Databases for Drug Discovery and Development

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Computational drug design and discovery have taken center stage attention during the time of COVID-19. The science community acknowledges the importance of ligand-based drug design (LBDD) and structure-based drug design (SBDD) to nullify the problem associated with a typical drug discovery process. In the modern era, a complement between experimental, theoretical, and computational approaches can make the drug discovery process rational, economical, and fast. Undoubtedly, computational power has increased manifold compared to the last few decades, making it possible to run many unthinkable calculations that cannot be imagined a few years ago. Along with the computational power, resources like open-access and commercial organic chemicals, phytochemicals, approved, experimental and investigational drugs, peptides, and metabolomic databases have increased enormously. Compared to designing a new drug, utilizing existing chemical and drug databases for virtual screening makes the process faster as the database chemicals are already synthesized (in most cases) and characterized. Even in a few instances, absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles are checked along with data for preclinical and clinical trials (primarily for investigational and/or in the process of approval drugs). A drug database is also a powerful resource for drug repurposing, where an old, approved drug for a specific disease can be used to treat another common/new/rare disease. The idea is increasingly becoming an attractive proposition as it comprises the use of already evaluated de-risked compounds which help lower the new drug development costs in a shorter time. Therefore, drug databases have an immense role to play as a repository of potential drugs for any common to a rare disease in the process of CADD and for the experimental scientists.

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Challenges and Advances in Computational Chemistry and Physics

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