The aminoacyl-tRNA synthetases (aaRSs) are the universal set of enzymes responsible for attaching amino acids to tRNA to be used as substrates in the process of protein translation. As these enzymes act at the transition between nucleic acids and proteins, their specificity of action is critical for maintaining the fidelity of the genetic code. From a mechanistic standpoint, aaRS specificity is enforced by a complex series of tRNA structural and chemical elements that collectively make up its identity set and serve to distinguish one tRNA from another. Based on sequence, structure, and oligomeric differences, the aaRS family has been partitioned into two classes, each of which is responsible for roughly half of the 22 genetically encoded amino acids. In the studies presented here, pre-steady-state kinetic methods were employed to measure individual events that collectively make up the catalytic cycle of the class II Escherichia coli Histidyl-tRNA Synthetase (HisRS) in order to elucidate the nature of its enzymatic activity and determine how these events contribute to the exquisite specificity between enzyme and tRNA. The results presented here indicate indentiy elements of tRNAHis regulate the activity of the amino acid activation and aminoacyl transfer half reactions. Additional evidence suggests communication between active sites of the HisRS homodimer plays a role in establishing an alternating cycle of catalysis in the steady state.

Biological processes are so complicated that to understand the mechanisms underlying the functioning of biomolecules it is inevitable to study them from various perspectives and with a wide range of tools. Understanding the function at the molecular level obviously requires the knowledge of the three dimensional structure of the biomolecules. Experimentally this can be obtained by techniques such as X‐ray crystallography and NMR studies. Computational biology has also played an important role in elucidating the structure function relationship in biomolecules. Computationally one can obtain the temporal as well as ensemble behavior of biomolecules at atomic level under conditions that are experimentally not accessible. Molecular dynamics(MD) study is a technique that can be used to obtain information of the dynamic behavior of the biomolecules. Dynamics of large systems like proteins can be investigated by classical force fields. However, the changes at the level of covalent bond involve the reorganization of electron density distribution which can be addressed only at Quantum mechanical level. In the present thesis, some of the biological systems have been characterized both at the classical and quantum mechanical level. The systems investigated by MD simulations and the insights brought from these studies are presented in Chapters 3 and 4. The unusual bonds such as pyrophosphate linkage in ATP and short strong hydrogen bonds in proteins, investigated through high level quantum chemical methods, are presented in Chapters 5, 6 and 7. Part of this thesis is aimed to address some important issues related to the dynamics of Tryptophanyl tRNA synthetase (TrpRS) which belongs to classic of aminoacyl‐tRNA synthetases (aaRS). aaRSs are extremely important class of enzymes involved in the translation of genetic code. These enzymes catalyze the aminoacylation of tRNAs to relate the cognate amino acids to the anticodon trinucleotide sequences. aaRSs are modular enzymes with distinct domains on which extensive kinetic and mutational experiments as well as structural analyses have been carried out, highlighting the role of inter‐domain communication (Alexander and Schimmel, 2001). The overall architecture of tRNA synthetases consists of primarily two domains. The active site domain is responsible for the activation of an amino acid with ATP in synthesizing an enzyme‐bound aminoacyl‐adenylate, and transfer of the aminoacyl‐adenylate intermediate to the 3’end of tRNA. The second domain is responsible for selection and binding of the cognate tRNA. aaRSs are allosteric proteins in which the binding of tRNA at the anticodon domain influences the activity at the catalytic region. These two binding sites are separated by a large distance. One of the aims of this thesis is to characterize such long distance communication (allosteric communication) at atomic level in Tryptophanyl tRNA synthetase. This is achieved by generating ensembles of conformations by MD simulations and analyzing the trajectories by novel graph theoretic approach. Graph and network based approaches are well established in the field of protein structure analysis for analyzing protein structure, stability and function (Kannan and Vishveshwara, 1999; Brinda and Vishveshwara, 2005). The parameters such as clusters, hubs and shortest paths provide valuable information on the structure and dynamics of the proteins. In this thesis, network parameters are used for the analysis of molecular dynamics MD) simulation data, to represent the global dynamic behavior of protein in a more elegant way. MD simulations are performed on some available (and modeled) structures of TrpRS bound to a variety of ligands, and the protein structure networks( PSN) of non‐covalent interactions are characterized in dynamical equilibrium. The ligand induced conformational changes are investigated through structure networks. These networks are used to understand the mode of communication between the anticodon domain and the active site. The interface dynamics is crucial for the function of TrpRS (since it is a functional dimer) and it is investigated through interface clusters. The matter embodied in the thesis is presented as 9 