Reconstruction of Atomistic Structures from Coarse-Grained Models for Protein-DNA Complexes.

While coarse-grained (CG) simulations have widely been used to accelerate structure sampling of large biomolecular complexes, they are unavoidably less accurate and thus the reconstruction of all-atom (AA) structures and the subsequent refinement is desirable. In this study we developed an efficient method to reconstruct AA structures from sampled CG protein-DNA complex models, which attempts to model the protein-DNA interface accurately. First we developed a method to reconstruct atomic details of DNA structures from a three-site per nucleotide CG model, which uses a DNA fragment library. Next, for the protein-DNA interface, we referred to the side chain orientations in the known structure of the target interface when available. The other parts are modeled by existing tools. We confirmed the accuracy of the protocol in various aspects including the structure deviation in the self-reproduction, the base pair reproducibility, atomic contacts at the protein-DNA interface, and feasibility of the posterior AA simulations.

[1]  A Joshua Wand,et al.  Improved side‐chain prediction accuracy using an ab initio potential energy function and a very large rotamer library , 2004, Protein science : a publication of the Protein Society.

[2]  James W. Murray,et al.  High–quality protein backbone reconstruction from alpha carbons using Gaussian mixture models , 2013, J. Comput. Chem..

[3]  Dirar Homouz,et al.  Multiscale investigation of chemical interference in proteins. , 2010, The Journal of chemical physics.

[4]  Shoji Takada,et al.  Energy landscape views for interplays among folding, binding, and allostery of calmodulin domains , 2014, Proceedings of the National Academy of Sciences.

[5]  Mariusz Milik,et al.  Algorithm for rapid reconstruction of protein backbone from alpha carbon coordinates , 1997, J. Comput. Chem..

[6]  J. S. Sodhi,et al.  Prediction and functional analysis of native disorder in proteins from the three kingdoms of life. , 2004, Journal of molecular biology.

[7]  Thomas Simonson,et al.  Protein side chain conformation predictions with an MMGBSA energy function , 2016, Proteins.

[8]  Y. Levy,et al.  Molecular determinants of the interactions between proteins and ssDNA , 2015, Proceedings of the National Academy of Sciences.

[9]  Deok-Soo Kim,et al.  BetaSCPWeb: side-chain prediction for protein structures using Voronoi diagrams and geometry prioritization , 2016, Nucleic Acids Res..

[10]  Rolando Castillo,et al.  Multiscale molecular dynamics simulations of micelles: coarse-grain for self-assembly and atomic resolution for finer details† , 2012 .

[11]  Berk Hess,et al.  GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers , 2015 .

[12]  P. Derreumaux,et al.  Coarse-grained simulations of RNA and DNA duplexes. , 2013, The journal of physical chemistry. B.

[13]  Z. Xiang,et al.  Extending the accuracy limits of prediction for side-chain conformations. , 2001, Journal of molecular biology.

[14]  Andrzej J. Rzepiela,et al.  Reconstruction of atomistic details from coarse‐grained structures , 2010, J. Comput. Chem..

[15]  Lydia E Kavraki,et al.  From coarse‐grain to all‐atom: Toward multiscale analysis of protein landscapes , 2007, Proteins.

[16]  O. Schueler‐Furman,et al.  Improved side‐chain modeling for protein–protein docking , 2005, Protein science : a publication of the Protein Society.

[17]  Siewert J Marrink,et al.  Going Backward: A Flexible Geometric Approach to Reverse Transformation from Coarse Grained to Atomistic Models. , 2014, Journal of chemical theory and computation.

[18]  Alessandro Senes,et al.  Backbone dependency further improves side chain prediction efficiency in the Energy‐based Conformer Library (bEBL) , 2014, Proteins.

[19]  Shayantani Mukherjee,et al.  PRIMO/PRIMONA: A coarse‐grained model for proteins and nucleic acids that preserves near‐atomistic accuracy , 2010, Proteins.

[20]  A. Laaksonen,et al.  A coarse-grained simulation study of the structures, energetics, and dynamics of linear and circular DNA with its ions. , 2015, Journal of chemical theory and computation.

[21]  Klaus Schulten,et al.  Disassembly of nanodiscs with cholate. , 2007, Nano letters.

[22]  Timothy S. Carpenter,et al.  Self-assembly of a simple membrane protein: coarse-grained molecular dynamics simulations of the influenza M2 channel. , 2008, Biophysical journal.

