-protein complex and unbound forms has been used. Significantly low B-factors at the core of the interface in the unbound form are observed in these structures, indicating high rigidity. Many of these residues also show B-factors comparable to those of buried residues in a protein, which formed the basis for classifying interface residues as ‘rigid’ and‘ non-rigid’. These two types of residues have differential contribution towards the energetics of complex formation. It is also observed that rigid interfacial residues are conserved better in evolution than non-rigid interfacial residues. Their stronger selection is highlighted by substantial conservation of microenvironment (rigidness), sequence(amino acid identity/similarity) and structure(specific side-chain orientation) in homologous proteins. These observations coupled with the absence of any specific type of amino acid to occur preferentially at a rigid site indicates that rigidness is a property of the topological location of the residue at the interface and not the type of the amino acid present at that site. Analysis of the energetic parameters of these residues indicates that the y contribute significantly to the molecular recognition process by reducing the entropic cost on complexation by virtue of their pre-ordered conformation. This chapter also explores the contribution of interface residues towards the stability of the self-protein vis-à-vis that of the complex. It was seen that most interface residues contribute towards stabilizing the bound form. Interestingly, some of the interfacial residues predominantly stabilize the self-protein(the protein in which they are situated) and have a negligible contribution towards stabilization of the bound form. Thus, though these residues are located in the protein-protein interface their main role seems to be in the stabilization of the self-protein both in the unbound and bound forms. These residues are classified as Self-protein Stabilizing Residues(SSR -6.93%) and the rest as Neutrally Stabilizing Residues(NR -42.60%) and Complex Stabilizing Residues(CSR -50.46%). In addition, it was noted that the proportion of rigid residues is more in SSR(73.33%) than in NR(58.13%) and CSR(48.90%)sites. Apart from the favorable energetic contribution by rigid residues to the free energy of the unbound form than non-rigid residues, their predominance in SSRs suggests that rigid residues play an important role in the stabilization of the unbound form of the protein.The analyses performed in this chapter suggest that not all the protein-protein interfacial residues have the major role of stabilizing the complex; some of these residues seem to have more significant role in the unbound form than the bound form. Chapter4 provides a discussion on the prevalence and relevance of a symmetry in homodimeric proteins. One of the main features characterizing homodimers is the symmetric arrangement of subunits in the three-dimensional structures.Typically, asymmetric arrangements of subunits are associated with disease states; however, they are also observed in normal homodimers performing specialized functions. Two measures to quantify structural asymmetry in homodimers (global asymmetry and interface asymmetry)have been used on an on-redundant dataset of 223 biologically relevant homodimers. The survey for globally asymmetric homodimers in the dataset indicates that they are very rare(n=11).The chapter discusses cases where a globally asymmetric arrangement of homodimeric proteins has been utilized by the nature to perform certain specialized functions, such as linking of a dimeric system with a monomeric system(half-of-sites reactivity) and the transmission of signals emanating from asymmetric DNA repeats. Analysis of the 3-D structures of homologues reveals that there is no clear conservation of asymmetry. Specifically, the function of the homologous protein appears to dictate the pattern of structural organization. This chapter also describes the structural and evolutionary analyses of the 11 globally asymmetric complexes, which suggest possible mechanisms adopted by nature for preventing infinite array formation. The postulated mechanisms are:(i) In case of homodimers associating via non-topologically equivalent surfaces in their tertiary structures, ligand-dependent mechanisms are used.(ii) In case of homodimers associating via partially topologically equivalent surfaces, steric hindrance serves as the preventive mechanism of infinite array. Since most of the biologically relevant homodimers exhibit gross structural symmetry, this chapter explores further the extent of interface asymmetry in symmetric homodimers. It was observed that homodimers exhibiting grossly symmetric organization rarely exhibit either perfect local symmetry or high local asymmetry. Further, binding of small ligands at the interface does not cause any significant variation in interface asymmetry.The chapter provides new insights regarding accommodation of structural asymmetry in homodimers. Chapter 5 describes the ability of residue conservation of interface residues vis-à-vis surface residues near interface residues to identify fitting errors caused due to mis-orientation in cryo-electron microscopy maps. Cryo-electron microscopy is the most popular technique for solving structures of large assemblies in physiological conditions. However, the structures are usually solved at low resolution and atomic resolution is desired to get insights at the molecular-level. Although several methods have been developed for the fitting of atomic structures or models in to low-resolution cryo-electron microscopic maps, inaccurate