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Workshop on HPC in India ATIP 1 st Workshop on HPC in SC-09 Saraswathi Vishveshwara Molecular Biophysics Unit Indian Institute of Science Bangalore.

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Presentation on theme: "Workshop on HPC in India ATIP 1 st Workshop on HPC in SC-09 Saraswathi Vishveshwara Molecular Biophysics Unit Indian Institute of Science Bangalore."— Presentation transcript:

1 Workshop on HPC in India ATIP 1 st Workshop on HPC in SC-09 Saraswathi Vishveshwara Molecular Biophysics Unit Indian Institute of Science Bangalore Understanding Protein stability and Function through simulations and Structure networks Workshop on HPC in India

2 HPC in Biology a)Use of quantum chemistry to understand enzyme mechanism at the level of covalent bonds b) Molecular dynamics simulations in the classical regime to generate equilibrium population of protein conformations Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 2

3 Protein Structure to Function Fold evolutionary relationships Biological multimeric states Disease states mutations Active sites, enzyme clefts Antigenic sites Surface properties 3D STRUCTURE Protein-Ligand Interactions Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 3

4 Outline Generation of equilibrium ensemble of protein structures in their unbound and complex states, by extensive molecular dynamics (MD) simulations. Analysis of the ensemble through network parameters by representing the structure as a network of non-bonded interactions. Evaluation of conformational free energy by integrating MD simulations and network analysis Investigate functional correlations with the free energy landscape Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 4

5 1. Simulation trajectories of H.pylori LuxS (10ns for each system) A: LuxS B: LuxS + SRH C: LuxS + 2SRH Total no. of protein residues ~ 145 Examples of MD simulations from our Lab Bhattacharyya, M., and Vishveshwara, S. (2009) Functional correlation of bacterial LuxS with their quaternary associations: Interface analysis of the structure networks, BMC Structural Biology 9, 8. Bhattacharyya, M., and Vishveshwara, S. (Simulations of LuxS related manuscript submitted ) Simulations are performed using AMBER package LuxS is a bacterial enzyme involved in a variety of functions- like quorum sensing, toxicity, etc Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 5

6 2. Simulation trajectories of A. aeolicus MetRS (10ns for each system) A: AmetRS B: AmetRS + MetAMP C: AmetRS + MetAMP + tRNA Total no. of protein+ligand residues ~ Simulation trajectories of human TrpRS (5ns for each system) 1: monomeric TrpRS 2: dimeric TrpRS 3: dimeric TrpRS+2TrpAMPs 4: dimeric TrpRS+1tRNA+2TrpAMPs 5: dimeric TrpRS+2tRNAs+2Trps 6: dimeric TrpRS+2tRNAs+2TrpAMPs Total no. of protein+ligand residues ~ Ghosh, A., and Vishveshwara, S. (2007) A study of communication pathways in methionyl- tRNA synthetase by molecular dynamics simulations and structure network analysis, Proc. Natl. Acad. Sci. U.S.A. 104, Ghosh, A., and Vishveshwara, S. (2008) Variations in Clique and Community Patterns in Protein Structures during Allosteric Communication: Investigation of Dynamically Equilibrated Structures of Methionyl tRNA Synthetase Complexes, Biochemistry 47, Hansia, P., Ghosh, A., Vishveshwara, S. (2009) Ligand dependent intra and inter subunit communication in human tryptophanyl tRNA synthetase as deduced from the dynamics of structure networks, Mol. Biosyst. DOI: /b903807h Bhattacharyya, M., Ghosh, A.,Hansia, P.,Vishveshwara S. (2009) Allostery and conformational free energy changes in human tryptophanyl-tRNA synthetase from essential dynamics and structure networks, Proteins: Structure Function Bioinformatics DOI: /prot Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 6

7 6 systems of TrpRS 30ns ~57 days Example: Trp-tRNA synthetase Number of atoms in protein + tRNA: Number of water molecules added: Total simulation time for 5ns simulation: 9.5 days On an Intel Xeon E5440-Quad Core (using 32 processors) machine. System Sizes and Simulation Times Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 7

8 Analysis of Simulation Trajectories to Establish Structure-Function Correlations Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 8

9 Conventional Methods of structure Analysis Backbone Topology Identification of secondary structures, folds, families Compare the structures (RMSD) Side-chain analysis Identify hydrogen bonds, salt bridges, conformational rotamer Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 9

10 Novel and effective method of analysis to characterize side-chain interactions Protein structures can be represented as Graphs/Networks Structure network analysis provides a global view of the connections Network parameters of interest Clusters Hubs Shortest path between two nodes Cliques/Communities Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 10

11 Protein structures as Graphs Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 11

12 High and low contact criteria. A pair of phenylalanine rings interacting with each other are shown. The lines between the phenylalanines indicate the atoms that are within a distance of 4.5Å. a) High Contactb) Low Contact Quantifying Side Chain Interactions c)No interaction High (Iij=11%) Iij=0% Low (Iij=4%) I ij = (n ij  (N i *N j ))  100 I min is user defined interaction cutoff. An (ij) residue pair with I ij > I min is connected by an edge. Kannan, Visveshwara, JMB (1999) Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 12

13 Hubs Vicsek et al Nature (2005). Ciques/Communities Protein Structure Network-Parameters Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 13

14 Integration of simulations with network analysis can provide valuable functional information Simulations can provide dynamical properties such as equilibrium conformation, fluctuations, conformational populations Function involves dynamics Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 14

