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

The flow of genetic information from genes to proteins is mediated through proteins which interact with the nucleic acids at several stages to successfully transmit the information from the nucleus to the cell cytoplasm. Unlike in the case of protein-protein interactions, the principles behind protein-nucleic acid interactions are still not very (Pabo and Nekludova, 2000) and efforts are still underway to arrive at the basic principles behind the specific recognition of nucleic acids by proteins (Prabakaran et al., 2006). This is mainly due to the innate complexity involved in recognition of nucleotides by proteins, where, even within a given family of DNA binding proteins, different modes of binding and recognition strategies are employed to suit their function (Luscomb et al., 2000). Such difficulties have also not made possible, a thorough classification of DNA/RNA binding proteins based on the mode of interaction as well as the specificity of recognition of the nucleotides. The availability of a large number of structures of protein-nucleic acids complexes (albeit lesser than the number of protein structures present in the PDB) in the past few decades has provided the knowledge-base for understanding the details behind their molecular mechanisms (Berman et al., 1992). Previously, studies have been carried out to characterize these interactions by analyzing specific non-covalent interactions such as hydrogen bonds, van der Walls, and hydrophobic interactions between a given amino acid and the nucleic acid (DNA, RNA) in a pair-wise manner, or through the analysis of interface areas of the protein-nucleic acid complexes (Nadassy et al., 1998; Jones et al., 1999). Though the studies have deciphered the common pairing preferences of a particular amino acid with a given nucleotide of DNA or RNA, there is little room for understanding these specificities in the context of spatial interactions at a global level from the protein-nucleic acid complexes. The representation of the amino acids and the nucleotides as components of graphs, and trying to explore the nature of the interactions at a level higher than exploring the individual pair-wise interactions, could provide greater details about the nature of these interactions and their specificity. This thesis reports the study of protein-nucleic interactions using graph and network based approaches. The evaluation of the parameters for characterizing protein-nucleic acid graphs have been carried out for the first time and these parameters have been successfully employed to capture biologically important non-covalent interactions as clusters of interacting amino acids and nucleotides from different protein-DNA and protein-RNA complexes. 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). However, the use of graph and network principles for analyzing structures of protein-nucleic acid complexes is so far not accomplished and is being reported the first time in this thesis. The matter embodied in the thesis is presented as ten chapters. Chapter 1 lays the foundation for the study, surveying relevant literature from the field. Chapter 2 describes in detail the methods used in constructing graphs and networks from protein-nucleic acid complexes. Initially, only protein structure graphs and networks are constructed from proteins known to interact with specific DNA or RNA, and inferences with regard to nucleic acid binding and recognition were indirectly obtained . Subsequently, parameters were evaluated for representing both the interacting amino acids and the nucleotides as components of graphs and a direct evaluation of protein-DNA and Protein-RNA interactions as graphs has been carried out. Chapter 3 and 4 discuss the graph and network approaches applied to proteins from a dataset of DNA binding proteins complexed with DNA. In chapter 3, the protein structure graphs were constructed on the basis of the non-covalent interactions existing between the side chains of amino acids. Clusters of interacting side chains from the graphs were obtained using the graph spectral method. The clusters from the protein-DNA interface were analyzed in detail for the interaction geometry and biological importance (Sathyapriya and Vishveshwara, 2004). Chapter 4 also uses the same dataset of DNA binding proteins, but a network-based approach is presented. From the analysis of the protein structure networks from these DNA binding proteins, interesting observations relating the presence of highly connected nodes(or hubs) of the network to functionally important amino acids in the structure, emerged. Also, the comparison between the hubs identified from the protein-protein and the protein-DNA interfaces in terms of their amino acid composition and their connectivity are also presented (Sathyapriya and Vishveshwara, 2006) Chapter 5 and 6 deal with the graph and network applications to a specific system of protein-RNA complex (aminoacyl-tRNA synthetases) to gain insights into their interface biology based on amino acid connectivity. Chapter 5 deals with a dataset of