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Combining atomic-level Molecular Dynamics with coarse-grained Monte-Carlo dynamics Andrzej Koliński Laboratory of Theory of Biopolymers, Faculty of Chemistry,

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Presentation on theme: "Combining atomic-level Molecular Dynamics with coarse-grained Monte-Carlo dynamics Andrzej Koliński Laboratory of Theory of Biopolymers, Faculty of Chemistry,"— Presentation transcript:

1 Combining atomic-level Molecular Dynamics with coarse-grained Monte-Carlo dynamics Andrzej Koliński Laboratory of Theory of Biopolymers, Faculty of Chemistry, University of Warsaw http://www.biocomp.chem.uw.edu.pl Bioinformatics 2013 / BIT13, 26-29 June 2013, Toruń, Poland

2 All-atom MD with explicit water Atomic-Level Characterization of the Structural Dynamics of Proteins, Science, 2010 How Fast-Folding Proteins Fold, Science, 2011 1 milisecond simulations ANTON - David E. Shaw group

3 Different all-atom force-fields (explicit water) are: - able to fold a protein into its native tertiary structure - inconsistent in the description of a folding pathway Simulations of near-native dynamics seem to be essentially force-field independent. M. Rueda, C. Ferrer-Costa, T. Meyer, A. Perez, J. Camps, A. Hospital, J. L. Gelpi, M. Orozco, A consensus view of protein dynamics Proc. Natl. Acad. Sci. U.S.A. 104:796−801, 2007

4 Coarse-grained models

5 Coarse-grained models of moderate resolution (~10 2 faster than all-atom MD) Lattice Kolinski et al. Continuous Baker et al. Liwo et al.

6 CABS model Force field Short range conformational propensities Context-dependent pairwise interactions of side groups A model of main chain hydrogen bonds Interaction parameters are modulated by the predicted secondary structure and account for complex multibody interactions and the averaged effect of solvent Sampling – Monte Carlo dynamics A. Kolinski, Protein modeling and structure prediction with a reduced representation Acta Biochimica Polonica 51:349-371, 2004

7 Reconstruction & optimization procedure protein backbone reconstruction side chain reconstruction all-atom minimization step

8 All-atom MD (A – Amber, C – Charmm, G – Gromos and O – OPLS/AA force-fields) is consistent with CABS stochastic dynamics (after a proper renormalizations) at short time-scales (10 ns) M. Jamroz, M. Orozco, A. Kolinski, S. Kmiecik, A Consistent View of Protein Fluctuations from All-atom Molecular Dynamics and Coarse-Grained Dynamics with Knowledge-based Force-field, J. Chem. Theory Comput. 9:19–125, 2013 J. Wabik, S. Kmiecik, D. Gront, M. Kouza, A. Kolinski, Combining Coarse- Grained Protein Models with Replica-Exchange All-Atom Molecular Dynamics, International Journal of Molecular Sciences 14:9893-9905, 2013. Protein dynamics

9 CABS models reconstructed all-atom models (AMBER) Kmiecik, D. Gront, M. Kouza, A. Kolinski, From Coarse-Grained to Atomic-Level Characterization of Protein Dynamics: Transition State for the Folding of B Domain of Protein A, J. Phys. Chem. B 116:7026-7032, 2012

10 Dynamics: CABS and all-atoms MD

11 Example of residue fluctuation profiles

12 Benchmarks summary Test set (10 ns trajectories) Compared data Avg. Spearman’s corr. coeff. between residue fluctuation profiles 22 proteins (each one by 4 different force fields) MD vs. CABS 0.70 (J Chem Theory Comput, 2013) 393 non-redundant proteins (Amber force field) MD vs. CABS 0.70 (Nucl Acid Res, 2013) 140 non-redundant and NMR solved proteins (Amber force field) NMR vs. CABS 0.72 (yet unpublished ) NMR vs. MD0.65 MD vs. CABS0.69

13 http://biocomp.chem.uw.edu.pl/CABSflex

14 PDB: 1BSN, F1-ATPase subunit, 138 AA CABS-flex

15 PDB: 1BSN, F1-ATPase subunit, 138 AA CABS-flex

16 PDB: 1BHE, polygalacturonase, 376 AA CABS-flex

17 CABS-fold: server for protein structure prediction http://biocomp.chem.uw.edu.pl/CABSfold

18 CABS in structure prediction M. Blaszczyk, M. Jamroz, S. Kmiecik, A. Kolinski, CABS-fold: server for the novo and consensus-based prediction of protein structure, Nucleic Acids Research, 2013

19 Structure prediction (de-novo) The predicted models (colored in rainbow) are superimposed on native structures (colored in magenta) Modeling accuracy could be highly improved when combined with compartive modeling. A. Kolinski, J. M. Bujnicki, Generalized protein structure prediction based on combination of fold-recognition with de novo folding and evaluation of models, Proteins 61(S7):84-90, 2005

20 Structure prediction (homology modeling) CASP9 examples 9th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction

21 CABS – docking and interactions Simulations of induced folding (binding) of intrisingly disordered protein pKIG with KIX domain

22

23 Summary: CABS could be easily combined with all-atom Molecular Dynamics and used in studies of protein dynamics, interactions and structure prediction LTB servers based on CABS tools: URL: http://biocomp.chem.uw.edu.pl/CABSfoldhttp://biocomp.chem.uw.edu.pl/CABSfold URL: http://biocomp.chem.uw.edu.pl/CABSflexhttp://biocomp.chem.uw.edu.pl/CABSflex M. Jamroz, A. Kolinski & S. Kmiecik, CABS-flex: server for fast simulation of protein structure fluctuations, Nucleic Acids Research, 1-5, 2013 M. Blaszczyk, M. Jamroz, S. Kmiecik, A. Kolinski, CABS-fold: server for the novo and consensus-based prediction of protein structure, Nucleic Acids Research 1-6, 2013

24 Thank you! Co-authors: Drs. Sebastian Kmiecik, Michał Jamróz, Dominik Gront, Maciej Błaszczyk, Mateusz Kurciński, Jacek Wabik and others ….


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