chapters. Chapter 1 lays the suitable background and foundation for the study, surveying relevant literature from different fields .Chapter 2 describes in detail the various materials, methods and techniques employed in the different analyses and studies presented in this thesis. A brief description of well‐known methods of molecular dynamics simulations, essential dynamics calculations, cross correlation maps, conformational clustering etc.is presented. The methods for constructing protein structure graphs and networks, developed in our lab, are described in detail. The use of network parameters for the analysis of MD simulation data to address the problem of communication between the two distal sites is also presented. Some descriptions of the ab initio quantum mechanical methods, which are used to investigate the unusual bonds in biomolecules, are also presented in this chapter. Chapter 3 is devoted in discussing the results from several normal as well as high temperature MD simulations of ligand‐free and ligand bound Bacillus stearothermophilus Tryptophanyl‐tRNA synthetase (bsTrpRS). The essential modes of the protein in the presence of different ligands are captured by essential dynamics calculations. Different conformations of the protein associated with the catalysis process of TrpRS, as captured through experiments, are discussed in the context of conformational sampling. High temperature simulations are carried out to explore the larger conformational space. Chapter 4 is focused on the results obtained from the MD simulation of human Tryptophanyl‐tRNA synthetase (hTrpRS). The structure of human TrpRS bound to the activated ligand (TrpAMP) and the cognate tRNA(tRNATRP) is modeled since no structure in the presence of both TrpAMP and tRNATRP is available. MD simulations on these modeled as well as other complexes of hTrpRS are performed to capture the dynamical process of ligand induced conformational changes (Hansiaetal., communicated). Both the local and the global changes in the protein conformation from the protein structure network (PSN) of MD snapshots are analyzed. Several important information such as the ligand induced correlation between different residues of the protein, asymmetric binding of the ligands to the two subunits of the protein, and the path of communication between the anticodon region and the aminoacylation site are obtained. Also, the role of the dimmer interface, from a dynamic perspective, is obtained for the first time. The interface dynamics which stabilize different quaternary structures of lectins (with high sequence and structure similarity) were investigated in a collaborative work (Hansiaetal.,2007). The lectin peanut agglutinin (PNA) is a tetramer with three different types of interfaces. The interface dynamics of this protein in the presence and in the absence of metal ions was investigated and the paper reporting the results from this study is included as appendix in this thesis. Chapter 5 deals with high level ab initio quantum chemical calculations on tri‐ and diphosphate fragments of adenosine triphosphate (ATP). Pyrophosphate prototypes such as methyl triphosphate and methyl diphosphate molecules in their different protonation states have been investigated at high levels of calculations (Hansiaetal., 2006a). The optimized geometries, the thermochemistry of the hydrolysis and the molecular orbitals contributing to the high energy of these compounds have been analyzed. These investigations provide insights into the‘‘highenergy’’character of ATP molecule. Further, the dependence of vibrational frequencies on the number of phosphate groups and the charged states has also been presented. These results aid in the interpretation of spectra obtained by experiments on complexes containing pyrophosphate prototypes. Hydrogen bonding is fundamental in understanding the structure and properties of molecules of biological interest including proteins. A recent analysis carried out in our lab showed that a significant number of short hydrogen bonds (SHB) are present in proteins (Rajagopal and Vishveshwara, 2005). Chapters 6 and 7 elucidate the results obtained from ab initio quantum chemical calculations on some of these SHBs to get aquantitative estimation of their geometry and strength. In chapter 6, asystematic analysis of the geometries and the energetics of possible SHB systems, which are frequently encountered in proteins, are presented at different levels of theory (HF,DFTandMP2). It is found that the SHBs involving both charged residues in the proteins are intrinsic in nature. However, two neutral residues form a SHB in the protein crystal structures either due to geometric constraints or due to the environment of these residues. This analysis enables one to distinguish SHBs which are formed because of geometric constraints from those which are formed because of the inherent property of the chemical groups involved in the hydrogen bonding. These results are useful in refining protein structures determined by crystallographic or NMR methods. In addition, sulfur atom of methionine and cysteinein proteins also participate in SHBs, which are not so well characterized. Chapter 7 presents the similar analysis carried out on short hydrogen bonds in proteins involving sulfur atom. A detailed analysis of SHBs of sulfur containing groups in a data set of proteins has been carried out. Some of the residue pairs from this analysis were considered for ab initio calculations. However, the optimization of these examples resulted in breaking of the hydrogen bonds involving sulfur atoms and formation of new hydrogen bonds with oxygen and/or nitrogen atoms. Hence model