A Review on Procedure of QSAR Assessment in Organic Compounds as a Measure of Antioxidant Potentiality

Abstract

Chemical and biological properties of substances may be inferred from their more fundamental physical, chemical, and biological characteristics using QSAR models. An insilico model may be built using QSAR to anticipate the activity of novel molecules before they are synthesised, allowing the author to establish a quantifiable link between structure and behaviour. QSAR is a powerful tool. Although QSAR modelling is a computer area, medicinal chemists are the main users and ultimate assessors, especially when it comes to developing compounds with the necessary biological activity. Several studies were conducted in which medicinal chemists and cheminformaticians collaborated to discover new compounds with specific biological activity. This was done through the development of QSAR models and their use in virtual screening, followed by experimental verification. Despite the fact that QSAR methods have their own set of limitations, their use in molecular prediction and assessment has been effective due to a division of labour in which mathematical professionals ensured the greatest quality of models. The predictions also helped experimental chemists design and test compounds that were expected to be successful. This review is being developed and implemented to look into the development of the QSAR tool in the assessment of antioxidant potentiality for diverse organic chemicals found in our environment.