MOLS 2.0: software package for peptide modeling and protein–ligand docking

We previously developed an algorithm to perform conformational searches of proteins and peptides, and to perform the docking of ligands to protein receptors. In order to identify optimal conformations and docked poses, this algorithm uses mutually orthogonal Latin squares (MOLS) to rationally sample the vast conformational (or docking) space, and then analyzes this relatively small sample using a variant of mean field theory. The conformational search part of the algorithm was denoted MOLS 1.0. The docking portion of the algorithm, which allows only “flexible ligand/rigid receptor” docking, was denoted MOLSDOCK. Both are FORTRAN-based command-line-only molecular docking computer programs, though a GUI was developed later for MOLS 1.0. Both the conformational search and the rigid receptor docking parts of the algorithm have been extensively validated. We have now further enhanced the capabilities of the program by incorporating “induced fit” side-chain receptor flexibility for docking peptide ligands. Benchmarking and extensive testing is now being carried out for the flexible receptor portion of the docking. Additionally, to make both the peptide conformational search and docking algorithms (the latter including both flexible ligand/rigid receptor and flexible ligand/flexible receptor techniques) more accessible to the research community, we have developed MOLS 2.0, which incorporates a new Java-based graphical user interface (GUI). Here, we give a detailed description of MOLS 2.0. The source code and binary for MOLS 2.0 are distributed free (under a GNU Lesser General Public License) to the scientific community. They are freely available for download at https://sourceforge.net/projects/mols2-0/files/.

[1]  D. Koshland.  Application of a Theory of Enzyme Specificity to Protein Synthesis. , 1958, Proceedings of the National Academy of Sciences of the United States of America.

[2]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[3]  P Koehl,et al.  Mean-field minimization methods for biological macromolecules. , 1996, Current opinion in structural biology.

[4]  Woody Sherman,et al.  Use of an Induced Fit Receptor Structure in Virtual Screening , 2006, Chemical biology & drug design.

[5]  P Tufféry,et al.  Prediction of protein side chain conformations: a study on the influence of backbone accuracy on conformation stability in the rotamer space. , 1997, Protein engineering.

[6]  H. Scheraga,et al.  Energy parameters in polypeptides. 10. Improved geometrical parameters and nonbonded interactions for use in the ECEPP/3 algorithm, with application to proline-containing peptides , 1994 .

[7]  S Subbiah,et al.  How similar must a template protein be for homology modeling by side-chain packing methods? , 1996, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.

[8]  H. Scheraga,et al.  On the multiple-minima problem in the conformational analysis of molecules: deformation of the potential energy hypersurface by the diffusion equation method , 1989 .

[9]  Rafael Najmanovich,et al.  Side‐chain flexibility in proteins upon ligand binding , 2000, Proteins.

[10]  A. Griewank.  Generalized descent for global optimization , 1981 .

[11]  Iris Antes,et al.  DynaDock: A new molecular dynamics‐based algorithm for protein–peptide docking including receptor flexibility , 2010, Proteins.

[12]  N Gautham,et al.  Conformational studies on enkephalins using the MOLS technique , 2004, Biopolymers.

[13]  L. Piela,et al.  Mean field theory as a tool for intramolecular conformational optimization. 1. Tests on terminally-blocked alanine and met-enkephalin , 1992 .

[14]  J. Richardson,et al.  Asparagine and glutamine: using hydrogen atom contacts in the choice of side-chain amide orientation. , 1999, Journal of molecular biology.

[15]  David S. Goodsell,et al.  AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility , 2009, J. Comput. Chem..

[16]  N. Gautham,et al.  Enhanced sampling of the molecular potential energy surface using mutually orthogonal latin squares: application to peptide structures. , 2003, Biophysical journal.

[17]  Gennady M Verkhivker,et al.  Molecular recognition of the inhibitor AG-1343 by HIV-1 protease: conformationally flexible docking by evolutionary programming. , 1995, Chemistry & biology.

[18]  Nir London,et al.  The structural basis of peptide-protein binding strategies. , 2010, Structure.

[19]  N. Gautham,et al.  An application of experimental design using mutually orthogonal Latin squares in conformational studies of peptides. , 2004, Biochemical and biophysical research communications.

