Mycobacterium tuberculosis is responsible for severe mortality and morbidity worldwide but, under-developed and developing countries are more prone to infection. In search of effective and wide-spectrum anti-tubercular agents, interdisciplinary approaches are being explored. Of the several approaches used, computer based quantitative structure activity relationship (QSAR) have gained momentum. Structure-based drug design and discovery implies a combined knowledge of accurate prediction of ligand poses with the good prediction and interpretation of statistically validated models derived from the 3D-QSAR approach. The validated models are generally used to screen a small combinatorial library of potential synthetic candidates to identify hits which further subjected to docking to filter out compounds as novel potential emerging drug molecules to address multidrug-resistant tuberculosis. Several newer models are integrated to QSAR methods which include different types of chemical and biological data, and simultaneous prediction of pharmacological activities including toxicities and/or other safety profiles to get new compounds with desired activity. In the process, several newer molecules have been identified which are now being assessed for their clinical efficacy. Present review deals with the advances made in the field highlighting overall future prospects of the development of anti-tuberculosis drugs.

Tuberculosis (Tb) is an airborne infectious disease caused by () has emerged as one of the potential targets for new antitubercular drug development. In this work, three-dimensional quantitative structure-activity relationships (3D-QSAR), molecular docking, and molecular dynamics (MD) simulation approaches were performed on a series of natural and synthetic phenol-based inhibitors. The developed 3D-QSAR model ( = 0.94, = 0.86, and pred_r = 0.74) indicated that the steric and electrostatic factors are important parameters to modulate the bioactivity of phenolic compounds. Based on this indication, we designed 72 new phenolic inhibitors, out of which two compounds (D25 and D50) effectively stabilized receptor and, thus, are potential candidates for new generation antitubercular drug discovery program.

Objective: To investigate the antioxidant activity of ethanolic extract of Terminalia bellerica fruit pulp (TBFP), seed (TBS) and bark (TBB), and identification of phytochemical constituents of said extracts. Methods:The antioxidant potential of T. bellerica (TB) parts was evaluated by free radical scavenging activity (FRSA), superoxide anion radical scavenging activity (SARSA), hydroxyl radical scavenging activity (HRSA) and compared with reference standard quercetin. Lipid peroxidation (LPO), ferric thiocyanate activity (FTC) and reducing power (RP) of the plant extracts were also examined. The phytochemical constituents of said extracts have been quantified by gas chromatography-mass spectrometer (GC-MS) method.Results: Ethanolic extract of TBFP exhibited high phenolic content (254.33) followed by TBS (227.33) and TBB (185) mg/g of GAE. TBFP showed lowest IC 50 for FRSA (62 µg/ml), SARSA (39 µg/ml) and HRSA (27 µg/ml) and highest RP (3.39 ascorbic acid equivalents/ml). TBB showed lowest IC 50 for LPO (48 µg/ml) whereas TBS showed lowest IC50 Conclusion: On the basis of correlation of antioxidant studies with total phenolic content (TPC) and GC-MS analysis of different part of TB, it may be concluded that high concentration of total phenolics and other bioactive phytochemicals of TB extracts make it a potential source of nutraceutical antioxidants.for FTC (109 µg/ml). Predominant phyto-compounds present in TB extracts were quinic acid, gallic acid, ethyl galate, 9, 12 octadecadienoic acid and glucopyranose in varying concentrations as analyzed by GC-MS.

A quantitative structure activity relationship study was performed on different groups of anti-tuberculosis drug compound for establishing quantitative relationship between biological activity and their physicochemical /structural properties. In recent years, a large number of herbal drugs are promoted in treatment of tuberculosis especially due to the emergence of MDR (multi drug resistance) and XDR (extensive drug resistance) tuberculosis. Multidrug-resistant TB (MDR-TB) is resistant to front-line drugs (isoniazid and rifampicin, the most powerful anti-TB drugs) and extensively drug-resistant TB (XDR-TB) is resistant to front-line and second-line drugs. The possibility of drug resistance TB increases when patient does not take prescribed drugs for defined time period. Natural products (secondary metabolites) isolated from the variety of sources including terrestrial and marine plants and animals, and microorganisms, have been recognized as having antituberculosis action and have recently been tested preclinically for their growth inhibitory activity towards Mycobacterium tuberculosis or related organisms. A quantitative structure activity relationship (QSAR) studies were performed to explore the antituberculosis compound from the derivatives of natural products . Theoretical results are in accord with the in vitro experimental data with reported growth inhibitory activity towards Mycobacterium tuberculosis or related organisms. Antitubercular activity was predicted through QSAR model, developed by forward feed multiple linear regression method with leave-one-out approach. Relationship correlating measure of QSAR model was 74% (R2 = 0.74) and predictive accuracy was 72% (RCV2 = 0.72). QSAR studies indicate that dipole energy and heat of formation correlate well with anti-tubercular activity. These results could offer useful references for understanding mechanisms and directing the molecular design of new lead compounds with improved anti-tubercular activity. The generated QSAR model revealed the importance of structural, thermodynamic and electro topological parameters. The quantitative structure activity relationship provides important structural insight in designing of potent antitubercular agent.

The availability of completely sequenced genomes allow the use of computational techniques to investigate cis-acting sequences controlling transcription regulation associated with groups of functionally related genes. Theoretical analysis was performed to assign functions to regulatory systems. The identification of such sites is relevant for locating a promoter at the 5′ boundary of a gene. They also allow the prediction of specific gene-expression pattern and response to disturbances in a known signaling pathway. Here, we describe the identification of composite transcription factor (TF) binding sites over promoter regions in16s-rRNA gene for mycobacterium species strains ICC47, ICC67, ICC43 and CMVL700. It is established that the ribosomal gene comprises of sequences that are conserved during evolution and interspersed with divergent regions. Computational identification of known TF-binding sites was performed using TFSITESCAN tool and ooTFD database. The ICC67, ICC47, ICC43 and CMYL700 strains showed 12, 13, 9 and 15 known TF binding sites, respectively. Comparison between strains suggests 9 known TF predicted binding sites to be conserved among them. These data provide basis for the understanding of promoter regulation in 16s-rRNA.