New preprint: predicting rifampicin resistance

In this preprint we train a series of machine learning models on protein mutations found in rpoB — this is the gene in the M. tuberculosis RNA polymerase complex where mutations can introduce resistance to rifampicin, an important first-line drug in the treatment of tuberculosis. Unlike pyrazinamide, which we have previously published and binds to pncA, the RNA polymerase is an essential gene and therefore resistance-conferring mutations tend to be subtle and, in this case, mostly close to the rifampicin binding site.

We find that all the models achieve similar levels of prediction performance and that the most predictive feature is, perhaps unsurprisingly, the distance from the amino acid being mutated to the centre of mass of rifampicin. All the data and code required to create our Test+Train datasets, train the models and produce nearly all the figures in the preprint is available on GitHub.