fitting is observed in several cases. Using a non-redundant and high-resolution dataset of 125 permanent interactions and 95 transient interactions, it was observed that interface residues are significantly conserved better than residues near to the interface. The chapter describes the ability of this differential conservation to identify probable mis-fittings in cryo-EM maps for three case-studies: ribosomal complex from Escherichia coli, transferring-transferrin receptor complex from Homosapiens, and glutamate synthase complex from Azospirillum brasilense. For these cases, the use of conservation information resulted in the identification of a few residues in the vicinity of the interface with significantly higher conservation, implying their probable occurrence in the interface. These findings were verified against the high-resolution structures for two of these complexes (ribosomal assembly and transferring-transferrin receptor complex).These analyses suggest that residue conservation information can be useful in the fitting process to arrive at the fitted structure with an improved accuracy. Further, the discriminative power of the simplistic measure of residue conservation coupled with residue surface accessibility in identifying interacting residues on protein structures is also analyzed in this chapter. Testing on a set of signaling and scaffolding molecules indicates that this simplistic measure can identify interface residues in protein structures, indicating that conservation contains a distinct, although weak, signal for functional regions. Chapters 6 to 9 discuss studies involving evolutionary aspects of protein-protein interactions. Chapter 6 describes the usage of phylogenetic tree construction using maximum likelihood method to understand the origin of the signal captured by the mirror tree approach. Mirror tree is one of the most popular approaches for identifying interacting proteins based on co-evolution. This method uses the similarity in phylogenetic trees as an indicator of protein-protein interaction. The origin of the evolutionary signal detected by the mirror tree method is a subject of some controversy. Two broad hypotheses have been postulated in the literature to explain the origin of the signal(i)site-specific co-evolution alone and(ii)correlation induced by external factors with only minor, if any, contribution from site-specific co-evolution. In the typical mirror tree protocol, inferences from phylogenetic tree are optional and only genetic distances are analysed. Even if the tree is constructed, usually the Neighbor-Joining approach is used. However ,with Neighbor-Joining method the inferred tree topology and genetic distances are directly linked. With maximum likelihood the tree topology is not derived directly from the genetic distances and therefore the contributions of the signals arising from tree topology and genetic distances can be studied separately. Tree topologies can be considered to serve as indicators of compensatory substitutions(implicated in site-specific co-evolution)as well as shared evolutionary history. Genetic distances correspond to evolutionary rates(implicated in correlation induced by external factors).Using this method, phylogenetic trees for a range of datasets of interacting and non-interacting proteins corresponding to yeast(S.cerevisiae) have been derived. The analysis performed in this chapter reveals no strong correlation between phylogenetic tree topologies, and significant correlation between genetic distance matrices for interacting proteins. The chapter discusses the implications of these findings and attempts to understand the origin of the signal captured by mirror tree protocol using the following points.(i) The near lack of correlation in tree topologies is not surprising since compensatory substitutions accounts for only a minority of the sites in a protein.(ii) The influence of shared evolutionary history has also been tested in the chapter by comparison of tree topologies of interacting proteins and non-interacting with 18S rRNA tree. Tree topologies of both interacting and non-interacting proteins do not mirror the 18S rRNA tree, ruling out shared evolutionary history as the signal of correlated evolution.(iii) By contrast, the significant correlation observed between branch lengths(genetic distances) of interacting proteins in all the variant datasets demonstrates correlation between evolutionary rates, independent of evolutionary divergence. In summary, the chapter concludes by providing support for the theory of correlation induced by external factors with only minor contribution from site-specific co-evolution. Chapter 7 explores the homology based transfer of interactions by quantifying the extent of retention/variation of interaction partnerships amongst a set of homologous proteins related at SCOP family level(which indicates clear evolutionary relationship).A large dataset of domain-domain interacting pairs(n=20,254)culled from SCOP1.73 was used for this analysis. Study involving this dataset shows that in around~80% of the cases, interacting partners are completely retained(evaluated as proteins belonging to the same SCOP family).If‘common’ partnership is evaluated at the level of SCOP folds, which are known to be structurally similaral though not necessarily evolutionarily related, the percentage of homologous domains with complete retention of partnership increases only by~5%. This indicates that only the presence of a common structural scaffold is not a sufficient feature for interaction. Further, the chapter also describes the retention/variation in partnerships analyzed as a function of