aminoacyl-tRNA synthetase (aaRS) complexes obtained with various ligands like ATP, tRNA and L-amino acids. A graph based identification of side chain clusters from these ligand-bound aaRS structures has highlighted important features of ligand-binding at the catalytic sites of the two structurally different classes of aaRS (Class I and Class II). Side chain clusters from other regions of aaRS such as the anticodon binding region and the ligand-activation sites are discussed. A network approach is used in a specific system of aaRS(E.coli Glutaminyl-tRNA synthetase (GlnRS) complexed with its ligands, to specifically understand the effects of different ligand binding., in chapter 6. The structure networks of E.coli GlnRS in the ligand-free and different ligand-bound states are constructed. The ligand-free and the ligand-bound complexes are compared by analyzing their network properties and the presence of hubs to understand the effect of ligand-binding. These properties have elegantly captured the effects of ligand-binding to the GlnRS structure and have also provided an alternate method for comparing three dimensional structures of proteins in different ligand-bound states (Sathyapriya and Vishveshwara, 2007). In contrast to protein structure graphs (PSG), both the interacting amino acids and nucleotides (DNA/RNA) form the components of the protein-nucleic acid graphs (PNG) from protein-nucleic acid complexes. These graphs are constructed based on the non-covalent interactions existing between the side chains of the amino acids and nucleotides. After representing the interacting nucleotides and amino acids as graphs, clusters of the interacting components are identified. These clusters are the strongly interacting amino acids and nucleotides from the protein-nucleic acid complexes. These clusters can be generated at different strengths of interaction between the amino acid side chain and the nucleotide (measured in terms of its atomic connectivity) and can be used for detecting clusters of non-specific as well as specific interactions of amino acids and nucleotides. Though the methodology of graph construction and cluster identification are given in chapter 2, the details of the parameters evaluated for constructing PNG are given in chapter 7. Unlike in the previous chapters, the succeeding chapters deal exclusively with results that are obtained from the analyses of PNG. Two examples of obtaining clusters from a PNG are given, one each for a protein-DNA and a protein-RNA complex. In the first example, a nucleosome core particle is subjected to the graph based analysis and different clusters of amino acids with different regions of the DNA chain such as phosphate, deoxyribose sugar and the base are identified. Another example of aminoacyl-tRNA synthetase complexed with its cognate tRNA is used to illustrate the method with a protein-RNA complex. Further, the method of constructing and analyzing protein-nucleic acid graphs has been applied to the macromolecular machinery of the pre-translocation complex of the T. thermophilus 70S ribosome. Chapter 8 deals exclusively with the results identified from the analysis of this magnificent macromolecular ensemble. The availability of the method that can handle interactions between both amino acids and the nucleotides of the protein-nucleic acid complexes has given us the basis fro evaluating these interactions in a level higher than that of analyzing pair-wise interactions. A study on the evaluation of short hydrogen bonds(SHB) in proteins, which does not fall under the realm of the main objective of the thesis, is discussed in the Chapter 9. The short hydrogen bonds, defined by the geometrical distance and angle parameters, are identified from a non-redundant dataset of proteins. The insights into their occurrence, amino acid composition and secondary structural preferences are discussed. The SHB are present in distinct regions of protein three-dimensional structures, such that they mediate specific geometrical constraints that are necessary for stability of the structure (Sathyapriya and Vishveshwara, 2005). The significant conclusions of various studies carried out are summarized in the last chapter (Chapter 10). In conclusion, this thesis reports the analyses performed with protein-nucleic acid complexes using graph and network based methods. The parameters necessary for representing both amino acids and the nucleotides as components of a graph, are evaluated for the first time and can be used subsequently for other analyses. More importantly, the use of graph-based methods has resulted in considering the interaction between the amino acids and the nucleotides at a global level with respect to their topology of the protein-nucleic acid complexes. Such studies performed on a wide variety of protein-nucleic acid complexes could provide more insights into the details of protein-nucleic acid recognition mechanisms. The results of these studies can be used for rational design of experimental mutations that ascertain the structure-function relationships in proteins and protein-nucleic acid complexes.