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    • 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



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

  • Journal of Chemical Sciences | News

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