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Prediction of the enantioselectivity of lipases and esterases by molecular docking method with modified force field parameters
Author(s) -
Ji Liu,
Xiaoling Tang,
Hongwei Yu
Publication year - 2009
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.22596
Subject(s) - docking (animal) , chemistry , protein–ligand docking , van der waals force , molecular dynamics , hydrogen bond , stereochemistry , computational chemistry , searching the conformational space for docking , enantiomer , force field (fiction) , enzyme , molecule , protein structure , organic chemistry , biochemistry , computer science , virtual screening , medicine , nursing , artificial intelligence
In the work, molecular docking method was applied to extensively predict the enantioselectivity of lipases and esterases. A ligand library consisted of 69 chiral substrates was docked to four lipases and two esterases to set up the prediction model. During the docking process, necessary modification was carried out on van de Waals and hydrogen bond parameters of enzyme/substrate pair so that the ligands were able to adopt productive geometry in the enzymes. The docking results correctly indicated the enantiopreference for 91% (63/69) of docking pairs and the docking energy difference between substrate enantiomers (ΔΔ G docking ) was significantly (correlation coefficient = 0.72, P < 0.05) correlated with the activation free energy difference (ΔΔ G ≠ ) that was quantitatively correlated with enantioselectivity of the enzymes. The prediction method was further validated by docking with another 12 enzyme/substrate pairs. Moreover, the prediction error was susceptible to the size of groups bonded to substrate's chiral center and expected ΔΔ G ≠ values but was not related to the substrate type and reaction medium. The possible reasons of observed error were discussed. It is demonstrated that the docking method has great application potential in high performance prediction of enzyme enantioselectivity. Biotechnol. Bioeng. 2010. 105: 687–696. © 2009 Wiley Periodicals, Inc.