Browsing by Author "Singh, Parvinder Pal"
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- Functionalized Nitroimidazole Scaffold Construction and Their Pharmaceutical Applications: A 1950–2021 Comprehensive OverviewPublication . Gupta, Ria; Sharma, Sumit; Singh, Rohit; Vishwakarma, Ram A.; Mignani, Serge; Singh, Parvinder PalNitroimidazole represents one of the most essential and unique scaffolds in drug discovery since its discovery in the 1950s. It was K. Maeda in Japan who reported in 1953 the first nitroimidazole as a natural product from Nocardia mesenterica with antibacterial activity, which was later identified as Azomycin 1 (2-nitroimidazole) and remained in focus until now. This natural antibiotic was the starting point for synthesizing numerous analogs and regio-isomers, leading to several life-saving drugs and clinical candidates against a number of diseases, including infections (bacterial, viral, parasitic) and cancers, as well as imaging agents in medicine/diagnosis. In the present decade, the nitroimidazole scaffold has again been given two life-saving drugs (Delamanid and Pretomanid) used to treat MDR (multi-drug resistant) tuberculosis. Keeping in view the highly successful track-record of the nitroimidazole scaffold in providing breakthrough therapeutic drugs, this comprehensive review focuses explicitly on presenting the activity profile and synthetic chemistry of functionalized nitroimidazole (2-, 4- and 5-nitroimidazoles as well as the fused nitroimidazoles) based drugs and leads published from 1950 to 2021. The present review also presents the miscellaneous examples in each class. In addition, the mutagenic profile of nitroimidazole-based drugs and leads and derivatives is also discussed.
- Present drug-likeness filters in medicinal chemistry during the hit and lead optimization process: how far can they be simplified?Publication . Mignani, Serge; Rodrigues, João; Tomás, Helena; Jalal, Rachid; Singh, Parvinder Pal; Majoral, Jean-Pierre; Vishwakarma, Ram A.During the past decade, decreasing the attrition rate of drug development candidates reaching the market has become one of the major challenges in pharmaceutical research and drug development (R&D). To facilitate the decision-making process, and to increase the probability of rapidly finding and developing high-quality compounds, a variety of multiparametric guidelines, also known as rules and ligand efficiency (LE) metrics, have been developed. However, what are the 'best' descriptors and how far can we simplify these drug-likeness prediction tools in terms of the numerous, complex properties that they relate to?