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Multi-algorithm and multi-model based drug target prediction and web server.

ABSTRACT: To develop a reliable computational approach for predicting potential drug targets based merely on protein sequence.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.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.Reliable and robust drug target prediction based on protein sequences is achieved using the multi-algorithm and multi-model strategy.

SUBMITTER: Liu YT

PROVIDER: S-EPMC4647888 | biostudies-other | 2014 Mar

REPOSITORIES: biostudies-other

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Multi-algorithm and multi-model based drug target prediction and web server.

Liu Ying-tao YT Li Yi Y Huang Zi-fu ZF Xu Zhi-jian ZJ Yang Zhuo Z Chen Zhu-xi ZX Chen Kai-xian KX Shi Ji-ye JY Zhu Wei-liang WL

Acta pharmacologica Sinica 20140203 3

<h4>Aim</h4>To develop a reliable computational approach for predicting potential drug targets based merely on protein sequence.<h4>Methods</h4>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.<h4>Results</h4>Twenty one prediction models for each of the 3 algorithms were successfully de ...[more]

PMID: 24487966

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