[20]  Chris Morley,et al.  Open Babel: An open chemical toolbox , 2011, J. Cheminformatics.

[21]  N. Gautham,et al.  Energy Landscape of Met-Enkephalin and Leu-Enkephalin Drawn Using Mutually Orthogonal Latin Squares Sampling , 2004 .

[22]  P Willett,et al.  Development and validation of a genetic algorithm for flexible docking. , 1997, Journal of molecular biology.

[23]  Kiyosi Itô.  Encyclopedic dictionary of mathematics (2nd ed.) , 1993 .

[24]  J. Thornton,et al.  Conformational changes observed in enzyme crystal structures upon substrate binding. , 2005, Journal of molecular biology.

[25]  H. Scheraga,et al.  Monte Carlo-minimization approach to the multiple-minima problem in protein folding. , 1987, Proceedings of the National Academy of Sciences of the United States of America.

[26]  H. Scheraga,et al.  Free energy and stability of macromolecules studied by the double scanning simulation procedure , 1990 .

[27]  Ian W. Davis,et al.  RosettaLigand docking with full ligand and receptor flexibility. , 2009, Journal of molecular biology.

[28]  M. Totrov,et al.  Contact area difference (CAD): a robust measure to evaluate accuracy of protein models. , 1997, Journal of molecular biology.

[29]  J. Mccammon,et al.  Accounting for Receptor Flexibility and Enhanced Sampling Methods in Computer‐Aided Drug Design , 2013, Chemical biology & drug design.

[30]  N. Gautham,et al.  MOLS--a program to explore the potential energy surface of a peptide and locate its low energy conformations. , 2005, In silico biology.

[31]  N. Gautham,et al.  Molecular docking studies of protein-nucleotide complexes using MOLSDOCK (mutually orthogonal Latin squares DOCK) , 2012, Journal of Molecular Modeling.

[32]  J. Sussman,et al.  Gamma-chymotrypsin is a complex of alpha-chymotrypsin with its own autolysis products. , 1991, Biochemistry.

[33]  António J. M. Ribeiro,et al.  Protein-ligand docking in the new millennium--a retrospective of 10 years in the field. , 2013, Current medicinal chemistry.

[34]  Jacques Monod,et al.  Allosteric Proteins and Cellular Control Systems , 1989 .

[35]  I. Kuntz.  Structure-Based Strategies for Drug Design and Discovery , 1992, Science.

[36]  Michael G. Lerner,et al.  Binding MOAD (Mother Of All Databases) , 2005, Proteins.

[37]  David S. Goodsell,et al.  AutoDockFR: Advances in Protein-Ligand Docking with Explicitly Specified Binding Site Flexibility , 2015, PLoS Comput. Biol..

[38]  H A Scheraga,et al.  An approach to the multiple-minima problem in protein folding by relaxing dimensionality. Tests on enkephalin. , 1987, Journal of molecular biology.

[39]  J. Mccammon,et al.  Exploring the role of receptor flexibility in structure-based drug discovery. , 2014, Biophysical chemistry.

[40]  Arun Prasad Pandurangan,et al.  A new peptide docking strategy using a mean field technique with mutually orthogonal Latin square sampling , 2008, J. Comput. Aided Mol. Des..

[41]  J. Dieudonne,et al.  Encyclopedic Dictionary of Mathematics , 1979 .

[42]  Vincent Le Guilloux,et al.  Fpocket: An open source platform for ligand pocket detection , 2009, BMC Bioinformatics.

[43]  Leslie A Kuhn,et al.  Side‐chain flexibility in protein–ligand binding: The minimal rotation hypothesis , 2005, Protein science : a publication of the Protein Society.

[44]  T. Halgren.  Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94 , 1996, J. Comput. Chem..

[45]  J. Changeux,et al.  ON THE NATURE OF ALLOSTERIC TRANSITIONS: A PLAUSIBLE MODEL. , 1965, Journal of molecular biology.

[46]  P. Kollman,et al.  A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules , 1995 .

[47]  R. Friesner,et al.  Novel procedure for modeling ligand/receptor induced fit effects. , 2006, Journal of medicinal chemistry.