Predicting rifampicin resistance mutations in bacterial RNA polymerase subunit beta based on majority consensus.

ABSTRACT:

Background

Mutations in an enzyme target are one of the most common mechanisms whereby antibiotic resistance arises. Identification of the resistance mutations in bacteria is essential for understanding the structural basis of antibiotic resistance and design of new drugs. However, the traditionally used experimental approaches to identify resistance mutations were usually labor-intensive and costly.

Results

We present a machine learning (ML)-based classifier for predicting rifampicin (Rif) resistance mutations in bacterial RNA Polymerase subunit β (RpoB). A total of 186 mutations were gathered from the literature for developing the classifier, using 80% of the data as the training set and the rest as the test set. The features of the mutated RpoB and their binding energies

SUBMITTER: Ning Q 

PROVIDER: S-EPMC8063314 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature