SmoPSI: Analysis and Prediction of Small Molecule Binding Sites Based on Protein Sequence Information
Joint Authors
Wang, Wei
Li, Keliang
Lv, Hehe
Zhang, Hongjun
Wang, Shixun
Huang, Junwei
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-11-13
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
The analysis and prediction of small molecule binding sites is very important for drug discovery and drug design.
The traditional experimental methods for detecting small molecule binding sites are usually expensive and time consuming, and the tools for single species small molecule research are equally inefficient.
In recent years, some algorithms for predicting binding sites of protein-small molecules have been developed based on the geometric and sequence characteristics of proteins.
In this paper, we have proposed SmoPSI, a classification model based on the XGBoost algorithm for predicting the binding sites of small molecules, using protein sequence information.
The model achieved better results with an AUC of 0.918 and an ACC of 0.913.
The experimental results demonstrate that our method achieves high performances and outperforms many existing predictors.
In addition, we also analyzed the binding residues and nonbinding residues and finally found the PSSM; hydrophilicity, hydrophobicity, charge, and hydrogen bonding have obviously different effects on the binding-site predictions.
American Psychological Association (APA)
Wang, Wei& Li, Keliang& Lv, Hehe& Zhang, Hongjun& Wang, Shixun& Huang, Junwei. 2019. SmoPSI: Analysis and Prediction of Small Molecule Binding Sites Based on Protein Sequence Information. Computational and Mathematical Methods in Medicine،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1130481
Modern Language Association (MLA)
Wang, Wei…[et al.]. SmoPSI: Analysis and Prediction of Small Molecule Binding Sites Based on Protein Sequence Information. Computational and Mathematical Methods in Medicine No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1130481
American Medical Association (AMA)
Wang, Wei& Li, Keliang& Lv, Hehe& Zhang, Hongjun& Wang, Shixun& Huang, Junwei. SmoPSI: Analysis and Prediction of Small Molecule Binding Sites Based on Protein Sequence Information. Computational and Mathematical Methods in Medicine. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1130481
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1130481