Literature DB >> 29694035

Optimized Lennard-Jones Parameters for Druglike Small Molecules.

Eliot Boulanger1, Lei Huang1, Chetan Rupakheti1, Alexander D MacKerell2, Benoît Roux1.   

Abstract

Meaningful efforts in computer-aided drug design (CADD) require accurate molecular mechanical force fields to quantitatively characterize protein-ligand interactions, ligand hydration free energies, and other ligand physical properties. Atomic models of new compounds are commonly generated by analogy from the predefined tabulated parameters of a given force field. Two widely used approaches following this strategy are the General Amber Force Field (GAFF) and the CHARMM General Force Field (CGenFF). An important limitation of using pretabulated parameter values is that they may be inadequate in the context of a specific molecule. To resolve this issue, we previously introduced the General Automated Atomic Model Parameterization (GAAMP) for automatically generating the parameters of atomic models of small molecules, using the results from ab initio quantum mechanical (QM) calculations as target data. The GAAMP protocol uses QM data to optimize the bond, valence angle, and dihedral angle internal parameters, and atomic partial charges. However, since the treatment of van der Waals interactions based on QM is challenging and may often be unreliable, the Lennard-Jones 6-12 parameters are kept unchanged from the initial atom types assignments (GAFF or CGenFF), which limits the accuracy that can be achieved by these models. To address this issue, a new set of Lennard-Jones 6-12 parameters was systematically optimized to reproduce experimental neat liquid densities and enthalpies of vaporization for a large set of 430 compounds, covering a wide range of chemical functionalities. Calculations of the hydration free energy indicate that optimal accuracy for these models is achieved when the molecule-water van der Waals dispersion is rescaled by a factor of 1.115. The final optimized model yields an average unsigned error of 0.79 kcal/mol in the hydration free energies.

Entities:  

Mesh:

Substances:

Year:  2018        PMID: 29694035      PMCID: PMC5997559          DOI: 10.1021/acs.jctc.8b00172

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  41 in total

Review 1.  Molecular dynamics simulations of biomolecules.

Authors:  Martin Karplus; J Andrew McCammon
Journal:  Nat Struct Biol       Date:  2002-09

2.  Improved treatment of the protein backbone in empirical force fields.

Authors:  Alexander D MacKerell; Michael Feig; Charles L Brooks
Journal:  J Am Chem Soc       Date:  2004-01-28       Impact factor: 15.419

3.  Accuracy of free energies of hydration using CM1 and CM3 atomic charges.

Authors:  Marina Udier-Blagović; Patricia Morales De Tirado; Shoshannah A Pearlman; William L Jorgensen
Journal:  J Comput Chem       Date:  2004-08       Impact factor: 3.376

4.  Development and testing of a general amber force field.

Authors:  Junmei Wang; Romain M Wolf; James W Caldwell; Peter A Kollman; David A Case
Journal:  J Comput Chem       Date:  2004-07-15       Impact factor: 3.376

Review 5.  Empirical force fields for biological macromolecules: overview and issues.

Authors:  Alexander D Mackerell
Journal:  J Comput Chem       Date:  2004-10       Impact factor: 3.376

6.  A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6.

Authors:  Chris Oostenbrink; Alessandra Villa; Alan E Mark; Wilfred F van Gunsteren
Journal:  J Comput Chem       Date:  2004-10       Impact factor: 3.376

7.  Comparison of charge models for fixed-charge force fields: small-molecule hydration free energies in explicit solvent.

Authors:  David L Mobley; Elise Dumont; John D Chodera; Ken A Dill
Journal:  J Phys Chem B       Date:  2007-02-10       Impact factor: 2.991

8.  Accurate and efficient corrections for missing dispersion interactions in molecular simulations.

Authors:  Michael R Shirts; David L Mobley; John D Chodera; Vijay S Pande
Journal:  J Phys Chem B       Date:  2007-10-19       Impact factor: 2.991

Review 9.  CHARMM: the biomolecular simulation program.

