Literature DB >> 27862047

CHARMM-GUI 10 years for biomolecular modeling and simulation.

Sunhwan Jo1, Xi Cheng2, Jumin Lee3, Seonghoon Kim3, Sang-Jun Park3, Dhilon S Patel3, Andrew H Beaven4, Kyu Il Lee3, Huan Rui5, Soohyung Park3, Hui Sun Lee3, Benoît Roux5, Alexander D MacKerell6, Jeffrey B Klauda7, Yifei Qi3, Wonpil Im3.   

Abstract

CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface that prepares complex biomolecular systems for molecular simulations. CHARMM-GUI creates input files for a number of programs including CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Since its original development in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to set up a broad range of simulations: (1) PDB Reader & Manipulator, Glycan Reader, and Ligand Reader & Modeler for reading and modifying molecules; (2) Quick MD Simulator, Membrane Builder, Nanodisc Builder, HMMM Builder, Monolayer Builder, Micelle Builder, and Hex Phase Builder for building all-atom simulation systems in various environments; (3) PACE CG Builder and Martini Maker for building coarse-grained simulation systems; (4) DEER Facilitator and MDFF/xMDFF Utilizer for experimentally guided simulations; (5) Implicit Solvent Modeler, PBEQ-Solver, and GCMC/BD Ion Simulator for implicit solvent related calculations; (6) Ligand Binder for ligand solvation and binding free energy simulations; and (7) Drude Prepper for preparation of simulations with the CHARMM Drude polarizable force field. Recently, new modules have been integrated into CHARMM-GUI, such as Glycolipid Modeler for generation of various glycolipid structures, and LPS Modeler for generation of lipopolysaccharide structures from various Gram-negative bacteria. These new features together with existing modules are expected to facilitate advanced molecular modeling and simulation thereby leading to an improved understanding of the structure and dynamics of complex biomolecular systems. Here, we briefly review these capabilities and discuss potential future directions in the CHARMM-GUI development project.
© 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Entities:  

Keywords:  Coarse-grained simulation; Glycan; Membranes; Protein-ligand interactions; mmCIF

Mesh:

Substances:

Year:  2016        PMID: 27862047      PMCID: PMC5403596          DOI: 10.1002/jcc.24660

Source DB:  PubMed          Journal:  J Comput Chem        ISSN: 0192-8651            Impact factor:   3.376


  127 in total

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2.  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
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Authors:  Jana Khandogin; Charles L Brooks
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Review 4.  Computations of standard binding free energies with molecular dynamics simulations.

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Journal:  J Phys Chem B       Date:  2009-02-26       Impact factor: 2.991

5.  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

6.  Ions and counterions in a biological channel: a molecular dynamics simulation of OmpF porin from Escherichia coli in an explicit membrane with 1 M KCl aqueous salt solution.

Authors:  Wonpil Im; Benoît Roux
Journal:  J Mol Biol       Date:  2002-06-21       Impact factor: 5.469

7.  Generalized born model with a simple smoothing function.

Authors:  Wonpil Im; Michael S Lee; Charles L Brooks
Journal:  J Comput Chem       Date:  2003-11-15       Impact factor: 3.376

8.  Molecular dynamics simulation of the gramicidin channel in a phospholipid bilayer.

Authors:  T B Woolf; B Roux
Journal:  Proc Natl Acad Sci U S A       Date:  1994-11-22       Impact factor: 11.205

9.  Simulating the distance distribution between spin-labels attached to proteins.

Authors:  Shahidul M Islam; Benoît Roux
Journal:  J Phys Chem B       Date:  2015-02-18       Impact factor: 2.991

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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  61 in total

1.  CHARMM-GUI Martini Maker for modeling and simulation of complex bacterial membranes with lipopolysaccharides.

Authors:  Pin-Chia Hsu; Bart M H Bruininks; Damien Jefferies; Paulo Cesar Telles de Souza; Jumin Lee; Dhilon S Patel; Siewert J Marrink; Yifei Qi; Syma Khalid; Wonpil Im
Journal:  J Comput Chem       Date:  2017-08-03       Impact factor: 3.376

2.  Coarse-Grained Molecular Dynamics Simulations of Membrane Proteins: A Practical Guide.

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3.  A Kepler Workflow Tool for Reproducible AMBER GPU Molecular Dynamics.

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Journal:  Environ Sci Nano       Date:  2017-12-20

5.  In silico characterization of residues essential for substrate binding of human cystine transporter, xCT.

Authors:  Monika Sharma; C R Anirudh
Journal:  J Mol Model       Date:  2019-11-09       Impact factor: 1.810

6.  Characterization of Lipid-Protein Interactions and Lipid-Mediated Modulation of Membrane Protein Function through Molecular Simulation.

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7.  Chemical Additives Enable Native Mass Spectrometry Measurement of Membrane Protein Oligomeric State within Intact Nanodiscs.

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8.  Computer simulations of protein-membrane systems.

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Review 9.  Molecular dynamics simulations in photosynthesis.

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10.  Deciphering collaborative sidechain motions in proteins during molecular dynamics simulations.

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