systems, which mimic the real examples, were designed to carry out ab initio studies and to investigate the short hydrogen bonds involving sulfur atoms. Another study on the protein‐water interaction, which does not fall under the realm of the main objective of the thesis, is discussed in Chapter 8. Protein–water interaction is crucial for accomplishing many biological functions of proteins. In the recent past, natural probe tryptophan, located at the protein surfaces, has been extensively investigated using femtosecond spectroscopy experiments to understand salvation dynamics (Peonetal.,2002). In this chapter a method is described to follow up the molecular events of the protein–water interactions in detail. Tryptophan–water interaction in the protein Monellin is investigated in order to get the atomic level insights into the hydration dynamics, by carrying out MD simulations on Monellin (Hansiaetal.,2006b). The results are compared with those obtained from femtosecond resolved fluorescence spectroscopy. The time constants of the survival correlation function match well with the reported experimental values.This validates the procedure, adapted here for Monellin, to investigate the hydration dynamics in general. The last chapter (Chapter9) summarizes the results obtained from various studies and discusses the future directions. First part of this thesis aims to present the analysis by carrying out MD simulations on monomeric and dimeric TrpRS protein in order to understand the two steps of the aminoacylation reaction: activation of the aminoacid Trp in the first step and the transfer of the activated amino acid in the next step. In the second part, quantitative estimation of the geometry and the strength of pyrophosphate bond and short hydrogen bonds in proteins are reported in detail by subjecting the systems to high levels of quantum mechanical calculations(QM). The use of ab initio QM/MM calculations by combining the quantum mechanics(QM) with the molecular mechanics(MM) in order to study the enzymatic reactions is discussed as the future

Aminoacyl-tRNA synthetases (aaRSs) are at the center of the question of the origin of life and are essential proteins found in all living organisms. AARSs arose early in evolution to interpret genetic code and are believed to be a group of ancient proteins. They constitute a family of enzymes integrating the two levels of cellular organization: nucleic acids and proteins. These enzymes ensure the fidelity of transfer of genetic information from the DNA to the protein. They are responsible for attaching amino acid residues to their cognate tRNA molecules by virtue of matching the nucleotide triplet, which is the first step in the protein synthesis. The translation of genetic code into protein sequence is mediated by tRNA, which accurately picks up the cognate amino acids. The attachment of the cognate amino acid to tRNA is catalyzed by aaRSs, which have binding sites for the anticodon region of tRNA and for the amino acid to be attached. The two binding sites are separated by ≈ 76 Å and experiments have shown that the communication does not go through tRNA (Gale et al., 1996). The problem addressed here is how the information of binding of tRNA anticodon near the anticodon binding site is communicated to the active site through the protein structure. These enzymes are modular with distinct domains on which extensive kinetic and mutational experiments and supported by structural data are available, highlighting the role of inter-domain communication (Alexander and Schimmel, 2001). Hence these proteins present themselves as excellent systems for in-silico studies. Various methods involved for the construction of protein structure networks are well established and analyzed in a variety of ways to gain insights into different aspects of protein structure, stability and function (Kannan and Vishveshwara, 1999; Brinda and Vishveshwara, 2005). In the present study, we have incorporated network parameters for the analysis of molecular dynamics (MD) simulation data, representing the global dynamic behavior of protein in a more elegant way. MD simulations have been performed on the available (and modeled) structures of aaRSs bound to a variety of ligands, and the protein structure networks (PSN) of non-covalent interactions have been characterized in dynamical equilibrium. The changes in the structure networks are used to understand the mode of communication, and the paths between the two sites of interest identified by the analysis of the shortest path. The allosteric concept has played a key role in understanding the biological functions of aaRSs. The rigidity/plasticity and the conformational population are the two important ideas invoked in explaining the allosteric effect. We have explored the conformational changes in the complexes of aaRSs through novel parameters such as cliques and communities (Palla et al., 2005), which identify the rigid regions in the protein structure networks (PSNs) constructed from the non-covalent interactions of amino acid side chains. The thesis consists of 7 chapters. The first chapter constitutes the survey of the literature and also provides suitable background for this study. The aims of the thesis are presented in this chapter. Chapter 2 describes various techniques employed and the new techniques developed for the analysis of PSNs. It includes a brief description of well -known methods of molecular dynamics simulations, essential dynamics, and cross correlation maps. The method used for the construction of graphs and networks is also described in detail. The incorporation of network parameters for the analysis of