Literature DB >> 27196035

TopoGromacs: Automated Topology Conversion from CHARMM to GROMACS within VMD.

Josh V Vermaas1,2,3, David J Hardy3, John E Stone3, Emad Tajkhorshid1,2,3, Axel Kohlmeyer4.   

Abstract

Molecular dynamics (MD) simulation engines use a variety of different approaches for modeling molecular systems with force fields that govern their dynamics and describe their topology. These different approaches introduce incompatibilities between engines, and previously published software bridges the gaps between many popular MD packages, such as between CHARMM and AMBER or GROMACS and LAMMPS. While there are many structure building tools available that generate topologies and structures in CHARMM format, only recently have mechanisms been developed to convert their results into GROMACS input. We present an approach to convert CHARMM-formatted topology and parameters into a format suitable for simulation with GROMACS by expanding the functionality of TopoTools, a plugin integrated within the widely used molecular visualization and analysis software VMD. The conversion process was diligently tested on a comprehensive set of biological molecules in vacuo. The resulting comparison between energy terms shows that the translation performed was lossless as the energies were unchanged for identical starting configurations. By applying the conversion process to conventional benchmark systems that mimic typical modestly sized MD systems, we explore the effect of the implementation choices made in CHARMM, NAMD, and GROMACS. The newly available automatic conversion capability breaks down barriers between simulation tools and user communities and allows users to easily compare simulation programs and leverage their unique features without the tedium of constructing a topology twice.

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Year:  2016        PMID: 27196035      PMCID: PMC5543333          DOI: 10.1021/acs.jcim.6b00103

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  23 in total

Review 1.  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

2.  GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit.

Authors:  Sander Pronk; Szilárd Páll; Roland Schulz; Per Larsson; Pär Bjelkmar; Rossen Apostolov; Michael R Shirts; Jeremy C Smith; Peter M Kasson; David van der Spoel; Berk Hess; Erik Lindahl
Journal:  Bioinformatics       Date:  2013-02-13       Impact factor: 6.937

3.  Potentials of mean force and permeabilities for carbon dioxide, ammonia, and water flux across a Rhesus protein channel and lipid membranes.

Authors:  Jochen S Hub; Fritz K Winkler; Mike Merrick; Bert L de Groot
Journal:  J Am Chem Soc       Date:  2010-09-29       Impact factor: 15.419

4.  Automation of the CHARMM General Force Field (CGenFF) II: assignment of bonded parameters and partial atomic charges.

Authors:  K Vanommeslaeghe; E Prabhu Raman; A D MacKerell
Journal:  J Chem Inf Model       Date:  2012-11-28       Impact factor: 4.956

5.  Rapid parameterization of small molecules using the Force Field Toolkit.

Authors:  Christopher G Mayne; Jan Saam; Klaus Schulten; Emad Tajkhorshid; James C Gumbart
Journal:  J Comput Chem       Date:  2013-09-02       Impact factor: 3.376

6.  Implementation of the CHARMM Force Field in GROMACS: Analysis of Protein Stability Effects from Correction Maps, Virtual Interaction Sites, and Water Models.

Authors:  Pär Bjelkmar; Per Larsson; Michel A Cuendet; Berk Hess; Erik Lindahl
Journal:  J Chem Theory Comput       Date:  2010-01-25       Impact factor: 6.006

7.  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.

Authors:  Robert B Best; Xiao Zhu; Jihyun Shim; Pedro E M Lopes; Jeetain Mittal; Michael Feig; Alexander D Mackerell
Journal:  J Chem Theory Comput       Date:  2012-07-18       Impact factor: 6.006

8.  Additive empirical force field for hexopyranose monosaccharides.

Authors:  Olgun Guvench; Shannon N Greene; Ganesh Kamath; John W Brady; Richard M Venable; Richard W Pastor; Alexander D Mackerell
Journal:  J Comput Chem       Date:  2008-11-30       Impact factor: 3.376

9.  LipidBuilder: A Framework To Build Realistic Models for Biological Membranes.

Authors:  Christophe Bovigny; Giorgio Tamò; Thomas Lemmin; Nicolas Maïno; Matteo Dal Peraro
Journal:  J Chem Inf Model       Date:  2015-12-10       Impact factor: 4.956

10.  CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field.

Authors:  Jumin Lee; Xi Cheng; Jason M Swails; Min Sun Yeom; Peter K Eastman; Justin A Lemkul; Shuai Wei; Joshua Buckner; Jong Cheol Jeong; Yifei Qi; Sunhwan Jo; Vijay S Pande; David A Case; Charles L Brooks; Alexander D MacKerell; Jeffery B Klauda; Wonpil Im
Journal:  J Chem Theory Comput       Date:  2015-12-03       Impact factor: 6.006

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  11 in total

1.  From GROMACS to LAMMPS: GRO2LAM : A converter for molecular dynamics software.

Authors:  Hernán Chávez Thielemann; Annalisa Cardellini; Matteo Fasano; Luca Bergamasco; Matteo Alberghini; Gianmarco Ciorra; Eliodoro Chiavazzo; Pietro Asinari
Journal:  J Mol Model       Date:  2019-05-07       Impact factor: 1.810

2.  Early Experiences Porting the NAMD and VMD Molecular Simulation and Analysis Software to GPU-Accelerated OpenPOWER Platforms.

Authors:  John E Stone; Antti-Pekka Hynninen; James C Phillips; Klaus Schulten
Journal:  High Perform Comput (2016)       Date:  2016-10-06

3.  Passive membrane transport of lignin-related compounds.

Authors:  Josh V Vermaas; Richard A Dixon; Fang Chen; Shawn D Mansfield; Wout Boerjan; John Ralph; Michael F Crowley; Gregg T Beckham
Journal:  Proc Natl Acad Sci U S A       Date:  2019-10-28       Impact factor: 11.205

4.  Lessons learned from comparing molecular dynamics engines on the SAMPL5 dataset.

Authors:  Michael R Shirts; Christoph Klein; Jason M Swails; Jian Yin; Michael K Gilson; David L Mobley; David A Case; Ellen D Zhong
Journal:  J Comput Aided Mol Des       Date:  2016-10-27       Impact factor: 3.686

5.  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

6.  Mechanistic basis for multidrug resistance and collateral drug sensitivity conferred to the malaria parasite by polymorphisms in PfMDR1 and PfCRT.

Authors:  Sarah Heckmatt Shafik; Sashika Natasha Richards; Ben Corry; Rowena Elizabeth Martin
Journal:  PLoS Biol       Date:  2022-05-04       Impact factor: 9.593

7.  Electrostatic lock in the transport cycle of the multidrug resistance transporter EmrE.

Authors:  Josh V Vermaas; Susan B Rempe; Emad Tajkhorshid
Journal:  Proc Natl Acad Sci U S A       Date:  2018-07-19       Impact factor: 11.205

8.  Supercomputer-Based Ensemble Docking Drug Discovery Pipeline with Application to Covid-19.

Authors:  A Acharya; R Agarwal; M B Baker; J Baudry; D Bhowmik; S Boehm; K G Byler; S Y Chen; L Coates; C J Cooper; O Demerdash; I Daidone; J D Eblen; S Ellingson; S Forli; J Glaser; J C Gumbart; J Gunnels; O Hernandez; S Irle; D W Kneller; A Kovalevsky; J Larkin; T J Lawrence; S LeGrand; S-H Liu; J C Mitchell; G Park; J M Parks; A Pavlova; L Petridis; D Poole; L Pouchard; A Ramanathan; D M Rogers; D Santos-Martins; A Scheinberg; A Sedova; Y Shen; J C Smith; M D Smith; C Soto; A Tsaris; M Thavappiragasam; A F Tillack; J V Vermaas; V Q Vuong; J Yin; S Yoo; M Zahran; L Zanetti-Polzi
Journal:  J Chem Inf Model       Date:  2020-12-16       Impact factor: 4.956

9.  Accurate Simulations of Lipid Monolayers Require a Water Model with Correct Surface Tension.

Authors:  Carmelo Tempra; O H Samuli Ollila; Matti Javanainen
Journal:  J Chem Theory Comput       Date:  2022-02-08       Impact factor: 6.006

10.  Assigning crystallographic electron densities with free energy calculations-The case of the fluoride channel Fluc.

Authors:  Igor Ariz-Extreme; Jochen S Hub
Journal:  PLoS One       Date:  2018-05-17       Impact factor: 3.240

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