Effect of altering local protein fluctuations using artificial intelligence | Zendy

Katsuhiko Nishiyama | Zendy

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Effect of altering local protein fluctuations using artificial intelligence

Author(s) -

Katsuhiko Nishiyama

Publication year - 2017

Publication title -

aip advances

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.421

H-Index - 58

ISSN - 2158-3226

DOI - 10.1063/1.4978221

Subject(s) - peptide , cathepsin d , biophysics , chemistry , decision tree , biological system , biochemistry , computer science , enzyme , artificial intelligence , biology

The fluctuations in Arg111, a significantly fluctuating residue in cathepsin K, were locally regulated by modifying Arg111 to Gly111. The binding properties of 15 dipeptides in the modified protein were analyzed by molecular simulations, and modeled as decision trees using artificial intelligence. The decision tree of the modified protein significantly differed from that of unmodified cathepsin K, and the Arg-to-Gly modification exerted a remarkable effect on the peptide binding properties. By locally regulating the fluctuations of a protein, we may greatly alter the original functions of the protein, enabling novel applications in several fields

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