A quantum mechanics-based halogen bonding scoring function for protein-ligand interactions.

Yang, Zhuo; Liu, Yingtao; Chen, Zhaoqiang; Xu, Zhijian; Shi, Jiye; Chen, Kaixian; Zhu, Weiliang

doi:10.1007/s00894-015-2681-6

Cited by 23Computational Drug Discovery MethodsCrystallography and molecular interactionsAdvanced Chemical Physics Studies

A quantum mechanics-based halogen bonding scoring function for protein-ligand interactions.

Yang, Zhuo, Liu, Yingtao, Chen, Zhaoqiang, Xu, Zhijian, Shi, Jiye, Chen, Kaixian, Zhu, Weiliang·2015·Journal of Molecular Modeling

DOI 10.1007/s00894-015-2681-6

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Abstract

A quantum mechanics-based scoring function for halogen bonding interaction, namely XBScore(QM), is developed based on 18,135 sets of geometrical and energetical parameters optimized at M06-2X/aug-cc-pVDZ level. Applying the function on typical halogen bonding systems from Protein Data Bank demonstrates its strong ability of predicting halogen bonding as attractive interaction with strength up to -4 kcal mol(-1). With a diverse set of proteins complexed with halogenated ligands, a systematic evaluation demonstrates the integrative advantage of XBScore(QM) over 12 other scoring functions on halogen bonding in four aspects, viz. pseudo docking power, ranking power, scoring power, and genuine docking power. Thus, this study not only provides a practicable scoring function of halogen bonding for high throughput virtual screening, but also serves as a benchmark for evaluating the performance of current scoring functions on characterizing halogen bonding.

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The XBScoreQM scoring function achieved good performance on both pose and affinity prediction when compared against 12 diverse scoring functions and increased predictive capacity for protein-ligand complexes with X-bond interactions.
“The new scoring function achieved good performances on both pose and affinity prediction when compared against 12 diverse scoring functions, and increase predictive capacity to deal with protein–ligand complexes with X-bond interactions.”
From Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges (2018) · cites this paper as Yang et al., 2015

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Authors: Yang, Z., Liu, Y., Chen, Z., Xu, Z., Shi, J., Chen, K., & Zhu, W.
Affiliations: Chinese Academy of Sciences (CN)
UCB Pharma (United Kingdom) (GB)
Corresponding author: Zhu, Weiliang
ORCID: Yang, Zhuo
Liu, Yingtao
Chen, Zhaoqiang
Xu, Zhijian
Shi, Jiye
Chen, Kaixian
Zhu, Weiliang
Venue: Journal of Molecular Modeling
Publisher: Springer Science and Business Media LLC
Published: 2015-05-10
Volume: 21
Issue: 6
Pages: 138-138
ISSN: 0948-5023 (ISSN-L)
1610-2940
DOI: 10.1007/s00894-015-2681-6
OpenAlex: W2111431601
Cited by: 23
References: 99
Citations by year: 2026: 1 · 2022: 2 · 2021: 2 · 2020: 3 · 2019: 4 · 2018: 2 · 2017: 3 · 2016: 5 · 2015: 1
FWCI: 3.77
Type: journal article
Language: en
Open access: closed
Licence: www.springer.com/tdm (tdm)
Locations: Journal of Molecular Modeling (publishedVersion)
PubMed (publishedVersion)
Topics: Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Crystallography and molecular interactions
Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Advanced Chemical Physics Studies
Keywords: halogen bonding, protein-ligand interactions, scoring functions, quantum chemical calculations, M06-2X, virtual screening, docking, binding affinity prediction, halogenated ligands
MeSH terms: Algorithms, Halogens, Ligands, Protein Binding, Proteins, Quantum Theory, Molecular Structure

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A quantum mechanics-based halogen bonding scoring function for protein-ligand interactions.

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