SAAMBE-SEQ: a sequence-based method for predicting mutation effect on protein-protein binding affinity.

ABSTRACT:

Motivation

Vast majority of human genetic disorders are associated with mutations that affect protein-protein interactions by altering wild-type binding affinity. Therefore, it is extremely important to assess the effect of mutations on protein-protein binding free energy to assist the development of therapeutic solutions. Currently, the most popular approaches use structural information to deliver the predictions, which precludes them to be applicable on genome-scale investigations. Indeed, with the progress of genomic sequencing, researchers are frequently dealing with assessing effect of mutations for which there is no structure available.

Results

Here, we report a Gradient Boosting Decision Tree machine learning algorithm, the SAAMBE-SEQ, which is completely sequence-bas

SUBMITTER: Li G 

PROVIDER: S-EPMC8128451 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature