Accelerate Sampling in Atomistic Energy Landscapes Using Topology-Based Coarse-Grained Models.

We describe a multiscale enhanced sampling (MSES) method where efficient topology-based coarse-grained models are coupled with all-atom ones to enhance the sampling of atomistic protein energy landscape. The bias from the coupling is removed by Hamiltonian replica exchange, thus allowing one to benefit simultaneously from faster transitions of coarse-grained modeling and accuracy of atomistic force fields. The method is demonstrated by calculating the conformational equilibria of several small but nontrivial β-hairpins with varied stabilities.

[1]  Y. Sugita,et al.  Replica-exchange molecular dynamics method for protein folding , 1999 .

[2]  R. Luo,et al.  Overcoming entropic barrier with coupled sampling at dual resolutions. , 2005, The Journal of chemical physics.

[3]  John Karanicolas,et al.  The origins of asymmetry in the folding transition states of protein L and protein G , 2002, Protein science : a publication of the Protein Society.

[4]  U. Hansmann,et al.  Protein simulations combining an all-atom force field with a Go term , 2009, 0908.0419.

[5]  Edward Lyman,et al.  A Second Look at Canonical Sampling of Biomolecules using Replica Exchange Simulation. , 2006, Journal of chemical theory and computation.

[6]  Wang,et al.  Replica Monte Carlo simulation of spin glasses. , 1986, Physical review letters.

[7]  D J Bicout,et al.  Entropic barriers, transition states, funnels, and exponential protein folding kinetics: A simple model , 2008, Protein science : a publication of the Protein Society.

[8]  Ulrich H E Hansmann,et al.  Efficient sampling of protein structures by model hopping. , 2005, Physical review letters.

[9]  A. Mark,et al.  Convergence and sampling efficiency in replica exchange simulations of peptide folding in explicit solvent. , 2007, The Journal of chemical physics.

[10]  R. Levy,et al.  Simulating replica exchange simulations of protein folding with a kinetic network model , 2007, Proceedings of the National Academy of Sciences.

[11]  M. Nilges,et al.  Computational challenges for macromolecular structure determination by X-ray crystallography and solution NMRspectroscopy , 1993, Quarterly Reviews of Biophysics.

[12]  David A C Beck,et al.  Exploring the energy landscape of protein folding using replica-exchange and conventional molecular dynamics simulations. , 2007, Journal of structural biology.

[13]  Gregory A Voth,et al.  Smart resolution replica exchange: an efficient algorithm for exploring complex energy landscapes. , 2007, The Journal of chemical physics.

[14]  Edward Lyman,et al.  Resolution exchange simulation. , 2005, Physical review letters.

[15]  Alexander D. MacKerell,et al.  Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone φ, ψ and side-chain χ(1) and χ(2) dihedral angles. , 2012, Journal of chemical theory and computation.

[16]  C. Brooks,et al.  Balancing solvation and intramolecular interactions: toward a consistent generalized Born force field. , 2006, Journal of the American Chemical Society.

[17]  Michael Feig,et al.  MMTSB Tool Set: enhanced sampling and multiscale modeling methods for applications in structural biology. , 2004, Journal of molecular graphics & modelling.

[18]  Jianhan Chen.  Effective Approximation of Molecular Volume Using Atom-Centered Dielectric Functions in Generalized Born Models. , 2010, Journal of chemical theory and computation.

[19]  Charles L. Brooks,et al.  Insights from Coarse-Grained Gō Models for Protein Folding and Dynamics , 2009, International journal of molecular sciences.

[20]  Hugh Nymeyer,et al.  How Efficient Is Replica Exchange Molecular Dynamics? An Analytic Approach. , 2008, Journal of chemical theory and computation.

[21]  Daniel J. Sindhikara,et al.  Exchange frequency in replica exchange molecular dynamics. , 2008, The Journal of chemical physics.

[22]  Lorant Janosi,et al.  Multiscale modeling of biomolecular systems , 2007 .

[23]  John E Straub,et al.  Generalized replica exchange method. , 2010, The Journal of chemical physics.

[24]  P. Wolynes.  Recent successes of the energy landscape theory of protein folding and function , 2005, Quarterly Reviews of Biophysics.

[25]  B. Berne,et al.  Replica exchange with solute tempering: a method for sampling biological systems in explicit water. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[26]  Gregory A Voth,et al.  Multiscale modeling of biomolecular systems: in serial and in parallel. , 2007, Current opinion in structural biology.

[27]  R. Jernigan,et al.  Residue-residue potentials with a favorable contact pair term and an unfavorable high packing density term, for simulation and threading. , 1996, Journal of molecular biology.

[28]  Paul Tavan,et al.  Efficiency reduction and pseudo-convergence in replica exchange sampling of peptide folding–unfolding equilibria , 2008 .

[29]  J. Hofrichter,et al.  The protein folding 'speed limit'. , 2004, Current opinion in structural biology.

[30]  Jianhan Chen,et al.  Efficiency of Adaptive Temperature-Based Replica Exchange for Sampling Large-Scale Protein Conformational Transitions. , 2013, Journal of chemical theory and computation.

[31]  Hongxing Lei,et al.  Improved sampling methods for molecular simulation. , 2007, Current opinion in structural biology.

[32]  Jianpeng Ma,et al.  CHARMM: The biomolecular simulation program , 2009, J. Comput. Chem..

[33]  R. Fesinmeyer,et al.  Enhanced hairpin stability through loop design: the case of the protein G B1 domain hairpin. , 2004, Journal of the American Chemical Society.

[34]  A. Kidera,et al.  Scalable free energy calculation of proteins via multiscale essential sampling. , 2010, The Journal of chemical physics.

[35]  W. Eaton,et al.  Probing the free-energy surface for protein folding with single-molecule fluorescence spectroscopy , 2002, Nature.

[36]  Yuko Okamoto,et al.  Numerical comparisons of three recently proposed algorithms in the protein folding problem , 1997, J. Comput. Chem..