A Web Server and Mobile App for Computing Hemolytic Potency of Peptides.

Chaudhary, Kumardeep and Kumar, Ritesh and Singh, Sandeep and Tuknait, Abhishek and Gautam, Ankur and Mathur, Deepika and Anand, Priya and Varshney, Grish C and Raghava, G.P.S. (2016) A Web Server and Mobile App for Computing Hemolytic Potency of Peptides. Scientific reports, 6. ISSN 2045-2322

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Official URL: http://www.nature.com/articles/srep22843


Numerous therapeutic peptides do not enter the clinical trials just because of their high hemolytic activity. Recently, we developed a database, Hemolytik, for maintaining experimentally validated hemolytic and non-hemolytic peptides. The present study describes a web server and mobile app developed for predicting, and screening of peptides having hemolytic potency. Firstly, we generated a dataset HemoPI-1 that contains 552 hemolytic peptides extracted from Hemolytik database and 552 random non-hemolytic peptides (from Swiss-Prot). The sequence analysis of these peptides revealed that certain residues (e.g., L, K, F, W) and motifs (e.g., "FKK", "LKL", "KKLL", "KWK", "VLK", "CYCR", "CRR", "RFC", "RRR", "LKKL") are more abundant in hemolytic peptides. Therefore, we developed models for discriminating hemolytic and non-hemolytic peptides using various machine learning techniques and achieved more than 95% accuracy. We also developed models for discriminating peptides having high and low hemolytic potential on different datasets called HemoPI-2 and HemoPI-3. In order to serve the scientific community, we developed a web server, mobile app and JAVA-based standalone software (http://crdd.osdd.net/raghava/hemopi/).

Item Type: Article
Additional Information: Open Access
Uncontrolled Keywords: Computational models;Machine learning;Software
Subjects: Q Science > QR Microbiology
Depositing User: Dr. K.P.S.Sengar
Date Deposited: 30 Sep 2016 04:54
Last Modified: 30 Sep 2016 04:54
URI: http://crdd.osdd.net/open/id/eprint/1860

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