FtsZ, the principal cell-division protein, polymerizes in GTP-dependent manner in vitro (Bramhill and Thompson, 1994; Mukherjee and Lutkenhaus, 1994; Rivas et al., 2000). FtsZ polymerization at the mid-cell site of bacterium leads to formation of a guiding scaffold, the Z-ring, for bacterial cytokinesis (Bi and Lutkenhaus, 1991; Sun and Margolin, 1998). GTP-induced polymerization process of FtsZ can be monitored in vitro Using 90º light scattering (Mukherjee and Lutkenhaus, 1999) and polymers formed can be visualized using transmission electron microscopy (Lu and Erickson, 1998) or quntitated in terms of the amount of FtsZ polymer pelleted during ultracentrifugation (Mukherjee and Lutkenhaus, 1998). The research work presented in this thesis focused on structure-function correlative analysis of Mycobacterium tuberculosis FtsZ(MtFtsZ0 and FtsZ proteins of Mycobacterium leprae (M1FtsZ), Mycobacterium smegmatis(MsFtsZ), and Streptomyces coelicolor (ScFtsZ) (as it is from Actinomycetes family to which mycobacteria belong) in vitro. It was initiated with investigation on the biochemical properties of Mycobacterium leprae FtsZ (M1FtsZ) in vitro. In comparison with those of MtFtsZ. Subsequently, the role of C-terminal stretch of amino acid residues of MtFtsZ in polymerization was investigated. Finally, a comparative analysis of the biochemical properties of MtFtsZ, MsFtsZ, and ScFtsZ was carried out in order to find out whether a correlation exists between the time taken by the FtsZ of a bacterium to polymerise and the generation time of the organism. The thesis is presented in five chapters. First Chapter gives an exhaustive introduction on the structure-function aspects of FtsZ. Second Chapter deals with materials used in this research work and details of various experimental methods [cloning and expression of FtsZ (White et. Al., 2000), decision and point mutagenesis, preparation of His-tag free MtFtsZ and M1FtsZ by thrombin cleavage method, 90º light scattering (Mukherjee and Lutkenhaus, 1999), White, et al., 2000), transmission electron microscopy (Lu and Erickson, 1998), pelleting assay for polymeric FtsZ (Mukherjee and Lutkenhaus, 1998), GTP-binding by UV-crosslinking (RayChaudhuri and Park, 1992; de Boer et al.,) GTPase assay(RayChaudhuri and Park, 1992); de Boer et al., 1992), Circular Dichroism (Saxena and Wetlaufer, 1971) and ANS fluorescence emission spectroscopy (Semisotnov, et al., 1991)]. The Chapters three to five contain all the data related to the research work, the outlines of which are given below. Chapter 3. Biochemical Characterisation of FtsZ Protein of Mycobacterium leprae In Comparison with the Biochemical Properties of FtsZ Protein of Mycobacteriulm tulberculosis In Vitro The major finding in this part of thesis work is on the demonstration that single reciprocal point mutation partially revives polymerization-inactive M1FtsZ and Inactivates polymerization-active MtFtsZ in vitro. In brief, soluble, recombinant M1FtsZ did not show detectable polymerization in vitro, in contrast to MtFtsZ, which showed appreciable polymerization, under standard conditions, when monitored using 90º light scattering assay and transmission electron microscopy. This was a surprising result, as M1FtsZ and MtFtsZ has 96% protein sequence identity. Mutation f T172 in the N-terminal domain of M1FtsZ to A172, as it exists in MtFtsZ, showed dramatic levels of polymerization in vitro. Reciprocal mutation of A172 in MtFtsZ to T172, as it exists in M1FtsZ, abolished polymerization in vitro. Further, M1FtsZ showed weak GTPase activity, in contrast to MtFtsZ, which showed appreciable GTPase activity. While T172A mutation enhanced GTPase activity of MtFtsZ in vitro. Circular dichroism spectroscopy and ANS fluorescence emission spectroscopy showed that there were no major secondary or tertiary structural changes in these point mutants. These observations demonstrate that the residue at position 172 plays a critical role in the polymerization of M1FtsZ and MtFtsZ, without appreciably affecting their respective GTpPase activity. Further, this result might have implications on evolution of a slow polymerizing FtsZ in slow growing bacteria. Further details of evolution related questions are addressed in Chapter 5. Chapter 4. Role of Carboxy Terminal Residues in the Biochemical Properties of FtsZ Protein of Mycobacterium tuberculosis In Vitro The major finding in this part of thesis work is the demonstration that the C-terminal end residues are critically required for polymerization of MtFtsZ in vitro, which is in direct contrast to the dispensability of C-terminal residues of Escherichia coli FtsZ(EcFtsZ), Bacillus subtilis FtsZ (BsFtsZ), and Pseudomonas aeruginosa (PaFtsZ) for polymerization. FtsZ protein from several bacterial species namely, Methanococcus jannaschii (MjFtsZ), Bacillus subtillis(BsFtsZ), Pseudomonas aeruginosa (PaFtsZ), and Aquifex aeolicus (AaFtsZ) (Lowe and Amos, 1998; Oliva et al., 2007), and Mycobacterium tuberculosis H37Rv (mtFtsZl Leung et al., 2004), whose crystal structures have been solved so far, were found to possess an N-terminal domain and a