An improved GROMOS96 force field for aliphatic hydrocarbons in the condensed phase

By Lukas D. Schuler, Xavier Daura, W. V. van Gunsteren. Journal of Computational Chemistry, 2001

847 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/c6ddec26e07fe9185d8da7f616db8cf6400fd261

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In Atomic and Molecular Physics, and Optics

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Citations in the corpus

ProteinGCN: Protein model quality assessment using Graph Convolutional Networks (2020, background): “[30]), or deduced from diverse sets of known protein structures (various knowledge-based or statistical potentials GOAP [38], RW [36], DFIRE [39]), or both (Rosetta [17]), to the ones trained to estimate particular similarity scores (e.”
From Proteins to Perturbed Hamiltonians: A Suite of Tutorials for the GROMACS-2018 Molecular Simulation Package [Article v1.0] (2019, methodology): “com/gmx/biphasic) is a recent paper [63] that explored smallmolecule and amino-acid dynamics at a water-cyclohexane interface, to test the behavior of the GROMOS96 43A1 force field [22, 23] and topologies produced by the PRODRG server [64].”
A position-specific distance-dependent statistical potential for protein structure and functional study (2012, background): “, 1997; Sippl, 1990; Tanaka and Scheraga, 1976; Zhang and Zhang, 2010; Zhou and Zhou, 2002) compare favorably to physics-based potentials (Brooks et al., 2009; Bryngelson et al., 1995; Case et al., 2005; Dill, 1985, 1997; Dobson et al., 1998; Schuler et al., 2001; Shakhnovich, 2006) in many applicat”
Validation of the 53A6 GROMOS force field (2005, methodology): “Finally, the peptide simulations were compared to previous simulations based on the 45A3 parameter set (Schuler et al. 2001) and an older version of the methanol model”
Definition and testing of the GROMOS force-field versions 54A7 and 54B7 (2011, methodology): “2005) in conjunction with the parameter set of the GROMOS force field indicated: 45A4 (Schuler et al. 2001), 53A6 (Oostenbrink et al.”
ACPYPE - AnteChamber PYthon Parser interfacE (2012, methodology): “AutoSMILES [29] is implemented for YASARA [46], but is restricted to this commercial software package; the programme topolbuild is developed by Bruce D. Ray (personal communication), and generates topologies and parameters from a MOL2 file (with known charges) by using AMBER, GROMOS [47] or OPLS/AA ”
Strategies and molecular tools to fight antimicrobial resistance: resistome, transcriptome, and antimicrobial peptides (2013, methodology): “The refinement of the model in general uses methods of molecular dynamics calculations of force fields, the most common being the CHARMM (Brooks et al., 1983) and GROMOS (Schuler et al., 2001).”