iATP: A Sequence Based Method for Identifying Anti-tubercular Peptides

Author(s): Wei Chen*, Pengmian Feng, Fulei Nie

Journal Name: Medicinal Chemistry

Volume 16 , Issue 5 , 2020

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Graphical Abstract:


Background: Tuberculosis is one of the biggest threats to human health. Recent studies have demonstrated that anti-tubercular peptides are promising candidates for the discovery of new anti-tubercular drugs. Since experimental methods are still labor intensive, it is highly desirable to develop automatic computational methods to identify anti-tubercular peptides from the huge amount of natural and synthetic peptides. Hence, accurate and fast computational methods are highly needed.

Methods and Results: In this study, a support vector machine based method was proposed to identify anti-tubercular peptides, in which the peptides were encoded by using the optimal g-gap dipeptide compositions. Comparative results demonstrated that our method outperforms existing methods on the same benchmark dataset. For the convenience of scientific community, a freely accessible web-server was built, which is available at http://lin-group.cn/server/iATP.

Conclusion: It is anticipated that the proposed method will become a useful tool for identifying anti-tubercular peptides.

Keywords: Tuberculosis, anti-tubercular peptides, g-gap dipeptide, support vector, machine, feature selection, web-server.

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Article Details

Year: 2020
Published on: 07 August, 2020
Page: [620 - 625]
Pages: 6
DOI: 10.2174/1573406415666191002152441
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