Tuberculosis kills about 3 million people each year and it is estimated that around a third of the world’s population is infected with the pathogen Mycobacterium tuberculosis. Unfortunately, this bacteria has evolved resistance to many antibiotics and so new drug targets are eagerly sought that might provide a way to prevent the spread of infection. Writing in the International Journal of Computational Biology and Drug Design, researchers in India have turned to the microbe’s “riboswitch” as just such a target.
Somdutt Mujwar and Kamal Raj Pardasani Department of Bioinformatics at Maulana Azad National Institute of Technology, in Bhopal, point out that antibiotics used against TB, including isoniazid, rifampicin, fluoroquinolones, pyrazinamide, ethambutol and streptomycin, all work by targeting and blocking the activity of proteins such as enzymes and receptors in the bacteria. However, the bacteria can quickly evolve resistance to even the most potent drugs that target these so-called non-homologous proteins.
The team suggests that rather than targeting individual proteins in the bacteria a more robust attack might involve blocking the action of the riboswitch, a system that controls gene expression and so protein manufacture. Blocking the binding site in this system would stop production of the very proteins that are usually targeted individually by antibiotics. The team has now used a computer program that simulates molecular docking to see which of more than 5000 chemicals, or ligands, can fit into the riboswitch binding site. Those that bind the most tightly would represent those compounds best able to disable the riboswitch by preventing its natural ligand from entering the binding site. The most potent could be plucked from the database and made in the laboratory for further testing against tuberculosis.
The in silico framework developed in the present study can also be used for generating information and knowledge to minimize and supplement wet lab experiments for the design of drug molecules for TB and other infectious diseases, the team reports.
Mujwar, S. and Pardasani, K.R. (2015) ‘Prediction of riboswitch as a potential drug target and design of its optimal inhibitors for Mycobacterium tuberculosis’, Int. J. Computational Biology and Drug Design, Vol. 8, No. 4, pp.326–347.