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      https://www.ias.ac.in/article/fulltext/jcsc/131/02/0016

    • Keywords

       

      QSAR; CAMEL-s; molecular dynamics; artificial neural networks; activity prediction; drug design

    • Abstract

       

      There is an urgent need to identify novel antimicrobial drugs in light of the development of resistance by the bacteria for a broad spectrum of antibiotics. Antimicrobial peptides are proving to be an effective remedy to which bacteria have not been able to develop resistance easily. With the goal of progressing towards a rational design of AMPs, we developed a neural network based quantitative model relating their physicochemical properties to their activity. A set of synthetic cationic polypeptides (CAMEL-s) (Mee et al. in J. Peptide Res.49:89, 1997) which were studied systematically in experiments was used in the development of our model. Intuitive variables derived from short molecular dynamics simulations in octanol were used as descriptors, resulting in a good prediction of activity and underscoring the possibility of a rational design.

    • Author Affiliations

       

      MALAY RANJAN BISWAL SANDHYA RAI MEHER K PRAKASH1

      1. Theoretical Science Unit, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur, Bengaluru, India
    • Dates

       
    • Supplementary Material

       
  • Journal of Chemical Sciences | News

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