Authors:  B R Brooks; C L Brooks; A D Mackerell; L Nilsson; R J Petrella; B Roux; Y Won; G Archontis; C Bartels; S Boresch; A Caflisch; L Caves; Q Cui; A R Dinner; M Feig; S Fischer; J Gao; M Hodoscek; W Im; K Kuczera; T Lazaridis; J Ma; V Ovchinnikov; E Paci; R W Pastor; C B Post; J Z Pu; M Schaefer; B Tidor; R M Venable; H L Woodcock; X Wu; W Yang; D M York; M Karplus
Journal:  J Comput Chem       Date:  2009-07-30       Impact factor: 3.376

10.  CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields.

Authors:  K Vanommeslaeghe; E Hatcher; C Acharya; S Kundu; S Zhong; J Shim; E Darian; O Guvench; P Lopes; I Vorobyov; A D Mackerell
Journal:  J Comput Chem       Date:  2010-03       Impact factor: 3.376

View more
  13 in total

1.  Blinded prediction of protein-ligand binding affinity using Amber thermodynamic integration for the 2018 D3R grand challenge 4.

Authors:  Junjie Zou; Chuan Tian; Carlos Simmerling
Journal:  J Comput Aided Mol Des       Date:  2019-09-25       Impact factor: 3.686

2.  Force Field Optimization Guided by Small Molecule Crystal Lattice Data Enables Consistent Sub-Angstrom Protein-Ligand Docking.

Authors:  Hahnbeom Park; Guangfeng Zhou; Minkyung Baek; David Baker; Frank DiMaio
Journal:  J Chem Theory Comput       Date:  2021-02-12       Impact factor: 6.006

3.  Solvation Free Energy Calculations with Quantum Mechanics/Molecular Mechanics and Machine Learning Models.

Authors:  Pan Zhang; Lin Shen; Weitao Yang
Journal:  J Phys Chem B       Date:  2019-01-15       Impact factor: 2.991

4.  Molecular Dynamics Simulations of Ionic Liquids and Electrolytes Using Polarizable Force Fields.

Authors:  Dmitry Bedrov; Jean-Philip Piquemal; Oleg Borodin; Alexander D MacKerell; Benoît Roux; Christian Schröder
Journal:  Chem Rev       Date:  2019-05-29       Impact factor: 60.622

5.  Toward Prediction of Electrostatic Parameters for Force Fields That Explicitly Treat Electronic Polarization.

Authors:  Esther Heid; Markus Fleck; Payal Chatterjee; Christian Schröder; Alexander D MacKerell
Journal:  J Chem Theory Comput       Date:  2019-03-12       Impact factor: 6.006

6.  Computational methods and theory for ion channel research.

Authors:  C Guardiani; F Cecconi; L Chiodo; G Cottone; P Malgaretti; L Maragliano; M L Barabash; G Camisasca; M Ceccarelli; B Corry; R Roth; A Giacomello; B Roux
Journal:  Adv Phys X       Date:  2022

7.  Replica-Exchange Enveloping Distribution Sampling Using Generalized AMBER Force-Field Topologies: Application to Relative Hydration Free-Energy Calculations for Large Sets of Molecules.

Authors:  Salomé R Rieder; Benjamin Ries; Kay Schaller; Candide Champion; Emilia P Barros; Philippe H Hünenberger; Sereina Riniker
Journal:  J Chem Inf Model       Date:  2022-06-08       Impact factor: 6.162

8.  Bayesian-Inference-Driven Model Parametrization and Model Selection for 2CLJQ Fluid Models.

Authors:  Owen C Madin; Simon Boothroyd; Richard A Messerly; Josh Fass; John D Chodera; Michael R Shirts
Journal:  J Chem Inf Model       Date:  2022-02-07       Impact factor: 6.162

9.  Harnessing Deep Learning for Optimization of Lennard-Jones Parameters for the Polarizable Classical Drude Oscillator Force Field.

Authors:  Payal Chatterjee; Mert Y Sengul; Anmol Kumar; Alexander D MacKerell
Journal:  J Chem Theory Comput       Date:  2022-04-01       Impact factor: 6.578

10.  Development and application of quantum mechanics/molecular mechanics methods with advanced polarizable potentials.

Authors:  Jorge Nochebuena; Sehr Naseem-Khan; G Andrés Cisneros
Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2021-01-12
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.