[23]  Gregory A Voth,et al.  Reconstructing atomistic detail for coarse-grained models with resolution exchange. , 2008, The Journal of chemical physics.

[24]  Marcelo A. Marti,et al.  CG2AA: backmapping protein coarse-grained structures , 2016, Bioinform..

[25]  Dominik Gront,et al.  Backbone building from quadrilaterals: A fast and accurate algorithm for protein backbone reconstruction from alpha carbon coordinates , 2007, J. Comput. Chem..

[26]  Sergio Pantano,et al.  A Coarse Grained Model for Atomic-Detailed DNA Simulations with Explicit Electrostatics. , 2010, Journal of chemical theory and computation.

[27]  Gregory A Voth,et al.  Peptide folding using multiscale coarse-grained models. , 2008, The journal of physical chemistry. B.

[28]  Shoji Takada,et al.  Modeling Structural Dynamics of Biomolecular Complexes by Coarse-Grained Molecular Simulations. , 2015, Accounts of chemical research.

[29]  W. Olson,et al.  3DNA: a software package for the analysis, rebuilding and visualization of three-dimensional nucleic acid structures. , 2003, Nucleic acids research.

[30]  Shoji Takada,et al.  CafeMol: A Coarse-Grained Biomolecular Simulator for Simulating Proteins at Work. , 2011, Journal of chemical theory and computation.

[31]  Shoji Takada,et al.  Near-atomic structural model for bacterial DNA replication initiation complex and its functional insights , 2016, Proceedings of the National Academy of Sciences.

[32]  Roland L. Dunbrack,et al.  proteins STRUCTURE O FUNCTION O BIOINFORMATICS Improved prediction of protein side-chain conformations with SCWRL4 , 2022 .

[33]  Alessandra Villa,et al.  Self-assembling dipeptides: conformational sampling in solvent-free coarse-grained simulation. , 2009, Physical chemistry chemical physics : PCCP.

[34]  J Andrew McCammon,et al.  Configurational‐bias sampling technique for predicting side‐chain conformations in proteins , 2006, Protein science : a publication of the Protein Society.

[35]  N. Grishin,et al.  Side‐chain modeling with an optimized scoring function , 2002, Protein science : a publication of the Protein Society.

[36]  Shoji Takada,et al.  Dynamic Coupling among Protein Binding, Sliding, and DNA Bending Revealed by Molecular Dynamics. , 2016, Journal of the American Chemical Society.

[37]  Yang Zhang,et al.  REMO: A new protocol to refine full atomic protein models from C‐alpha traces by optimizing hydrogen‐bonding networks , 2009, Proteins.

[38]  D. Schwartz,et al.  Tension-Dependent Free Energies of Nucleosome Unwrapping , 2016, ACS central science.

[39]  Jianpeng Ma,et al.  OPUS‐Rota: A fast and accurate method for side‐chain modeling , 2008, Protein science : a publication of the Protein Society.

[40]  Sergio Pantano,et al.  SIRAH tools: mapping, backmapping and visualization of coarse-grained models , 2016, Bioinform..

[41]  Jeffrey Skolnick,et al.  Fast procedure for reconstruction of full‐atom protein models from reduced representations , 2008, J. Comput. Chem..

[42]  David A. Case,et al.  Modeling Unusual Nucleic Acid Structures , 1998 .

[43]  Daniel Durocher,et al.  The control of DNA repair by the cell cycle , 2016, Nature Cell Biology.

[44]  Phillip J Stansfeld,et al.  From Coarse Grained to Atomistic: A Serial Multiscale Approach to Membrane Protein Simulations. , 2011, Journal of chemical theory and computation.

[45]  Pierre Tufféry,et al.  SABBAC: online Structural Alphabet-based protein BackBone reconstruction from Alpha-Carbon trace , 2006, Nucleic Acids Res..

[46]  Shoji Takada,et al.  p53 searches on DNA by rotation-uncoupled sliding at C-terminal tails and restricted hopping of core domains. , 2012, Journal of the American Chemical Society.

[47]  Berk Hess,et al.  LINCS: A linear constraint solver for molecular simulations , 1997, J. Comput. Chem..

[48]  Peter G Wolynes,et al.  Exploring the Free Energy Landscape of Nucleosomes. , 2016, Journal of the American Chemical Society.