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.

Acetohydroxyacid synthase is a multisubunit enzyme that catalyses the first committed step in the biosynthesis of the branched chain amino acids viz., valine, leucine and isoleucine. In order to understand the structural basis for the observed allosteric feedback inhibition in AHAS, the regulatory subunit of AHAS isozymes I from E. coli was cloned, expressed, purified and the conditions were optimized for solution NMR spectroscopy. IlvN was found to exist as a dimer both in the presence and absence of the feedback inhibitor. Using high-resolution multidimensional, multinuclear NMR experiments, the structure of the dimeric valine-bound 22 kDa IlvN was determined. The ensemble of twenty low energy structures shows a backbone root mean square deviation of 0.73 ± 0.13 Å and a root mean square deviation of 1.16 ± 0.13 Å for all heavy atoms. Furthermore, greater than 98% of the backbone φ, ψ dihedral angles occupy the allowed and additionally allowed regions of the Ramachandran map. Each protomer exhibits a βαββαβα topology that is a characteristic feature of the ACT domain fold that is observed in regulatory domains of metabolic enzymes. In the free form, IlvN exists as a mixture of conformational states that are in intermediate exchange on the NMR timescale. Important structural properties of the unliganded state were probed by H-D exchange studies by NMR, alkylation studies by mass spectrometry and other biophysical methods. It was observed that the dynamic unliganded IlvN underwent a coil-to-helix transition upon binding the effector molecule and this inherent conformational flexibility was important for activation and valine-binding. A mechanism for allosteric regulation in the AHAS holoenzyme was proposed. Study of the structural and conformational properties of IlvN enabled a better understanding of the mechanism of regulation of branched chain amino acid biosynthesis. Solution structural studies of 32 kDa Protease-VPg (PVPg) from Sesbania mosaic virus (SeMV) Polyprotein processing is a commonly found mechanism in animal and plant viruses, by which more than one functional protein is produced from the same polypeptide chain. In Sesbania Mosaic Virus (SeMV), two polyproteins are expressed that are catalytically cleaved by a serine protease. The VPg protein that is expressed as a part of the polyprotein is an intrinsically disordered protein (by recombinant expression) that binds to various partners to perform several vital functions. The viral protease (Pro), though possessing the necessary catalytic residues and the substrate binding pocket is unable to catalyse the cleavage reactions without the VPg domain fused at the C-terminus. In order to determine the structural basis for the aforementioned activation of protease by VPg I undertook the structural studies of the 32 kDa PVPg domains of SeMV by solution NMR spectroscopy. NMR studies on this protein were a challenge due to the large size and spectral overlap. Using a combination of methods such as deuteration, TROSY-enhanced NMR experiments and selective ‘reverse-labelling’, the sequence specific assignments were completed for ~80% of the backbone and 13C nuclei. NMR studies on mutants such as the C-terminal deletion mutant, I/L/V to A mutants in VPg domain were conducted in order to identify the residues important for aliphatic-aromatic interactions observed in PVPg. Attempts were made to obtain NOE restraints between Pro and VPg domains through ILV labelled samples; however these proved unsuccessful. It was observed that ‘natively unfolded’ VPg possessed both secondary and tertiary structure in PVPg. However, 30 residues at the C-terminus were found to be flexible. Even though atomic-resolution structure could not be determined, the region of interaction between the domains was determined by comparing NMR spectra of Pro and PVPg. The conditions for reconstitution of the Protease-VPg complex by recombinantly expressed Pro and VPg proteins were standardised. These studies lay the foundation for future structural investigations into the Protease-VPg complex.

