Machine learning uncovers potential new TB drugs

Good news! This is only the very early beginning of using the power of machine learning to advance medical treatments!

"... the MIT team identified several promising compounds that target a protein required by the bacteria that cause tuberculosis. ... Using this approach, the researchers were able to identify molecules with very strong predicted binding affinities for the protein kinases they put into the model. These included three human kinases, as well as one kinase found in Mycobacterium tuberculosis. That kinase, PknB, is critical for the bacteria to survive, but is not targeted by any frontline TB antibiotics. ... The researchers then took some of their most promising PknB inhibitors and tested them against Mycobacterium tuberculosis grown in bacterial culture media, and found that they inhibited bacterial growth. The inhibitors also worked in human immune cells infected with the bacterium."

Machine learning uncovers potential new TB drugs | MIT News | Massachusetts Institute of Technology Computational method for screening drug compounds can help predict which ones will work best against tuberculosis or other diseases.