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

被引:172
作者
Chaudhary, Kumardeep [1 ]
Kumar, Ritesh [2 ]
Singh, Sandeep [1 ]
Tuknait, Abhishek [1 ]
Gautam, Ankur [1 ]
Mathur, Deepika [1 ]
Anand, Priya [1 ]
Varshney, Grish C. [3 ]
Raghava, Gajendra P. S. [1 ]
机构
[1] CSIR, Inst Microbial Technol, Bioinformat Ctr, Sect 39A, Chandigarh, India
[2] CSIR, Cent Sci Instruments Org, Sect 30C, Chandigarh, India
[3] CSIR, Inst Microbial Technol, Div Cell Biol & Immunol, Chandigarh, India
关键词
CATIONIC ANTIMICROBIAL PEPTIDES; DATABASE; PREDICTION; DESIGN;
D O I
10.1038/srep22843
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
070301 [无机化学]; 070403 [天体物理学]; 070507 [自然资源与国土空间规划学]; 090105 [作物生产系统与生态工程];
摘要
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/).
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页数:13
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