MD simulation data are done for the first time and has been applied on a well studied protein lysozyme, as described in chapter 3. Chapter 3 focuses on the dynamical behavior of protein structure networks, examined by considering the example of T4-lysozyme. The equilibrium dynamics and the process of unfolding are followed by simulating the protein with explicit water molecules at 300K and at higher temperatures (400K, 500K) respectively. Three simulations of 10ns duration have been performed at 500K to ensure the validity of the results. The snapshots of the protein structure from the simulations are represented as Protein Structure Networks (PSN) of non-covalent interactions. The strength of the non-covalent interaction is evaluated and used as an important criterion in the construction of edges. The profiles of the network parameters such as the degree distribution and the size of the largest cluster (giant component) have been examined as a function of interaction strength (Ghosh et al., 2007). We observe a critical strength of interaction (Icritical) at which there is a transition in the size of the largest cluster. Although the transition profiles at all temperatures show behavior similar to those found in the crystal structures, the 500K simulations show that the non-native structures have lower Icritical values. Based on the interactions evaluated at Icritical value, the folding/unfolding transition region has been identified from the 500K simulation trajectories. Furthermore, the residues in the largest cluster obtained at interaction strength higher than Icritical have been identified to be important for folding. Thus, the compositions of the top largest clusters in the 500K simulations have been monitored to understand the dynamical processes such as folding/unfolding and domain formation/disruption. The results correlate well with experimental findings. In addition, the highly connected residues in the network have been identified from the 300K and 400K simulations and have been correlated with the protein stability as determined from mutation experiments. Based on these analyses, certain residues, on which experimental data is not available, have been predicted to be important for the folding and the stability of the protein. The method can also be employed as a valuable tool in the analysis of MD simulation data, since it captures the details at a global level, which may elude conventional pair-wise interaction analysis. After standardizing the concept of dynamical network analysis using Lysozyme, it was applied to our system of interest, the aaRSs. The investigations carried out on Methionyl-tRNA synthetases (MetRS) are presented in chapter 4. This chapter is divided into three parts: Chapter 4A deals with the introduction to aminoacyl tRNA synthetases (aaRS). Classification and functional insights of aaRSs obtained through various studies are presented. Chapter 4B is again divided into parts: BI and BII. Chapter 4BI elucidates a new technique developed for finding communication pathways essential for proper functioning of aaRS. The enzymes of the family of tRNA synthetases perform their functions with high precision, by synchronously recognizing the anticodon region and the amino acylation region, which is separated by about 70Å in space. This precision in function is brought about by establishing good communication paths between the two regions. We have modelled the structure of E.coli Methionyl tRNA synthetase, which is complexed with tRNA and activated methionine. Molecular dynamics simulations have been performed on the modeled structure to obtain the equilibrated structure of the complex and the cross correlations between the residues in MetRS. Furthermore, the network analysis on these structures has been carried out to elucidate the paths of communication between the aminoacyl activation site and the anticodon recognition site (Ghosh and Vishveshwara, 2007). This study has provided the detailed paths of communication, which are consistent with experimental results. A similar study on the (MetRS + activated methionine) and (MetRS+tRNA) complexes along with ligand free-native enzyme has also been carried out. A comparison of the paths derived from the four simulations has clearly shown that the communication path is strongly correlated and unique to the enzyme complex, which is bound to both the tRNA and the activated methionine. The method developed here could also be utilized to investigate any protein system where the function takes place through long distance communication. The details of the method of our investigation and the biological implications of the results are presented in this chapter. In chapter 4BII, we have explored the conformational changes in the complexes of E.coli Methionyl tRNA synthetase (MetRS) through novel parameters such as cliques and communities, which identify the rigid regions in the protein structure networks (PSNs). The rigidity/plasticity and the conformational population are the two important ideas invoked in explaining the allosteric effect. MetRS belongs to the aminoacyl tRNA Synthetases (aaRSs) family that play a crucial role in initiating the protein synthesis process. The network parameters evaluated here on the conformational ensembles of MetRS complexes, generated from molecular dynamics simulations, have enabled us to understand the inter-domain communication in detail. Additionally, the characterization of conformational changes in terms of cliques/communities has also become possible, which had eluded conventional analyses. Furthermore, we find that most of the residues participating in clique/communities are strikingly