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. 2019 Mar;33(3):367-374.
doi: 10.1007/s10822-019-00185-0. Epub 2019 Jan 28.

Predicting protein-ligand binding modes for CELPP and GC3: workflows and insight

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Predicting protein-ligand binding modes for CELPP and GC3: workflows and insight

Xianjin Xu et al. J Comput Aided Mol Des. 2019 Mar.

Abstract

Drug Design Data Resource (D3R) continues to release valuable benchmarking datasets to promote improvement and development of computational methods for new drug discovery. We have developed several methods for protein-ligand binding mode prediction during the participation in the D3R challenges. In the present study, these methods were integrated, automated, and systematically tested using the large-scale data from Continuous Evaluation of Ligand Pose Prediction (CELPP) and a subset of Grand challenge 3 (GC3). The results show that current molecular docking methods benefit from the increasing number of protein-ligand complex structures deposited in Protein Data Bank. Using an appropriate protein structure for docking significantly improves the success rate of the binding mode prediction. The results of our template-based method and docking method are compared and discussed. Our future direction include the combination of these two methods for binding mode prediction.

Keywords: Drug discovery; Molecular docking; Molecular similarity; Protein–ligand interaction; Template-based.

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Figures

Figure 1
Figure 1
The results of binding mode prediction for CELPP using the bound protein structures and the candidate protein structures provided by CELPP for docking. Different RMSD values were used as the thresholds that defined successful predictions. (A) The success rate when only the top predicted model was considered for each protein structure. (B) The success rate when top 5 models were considered for each protein structure. (C) The success rate when all the models were considered for each protein structure.
Figure 2
Figure 2
(A) The results of binding mode prediction for CELPP using the user-specified protein structures (i.e. hiSHAFTS structures in this study) for both docking-based and template-based methods. Different RMSD values were used as the thresholds for the definition of successful predictions. (B) The correlation between the RMSD values of the binding modes predicted by the template-based method and the corresponding similarity scores between the query ligands and the corresponding template ligands.
Figure 3
Figure 3
The top predicted binding mode (colored red) of CatS_1 in comparison with the binding mode given by the crystal structure (colored green) released by D3R. The protein is shown in surface representation. The ligand (Cast_1) is plotted in stick representation. The predicted binding mode was obtained from the docking method using the bound protein structure.

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