Structure Based Thermostability Prediction Models for Protein Single Point Mutations with Machine Learning Tools.

ABSTRACT: Thermostability issue of protein point mutations is a common occurrence in protein engineering. An application which predicts the thermostability of mutants can be helpful for guiding decision making process in protein design via mutagenesis. An in silico point mutation scanning method is frequently used to find "hot spots" in proteins for focused mutagenesis. ProTherm (http://gibk26.bio.kyutech.ac.jp/jouhou/Protherm/protherm.html) is a public database that consists of thousands of protein mutants' experimentally measured thermostability. Two data sets based on two differently measured thermostability properties of protein single point mutations, namely the unfolding free energy change (ddG) and melting temperature change (dTm) were obtained from this database. Folding free energy change c

SUBMITTER: Jia L 

PROVIDER: S-EPMC4567301 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature