Abstract
Aim:
To develop a reliable computational approach for predicting potential drug targets based merely on protein sequence.
Methods:
With drug target and non-target datasets prepared and 3 classification algorithms (Support Vector Machine, Neural Network and Decision Tree), a multi-algorithm and multi-model based strategy was employed for constructing models to predict potential drug targets.
Results:
Twenty one prediction models for each of the 3 algorithms were successfully developed. Our evaluation results showed that ∼30% of human proteins were potential drug targets, and ∼40% of putative targets for the drugs undergoing phase II clinical trials were probably non-targets. A public web server named D3TPredictor (http://www.d3pharma.com/d3tpredictor) was constructed to provide easy access.
Conclusion:
Reliable and robust drug target prediction based on protein sequences is achieved using the multi-algorithm and multi-model strategy.
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Acknowledgements
This work was supported by National Natural Science Foundation of China (81273435 and 21021063), National Science & Technology Projects (2012ZX09301001-004, 2012AA01A305, and 2013ZX09103001-001). Computational resources were provided by supercomputer TianHe-I in Tianjin and the Shanghai Supercomputing Center (SCC). The authors thank the developers of free and/or open source software for academic use, including SignalP-3.0, netOglyc-3.1d, netNglyc-1.0, tmhmm-2.0c and EMBOSS-6.0.1.
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Dataset S1. Classification of predicted targets from 20 025 proteins in the human proteome using the multi-algorithm and multi-model strategy presented in this work (EXCEL).
Tables S1–S8. Quantitative results with tables from Figures 2, 3, 4, 5, 6, 7, and 9 (DOC).
Supplementary information is available at Acta Pharmacologica Sinica's website.
Supplementary information
Dataset S1 (download XLS )
The first sheet, namely Full Targets, lists the classification of predicted full targets, and the second sheet, namely Quasi Targets, lists the classification of predicted quasi targets (XLS 818 kb)
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Liu, Yt., Li, Y., Huang, Zf. et al. Multi-algorithm and multi-model based drug target prediction and web server. Acta Pharmacol Sin 35, 419–431 (2014). https://doi.org/10.1038/aps.2013.153
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DOI: https://doi.org/10.1038/aps.2013.153
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