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Binding affinity prediction with different force fields: Examination of the linear interaction energy method
Author(s) -
Almlöf Martin,
Brandsdal BjØrn O.,
Åqvist Johan
Publication year - 2004
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.20047
Subject(s) - force field (fiction) , binding energy , chemistry , energy (signal processing) , computational chemistry , biological system , statistical physics , computer science , mathematics , physics , statistics , artificial intelligence , atomic physics , biology
A systematic study of the linear interaction energy (LIE) method and the possible dependence of its parameterization on the force field and system (receptor binding site) is reported. We have calculated the binding free energy for nine different ligands in complex with P450cam using three different force fields (Amber95, Gromos87, and OPLS‐AA). The results from these LIE calculations using our earlier parameterization give relative free energies of binding that agree remarkably well with the experimental data. However, the absolute energies are too positive for all three force fields, and it is clear that an additional constant term (γ) is required in this case. Out of five examined LIE models, the same one emerges as the best for all three force fields, and this, in fact, corresponds to our earlier one apart from the addition of the constant γ, which is almost identical for the three force fields. Thus, the present free energy calculations clearly indicate that the coefficients of the LIE method are independent of the force field used. Their relation to solvation free energies is also demonstrated. The only free parameter of the best model is γ, which is found to depend on the hydrophobicity of the binding site. We also attempt to quantify the binding site hydrophobicity of four different proteins which shows that the ordering of γ's for these sites reflects the fraction of hydrophobic surface area. © 2004 Wiley Periodicals, Inc. J Comput Chem 10: 1242–1254, 2004