Enabling the Discovery and Virtual Screening of Potent and Safe Antimicrobial Peptides. Simultaneous Prediction of Antibacterial Activity and Cytotoxicity

• Type: Article in International Scientific Journal
• Date: 2016

Authors

Kleandrova, VV (Author) Other; Ruso, JM (Author) Other; Speck Planche, A (Author) Other; Natalia N D S Cordeiro (Author) FCUP

Journal

Title: ACS Combinatorial Science

Vol. 18

Pages: 490-498

ISSN: 2156-8952

Publisher: American Chemical Society

Indexing

ISI Web of Knowledge - 64 Citations

Scopus - 63 Citations

Other information

Authenticus ID: P-00K-R4D

DOI: 10.1021/acscombsci.6b00063

Abstract (EN): Antimicrobial peptides (AMPs) represent promising alternatives to fight against bacterial pathogens. However, cellular toxicity remains one of the main concerns in the early development of peptide-based drugs. This work introduces the first multitasking (mtk) computational model focused on performing simultaneous predictions of antibacterial activities, and cytotoxicities of peptides. The model was created from a data set containing 3592 cases, and it displayed accuracy higher than 96% for classifying/predicting peptides in both training and prediction (test) sets. The technique known as alanine scanning was computationally applied to illustrate the calculation of the quantitative contributions of the amino acids (in their respective positions of the sequence) to the biological effects of a defined peptide. A small library formed by 10 peptides was generated, where peptides were designed by considering the interpretations of the different descriptors in the mtk-computational model. All the peptides were predicted to exhibit high antibacterial activities against multiple bacterial strains, and low cytotoxicity against various cell types. The present mtk-computational model can be considered a very useful tool to support high throughput research for the discovery of potent and safe AMPs.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 9