Protein thermostability prediction within homologous families using temperature-dependent statistical potentials.

ABSTRACT: The ability to rationally modify targeted physical and biological features of a protein of interest holds promise in numerous academic and industrial applications and paves the way towards de novo protein design. In particular, bioprocesses that utilize the remarkable properties of enzymes would often benefit from mutants that remain active at temperatures that are either higher or lower than the physiological temperature, while maintaining the biological activity. Many in silico methods have been developed in recent years for predicting the thermodynamic stability of mutant proteins, but very few have focused on thermostability. To bridge this gap, we developed an algorithm for predicting the best descriptor of thermostability, namely the melting temperature Tm, from the protein's sequenc

SUBMITTER: Pucci F 

PROVIDER: S-EPMC3960129 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature