QSAR based therapeutic management of M. tuberculosis

Mycobacterium tuberculosis is responsible forsevere mortality and morbidity worldwide but, under-developedand developing countries are more prone toinfection. In search of effective and wide-spectrum antitubercularagents, interdisciplinary approaches are beingexplored. Of the several approaches used, computer basedquantitative structure activity relationship (QSAR) havegained momentum. Structure-based drug design and discoveryimplies a combined knowledge of accurate predictionof ligand poses with the good prediction andinterpretation of statistically validated models derived fromthe 3D-QSAR approach. The validated models are generallyused to screen a small combinatorial library ofpotential synthetic candidates to identify hits which furthersubjected to docking to filter out compounds as novelpotential emerging drug molecules to address multidrugresistanttuberculosis. Several newer models are integratedto QSAR methods which include different types of chemicaland biological data, and simultaneous prediction ofpharmacological activities including toxicities and/or othersafety profiles to get new compounds with desired activity. In the process, several newer molecules have been identifiedwhich are now being assessed for their clinical efficacy. Present review deals with the advances made in thefield highlighting overall future prospects of the developmentof anti-tuberculosis drugs.