During the past decade the effects of macromolecular crowding on reaction pathways is gaining in prominence. The stress is to move out of the realms of ideal solution studies and make conceptual modifications that consider non-ideality as a variable in our calculations. In recent years it has been shown that molecular crowding exerts significant effects on all in vivo processes, from DNA conformational changes, protein folding to DNA-protein interactions, enzyme pathways and signalling pathways. Both thermodynamic as well as kinetic parameters vary by orders of magnitude in uncrowded buffer system as compared to those in the crowded cellular milieu. Ignoring these differences will restrict our knowledge of biology to a “model system” with few practical understandings. The recent expansion of the genome database has stimulated a study on numerous previously unknown proteins. This has whetted our thirst to model the cellular determinants in a more comprehensive manner. Intracellular extract would have been the ideal solution to re-create the cellular environment. However, studies conducted in this solution will be contaminated by interference with other biologically active molecule and relevant statistical data cannot be extracted out from it. Recent advances in methodologies to mimic the cellular crowding include use of inert macromolecules to reduce the volume occupancy of target molecules and the use of immobilization techniques to increase the surface density of molecules in a small volumetric region. The use of crowding agents often results in non-specific interaction and side-reactions like aggregation of the target molecules with the crowding agents themselves. Immobilization of one of the interacting partners reduces the probability of aggregation and precipitation of bio-macromolecules by restricting their degrees of freedom. Covalent linkage of molecules on solid support is used extensively in research for creating a homogeneous surface of bound molecules which can be interrogated for their reactivity. However, when it comes to biomolecules, direct immobilization on solid support or use of organic linkers often results in denaturation. The use of bio-affinity immobilization techniques can help us overcome this problem. Since mild conditions are needed to regenerate such a surface, it finds universal applicability as bio-memory chips. This thesis focuses on our attempts to design a physiologically viable immobilization technique for following rotein-protein/protein-DNA interactions. The work explores the mechanism for biological interactions related to transcription process in E. coli. Chapter 1 deals with the literary survey of the importance and effects of molecular crowding on biological reactions. It gives a brief history of the efforts been made so far by experimentalists, to mimic macromolecular crowding and the methods applied. The chapter tries to project an all-round perspective of the pros and cons of different immobilization techniques as a means to achieve a high surface density of molecules and the advancements so far. Chapter 2 deals with the detailed technicality and applicability of the Langmuir-Blodgett method. It discusses the rationale behind our developing this technique as an alternate means of bio-affinity immobilization, under physiologically compatible conditions. It then goes on to describe our efforts to follow the sequence-specific and sequential assembly process of a functional RNA polymerase enzyme with one immobilized partner and also explore the role of omega subunit of RNAP in the reconstitution pathway. This chapter uses the assembly process of a multi-subunit enzyme to evaluate the efficiency of the LB system as a universal two-dimensional scaffold to follow sequence-specific protein-ligand interaction. Chapter 3 discusses the application of LB technique to quantitatively evaluate the kinetics and thermodynamics of promoter-RNA polymerase interaction under conditions of reduced dimensionality. Here, we follow the interaction of T7A1 phage promoter with Escherichia coli RNA polymerase using our Langmuir-Blodgett technique. The changes in mechanistic pathway and trapping of kinetic intermediates are discussed in detail due to the imposed restriction in the degrees of freedom of the system. The sensitivity of this detection method is compared vis-a-vis conventional immobilization methods like SPR. This chapter firmly establishes the universal application of LB technique as a means to emulate molecular crowding and as a sensitive assay for studying the effects of such crowding on vital biological reaction pathway. Chapter 4 describes the mechanistic pathway for the physical binding of MsDps1 protein with long dsDNA in order to physically protect DNA during oxidative stress. The chapter describes in detail the mechanism of physical sequestering of non-specific DNA strands and compaction of the genome under conditions where a kinetic bottleneck has been applied. The data obtained is compared with results obtained in the previous chapter for the sequence-specific DNA-protein interaction in order to understand the difference in recognition process between regulatory and structural proteins binding to DNA. Chapter 5 deals with the evaluation of the σ-competition model in E. coli for three different sigma factors (all belonging to the σ-70 family). Here again, we have evaluated the kinetic and thermodynamic parameters governing the binding of core RNAP with its different sigma factors (σ70, σ32and σ38) and performed a comparative study for the binding of each sigma factor to its core using two different non-homogeneous immobilization techniques. The data has been analyzed globally to resolve the discrepancies associated with establishing the relative affinity of the different sigma factors for the same core RNA polymerase under physiological conditions. Chapter 6 summarizes the work presented in this thesis. In the Appendix section we have followed the unzipping of promoter DNA sequence using Optical Tweezers in an attempt to follow the temporal fluctuations occurring in biological reactions in real time and at a single molecule level.

