Artifical intelligence : a virtual chemist for natural product drug discovery

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.

Medienart:

E-Artikel

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

Zur Gesamtaufnahme - volume:42

Enthalten in:

Journal of biomolecular structure & dynamics - 42(2024), 7 vom: 03. Apr., Seite 3826-3835

Sprache:

Englisch

Beteiligte Personen:

Arora, Shefali [VerfasserIn]
Chettri, Sukanya [VerfasserIn]
Percha, Versha [VerfasserIn]
Kumar, Deepak [VerfasserIn]
Latwal, Mamta [VerfasserIn]

Links:

Volltext

Themen:

Bioactivity data
Biological Products
Data mining
Encoding natural product
Journal Article
Molecular interaction attribute

Anmerkungen:

Date Completed 12.04.2024

Date Revised 12.04.2024

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1080/07391102.2023.2216295

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM357347315