ToxinPred2: an improved method for predicting toxicity of proteins

• Published in: Briefings in bioinformatics Vol. 23; no. 5
• Main Authors: Sharma, Neelam, Naorem, Leimarembi Devi, Jain, Shipra, Raghava, Gajendra P S
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 20.09.2022; Oxford Publishing Limited (England)
• Subjects: Chemical compounds; Correlation coefficient; Correlation coefficients; Datasets; Learning algorithms; Machine learning; Peptides; Pharmacology; Prediction models; Proteins; Sensitivity; Similarity; Toxic diseases; Toxicity; toxicity; motifs; proteins; toxins; prediction; machine learning; BLAST
• ISSN: 1467-5463; 1477-4054; 1477-4054
• DOI: 10.1093/bib/bbac174

Abstract Proteins/peptides have shown to be promising therapeutic agents for a variety of diseases. However, toxicity is one of the obstacles in protein/peptide-based therapy. The current study describes a web-based tool, ToxinPred2, developed for predicting the toxicity of proteins. This is an upda...