Protein structure sampling based on molecular dynamics and improvement of docking prediction

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1 1 1, 2 1 NMR X Protein structure sampling based on molecular dynamics and improvement of docking prediction Yusuke Matsuzaki, 1 Yuri Matsuzaki, 1 Masakazu Sekijima 1, 2 and Yutaka Akiyama 1 When a protein structure in the solvent changes greatly from its structre decided by NMR or X-ray crystallographic analysis, or a structural change is needed for docking, it is difficult to computationally predict the structure of the complex precisely with the rigid protein-protein docking method. In order to solve this problem, we calculate the ensemble of the protein conformations with molecular dynamics simulation, and then the cluster analysis is applied, and candidates structural group for rigid-docking is extracted. As a result, a protein-protein docking prediction that considers the structural change is achieved by executing the existing rigid-docking calculation with the obtained structures. 1. (PPI: protein-protein interaction) PPI bound docking NMR X bound docking unbound docking (MD: Molecular Dynamics) 2 1 AMBER 10 1) sander ZDOCK 3.0.1 2)3) ZDOCK benchmark 2.0 4) 1 Department of Computer Science Graduate School of Information Science and Engineering, Tokyo Institute of Technology 2 Global Scientific Information and Computing Center, Tokyo Institute of Technology 1 c 2009 Information Processing Society of Japan

2. 2.1 PDB 5) 1nsec sander 1 TSUBAME Grid Cluster 1 ZDOCK benchmark 2.0 PDB http://zlab.bu.edu/julianm/benchmark/ AMBER 10 protonate PDB HETATM 2.2 2.1 1 AMBER10 Table 1 Calculation condition of AMBER 10. Prior processing Solvation box Minimization minimization cycles 2000 Equilibration simulation time temperature ensemble TIP3PBOX (buffer: 10Å closeness 1.0Å) 40psec 0 300K(20psec), 300K(20psec) NVT nonbonded cutoff 8.0Å Molecular Dynamics simulation time temperature ensemble 1nsec 300K NPT nonbonded cutoff 8.0Å 1 CPU Opteron 880(2.4GH) 8 32GB 6) 2.2.1 Kabsch 7) RMSD(Root Mean Square Deviation) RMSD Cα RMSD http://www.personal.leeds.ac.uk/ bgy1mm/bioinformatics/rmsd.html 2.2.2 K-means 2 RMSD K-means 1nsec 5psec 200 10 1 2 3 4 4 8) RMSD RMSD δ d d(g i, G j ) = 1 2 δ2 G := G q G r [ d(g 1, G i) = ( G q + G i )d(g q, G i ) G q + G r + G i ] +( G r + G i )d(g r, G i ) G i d(g q, G r ) (1) 2 c 2009 Information Processing Society of Japan

2.2.3 2.2.2 ZDOCK 3.0.1 1 1 2000 1 1 3. Table 3 3 bound RMSD Minimum of RMSD between structures by clustering and bound structure. 1AY7 R 0.81 1.27 0.82 0.82 0.82 0.82 1AY7 L 0.67 1.27 0.79 0.87 0.78 0.67 1CGI R 1.64 2.15 1.67 1.67 1.67 1.71 1CGI L 1.27 2.08 1.34 1.34 1.34 1.34 1ACB R 1.98 2.29 1.98 1.98 2.028 2.03 1ACB L 1.37 2.32 1.71 1.71 1.68 1.71 1M10 R 1.31 1.89 1.38 1.34 1.38 1.38 1M10 L 1.66 2.51 1.81 1.81 1.73 1.73 1FQ1 R 1.07 1.65 1.26 1.32 1.22 1.20 1FQ1 L 2.94 3.44 2.94 2.98 2.97 2.94 3.1 ZDOCK benchmark 2.0 2 5 2 5 ZDOCK benchmark 2.0 Rigid-body Medium Difficulty Difficult 3 1 3.2 3.2.1 bound unbound bound bound RMSD 2 Table 2 Details of target proteins. complex categories receptor ID R RMSD 1 ligand ID L RMSD 1 1AY7 Rigid-body 1RGH B 0.506 1A19 B 0.602 1CGI Rigid-body 2CGA B 1.470 1HPT 1.783 1ACB Medium Difficulty 2CGA B 1.760 1EGL 1.493 1M10 Medium Difficulty 1AUQ 1.235 1MOZ B 1.697 1FQ1 Difficult 1FPZ F 0.803 1B39 A 3.292 1 bound unbound Kabsch RMSD ZDOCK benchmark 2.0 bound unbound BLAST2 bound unbound Cα RMSD Cα RMSD 3.2.2 Kabsch RMSD unbound bound 3.2.1 Cα 3.2.1 3.3 3.2.1 1 2 5psec bound RMSD 3 RMSD 10 bound RMSD 3 1ACB 4 3 4 RMSD 3 c 2009 Information Processing Society of Japan