Cancer is a leading cause of death worldwide. Development of new cancer drugs is increasingly costly and time-consuming. By exploiting massive amounts of biological data, computational repositioning proposes new uses for old drugs to reduce these development hurdles. A promising approach is the systematic analysis of structural data for identification of shared binding pockets and modes of action. In this thesis, I developed the Protein-Ligand Interaction Profiler (PLIP), which characterizes and indexes protein-ligand interactions to enable comparative analyses and searching in all available structures. Following, I applied PLIP to identify new treatment options in cancer: the heat shock protein Hsp27 confers resistance to drugs in cancer cells and is therefore an attractive target with a postulated drug binding site. Starting from Hsp27, I used PLIP to define an interaction profile to screen all structures from the Protein Data Bank (PDB). The top prediction was experimentally validated in vitro. It inhibits Hsp27 and significantly reduces resistance of multiple myeloma cells against the chemotherapeutic agent bortezomib. Besides computational repositioning, PLIP is used in docking, binding mode analysis, quantification of interactions and many other applications as evidenced by over 12,000 users so far. PLIP is provided to the community online and as open source.

The guanosine monophosphate synthetase (GMPS) is a class I glutamine amidotransferase, involved in the de-novo purine nucleotide biosynthesis. The enzyme catalyzes the biochemical transformation of xantosine (XMP) into guanosine monophosphate (GMP) in presence of ATP, Mg2+ and glutamine. All GMPSs consist of two catalytic sites 1) for GATase activity 2) for the ATPPase activity. The two catalytic sites may be housed in the same polypeptide (two-domain-type) or in separate polypeptides (two-subunit-type). Most of the studies have been performed on two-domain-type GMPSs, while only one study has been reported from two-subunit-type GMPS (Maruoka et al. 2009). The two-subunit-type GMPS presents an example where the component reactions of a single enzymatic reaction are carried out by two distinct subunits. In order to get better understanding of structural aspects and mechanistic principle that governs the GMPS activity in two-subunit-type GMPSs, we initiated the study by taking GMPS of Methanocaldococcus jannaschii as a model system. The GMPS of M. jannaschii (Mj) is a two-subunit-type protein. The GATase subunit catalyzes the hydrolysis of glutamine to produce glutamate and ammonia. The ATPPase subunit catalyses the amination of XMP to produce GMP using the ammonia generated in GATase subunit. Since the two component reactions are catalysed by two separate subunits and are coupled in the way that product of one reaction (ammonia) acts as a nucleophile in the second reaction. The cross-talk between these two subunits in order to maximise the efficiency of overall GMPS warrants investigation. The GATase activity is tightly regulated by the interaction with ATPPase domain/subunit, in all GMPS except in the case of P. falciparum. This interaction is facilitated by substrate binding to the ATPPase domain/subunit. Though, the conditions for the interaction between two subunits is known in a two-subunit-type GMP synthetase from P. horikoshii, the structural basis of substrate dependent interaction is not known. As a first step to understand the structural basis of interaction between the Mj GATase and Mj ATPPase subunits, we have determined the structure of Mj GATase (21 kDa) subunit using high resolution, multinuclear, multidimensional NMR spectroscopy. Sequence