DFT Based QSAR/QSPR Models in the Development of Novel Anti-tuberculosis Drugs Targeting Mycobacterium tuberculosis

Nov 20, 2013Current pharmaceutical design

Using computer models to design new drugs against tuberculosis bacteria

AI simplified

Abstract

More than 9 million people are affected by tuberculosis caused by Mycobacterium tuberculosis globally.

Current treatments for tuberculosis face challenges due to multidrug-resistant (MDR-TB) and extensively drug-resistant (XDR-TB) strains.
A significant effort is underway to explore the chemical-biological interactions of new anti-tubercular drugs.
The review focuses on studies that utilize 2D and 3D quantitative structure-activity relationship (QSAR) models.
The selected studies incorporate different density functional theory (DFT) based descriptors in their analyses.

AI simplified

Tuberculosis caused by Mycobacterium tuberculosis is an infectious bacterial disease which is a leading cause of mortality affecting more than 9 million people worldwide. The current standard regimens that are available for the treatment of TB are severely hampered due to the occurrence of multidrug-resistant (MDR-TB) and extensively drug-resistant (XDR-TB) strains of Mycobacterium tuberculosis. In the past few years, a huge and constantly expanding effort has been developed to understand the chemical-biological interaction of many new anti-tubercular drugs and their targets in mathematical terms. Here, we have elected to review only those studies concerning 2D and 3D QSAR models that contain different DFT based descriptors as their parameters.

Full Text

Full text is available at the source.

View full text ↗

Abstract

Full Text

Related papers

what lands in your inbox each week: