Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2010 Mar;31(4):671-90.
doi: 10.1002/jcc.21367.

CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields

K Vanommeslaeghe  1 , E Hatcher, C Acharya, S Kundu, S Zhong, J Shim, E Darian, O Guvench, P Lopes, I Vorobyov, A D Mackerell Jr
Affiliations

CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields

K Vanommeslaeghe et al. J Comput Chem. 2010 Mar.

Abstract

The widely used CHARMM additive all-atom force field includes parameters for proteins, nucleic acids, lipids, and carbohydrates. In the present article, an extension of the CHARMM force field to drug-like molecules is presented. The resulting CHARMM General Force Field (CGenFF) covers a wide range of chemical groups present in biomolecules and drug-like molecules, including a large number of heterocyclic scaffolds. The parametrization philosophy behind the force field focuses on quality at the expense of transferability, with the implementation concentrating on an extensible force field. Statistics related to the quality of the parametrization with a focus on experimental validation are presented. Additionally, the parametrization procedure, described fully in the present article in the context of the model systems, pyrrolidine, and 3-phenoxymethylpyrrolidine will allow users to readily extend the force field to chemical groups that are not explicitly covered in the force field as well as add functional groups to and link together molecules already available in the force field. CGenFF thus makes it possible to perform "all-CHARMM" simulations on drug-target interactions thereby extending the utility of CHARMM force fields to medicinally relevant systems.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Pyrrolidine with atom numbering convention.
Figure 2
Figure 2
Interaction orientations of pyrrolidine with water molecules that were used for charge optimization. Note that only a single water molecule is interacting with pyrrolidine during each calculation; all water molecules are shown simultaneously only for convenience.
Figure 3
Figure 3
The 1T2 (carbon atoms in black) and 1E (carbon atoms in cyan) conformations of pyrrolidine.
Figure 4
Figure 4
Potential energy scans of pyrrolidine. The HN PES was defined as N1-C1-C5-H (Figure 1).
Figure 5
Figure 5
3-phenoxymethylpyrrolidine (a) and two “parent” model compounds from which it “inherited” parameters: ethoxybenzene (b) and 3-hydroxymethyltetrahydrofuran (c)
Figure 6
Figure 6
Potential energy scans on the central torsion of the oxymethyl linker in 3-phenoxymethylpyrrolidine.
Figure 7
Figure 7
Comparison of the QM and CGenFF minimum water interaction energies for the model compound-water monohydrate interactions. The QM level of theory is MP2/6–31G(d) for model compounds containing sulfur atoms and scaled HF/6–31G(d) for all remaining compounds. The green lines represent deviations of ± 0.5 kcal/mol.
Figure 8
Figure 8
Comparison of the QM and CGenFF minimum water interaction distances for the model compound-water monohydrate interactions. The QM level of theory is MP2/6–31G(d) for model compounds containing sulfur atoms and HF/6–31G(d) for all remaining compounds. Green: direct interaction with heteroatoms (O, N, NH, NH+); cyan: 5-membered ring C(sp2) adjacent to heteroatom; blue: C(aromatic) adjacent to heteroatom; magenta: 5-membered ring C(sp3) adjacent to heteroatom; red: C(sp3) adjacent to N+; orange: C(sp), S. The bottom dotted line represents the situation where the CGenFF distance is 0.2 Å smaller than the QM distance, as ideally would be the case for regular hydrogen bonds. The top dotted line represents CGenFF=QM, which is the ideal case for interactions that have a weak hydrogen bonding character. The top and bottom solid lines represent deviations of ± 0.2 Å.
Figure 9
Figure 9
Molecular volumes from pure solvent simulations of the model compounds that exist as liquids at room temperature. The thick line is the regression line for which the equation is shown. The dotted line represents perfect reproduction of the experimental data, while the thin parallel lines represent deviations of ± 10 Å3. The experimental molecular volume of each compound was derived by dividing its molecular mass by its experimental density. Experimental densities were mostly obtained from the catalog of Sigma-Aldrich®, supplemented with data from the CAS REGISTRYSM (accessed through the SciFinder Scholar® interface), from the CRC Handbook of Chemistry and Physics, and from the catalog of TCI America.
Figure 10
Figure 10
Heats of vaporization from pure solvent simulations of the model compounds that exist as liquids at room temperature. The thick line is the regression line for which the equation is shown. The dotted line represents perfect reproduction of the experimental data, while the thin parallel lines represent deviations of ± 1 kcal/mol. Experimental data were mostly obtained from reference , supplemented with data from Dykyi,, Geiseler and Rauh (obtained through the NIST Chemistry Webbook82) and the CRC Handbook of Chemistry and Physics.
Scheme 1
Scheme 1
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Ruscio JZ, Onufriev A. Biophys J. 2006;91(11):4121–4132. - PMC - PubMed
    1. Noskov SYu, Roux B. Biophys Chem. 2006;124(3):279–291. - PubMed
    1. Sanbonmatsu KY, Joseph S, Tung CS. Proc Natl Acad Sci USA. 2005;102(44):15854–15859. - PMC - PubMed
    1. Phillips JC, Braun R, Wang W, Gumbart J, Tajkhorshid E, Villa E, Chipot C, Skeel RD, Kale L, Schulten K. J Comput Chem. 2005;26:1781–1802. - PMC - PubMed
    1. Bowers KJ, Chow E, Xu H, Dror RO, Eastwood MP, Gregersen BA, Klepeis JL, Kolossváry I, Moraes MA, Sacerdoti FD, Salmon JK, Shan Y, Shaw DE. Proceedings of the ACM/IEEE Conference on Supercomputing (SC06); Tampa, Florida. November 11–17 2006.

Publication types

LinkOut - more resources

-