Artifical intelligence: a virtual chemist for natural product drug discovery

Abstract

Nature is full of a bundle of medicinal substances and its product perceived as a prerogative structure to collaborate with protein drug targets. The natural product’s (NPs) structure heterogeneity and eccentric characteristics inspired scientists to work on natural product-inspired medicine. To gear NP drug-finding artificial intelligence (AI) to confront and excavate unexplored opportunities. Natural product-inspired drug discoveries based on AI to act as an innovative tool for molecular design and lead discovery. Various models of machine learning produce quickly synthesizable mimetics of the natural products templates. The invention of novel natural products mimetics by computer-assisted technology provides a feasible strategy to get the natural product with defined bio-activities. AI’s hit rate makes its high importance by improving trail patterns such as dose selection, trail life span, efficacy parameters, and biomarkers. Along these lines, AI methods can be a successful tool in a targeted way to formulate advanced medicinal applications for natural products. ‘Prediction of future of natural product based drug discovery is not magic, actually its artificial intelligence’

Communicated by Ramaswamy H. Sarma

Keywords:

• Data mining
• bioactivity data
• molecular interaction attribute
• encoding natural product

Acknowledgement

The author is thankful to the Department of Chemistry, University of Petroleum and Energy Studies, Dehradun (UK) India for providing the support to carry out this work.

Data availability statement

All data presented during this study are included and references are given in the article. Requests for material should be made to the corresponding authors.

Disclosure statement

The author declares that this review content has no conflict of interest.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.