sequence divergence between the homologous proteins. It is observed that there is a higher tendency to vary interacting partners as the evolutionary divergence between the homologues increases. In spite of this, interaction partnerships appear to be retained for homologous domains irrespective of their sequence divergence if the function mandates the presence of the interaction. However, all these observations could be influenced by the incomplete nature of information on the interactions available in the structural space. This problem has been addressed in this chapter by studying variation in interaction partnerships for Saccharomyces cerevisiae proteins. Yeast was chosen since it is extensively studied and interactions are available for~87% of proteins yielding a comprehensive list of interactions. To study this aspect, the SCOP dataset of interacting proteins(which represents a generic dataset) was compared with interactions of homologous proteins from yeast. The dataset of interacting proteins for yeast collated from all sources and documented in BIOGRID v50 was used. In this analysis, the proportion of homologous domains showing complete retention of interacting partners was only ~12%. This observation is the reverse of the trend observed for the dataset of homologous SCOP domains. Further analysis of homologous pairs of yeast-SCOP domains, containing only those pairs whose interacting protein families are found both in yeast and SCOP dataset, was performed to ascertain the extent of contribution of organism-specific proteins to the variation in interaction partnership for homologous domains. The proportion of homologous domains showing complete retention of interaction partners increases to~50% for these cases. These observations indicate that organism-specific proteins contribute significantly to the variation of interaction partnerships in homologous proteins. The next two chapters(8 and 9) discuss two contrasting scenarios of interaction partnerships. Chapter 8 describes the study of two protein families showing variation in interaction partnerships/interface structure and analyzes the drift in protein-protein interaction surfaces in each of the cases. The analysis in this chapter is facilitated by the large number of sequences available for the case studies. The first case study involves members of the glutamine amido transferase (GAT) superfamily of enzymes. Three remote homologues in this superfamily could also be related by sequence: intracellular protease(DJ-1/PfpIfamily),C-terminal domain of the small subunit of carbomoyl phosphate synthetase (ClassI glutamine amidotransferase-like family), and C-terminal domain of catalase (Catalase ,C-terminal domain family).In two cases, it is seen that domain recruitment influences the interacting surface(catalase, carbamoyl phosphate synthetase). The tethered domains, which are involved in interaction with the GAT domain, are from different SCOP folds, indicating that partnerships are not retained at extreme divergence. However, members of the DJ-1/PfpIfamily form homodimers with differing quaternary structures i.e. different orientations of the dimers. Four members have been studied in detail in this chapter (intracellular protease–two distinct interfaces–forming hexamer, stress-induced protein -dimer, DJ-1protein -dimer, sigma cross-reacting protein -dimer). Since the members are sequentially less divergent(as they are within the same family), it is possible to trace the drift in interfaces among these members based on the multiple sequence alignments of members with the differing quaternary structures and the sequences bridging them. The second case study involves analysis of the family of legume lectins, which corresponds to another set of proteins exhibiting differing quaternary structures for remarkably well conserved tertiary structures and sequences. Analysis of variations in protein-protein interaction surfaces when they show only slight differences between homologous members indicates that the drift is gradual, as seen when tracing the dynamics of DJ-1 family members and legume lectin family members. There exist sequences containing many different intermediate combinations of the interacting residues involved in both the sets of proteins. Comparisons of homologues where an entire interface seems to be lost show a different trend(intracellular protease and DJ-1).The most prominent interacting residues show an abrupt shift between the two different subfamilies. However, inspection of the other interacting residues reveals that there is a gradual change occurring generally, although a drastic change in the important(although quantitatively smaller) residues would have led to loss of interface. In summary, analysis of the evolutionary dynamics of the consensus interface residues of different quaternary structure types of DJ-1/PfpI family of enzymes and legume lectins shows that nature employs only the most important mutations to Prevent a specific interface and form a new interface and the rest of the positions drift and accumulate changes in the course of evolution. Chapter 9 describes the opposite scenario i.e. conservation of an interface even at high sequence divergence, using the RNA polymerase assembly as a case study. The multi-molecular assembly consists of four core subunits–alpha (I and II), beta, betaprime, and omega. These four subunits are common to RNA polymerase complexes of eubacteria, eukaryota and archaea. The sigma subunit aids in initiation of transcription in eubacteria (cor eenzyme +sigma = holoenzyme). Remarkably, prokaryotic and eukaryotic structures exhibit high degree of structural