[논문]Evaluation of Advanced Structure-Based Virtual Screening Methods for Computer-Aided Drug Discovery

Lee, Hui-Sun; Choi, Ji-Won; Yoon, Suk-Joon

Evaluation of Advanced Structure-Based Virtual Screening Methods for Computer-Aided Drug Discovery 원문보기

Genomics & informatics, v.5 no.1, 2007년, pp.24 - 29

Lee, Hui-Sun (Department of Biological Sciences, Research Center for Women’s Diseases (RCWD), Sookmyung Women’s University) , Choi, Ji-Won (Department of Biological Sciences, Research Center for Women’s Diseases (RCWD), Sookmyung Women’s University) , Yoon, Suk-Joon (1Department of Biological Sciences, Research Center for Women’s Diseases (RCWD), Sookmyung Women’s University)

Abstract ▼ AI-Helper

Computational virtual screening has become an essential platform of drug discovery for the efficient identification of active candidates. Moleculardocking, a key technology of receptor-centric virtual screening, is commonly used to predict the binding affinities of chemical compounds on target receptors. Despite the advancement and extensive application of these methods, substantial improvement is still required to increase their accuracy and time-efficiency. Here, we evaluate several advanced structure-based virtual screening approaches for elucidating the rank-order activity of chemical libraries, and the quantitative structureactivity relationship (QSAR). Our results show that the ensemble-average free energy estimation, including implicit solvation energy terms, significantly improves the hit enrichment of the virtual screening. We also demonstrate that the assignment of quantum mechanical-polarized (QM-polarized) partial charges to docked ligands contributes to the reproduction of the crystal pose of ligands in the docking and scoring procedure.

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제안 방법

eMBrAcE applies multiple minimizations, during which each of the specified pre-positioned ligands is minimized with the receptor. Forthe energy-minimized structures, the calculation is performed first on the receptor (Epra 어 n), then on the ligand (£焼扁), and finally on the complex (Eqbx). The energy difference is then calculated as:
Various descriptors extracted from the structural information on ligand-receptor complex may provide an advantageous solution to creating a reliable binding-affinity-prediction model. Here, we combined the results obtained from a standard docking protocol with data from three different structure-based descriptors, and then investigated the utility of these descriptors on the virtual screening efficiency for ERa ligands (Fig. 1). The virtual screening efficiency was compared using an analysis of receiver operating characteristic (ROC) curves (Hand ef al.
The authors gratefully acknowledge Dr. Weida Tong (National Center for Toxicological Research, U.S. Food & Drug Administration, Jefferson, AR) for providing the experimental data set and 2D structures of Estrogen Receptor compounds which were used in this study. This research was supported by Sookmyung Women's University Research Grants 1-0603-0020.
Two receptor co-crystal structures, estrogen receptor a (ERa, PDB entry: 3ERD) and peroxisome proliferatoractivated receptory(PPARy, PDB entry: 1KNU), both of which belong to the nuclear receptor superfamily, were used in this study. The coordinates for these proteins were obtained from the RCSB Protein Data Bank (http://w\aaa/.

이론/모형

TheeMBrAcE, Prime MM-GBSAand Liaison calculations were performed using the 니gand & Structure-Based Descriptors (LSBD) application of the Schrodinger sothAare package. These calculations w려*e applied the ligand-receptor complex structures obtained from Glide docking.

참고문헌 (19)

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