Insights into Protein–Ligand Noncovalent Interaction Networks: A Database Survey and Quantum Chemistry Calculation Study

Protein-ligand binding is largely determined by multiple noncovalent interactions (NCIs), which may exhibit synergistic or antagonistic effects. Here, we applied an approach combining PDB statistics with QM/MM calculations to quantify relationships among five major NCIs: halogen bonds (XB), hydrogen bonds (HB), cation-π interactions (CP), π-π interactions (PP), and salt bridges (SB). Statistical analysis showed that 69.28% of the ligands with SB acceptors interact with protein residues, followed by HB acceptors (65.21%) and XB donors (62.76%). Energy analysis revealed the strongest antagonism between the CP acceptor and SB acceptor (median Δ<i>E</i><sub>Syn</sub> = 1.31 kcal/mol) and the strongest synergy between the HB donor and acceptor (-0.73 kcal/mol). The effects are enhanced when their interaction distances are <7.5 Å. For three-NCI systems, overall energies were well approximated by the sum of the two-NCI systems (<i>R</i><sup>2</sup> = 0.980). These results reveal a complicated NCI network, which provides guidance for rational ligand design.

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Publication Details

Journal
Journal of Medicinal Chemistry
Published
2026-02-16
DOI
https://doi.org/10.1021/acs.jmedchem.5c03216
Primary Topic
Crystallography and molecular interactions
Type
article
Field-Weighted Citation Impact
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article

Insights into Protein–Ligand Noncovalent Interaction Networks: A Database Survey and Quantum Chemistry Calculation Study

Ziyu Peng, Zhijian Xu, Zijian Han, Ruitong Luo et al.
Journal of Medicinal Chemistry
Crystallography and molecular interactions
article

Insights into Protein–Ligand Noncovalent Interaction Networks: A Database Survey and Quantum Chemistry Calculation Study

Ziyu Peng, Zhijian Xu, Zijian Han, Ruitong Luo, Yuanjie Chen, Jintian Li, Qian Zhang
article en

Abstract

Protein-ligand binding is largely determined by multiple noncovalent interactions (NCIs), which may exhibit synergistic or antagonistic effects. Here, we applied an approach combining PDB statistics with QM/MM calculations to quantify relationships among five major NCIs: halogen bonds (XB), hydrogen bonds (HB), cation-π interactions (CP), π-π interactions (PP), and salt bridges (SB). Statistical analysis showed that 69.28% of the ligands with SB acceptors interact with protein residues, followed by HB acceptors (65.21%) and XB donors (62.76%). Energy analysis revealed the strongest antagonism between the CP acceptor and SB acceptor (median Δ<i>E</i><sub>Syn</sub> = 1.31 kcal/mol) and the strongest synergy between the HB donor and acceptor (-0.73 kcal/mol). The effects are enhanced when their interaction distances are <7.5 Å. For three-NCI systems, overall energies were well approximated by the sum of the two-NCI systems (<i>R</i><sup>2</sup> = 0.980). These results reveal a complicated NCI network, which provides guidance for rational ligand design.

Journal of Medicinal ChemistryVol. 69(6)
Nanjing University of Chinese Medicine (CN), East China University of Science and Technology (CN), Henan University (CN), Chinese Academy of Sciences (CN), Shanghai Institute of Materia Medica (CN), Drug Discovery Laboratory (Norway) (NO), University of Chinese Academy of Sciences (CN), State Key Laboratory of Drug Research, East China Normal University (CN)
Openalex Percentile: Top 53%
Crystallography and molecular interactions
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Insights into Protein–Ligand Noncovalent Interaction Networks: A Database Survey and Quantum Chemistry Calculation Study — Ziyu Peng, Zhijian Xu, et al. · Journal of Medicinal Chemistry (2026) | TGRS Research Map | TGRS