Predictive models for nucleoside bisubstrate analogs as inhibitors of siderophore biosynthesis in Mycobacterium tuberculosis: pharmacophore mapping and chemometric QSAR study

In Silico Strategies in Tuberculosis Drug Discovery

Tuberculosis (TB) remains a serious threat to global public health, responsible for an estimated 1.5 million mortalities in 2018. While there are available therapeutics for this infection, slow-acting drugs, poor patient compliance, drug toxicity, and drug resistance require the discovery of novel TB drugs. Discovering new and more potent antibiotics that target novel TB protein targets is an attractive strategy towards controlling the global TB epidemic. In silico strategies can be applied at multiple stages of the drug discovery paradigm to expedite the identification of novel anti-TB therapeutics. In this paper, we discuss the current TB treatment, emergence of drug resistance, and the effective application of computational tools to the different stages of TB drug discovery when combined with traditional biochemical methods. We will also highlight the strengths and points of improvement in in silico TB drug discovery research, as well as possible future perspectives in this field.

Kinetic Analyses of the Siderophore Biosynthesis Inhibitor Salicyl-AMS and Analogues as MbtA Inhibitors and Antimycobacterial Agents

There is a paramount need for expanding the drug armamentarium to counter the growing problem of drug-resistant tuberculosis. Salicyl-AMS, an inhibitor of salicylic acid adenylation enzymes, is a first-in-class antibacterial lead compound for the development of tuberculosis drugs targeting the biosynthesis of salicylic-acid-derived siderophores. In this study, we determined the K_i of salicyl-AMS for inhibition of the salicylic acid adenylation enzyme MbtA from Mycobacterium tuberculosis (MbtA_tb), designed and synthesized two new salicyl-AMS analogues to probe structure-activity relationships (SAR), and characterized these two analogues alongside salicyl-AMS and six previously reported analogues in biochemical and cell-based studies. The biochemical studies included determination of kinetic parameters ( K_i^app, k_on^app, k_off, and t_R) and analysis of the mechanism of inhibition. For these studies, we optimized production and purification of recombinant MbtA_tb, for which K_m and k_cat values were determined, and used the enzyme in conjunction with an MbtA_tb-optimized, continuous, spectrophotometric assay for MbtA activity and inhibition. The cell-based studies provided an assessment of the antimycobacterial activity and postantibiotic effect of the nine MbtA_tb inhibitors. The antimycobacterial properties were evaluated using a strain of nonpathogenic, fast-growing Mycobacterium smegmatis that was genetically engineered for MbtA_tb-dependent susceptibility to MbtA inhibitors. This convenient model system greatly facilitated the cell-based studies by bypassing the methodological complexities associated with the use of pathogenic, slow-growing M. tuberculosis. Collectively, these studies provide new information on the mechanism of inhibition of MbtA_tb by salicyl-AMS and eight analogues, afford new SAR insights for these inhibitors, and highlight several suitable candidates for future preclinical evaluation.

Computer-Aided Drug Discovery Approaches against the Tropical Infectious Diseases Malaria, Tuberculosis, Trypanosomiasis, and Leishmaniasis

Despite the tremendous improvement in overall global health heralded by the adoption of the Millennium Declaration in the year 2000, tropical infections remain a major health problem in the developing world. Recent estimates indicate that the major tropical infectious diseases, namely, malaria, tuberculosis, trypanosomiasis, and leishmaniasis, account for more than 2.2 million deaths and a loss of approximately 85 million disability-adjusted life years annually. The crucial role of chemotherapy in curtailing the deleterious health and economic impacts of these infections has invigorated the search for new drugs against tropical infectious diseases. The research efforts have involved increased application of computational technologies in mainstream drug discovery programs at the hit identification, hit-to-lead, and lead optimization stages. This review highlights various computer-aided drug discovery approaches that have been utilized in efforts to identify novel antimalarial, antitubercular, antitrypanosomal, and antileishmanial agents. The focus is largely on developments over the past 5 years (2010-2014).

Exploration of potential EGFR inhibitors: a combination of pharmacophore-based virtual screening, atom-based 3D-QSAR and molecular docking analysis

Epidermal growth factor receptor (EGFR) protein tyrosine kinases are over expressed in several human cancers and considered as a promising target for developing novel anticancer drugs. In this study, the ligand-based pharmacophore mapping and atom-based 3D-QSAR approach was carried out on a series of 40 novel pyrrolo[3, 2-d]pyrimidine derivatives acting as EGFR inhibitors. The best pharmacophore hypothesis AAADRR.295 was selected and an atom-based 3D-QSAR model was generated by applying partial least-squares algorithm. The developed model was validated and used as a 3D query in sequential virtual screening study to filter five chemical databases. The obtained compounds were further filtered according to Lipinski rule of five and fitness score. Subsequently, a multistep molecular docking study was employed on the retrieved hits and finally, 12 compounds were prioritized as potential leads against EGFR, which exhibited high docking scores, correlated binding mode to experimentally proven compounds and constructive drug-like properties. The results of this study provide detailed structural insights and emphasize the important binding features of these compounds, which may assists in the design and development of novel EGFR inhibitors.