specific resonance assignments were obtained through analysis of various 2D and 3D hetero-nuclear multidimensional NMR experiments. NMR based distance restraints were obtained from assignment of correlations observed in NOE based experiments. Data were acquired on isotopically enriched samples of Mj GATase. The structure of Mj GATase (2lxn) was solved by using cyana-3.0 using NMR based restraints as input for the structure calculation. The ensemble of 20 lowest-energy structures showed root-mean-square deviations of 0.35±0.06 Å for backbone atoms and 0.8±0.06 Å for all heavy atoms. Attempts were also made to obtain assignments for the 69.6 kDa dimeric ATPPase subunit. Partial assignments have been obtained for this subunit. The GATase subunit is catalytically inactive. So far, there has been only one published report on a two-subunit-type GMPS from P. horikashii. The study has shown that the catalytic activity of GATase is regulated by the GATase-ATPPase interaction which is facilitated by the substrate binding to the ATPPase subunit. For the first time, we have provided the structural basis of interaction between GATase-ATPPase (112 kDa) in a two-subunit-type GMPS. Observed line width changes were used to identify residues in GATase residues that are involved in the Mj GATase-ATPPase interaction. Our data provides a possible explanation for conformational changes observed in the Mj GATase subunit upon GATase-ATPPase interaction that lead to GATase activation. Ammonia is generated in GATase subunit and is very reactive and labile. Thus, the faithful transportation of ammonia from GATase to ATPPase subunit is very crucial for optimal GMPS activity. Till date, a PDB query for GMPS retrieves only one structure which belongs to two-subunit-type GMPS, where authors have determined the structures of GATase and ATPPase subunits separately. However, the structure of holo-GMPS is not determined yet. Using interface information from experimental data and HADDOCK, we have constructed a model for the holo-GMPS from M. jannaschii. A possible ammonia channel has been deduced using the programs MOLE 2.0 and CAVER 2.0. This ammonia channel has a length of 46 Å, which is well within the range of the lengths calculated for similar channels in other glutamine amidotransferase. It had been suggested earlier that in addition to the magnesium required for charge stabilization of ATP, additional binding sites were present on GMPS. The effect of excess Mg2+ requirement on the GMPS activity has been studied in two-domain-type GMPS. However, the interaction between GATase and Mg2+ has been not investigated in any GMPS. This prompted us to investigate the effect of MgCl2 on Mj GATase subunit. For the first time, using chemical shift perturbation, we have established interaction between Mj GATase and Mg2+. The dissociation constant (Kd) of the Mj GATase-Mg2+ interaction was determined. The Kd value was found to be 1 mM, which indicates a very weak interaction. The substrate of the GATase subunit is glutamine. The condition of the hydrolysis of the glutamine is known in GMPS. However, the binding of the glutamine and associated conformational changes in GATase have been not studied in GMPS. Furthermore, till date there is no structure available for the glutamine bound GMPS/GATase. Using isotope edited one dimensional and two-dimensional NMR spectroscopy; we have shown that the Mj GATase catalytic residues are not in a compatible conformation to bind with glutamine. Thus, a conformational change in Mj GATase subunit is a pre-requisite condition for the binding of glutamine. These conformational changes are brought by the Mj GATase-ATPPase interaction.

