Recognition of Ion Ligand Binding Sites Based on Amino Acid Features with the Fusion of Energy, Physicochemical and Structural Features

Author(s): Shan Wang, Xiuzhen Hu*, Zhenxing Feng, Liu Liu, Kai Sun, Shuang Xu

Journal Name: Current Pharmaceutical Design

Volume 27 , Issue 8 , 2021


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Abstract:

Background: Rational drug molecular design based on virtual screening requires the ligand binding site to be known. Recently, the recognition of ion ligand binding site has become an important research direction in pharmacology.

Methods: In this work, we selected the binding residues of 4 acid radical ion ligands (NO2 -, CO3 2-, SO4 2- and PO4 3-) and 10 metal ion ligands (Zn2+, Cu2+, Fe2+, Fe3+, Ca2+, Mg2+, Mn2+, Na+, K+ and Co2+) as research objects. Based on the protein sequence information, we extracted amino acid features, energy, physicochemical, and structure features. Then, we incorporated the above features and input them into the MultilayerPerceptron (MLP) and support vector machine (SVM) algorithms.

Results: In the independent test, the best accuracy was higher than 92.5%, which was better than the previous results on the same dataset. In addition, we found that energy information is an important factor affecting the prediction results.

Conclusion: Finally, we set up a free web server for the prediction of protein-ion ligand binding sites (http://39.104.77.103:8081/lsb/HomePage/HomePage.html). This study is helpful for molecular drug design.

Keywords: Energy feature, binding site, ion ligand, information entropy, protein-ion ligand binding, rational drug molecular design.

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Article Details

VOLUME: 27
ISSUE: 8
Year: 2021
Published on: 08 April, 2021
Page: [1093 - 1102]
Pages: 10
DOI: 10.2174/1381612826666201029100636
Price: $65

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