In Silico Approach for Prediction of Antifungal Peptides

This paper describes in silico models developed using a wide range of peptide features for predicting antifungal peptides (AFPs). Our analyses indicate that certain types of residue (e.g., C, G, H, K, R, Y) are more abundant in AFPs. The positional residue preference analysis reveals the prominence...

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Bibliographic Details
Published in:Front Microbiol
Main Authors: Agrawal, Piyush, Bhalla, Sherry, Chaudhary, Kumardeep, Kumar, Rajesh, Sharma, Meenu, Raghava, Gajendra P. S.
Format: Artigo
Language:Inglês
Published: Frontiers Media S.A. 2018
Subjects:
Microbiology
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC5834480/
https://ncbi.nlm.nih.gov/pubmed/29535692
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fmicb.2018.00323
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