15 Network communication in Methionyl-tRNA synthetase Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 15

16 tRNA Catalytic domain Anticodon binding domain 70A Communication between the anticodon region and the active-site region is crucial for the faithful translation of the genetic code Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC Aminoacyl tRNA Synthetase (AARS)

17 MD simulations on MetRS complexes A:MetRS B: MetRS+MetAMP C:MetRS+tRNA D:MetRS+tRNA+MetAMP Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 17

18 Dynamical cross correlation maps representing the collective atomic fluctuations MetRS+tRNA+MetAMPMetRS Leu13-His28-Lys388-Trp461 Correlated paths between two nodes extracted from simulations Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 18

19 Communication paths between the anti-codon region and the active site in MetRS Amit Ghosh and S. Vishveshwara, PNAS (2007) Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 19

20 Summary of the method of path identification CPPS Review 10 (2): (2009) Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 20

21 Ligand induced variations in flexibility and rigidity of proteins Tracking through cliques and communities Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 21

22 Population Shift MetRS MetRS+MetAMP MetRS+MetAMP+tRNA Major population derived from dynamically stable cliques/communities Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC Ghosh, A., and Vishveshwara, S. (2008) Biochemistry 47,

23 Exploration of the Free-energy landscape Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 23

24 24 METHOD: Simulation of the liganded and the unliganded structures of the protein Construction of covariance matrix on the basis of the atomic positional fluctuations Diagonalization of the covariance matrix to obtain the eigenvalues and eigenvectors Calculation of relative cumulative positional fluctuation (RCPF) Relative cumulative positional fluctuation gives the amount of dynamics constituted by the top essential modes An essential plane defined by the two principal components with highest eigenvalues Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC ESSENTIAL DYNAMICS ANALYSIS AND SAMPLING OF CONFORMATIONAL SPACE

25 UNLIGANDED E.coli METRSE.coli METRS+MET E.coli METRS+METAMPE.coli METRS+METAMP+tRNA CONTOUR MAPS OF POPULATION DISTRIBUTION AS A FUNCTION OF THE POSITION IN THE ESSENTIAL PLANE Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 25

26 Major conformational populations in terms of cliques/communities Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 26

27 UPPER LOBE ENERGY SURFACE IS HIGH LOWER LOBE ENERGY SURFACE IS LOW METRS+METAMP+TRNA METRS; METRS+MET; METRS+METAMP Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC FREE ENERGY CONTOUR MAP IN THE COLLECTIVE CONFORMATIONAL SPACE

28 Helmholtz Free Energy Contour Map p i and p ref probabilities of finding the system in state i and state ref respectively Free Energy Contour Plot for Systems under Study Transform information from MD simulationFree Energy Landscape Bhattacharyya, et.al., Proteins: Structure Function Bioinformatics DOI: /prot (2009) Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 28

29 Tryptophanyl tRNA Synthetase- Functional dimer Cross Correlation Maps Hansia, et.al., Mol. Biosyst. DOI: /b903807h (2009) Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 29

30 TrpRS dimer Interface cluster Asymmetric participation of residues at the interface Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 30

31 Essential Dynamics: Population Distribution Profile and Helmholtz Free Energy Sys1 Sys2 Sys3 Regions marked with digits indicate the energy minima for each contour regions in each system Sys1 (hTrpRS) Sys2 (hTrpRS+2tRNA) Sys3 (hTrpRS+2tRNA+2TYM) Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 31

32 Thermal stability is encoded in thermodynamics Energy landscape of E.Coli- MetRS complexes Energy landscape of Aquifex- MetRS complexes Energy landscapes of proteins performing the same function in a thermophilic and a mesophilic organism differ Amit Ghosh, S. Vishveshwara, manuscript to be submitted) Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 32

33 Total number of Protein + Ligand atoms: Total number of water molecules added: ~ Simulation time per ns: 32 hours on an Intel Xeon 2.66GHz) processor (using 32 processors) 4 systems of MutS total 210 ns ~137 days Collaboration with Prof. D.L. Beveridge, Wesleyan University The trajectories are stored every 20 ps for each of the 4 systems MutS Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 33

34 Understanding of the biological functions requires a knowledge of the dynamics of Macromolecular assemblies, which are much larger in size. For example, the Ribosome ( RNA-protein complex) contains Total number of nucleotide+amino acid residues:10374 Ribosome Future Challenges Simulations of Molecular assemblies mRNA 16SrRNA 23SrRNA mRNA 16SrRNA 23SrRNA Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 34

35 Summary Many crucial biological functions are controlled by macromolecular dynamics, which are sensitive to perturbations like binding of ligands Extensive equilibrium dynamics simulations and a careful analysis of the trajectories are required to understand the subtle changes brought out by interaction with molecules that play a crucial functional role. Diversity is the hallmark of biology. Each system should be carefully investigated. Hence HPC will contribute towards understanding the subtleness with which the biological systems function HPC would also prove to be useful in designing better drug targets Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 35

36 Acknowledgements Dr. Amit Ghosh MetRS, CysRS Dr. Priti Hansia TrpRS Dr. Sathyapriya and Mr. Vijaybhaskar Protein-DNA interaction Mr. Anupam Nath Jha Membrane proteins Ms. Moitrayee Bhattacharyya LuxS, Free-energy Landscape Dr Brinda, Dr.Kannan Development of structure network Computing facilities : SERC-IISc, DBT and DST (Govt. of India) Saraswathi Vishveshwara ATIP 1 st Workshop on HPC in SC-09 36


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