Harnessing Artificial Intelligence for Natural Product Research: A New Paradigm in Pharmaceutical Sciences
Year: 2024
Type: article
Abstract: The use of artificial intelligence (AI) into natural product research marks a paradigm breakthrough in the area of pharmaceutical sciences, providing new prospects for expediting medication discovery and development. Traditional techniques of natural product discovery have historically faced obstacles such as extensive screens, poor hit rates, and restricted scalability. However, AI technologies such as machine learning, deep learning, and data mining provide a unique way to quickly evaluate large datasets and predict compound bioactivity with high accuracy. This research investigates the use of AI-driven algorithms to speed up lead chemical identification, optimize therapeutic prospects, and understand complex structure-activity correlations. Furthermore, AI systems permit the integration of heterogeneous omics data, allowing for a thorough knowledge of the molecular pathways underlying the therapeutic qualities of natural compounds. Researchers may use artificial intelligence to produce tailored therapies for a wide range of ailments, including cancer, infectious diseases, and neurological problems. Furthermore, the combination of AI with highthroughput screening approaches enables the quick discovery of potential natural product-derived molecules with enhanced pharmacokinetic characteristics and lower toxicity. Accepting the confluence of AI and natural product research not only simplifies the medication development process, but it also holds great promise for tackling global healthcare concerns and improving patient outcomes.
Author: Juganta Kumar Kalita, Hrithik Rikhav Mohan, Gargi Bora, Shiny Ahmed, Dhiraj Baishya, Moksood Ahmed Laskar, Santa Mandal, Priyam Jyoti Das
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6892451550