similarity, although their sequence similarity is low(19-28% sequence identity).However, this is expected as the obligatory interaction between the various subunits is essential to successfully carry out transcription. This chapter investigates the structural accommodation of diverse sequences at the interface of RNA polymerase machinery of eubacteria, using sequence analysis and homology modelling. Analysis of domain composition and order of domains for the core subunits of the RNA polymerase assembly in>85 eubacterial species indicates complete conservation. However, conservation analysis of the various core subunits indicates that the interface residues are more divergent for alpha and omega subunits. Although beta and beta prime are generally well-conserved, the residues involved in interaction with the divergent subunits(i.e.alpha, omega) are not conserved. Insertions/deletions are also observed near the interacting surfaces even in the cases of most conserved subunits(beta and betaprime). The chapter describes the homology modeling of three divergent RNApolymerase complexes from Helicobacter pylori, Mycoplasma pulmonis and Onion yellows phytoplasma, highlighting that insertions/deletions can be accommodated near the interface as they generally occur at the periphery. The development of a generalized matrix capturing preferences of interface environment is documented, along with results comparing the similarity of the modeled interfaces to that of the template interface. It is observed that the modeled interfaces are physico-chemically similar to that of the template interfaces in Thermus thermophilus, indicating that nature accommodates substantial substitutions and insertions/deletions at and near the interface in order to retain the structure of the obligate complex, which is in dispensable for the process of transcription. The main conclusions of the entire thesis work are summarized in chapter10, which also places the work in the context of the field of protein-protein interactions. The new insights obtained for transient interactions and homodimers from structural studies are highlighted. The application of evolutionary conservation to improve fitting of atomic structures in cryo-electron microscopic maps is discussed. The understanding gained from study of different evolutionary aspects of protein-protein interactions, ranging from correlated evolution to evolutionary dynamics of variations in interactions is also highlighted. Appendix 1 of this thesis describes the homology modeling of the hexameric form of AAA ATPase domain of spastin along with associated structural analysis.

My thesis is divided into five chapters, starting with a general introduction in first chapter and sample preparation and protein-NMR assignment techniques in second chapter. The remaining three chapters focus on three different areas/projects that I have worked on. Chapter 1: Introduction to nanomaterials and all the experimental techniques This chapter reviews different kinds of nanomaterials and their application utilized for protein-nanomaterial interaction in our study, along with the introduction to different spectroscopy and microscopy techniques used for the interaction studies. Starting with introduction of nanomaterials and all the experimental techniques, which constitute the arsenal for structural studies of the protein-nanomaterial interaction, different steps enroute to structural and dynamic interaction are outlined in detail. Chapter 2: Preparation and Characterization of Proteins used for nanomaterial interaction studies Proteins are generally of three kinds- globular (structured), intrinsically disordered and membrane bound. These proteins have different functions in living organisms and play a major role to maintain metabolism and other important factors. To probe protein-nanomaterial interactions, we have chosen different protein/peptides. This chapter describes the protocol/procedure used for purifying the proteins. For studying a globular protein, ubiquitin was chosen. Nanomaterial-IDP interaction was investigated using the intrinsically disordered central linker domain of human insulin like growth factor binding protein-2 (L-hIGFBP2). The hydrophobic membrane interacting part of the prion protein was chosen as a representative membrane protein. The characterization of the proteins by NMR spectroscopy is also described. Chapter 3: A nanomaterial based novel macromolecular crowding agent Carbon quantum dots (CQD) are nanomaterials with size less than 10 nm, first obtained in 2004 during purification of single-walled carbon-nanotubes. Since then CQDs have been used in a wide range of applications due to their low cost of preparation and favorable properties such as chemical inertness, biocompatibility, non-toxicity and solubility in aqueous medium. One of the applications of CQDs has been their use for imaging and tracking proteins inside cells, based on their intrinsic fluorescence. Further, quantum dots exhibit concentration dependent aggregation while retaining their solubility. Fluorescent carbon quantum dots (CQD) induce macromolecular crowding making them suitable for probing the structure, function and dynamics of both hydrophilic and hydrophobic peptides/ proteins under near in-cell conditions. We have prepared hydrophilic and hydrophobic quantum dots to see the crowding effect. After characterization of CQD, we tested the property of proteins with CQD and found that CQD behaves as a macromolecular crowding agent by mimicking near in-cell conditions. In our study, we have chosen a globular protein, an intrinsically disordered protein (IDP) and one hydrophobic membrane