The fidelity of biological processes and reactions, inspite of the widespread diversity, is programmed by highly specific physico-chemical principles. This underlines our basic understanding of different interesting phenomena of biological relevance, ranging from enzyme specificity to allosteric communication, from selection of fold to structural organization / states of oligomerization, from half-sites-reactivity to reshuffling of the conformational free energy landscape, encompassing the dogma of sequence-structure dynamics-function of macromolecules. The role of striking an optimal balance between rigidity and flexibility in macromolecular 3D structural organisation is yet another concept that needs attention from the functional perspective. Needless to say that the variety of protein structures and conformations naturally leads to the diversity of their function and consequently many other biological functions in general. Classical models of allostery like the ‘MWC model’ or the ‘KNF model’ and the more recently proposed ‘population shift model’ have advanced our understanding of the underlying principles of long range signal transfer in macromolecules. Extensive studies have also reported the importance of the fold selection and 3D structural organisation in the context of macromolecular function. Also ligand induced conformational changes in macromolecules, both subtle and drastic, forms the basis for controlling several biological processes in an ordered manner by re-organizing the free energy landscape. The above mentioned biological phenomena have been observed from several different biochemical and biophysical approaches. Although these processes may often seem independent of each other and are associated with regulation of specialized functions in macromolecules, it is worthwhile to investigate if they share any commonality or interdependence at the detailed atomic level of the 3D structural organisation. So the nagging question is, do these diverse biological processes have a unifying theme, when probed at a level that takes into account even subtle re-orchestrations of the interactions and energetics at the protein/nucleic acid side-chain level. This is a complex problem to address and here we have made attempts to examine this problem using computational tools. Two methods have been extensively applied: Molecular Dynamics (MD) simulations and network theory and related parameters. Network theory has been extensively used in the past in several studies, ranging from analysis of social networks to systems level networks in biology (e.g., metabolic networks) and have also found applications in the varied fields of physics, economics, cartography and psychology. More recently, this concept has been applied to study the intricate details of the structural organisation in proteins, providing a local view of molecular interactions from a global perspective. On the other hand, MD simulations capture the dynamics of interactions and the conformational space associated with a given state (e.g., different ligand-bound states) of the macromolecule. The unison of these two methods enables the detection and investigation of the energetic and geometric re-arrangements of the 3D structural organisation of macromolecule/macromolecular complexes from a dynamical or ensemble perspective and this has been one of the thrust areas of the current study. So we not only correlate structure and functions in terms of subtle changes in interactions but also bring in conformational dynamics into the picture by studying such changes along the MD ensemble. The focus was to identify the subtle rearrangements of interactions between non-covalently interacting partners in proteins and the interacting nucleic acids. We propose that these rearrangements in interactions between residues (amino acids in proteins, nucleic acids in RNA/DNA) form the common basis for different biological phenomena which regulates several apparently unrelated processes in biology. Broadly, the major goal of this work is to elucidate the physico-chemical principles underlying some of the important biological phenomena, such as allosteric communication, ligand induced modulation of rigidity/flexibility, half-sites-reactivity and so on, in molecular details. We have investigated several proteins, protein-RNA/DNA complexes to formulate general methodologies to address these questions from a molecular perspective. In the process we have also specifically illuminated upon the mechanistic aspects of the aminoacylation reaction by aminoacyl-tRNA synthetases like tryptophanyl and pyrrolysyl tRNA synthetase, structural details related to an enzyme catalyzed reaction that influences the process of quorum sensing in bacteria. Further, we have also examined the ‘dynamic allosterism’ that manipulates the activity of MutS, a prominent component of the DNA bp ‘mismatch repair’ machinery. Additionally, our protein structure network (PSN) based studies on a dataset of Rossmann fold containing proteins have provided insights into the structural signatures that drive the adoption of a fold from a repertoire of diverse sequences. Ligand induced percolations distant from the active sites, which may be of functional relevance have also been probed, in the context of the S1A family of serine proteases. In the course of our investigation, we have borrowed several concepts of network