Synopsis of Epidemic Modeling Studies

Background: Azole antifungals are among the first-line drugs clinically used for the treatment of systemic candidiasis, a deadly type of fungal infection that threatens mostly immunecompromised and hospitalized patients. Some azole derivatives were also reported to have antiproliferative effects on cancer cells. Objective: In this study, 1-(4-trifluoromethylphenyl)-2-(1H-imidazol-1-yl)ethanone (3), its oxime (4), and a series of its novel oxime ester derivatives (5a-v) were synthesized and tested for their in vitro antimicrobial activities against certain ATCC standard strains of Candida sp. fungi and bacteria. The compounds were also tested for their cytotoxic effects against mouse fibroblast and human neuroblastoma cell lines. Molecular modeling studies were performed to provide insights into their possible mechanisms for antifungal and antibacterial actions. Methods: The compounds were synthesized by the reaction of various oximes with acyl chlorides. Antimicrobial activity of the compounds was determined according to the broth microdilution method. For the determination of cytotoxic effect, we used MTS assay. Molecular docking and QM/MM studies were performed to predict the binding mechanisms of the active compounds in the catalytic site of C. albicans CYP51 (CACYP51) and S. aureus flavohemoglobin (SAFH), the latter of which was created via homology modeling. Results: 5d, 5l, and 5t showed moderate antifungal activity against C. albicans, while 3, 5c, and 5r showed significant antibacterial activity against Staphylococcus aureus and Pseudomonas aeruginosa. Most of the compounds showed approximately 40-50% inhibition against the human neuroblastoma cells at 100 µM. In this line, 3 was the most potent with an IC50 value of 82.18 μM followed by 5a, 5o, and 5t. 3 and 5a were highly selective to the neuroblastoma cells. Molecular modelling results supported the hypothesis that our compounds were inhibitors of CAYP51 and SAFH. Conclusion: This study supports that oxime ester derivatives may be used for the development of new antimicrobial and cytotoxic agents.

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Computational Approaches as Rational Decision Support Systems for Discovering Next-Generation Antitubercular Agents: Mini-Review

Current Computer - Aided Drug Design ◽

10.2174/1573409915666190130153214 ◽

2019 ◽

Vol 15 (5) ◽

pp. 369-383

Author(s):

Rahul Balasaheb Aher ◽

Kunal Roy

Keyword(s):

Recent Progress ◽

Neglected Tropical Diseases ◽

Acyl Carrier Protein ◽

Thioredoxin Reductase ◽

Protein Tyrosine Phosphatases ◽

Antitubercular Agents ◽

Computer Aided Drug Design ◽

Modeling Studies ◽

Catalase Peroxidase ◽

Molecular Modeling Studies

Tuberculosis, malaria, dengue, chikungunya, leishmaniasis etc. are a large group of neglected tropical diseases that prevail in tropical and subtropical countries, affecting one billion people every year. Minimal funding and grants for research on these scientific problems challenge many researchers to find a different way to reduce the extensive time and cost involved in the drug discovery cycle of these problems. Computer-aided drug design techniques have already been proved successful in the discovery of new molecules rationally by reducing the time and cost involved in the development of drugs. In the current minireview, we are highlighting on the molecular modeling studies published during 2010-2018 for target specific antitubercular agents. This review includes the studies of Structure-Based (SB) and Ligand-Based (LB) modeling and those involving Machine Learning (ML) techniques against different antitubercular targets such as dihydrofolate reductase (DHFR), enoyl Acyl Carrier Protein (ACP) reductase (InhA), catalase-peroxidase (KatG), enzyme antigen 85C, protein tyrosine phosphatases (PtpA and PtpB), dUTPase, thioredoxin reductase (MtTrxR), etc. The information presented in this review will help the researchers to get acquainted with the recent progress in the modeling studies of antitubercular agents.

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