Computational prediction of binding affinity for CYP1A2-ligand complexes using empirical free energy calculations

Research output: Contribution to journalJournal article

Standard

Computational prediction of binding affinity for CYP1A2-ligand complexes using empirical free energy calculations. / Poongavanam, Vasanthanathan; Olsen, Lars; Jørgensen, Flemming Steen; Vermeulen, Nico P E; Oostenbrink, Chris.

In: Drug Metabolism and Disposition, Vol. 38, No. 8, 2010, p. 1347-1354.

Research output: Contribution to journalJournal article

Harvard

Poongavanam, V, Olsen, L, Jørgensen, FS, Vermeulen, NPE & Oostenbrink, C 2010, 'Computational prediction of binding affinity for CYP1A2-ligand complexes using empirical free energy calculations', Drug Metabolism and Disposition, vol. 38, no. 8, pp. 1347-1354. https://doi.org/10.1124/dmd.110.032946

APA

Poongavanam, V., Olsen, L., Jørgensen, F. S., Vermeulen, N. P. E., & Oostenbrink, C. (2010). Computational prediction of binding affinity for CYP1A2-ligand complexes using empirical free energy calculations. Drug Metabolism and Disposition, 38(8), 1347-1354. https://doi.org/10.1124/dmd.110.032946

Vancouver

Poongavanam V, Olsen L, Jørgensen FS, Vermeulen NPE, Oostenbrink C. Computational prediction of binding affinity for CYP1A2-ligand complexes using empirical free energy calculations. Drug Metabolism and Disposition. 2010;38(8):1347-1354. https://doi.org/10.1124/dmd.110.032946

Author

Poongavanam, Vasanthanathan ; Olsen, Lars ; Jørgensen, Flemming Steen ; Vermeulen, Nico P E ; Oostenbrink, Chris. / Computational prediction of binding affinity for CYP1A2-ligand complexes using empirical free energy calculations. In: Drug Metabolism and Disposition. 2010 ; Vol. 38, No. 8. pp. 1347-1354.

Bibtex

@article{cea26dc0a93011df928f000ea68e967b,
title = "Computational prediction of binding affinity for CYP1A2-ligand complexes using empirical free energy calculations",
abstract = "Predicting binding affinities for receptor-ligand complexes is still one of the challenging processes in computational structure-based ligand design. Many computational methods have been developed to achieve this goal, such as docking and scoring methods, the linear interaction energy (LIE) method, and methods based on statistical mechanics. In the present investigation, we started from an LIE model to predict the binding free energy of structurally diverse compounds of cytochrome P450 1A2 ligands, one of the important human metabolizing isoforms of the cytochrome P450 family. The data set includes both substrates and inhibitors. It appears that the electrostatic contribution to the binding free energy becomes negligible in this particular protein and a simple empirical model was derived, based on a training set of eight compounds. The root mean square error for the training set was 3.7 kJ/mol. Subsequent application of the model to an external test set gives an error of 2.1 kJ/mol, which is remarkably good, considering the simplicity of the model. The structures of the protein-ligand interactions are further analyzed, again demonstrating the large versatility and plasticity of the cytochrome P450 active site.",
keywords = "Former Faculty of Pharmaceutical Sciences",
author = "Vasanthanathan Poongavanam and Lars Olsen and J{\o}rgensen, {Flemming Steen} and Vermeulen, {Nico P E} and Chris Oostenbrink",
year = "2010",
doi = "10.1124/dmd.110.032946",
language = "English",
volume = "38",
pages = "1347--1354",
journal = "Drug Metabolism and Disposition",
issn = "0090-9556",
publisher = "American Society for Pharmacology and Experimental Therapeutics",
number = "8",

}

RIS

TY - JOUR

T1 - Computational prediction of binding affinity for CYP1A2-ligand complexes using empirical free energy calculations

AU - Poongavanam, Vasanthanathan

AU - Olsen, Lars

AU - Jørgensen, Flemming Steen

AU - Vermeulen, Nico P E

AU - Oostenbrink, Chris

PY - 2010

Y1 - 2010

N2 - Predicting binding affinities for receptor-ligand complexes is still one of the challenging processes in computational structure-based ligand design. Many computational methods have been developed to achieve this goal, such as docking and scoring methods, the linear interaction energy (LIE) method, and methods based on statistical mechanics. In the present investigation, we started from an LIE model to predict the binding free energy of structurally diverse compounds of cytochrome P450 1A2 ligands, one of the important human metabolizing isoforms of the cytochrome P450 family. The data set includes both substrates and inhibitors. It appears that the electrostatic contribution to the binding free energy becomes negligible in this particular protein and a simple empirical model was derived, based on a training set of eight compounds. The root mean square error for the training set was 3.7 kJ/mol. Subsequent application of the model to an external test set gives an error of 2.1 kJ/mol, which is remarkably good, considering the simplicity of the model. The structures of the protein-ligand interactions are further analyzed, again demonstrating the large versatility and plasticity of the cytochrome P450 active site.

AB - Predicting binding affinities for receptor-ligand complexes is still one of the challenging processes in computational structure-based ligand design. Many computational methods have been developed to achieve this goal, such as docking and scoring methods, the linear interaction energy (LIE) method, and methods based on statistical mechanics. In the present investigation, we started from an LIE model to predict the binding free energy of structurally diverse compounds of cytochrome P450 1A2 ligands, one of the important human metabolizing isoforms of the cytochrome P450 family. The data set includes both substrates and inhibitors. It appears that the electrostatic contribution to the binding free energy becomes negligible in this particular protein and a simple empirical model was derived, based on a training set of eight compounds. The root mean square error for the training set was 3.7 kJ/mol. Subsequent application of the model to an external test set gives an error of 2.1 kJ/mol, which is remarkably good, considering the simplicity of the model. The structures of the protein-ligand interactions are further analyzed, again demonstrating the large versatility and plasticity of the cytochrome P450 active site.

KW - Former Faculty of Pharmaceutical Sciences

U2 - 10.1124/dmd.110.032946

DO - 10.1124/dmd.110.032946

M3 - Journal article

C2 - 20413725

VL - 38

SP - 1347

EP - 1354

JO - Drug Metabolism and Disposition

JF - Drug Metabolism and Disposition

SN - 0090-9556

IS - 8

ER -

ID: 21406498