peptide. We have also compared the crowding property of CQD with ficoll which is widely used commercial crowding agent. The overall study tells that the CQD acts like crowding agent and can be used for the study of macromolecular crowding effect. This makes them suitable for structural and functional studies of proteins in near in-cell conditions. Chapter 4: Ubiquitin-Graphene oxide interactions Described here is the interaction of human ubiquitin with GO using NMR spectroscopy and other techniques such as Fluorescence spectroscopy, isothermal titration calorimetry (ITC), UV-Visible spectroscopy, dynamic light scattering (DLS), zeta potential measurements and transmission electron microscopy (TEM). The globular protein ubiquitin interacts with GO and undergoes a dynamic and reversible association-dissociation in a fast exchange regimen as revealed by NMR spectroscopy. The conformation of the protein is not affected and the primary interaction is seen to be electrostatic in nature due to the polar functional groups present on the protein and GO sheet surface. For the first time we have shown that the interaction between ubiquitin and GO is dynamic in nature with fast and reversible adsorption/desorption of protein from the surface of GO. This insight will help in understanding the mechanistic aspects of interaction of GO with cellular proteins and will help in designing appropriate functionalized graphene oxide for its biological application. Chapter 5: Section A: Interaction of an intrinsically disordered protein (L-HIGFBP2) with graphene oxide The interaction between intrinsically disordered linker domain of human insulin-like growth factor binding protein-2 (L-hIGFBP2) with GO was studied using NMR spectroscopy and other techniques such as isothermal titration calorimetry (ITC), dynamic light scattering (DLS), zeta-potential measurements. The study revealed that the disordered protein L-hIGFBP2 interacts with GO through electrostatic interaction and undergoes a dynamic and reversible association-dissociation in a fast exchange regime. The conformation of the protein is not affected. Section B: Stability of an Intrinsically disordered protein through weak interaction with Silver nanoparticles Using NMR spectroscopy and other techniques we probed the mechanism of L-hIGFBP2–AgNP interactions which render the IDP stable. The study reveals a mechanism which involves a relatively fast and reversible association–dissociation of L-hIGFBP2 (dynamic exchange) from the surface of AgNP. The AgNP–L-hIGFBP2 complex remains stable for more than a month. The techniques employed in addition to NMR include UV-Visible spectroscopy, dynamic light scattering (DLS), zeta potential measurements and transmission electron microscopy (TEM) to probe the protein-AgNP interaction here in this section.

Riboswitches have gained attention as tools for synthetic biology, since they enable researchers to reprogram cells to sense and respond to exogenous molecules. In vitro evolutionary approaches produced numerous RNA aptamers that bind such small ligands, but their conversion into functional riboswitches remains difficult. We previously developed a computational approach for the design of synthetic theophylline riboswitches based on secondary structure prediction. These riboswitches have been constructed to regulate ligand dependent transcription termination in Escherichia coli. Here, we test the usability of this design strategy by applying the approach to tetracycline and streptomycin aptamers. The resulting tetracycline riboswitches exhibit robust regulatory properties in vivo. Tandem fusions of these riboswitches with theophylline riboswitches represent logic gates responding to two different input signals. In contrast, the conversion of the streptomycin aptamer into functional riboswitches appears to be difficult. Investigations of the underlying aptamer secondary structure revealed differences between in silico prediction and structure probing. We conclude that only aptamers adopting the minimal free energy (MFE) structure are suitable targets for construction of synthetic riboswitches with design approaches based on equilibrium thermodynamics of RNA structures. Further improvements in the design strategy are required to implement aptamer structures not corresponding to the calculated MFE state.

Adaptive evolution of Toll-like receptors in birds Hana Velová, PhD thesis 6 Abstract Toll-like receptors (TLRs) are one of the key and presumably also evolutionary most original components of animal immune system. As Pattern recognition receptors they form the first line of innate immune defence against various pathogens. The proper receptor binding of pathogenic ligands is crucial for their correct recognition and for subsequent triggering of an appropriate immune response. Because there exists a direct interaction between the receptor surface and the pathogenic ligand, host-pathogen coevolution on molecular level can be predicted. Thus, through variability of their ligands, TLRs are exposed to extensive selective pressures that may be detected on both genetic and protein levels. Surprisingly, the variability we revealed in birds is even higher than previously expected based on the reports from other vertebrates, mainly mammals. In my doctoral thesis I summarise the results of my contribution to the avian TLR research. We were the first who experimentally verify the absence of functional TLR5 in several avian species and duplication of TLR7 in others. We finally resolved the origin of duplication in TLR1 and in TLR2 family. An important part of my research project focused on the prediction of potentially...