parameters from social network analysis and have developed new concepts. The Introduction (Chapter-1) summarizes the relevant literature and lays down a suitable background for the subsequent chapters in the thesis. The major questions addressed and the main goal of this thesis are described to set an appropriate stage for the detailed discussions. The methodologies involved are discussed in Chapter-2. Chapter-3 deals with a protein, LuxS that is involved in the bacterial quorum sensing; the first part of the chapter describes the application of network analysis on the static structures of several LuxS proteins from different organisms and the second part of this chapter describes the application of a dynamic network approach to analyze the MD trajectories of H.pylori LuxS. Chapter-4 focuses on the investigation of human tryptophanyl-tRNA synthetase (hTrpRS), with an emphasis to identify ligand induced subtle conformational changes in terms of the alternation of rigidity/flexibility at different sites and the re-organisation of the free energy landscape. Chapter-5 presents a novel application of a quantum clustering (QC) technique, popular in the fields of pattern recognition, to objectively cluster the conformations, sampled by molecular dynamics simulations performed on different ligand bound structures of the protein. The protein structure network (PSN) in the earlier studies were constituted on the basis of geometric interactions. In Chapters 6 and 7, we describe the networks (proteins+nucleic acids) using interaction energy as edges, thus incorporating the detailed chemistry in terms of an energy-weighted complex network. Chapter-6 describes an application of the energy weighted network formalism to probe allosteric communication in D.hafniense pyrrolysyl-tRNA synthetase. The methodology developed for in-depth study of ligand induced changes in DhPylRS has been adopted to the protein MutS, the first ‘check-point protein’ for DNA base pair (bp) mismatch repair. In Chapter-7, we describe the network analysis and the biological insights derived from this study (the work is done in collaboration with Prof. David Beveridge and Dr. Susan Pieniazek). Chapter-8 describes the application of a network approach to capture the ligand-induced subtle global changes in protein structures, using a dataset of high resolution structures from the S1A family of serine proteases. Chapter-9 deals with probing the structural rationale behind diverse sequences adopting the same fold with the NAD(P)-binding Rossmann fold as a case study. Future directions are discussed in the final chapter of the thesis (Chapter-10).

FKBP12 est une protéine ubiquitaire, principalement cytosolique, qui est au carrefour de plusieurs voies signalétiques. Son abondance naturelle dans les tissus nerveux peut être reliée à son implication dans les maladies neurodégénératives telles que les maladies d'Alzheimer et de Parkinson ainsi que dans les neuropathies périphériques et diabétiques ou dans des blessures des cordons spinaux. De nombreuses études ont montré que des molécules exogènes (ligands) venant se fixer sur cette protéine permettent la régénération d'un grand nombre de connexions neuronales endommagées. Une difficulté provient cependant du fait que, pour un ligand donné, il n'existe aucune relation claire entre sa structure et sa capacité de liaison à FKBP12. Notre étude vise ainsi à rationaliser la relation entre la structure d'un ligand et son affinité pour cette protéine. Deux complexes modèles, formés entre FKBP12 et chacun des deux ligands 8 et 308, ont été utilisés. Ces deux ligands de haute affinité ont des structures différentes. Notre travail s'est appuyé sur des simulations de dynamique moléculaire pour caractériser l'état intermédiaire qui est formé transitoirement lors du processus de complexation entre la protéine et son ligand. Dans cet état particulier, l'identification des interactions naissantes entre les partenaires a permis (i) de comprendre l'implication des différentes parties du ligand dans le mécanisme de reconnaissance avec FKBP12 et (ii) de rationaliser les affinités de certains ligands apparentés. / FKBP12 is an ubiquitous, mostly cytosolic, protein found at the crossroads of several signaling pathways. Its natural abundance in the nervous tissues can be related to its implication in neurodegenerative diseases like Alzheimer's and Parkinson's as well as in peripheral neuropathies and diabetes or in injuries of the spinal cords. Several studies have demonstrated that exogenous molecules (ligands) that can bind to FKBP12 allow the regeneration of many damaged neuron connections. However, there is no clear relationship between the structure of a ligand and its ability to bind to FKBP12. Our study aims at rationalizing the relationship between the structure of a ligand and its affinity to FKBP12. Two model complexes, formed between FKBP12 and each of the two high-affinity ligands 8 and 308, were studied. These two ligands are structurally different. We used molecular dynamics simulations to characterize the intermediate state that is transiently formed during the binding process between the protein and its ligand. In this state, the analysis of the nascent interactions allowed (i) to unravel the role played by the various ligand moieties in the recognition process with FKBP12 and (ii) to rationalize the affinities of related ligands.