C-terminal domain that were connected to each other through a helix. The extreme C-terminal portion of all these FtsZ proteins is constituted by an unstructured tail (Lowe and Amos, 1998; Oliva et al., 2007l Leung et al., 2004), which is not found in the respective crystal structure of the protein. We examined whether C-terminal residues of soluble recombinant FtsZ of Mycobacterium tuberculosis (mtFtsZ) have any role in MtFtsZ polymerization in vitro. Deletion of C-terminal 66 residues (313-379) was found to abolish polymerization. Replacement of the C-terminal 66 residues with the extreme C-terminal 13-residue stretch (DDDDVDVPPFMRR) did not restore polymerization. Although the terminal R in DDDDVDVPPFMRR is dispensable for full-length MtFtsZ polymerization, the terminal R in DDDDVDVPPFMR is indispensable for polymerization. Neither replacement of this R, in the terminal R deletion mutant DDDDVDVPPFMR, with K/H/D/A residues enabled polymerization. GTP binding and GTPase activities of the mutants were partially affected. The indispensable nature of C-terminal residues for MtFtsZ polymerization in vitro is contrary to the dispensability of the equivalent extreme C-terminal residues of Escherichi coli, Pseudomonas aeruginosa, and Bacillus subtilis FtsZ (Wang et. Al., 1997; Cordell et al., 2003; Singh et al., 2007) for in vitro polymerization. The essentiality of C-terminal extreme residues of BtFtsZ for polymerization offers direction to design anti MtFtsZ polymerization agents. Chapter 5. An attempt to find correlation between Biochemical properties of FtsZ and Generation Time of the Bacterium The clue that there might be a correlation between FtsZ polymeristion and generation time of the bacterium came from the observation mentioned in chapter 3. The presence of polymerization-aversive T172 in the FtsZ of extremely slow-growing M. leprae 913.5 days generation time, Levy, 1970) and polymerization-favouring A172 in the FtsZ of M. tuberculosis(18hrs generation time, Patterson and Youmans, 1970). For a bacterium, which has short generation time, it might be conducive to have an FtsZ that will also polymerise fast. Conversely, for a bacterium, which has long generation, it might be conducive to have an FtsZ molecule that will polymerise slow. In this respect, a preliminary comparative study was carried out between the generation time of bacterial species, E. coli, Mycobacterium smegmatis, Streptomyces coelicolor, M leprae, and M. tuhberculosis and their respective FtsZ (EcFtsZ, MsFtsZ, M1FtsZ and MtFtsZ). Detailed biochemical characterization of EcFtsZ and MtFtsZ has already been reported in the literature. In this thesis work, biochemical characterisation of M1FtsZ(Chapter 3), ScFtsZ and MsFtsZ (in this Chapter) were carried out. E. coli, which has a generation time of 18-55 min(labrum, 1953), possesses FtsZ (EcFtsZ) that reaches steady state of polymerization in about 10 sec under standard conditions in vitro (Beamhill and Thompson, 1994), using 90º light scattering assay (Mukherjee and Lukenhaus, 1999). On the other hand, M. tuberculosis, which has a generation time of 18hrs in vivo (Patterson and Youmans, 1970) and 24 hrs in vitro (Hiriyanna and Ramakrishnan, 1986) possesses FtsZ (MtFtsZ) that reaches steady state of polymerization in about 6 min post-addiction of GTP in vitro (White et al., 2000). Further, M. leprae, which takes 13.5 days tp divide once in vivo (levy, 1970), possesses an FtsZ (M1FtsZ) that does not even show polymerization under standard conditions in vitro (Chapter 3 of this thesis). The organisms Mycobacterium smegmatis and Streptomyces coelicolor have generation times that fall in between those of the other three organisms mentioned above. While M. smegmatis divides once in 2-3 hrs (Husson, 1998), S. coelicolor has a variable generation time depending on growth condition, which can be as fast as once in 2.31 hours, depending upon growth conditions (Cox, 2004). We found ScFtsZ and MsFtsZ takes around 4 min to reach polymerization saturation after addition of GTP, EcFtsZ( 10 sec), MtFtsZ (10 min) and M1FtsZ (dose not polymerise in vitro) seem to indicate that there exists a correlation between polymerization saturation after addition of GTP, EcFtsZ (10sec), MtFtsZ (10 min) and M1FtsZ (does not polymerise in vitro) seem to indicate that there exists a correlation between polymerization saturation time and the generation time of the respective bacterium. But when we compared polymerization time of ScFtsZ and MsFtsZ (4 min both case) with MtFtsZ ( 6 min), we found that there is no linear correlation with generation time of these bacteria and the time taken by their FtsZ to reach steady state of polymerization. Many more bacterial FtsZ proteins need to be characterized to conclusively state wthether there exist a correlation between generation time of bacteria and the time taken for their FtsZ to reach steady state of polymeristion. Such correlation would simply reveal the fact that the primary structure of an FtsZ protein might have evolved to suit the generation time of the bacterium.

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.