Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset.

ABSTRACT: Predicting the difference in thermodynamic stability between protein variants is crucial for protein design and understanding the genotype-phenotype relationships. So far, several computational tools have been created to address this task. Nevertheless, most of them have been trained or optimized on the same and 'all' available data, making a fair comparison unfeasible. Here, we introduce a novel dataset, collected and manually cleaned from the latest version of the ThermoMutDB database, consisting of 669 variants not included in the most widely used training datasets. The prediction performance and the ability to satisfy the antisymmetry property by considering both direct and reverse variants were evaluated across 21 different tools. The Pearson correlations of the tested tools were in t

SUBMITTER: Pancotti C 

PROVIDER: S-EPMC8921618 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature