CHARMM: A program for macromolecular energy, minimization, and dynamics calculations

By Bernard R. Brooks, R. Bruccoleri, B. D. Olafson, D. States, S. Swaminathan, Martin Karplus. 1983

Subfields: Computational Chemistry & Drug Discovery

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Citations in the corpus

Molecular Docking and Structure-Based Drug Design Strategies (2015, methodology): “Among the diverse available force-fields, AMBER [104], CHARMM [105] and GROMOS [106], can be highlighted as widely used in molecular dynamics simulations.”
Toward optimal fragment generations for ab initio protein structure assembly (2012, background): “For each query sequence with length L , top 0.4 L predicted contacts are selected for each of the three contact orders, that is, | i – j| in [6, 11], [12, 24], and > 24, which result in 1.2 L contact predictions in total for mixed-order contacts.”
The Rosetta all-atom energy function for macromolecular modeling and design (2017, background): “18,19 Many of these energy functions also rely on new terms and parameterizations.”
N-body Networks: a Covariant Hierarchical Neural Network Architecture for Learning Atomic Potentials (2018, background): “Popular examples of such so-called empirical potentials (empirical force ﬁelds) include the CHARMM models (Brooks et al., 1983; 2009) and others.”
Ab Initio Protein Structure Assembly Using Continuous Structure Fragments and Optimized Knowledge-based Force Field (2012, methodology): “(7) has the value in the range of [0, 1], whereas 0 means it is completely buried and 1 means it completely exposes in solution.”
Automated Minimization of Steric Clashes in Protein Structures (2011, methodology): “We calculate the Van der Waals repulsion energy using the nonbonded parameters from the CHARMM19 force field,13 which are identical to CNS14 parameters except for carboxyl oxygen atoms.”
Effective energy function for proteins in solution (1999, background): “DGi slv 5 DGi ref 2 o jÞi fi(rij)Vj (5)”
Force fields for protein simulations. (2003, methodology): “As with Amber, the CHARMM program (Chemistry at HARvard using Molecular Mechanics) (Brooks et al., 1983) was originally developed in the early 1980s and initially used an extended atom force field with no explicit hydrogens.”
Molecular docking: a powerful approach for structure-based drug discovery. (2011, methodology): “Molecular dynamics For further refinement after docking [68-70]”
ClusPro: a fully automated algorithm for protein-protein docking (2004, methodology): “The top cluster centers are then CHARMm (26) minimized in the presence of the receptor, and concatenated into PDB NMR format, compressed in the Unix '.gz' format, and sent back to the user via email.”