different from those that take part in long-range communication. The cliques/communities evaluated here for the first time on PSNs have beautifully captured the local geometries in their detail within the framework of global topology. Here the allosteric effect is revealed at the residue level by identifying the important residues specific for structural rigidity and functional flexibility in MetRS. Chapter 4C focuses on MD simulations of Methionyl tRNA synthetase (AmetRS) from a thermophilic bacterium, Aquifex aeolicus. As describe in Chapter 4B, we have explored the communication pathways between the anticodon binding region and the aminoacylation site, and the conformational changes in the complexes through cliques and communities. The two MetRSs from E.coli and Aquifex aeolicus are structurally and sequentially very close to each other. But the communication pathways between anticodon binding region and the aminoacylation site from A. aeolicus have differed significantly with the communication paths obtained from E.coli. The residue composition and cliques/communities structure participating in communication are not similar in the MetRSs of both these organisms. Furthermore the formation of cliques/communities and hubs in the communication paths are more in A. aeolicus compared to E.coli. The participation of structurally homologous linker peptide, essential for orienting the two domains for efficient communication is same in both the organisms although, the residues composition near domain interface regions including the linker peptide is different. Thus, the diversity in the functioning of two different MetRS has been brought out, by comparing the E.coli and Aquifex aeolicus systems. Protein Structure network analysis of MD simulated trajectories of various ligand bound complexes of Escherichia coli Cysteinyl-tRNA synthetase (CysRS) have been discussed in Chapter 5. The modeling of the complex is done by docking the ligand CysAMP into the tRNA bound structure of E.coli Cysteinyl tRNA synthetase. Molecular dynamics simulations have been performed on the modeled structure and the paths of communications were evaluated using a similar method as used in finding communication paths for MetRS enzymes. Compared to MetRS the evaluation of communication paths in CysRS is complicated due to presence of both direct and indirect readouts. The direct and indirect readouts (DR/IR) involve interaction of protein residues with base-specific functional group and sugar-phosphate backbone of nucleic acids respectively. Two paths of communication between the anticodon region and the activation site has been identified by combining the cross correlation information with the protein structure network constructed on the basis of non-covalent interaction. The complete paths include DR/IR interactions with tRNA. Cliques/communities of non-covalently interacting residues imparting structural rigidity are present along the paths. The reduction of cooperative fluctuation due to the presence of community is compensated by IR/DR interaction and thus plays a crucial role in communication of CysRS. Chapter 6 focuses on free energy calculations of aminoacyl tRNA synthetases with various ligands. The free energy contributions to the binding of the substrates are calculated using a method called MM-PBSA (Massova and Kollman, 2000). The binding free energies were calculated as the difference between the free energy of the enzyme-ligand complex, and the free ligand and protein. The ligand unbinding energy values obtained from the umbrella sampling MD correlates well with the ligand binding energies obtained from MM-PBSA method. Furthermore the essential dynamics was captured from MD simulations trajectories performed on E.coli MetRS, A. aeolius MetRS and E.coli CysRS in terms of the eigenvalues. The top two modes account for more than 50% of the motion in essential space for systems E.coli MetRS, A. aeolius MetRS and E.coli CysRS. Population distribution of protein conformation states are looked at the essential plane defined by the two principal components with highest eigenvalues. This shows how aaRSs existed as a population of conformational states and the variation with the addition of ligands. The population of conformational states is converted into Free energy contour surface. From free energy surfaces, it is evident that the E.coli tRNAMet bound MetRS conformational fluctuations are more, which attributes to less rigidity in the complex. Whereas E.coli tRNACys bound CysRS conformational fluctuations are less and this is reflected in the increase in rigidity of the complex as confirmed by its entropic contribution. Future directions have been discussed in the final chapter (Chapter 7). Specifically, it deals with the ab-initio QM/MM study of the enzymatic reaction involved in the active site of E.coli Methionyl tRNA synthetase. To achieve this, two softwares are integrated: the Quantum Mechanics (QM) part includes small ligands and the Molecular Mechanics (MM) part as protein MetRS are handled using CPMD and Gromacs respectively. The inputs for two reactions pathways are prepared. First reaction involves cyclization reaction of homocysteine in the active site of MetRS and the second reaction deals with charging of methionine in the presence of ATP and magnesium ion. These simulations require very high power computing systems and also time of computation is also very large. With the available computational power we could simulate up to 10ps and it is insufficient for analysis. The future direction will involve the simulations of these systems for longer time, followed by the analysis for reaction pathways.