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

By Kenno Vanommeslaeghe, E. P. Raman, Alexander D. MacKerell. 2012

1,579 citations recorded by the source corpus.

Molecular mechanics force fields are widely used in computer-aided drug design for the study of drug candidates interacting with biological systems. In these simulations, the biological part is typically represented by a specialized biomolecular force field, while the drug is represented by a matching general (organic) force field. In order to apply these general force fields to an arbitrary drug-like molecule, functionality for assignment of atom types, parameters and partial atomic charges is required. In the present article, algorithms for the assignment of parameters and charges for the CHARMM General Force Field (CGenFF) are presented. These algorithms rely on the existing parameters and charges that were determined as part of the parametrization of the force field. Bonded parameters are assigned based on the similarity between the atom types that define said parameters, while charges are determined using an extended bond-charge increment scheme. Charge increments were optimized to reproduce the charges on model compounds that were part of the parametrization of the force field. A “penalty score” is returned for every bonded parameter and charge, allowing the user to quickly and conveniently assess the quality of the force field representation of different parts of the compound of interest. Case studies are presented to clarify the functioning of the algorithms and the significance of their output data.

Subfields: Computational Theory and Mathematics, Molecular Biology, Physical and Theoretical Chemistry

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Citations in the corpus

Driven to Near-Experimental Accuracy by Refinement via Molecular Dynamics Simulations (2019, background): “32,33 For metal ions, additional distance restraints were applied to enforce their predicted coordination geometry with conserved nearby amino acids.”
Computer-Aided Drug Design Methods (2017, methodology): “When parameters are missing in the existing force field, which is common for small drug-like molecules, automated parameter generation programs such as the CGenFF program (41, 42) or Antechamber (43) can be used to complete the force field.”
From Proteins to Perturbed Hamiltonians: A Suite of Tutorials for the GROMACS-2018 Molecular Simulation Package [Article v1.0] (2019, methodology): “CGenFF is both a parameter set (compatible with the CHARMM force field) and a program that builds smallmolecule topologies according to existing rules [70, 71].”
LigParGen web server: an automatic OPLS-AA parameter generator for organic ligands (2017, background): “For commercial re-use, please contact journals.permissions@oup.com with parameters from the CHARMM36/CGenFF force field and charges assigned by analogy.”
Positive allosteric mechanisms of adenosine A1 receptor-mediated analgesia (2021, methodology): “Force field parameters of the agonist ADO and PAM MIPS521 were obtained from the CHARMM ParamChem web server[64, 65].”