Ligandbook: an online repository for small and drug-like molecule force field parameters

Summary: Ligandbook is a public database and archive for force field parameters of small and drug‐like molecules. It is a repository for parameter sets that are part of published work but are not easily available to the community otherwise. Parameter sets can be downloaded and immediately used in molecular dynamics simulations. The sets of parameters are versioned with full histories and carry unique identifiers to facilitate reproducible research. Text‐based search on rich metadata and chemical substructure search allow precise identification of desired compounds or functional groups. Ligandbook enables the rapid set up of reproducible molecular dynamics simulations of ligands and protein‐ligand complexes. Availability and Implementation: Ligandbook is available online at https://ligandbook.org and supports all modern browsers. Parameters can be searched and downloaded without registration, including access through a programmatic RESTful API. Deposition of files requires free user registration. Ligandbook is implemented in the PHP Symfony2 framework with TCL scripts using the CACTVS toolkit. Contact: oliver.beckstein@asu.edu or bogdan.iorga@cnrs.fr; contact@ligandbook.org. Supplementary information: Supplementary data are available at Bioinformatics online.

[1]  Wim F Vranken,et al.  ACPYPE - AnteChamber PYthon Parser interfacE , 2012, BMC Research Notes.

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

[3]  W. L. Jorgensen,et al.  Comparison of simple potential functions for simulating liquid water , 1983 .

[4]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

[5]  Jonas C. Ditz,et al.  Properties of Organic Liquids when Simulated with Long-Range Lennard-Jones Interactions. , 2015, Journal of chemical theory and computation.

[6]  K Schulten,et al.  VMD: visual molecular dynamics. , 1996, Journal of molecular graphics.

[7]  Berk Hess,et al.  P-LINCS:  A Parallel Linear Constraint Solver for Molecular Simulation. , 2008, Journal of chemical theory and computation.

[8]  Wolf-Dietrich Ihlenfeldt,et al.  Computation and management of chemical properties in CACTVS: An extensible networked approach toward modularity and compatibility , 1994, J. Chem. Inf. Comput. Sci..

[9]  T. Darden,et al.  A smooth particle mesh Ewald method , 1995 .

[10]  VINCENT ZOETE,et al.  SwissParam: A fast force field generation tool for small organic molecules , 2011, J. Comput. Chem..

[11]  Pramod C. Nair,et al.  An Automated Force Field Topology Builder (ATB) and Repository: Version 1.0. , 2011, Journal of chemical theory and computation.

[12]  Carl Caleman,et al.  GROMACS molecule & liquid database , 2012, Bioinform..

[13]  Bogdan I. Iorga,et al.  Prediction of cyclohexane-water distribution coefficients for the SAMPL5 data set using molecular dynamics simulations with the OPLS-AA force field , 2016, Journal of Computer-Aided Molecular Design.

[14]  G Vriend,et al.  WHAT IF: a molecular modeling and drug design program. , 1990, Journal of molecular graphics.

[15]  M. Parrinello,et al.  Polymorphic transitions in single crystals: A new molecular dynamics method , 1981 .

[16]  Piotr Cieplak,et al.  R.E.DD.B.: A database for RESP and ESP atomic charges, and force field libraries , 2007, Nucleic Acids Res..

[17]  Oliver Beckstein,et al.  MDAnalysis: A toolkit for the analysis of molecular dynamics simulations , 2011, J. Comput. Chem..

[18]  Alexander D. MacKerell,et al.  Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing , 2012, J. Chem. Inf. Model..

[19]  Yanli Wang,et al.  PubChem: Integrated Platform of Small Molecules and Biological Activities , 2008 .

[20]  Bogdan I. Iorga,et al.  Prediction of hydration free energies for the SAMPL4 diverse set of compounds using molecular dynamics simulations with the OPLS-AA force field , 2014, Journal of Computer-Aided Molecular Design.

[21]  R. Friesner,et al.  Evaluation and Reparametrization of the OPLS-AA Force Field for Proteins via Comparison with Accurate Quantum Chemical Calculations on Peptides† , 2001 .

[22]  Oliver Beckstein,et al.  MDAnalysis: A Python Package for the Rapid Analysis of Molecular Dynamics Simulations , 2016, SciPy.

[23]  Evan Bolton,et al.  The PubChem chemical structure sketcher , 2009, J. Cheminformatics.

[24]  William L Jorgensen,et al.  Halide, Ammonium, and Alkali Metal Ion Parameters for Modeling Aqueous Solutions. , 2006, Journal of chemical theory and computation.

[25]  Punit Kaur,et al.  Aspirin induces its anti-inflammatory effects through its specific binding to phospholipase A2: Crystal structure of the complex formed between phospholipase A2 and aspirin at 1.9 Å resolution , 2004, Journal of drug targeting.

[26]  Oliver Beckstein,et al.  Lipidbook: A Public Repository for Force-Field Parameters Used in Membrane Simulations , 2010, The Journal of Membrane Biology.

[27]  M. Parrinello,et al.  Canonical sampling through velocity rescaling. , 2007, The Journal of chemical physics.

[28]  Jonas C. Ditz,et al.  Large-scale calculations of gas phase thermochemistry: Enthalpy of formation, standard entropy, and heat capacity , 2016 .

[29]  Bogdan I. Iorga,et al.  Prediction of hydration free energies for aliphatic and aromatic chloro derivatives using molecular dynamics simulations with the OPLS-AA force field , 2012, Journal of Computer-Aided Molecular Design.

[30]  Holger Gohlke,et al.  The Amber biomolecular simulation programs , 2005, J. Comput. Chem..

[31]  Otis Gospodnetic,et al.  Lucene in Action, Second Edition: Covers Apache Lucene 3.0 , 2010 .

[32]  C. Fishwick,et al.  Molecular mechanism of ligand recognition by membrane transport protein, Mhp1 , 2014, The EMBO journal.

[33]  Carsten Kutzner,et al.  Tackling Exascale Software Challenges in Molecular Dynamics Simulations with GROMACS , 2015, EASC.