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A knowledge-based halogen bonding scoring function for predicting protein-ligand interactions

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Abstract

Halogen bonding, a non-covalent interaction between the halogen σ-hole and Lewis bases, could not be properly characterized by majority of current scoring functions. In this study, a knowledge-based halogen bonding scoring function, termed XBPMF, was developed by an iterative method for predicting protein-ligand interactions. Three sets of pairwise potentials were derived from two training sets of protein-ligand complexes from the Protein Data Bank. It was found that two-dimensional pairwise potentials could characterize appropriately the distance and angle profiles of halogen bonding, which is superior to one-dimensional pairwise potentials. With comparison to six widely used scoring functions, XBPMF was evaluated to have moderate power for predicting protein-ligand interactions in terms of “docking power”, “ranking power” and “scoring power”. Especially, it has a rather satisfactory performance for the systems with typical halogen bonds. To the best of our knowledge, XBPMF is the first halogen bonding scoring function that is not dependent on any dummy atom, and is practical for high-throughput virtual screening. Therefore, this scoring function should be useful for the study and application of halogen bonding interactions like molecular docking and lead optimization.

Heat map of 2D XB potentials for OA-Cl

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (81273435, 21021063 and 91013008) and the State Key Laboratory of Drug Research (SIMM1203KF-01). Computational resources were supported by Computer Network Information Center (CNIC), Chinese Academy of Science (CAS) and Shanghai Supercomputing Center (SCC).

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  1. Drug Discovery and Design Center, CAS Key Laboratory of Receptor Structure and Function, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China

    Yingtao Liu, Zhijian Xu, Zhuo Yang, Kaixian Chen & Weiliang Zhu

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  1. Yingtao Liu
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  2. Zhijian Xu
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  3. Zhuo Yang
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Correspondence to Weiliang Zhu.

Electronic supplementary material

Supporting information Table S1 lists the ligand atom types. Table S2 lists the protein atom types. Table S3 depicts the intercorrelations between any two scoring functions with correlation coefficient cutoff >=80 % on eight clusters with respect to ranking power. Figure S1 is the heat maps of 2D XB potentials for four selected donor-acceptor pairs based on TrainingSet-1. Figure S2 is the 1D pairwise potentials for five selected atom type pairs based on TrainingSet-2. Figure S3 is the heat maps of 2D HB potentials for five selected donor-acceptor pairs based on TrainingSet-1. Figure S4 depicts the intercorrelation coefficients of selected scoring functions based on optimized protein-ligand complexes of eight clusters. This material is available free of charge via the Internet at http://pubs.acs.org.

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Liu, Y., Xu, Z., Yang, Z. et al. A knowledge-based halogen bonding scoring function for predicting protein-ligand interactions. J Mol Model 19, 5015–5030 (2013). https://doi.org/10.1007/s00894-013-2005-7

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