Automation of the CHARMM General Force Field (CGenFF) I: Bond Perception and Atom Typing
Top Cited Papers
- 12 November 2012
- journal article
- research article
- Published by American Chemical Society (ACS) in Journal of Chemical Information and Modeling
- Vol. 52 (12), 3144-3154
- https://doi.org/10.1021/ci300363c
Abstract
Molecular mechanics force fields are widely used in computer-aided drug design for the study of drug-like molecules alone or interacting with biological systems. In simulations involving biological macromolecules, 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 charges is required. In the present article, which is part I of a series of two, we present the algorithms for bond perception and atom typing for the CHARMM General Force Field (CGenFF). The CGenFF atom typer first associates attributes to the atoms and bonds in a molecule, such as valence, bond order, and ring membership among others. Of note are a number of features that are specifically required for CGenFF. This information is then used by the atom typing routine to assign CGenFF atom types based on a programmable decision tree. This allows for straightforward implementation of CGenFF’s complicated atom typing rules and for equally straightforward updating of the atom typing scheme as the force field grows. The presented atom typer was validated by assigning correct atom types on 477 model compounds including in the training set as well as 126 test-set molecules that were constructed to specifically verify its different components. The program may be utilized via an online implementation at https://www.paramchem.org/.Keywords
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