3 1ACB L Fig. 3 Comparison of clustering algorithm (1ACB L). 1 bound RMSD Fig. 1 RMSD between torajectory data and bound structure of receptor. 2 bound RMSD Fig. 2 RMSD between torajectory data and bound structure of ligand. 4 RMSD 10 5 1AY7 L 1FQ1 L 4 1AY7 L 3 2 5 1 2 RMSD 1FQ1 bound X bound 3 1ACB, 1CGI, 1M10 RMSD bound 3 1ACB RMSD 300 500psec 2 3 1 3.2.2 4 unbound 2.2.3 RMSD Kabsch 1 10-1 RMSD 4 1AY7 4 c 2009 Information Processing Society of Japan

Table 4 4 unbound Performance comparison of the method using molecular dynamics with rigid docking for using unbound structures. rigid docking 1AY7 12.2 8.6 12.9 7.9 12.4 8.2(2) - 8.7(4) - 6.5(9) 1CGI 7.2 15.7 16.2 16.1 16.0 2.2(5) 15.4(10) 15.7(5) 15.5(3) 6.4(6) 1ACB 7.9 17.2 16.4 17.2 8.4 4.8(4) 11.6(9) 11.5(3) 11.0(3) 8.1(9) 1M10 13.4 15.6 21.7 20.0 21.7-13.9(9) 15.7(3) 13.9(6) 13.1(9) 1FQ1 18.7 17.6 15.6 17.2 21.0 12.8(9) 17.3(9) 15.5(5) 16.9(9) 15.7(9) Fig. 5 5 RMSD Complex structure with minimum RMSD predicted by Ward s method. Fig. 6 6 RMSD Complex structure with minimum RMSD predicted by rigid docking. bound RMSD 4 1AY7 Fig. 4 Comparison of docking results (1AY7). 1AY7 4 RMSD RMSD 1AY7 5 6 2 RMSD 1AY7 4 1CGI 3 RMSD 1M10 1FQ1 5 c 2009 Information Processing Society of Japan

RMSD 1CGI 1ACB 2.2.3 ZDOCK 1 4. AMBER 10 sander RMSD bound 4 bound bound ZDOCK 3.0.1 1 4 1 2 1nsec 5 5 unbound docking bound bound unbound dockign MEGADOCK 9) B 19300102 1) Case, D A ; Darden, T A ; Cheatham, T E ; Simmerling, C L ; Wang, J ; Duke, R E ; Luo, R ; Crowley, M ; Walker, R C ; Zhang, W ; Merz, K M ; Wang, B ; Hayik, S ; Roitberg, A ; Seabra, G ; Kolossvary, I ; Wong, K F ; Paesani, F ; Vanicek, J ; Wu, X et al. San Francisco : University of California, 2008. 2) Chen R, Li L, Weng Z: ZDOCK: an initial-stage protein-docking algorithm, Proteins, 52:80-87, 2003. 3) Mintseris J, Pierce B, Wiehe K, Anderson R, Chen R, Weng Z. Integrating statistical pair potentials into protein complex prediction. Proteins, 69, 511-520, 2007. 4) Mintseris J, Wiehe K, Pierce B, Anderson R, Chen R, Janin J, Weng Z: Protein- Protein Docking Benchmark 2.0: an update, Proteins, 60, 214-216, 2005. 5) H.M. Berman, J. Westbrook, Z. Feng, G. Gilliland, T.N. Bhat, H. Weissig, I.N. Shindyalov, P.E. Bourne. The Protein Data Bank Nucleic Acids Research, 28, 235-242, 2000. 6) Y. Matsuzaki, Y. Matsuzaki, T. Sato, Y. Akiyama. Development of post-docking system for protein-protein interation prediction., IPSJ-SIG Technical Report, 2008-BIO-13(5): 17-20, 2008. 7) Kabsch, Wolfgang. A solution of the best rotation to relate two sets of vectors, Acta Crystallographica, 32:922, 1976. 8) :, 2, 7, ( ), 1999. 9) Y. Akiyama, T. Sato, Y. Matsuzaki, Y. Matsuzaki: MEGADOCK - A rapid screening system for all-to-all protein docking analysis with pre-calculated Fourierlibrary of protein structures, Proceedings of the 2008 Annual Conference of the Japanese Society for Bioinformatics, P032 2008. 6 c 2009 Information Processing Society of Japan

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