This paper is published in Volume-7, Issue-4, 2021
Area
Computer Applications
Author
Mohit Singh Negi, Anosh Singh
Org/Univ
Uttaranchal Institute of Management, Dehradun, Uttarakhand, India
Pub. Date
22 July, 2021
Paper ID
V7I4-1472
Publisher
Keywords
Artificial Intelligence, Deep Learning, Drug Discovery, Machine Learning, QSAR

Citationsacebook

IEEE
Mohit Singh Negi, Anosh Singh. Application of AI in drug discovery, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Mohit Singh Negi, Anosh Singh (2021). Application of AI in drug discovery. International Journal of Advance Research, Ideas and Innovations in Technology, 7(4) www.IJARIIT.com.

MLA
Mohit Singh Negi, Anosh Singh. "Application of AI in drug discovery." International Journal of Advance Research, Ideas and Innovations in Technology 7.4 (2021). www.IJARIIT.com.

Abstract

Target-driven drug discovery is a process in which a known target is used to search for small molecules that interfere with it or influence its role in cells. These methods function well for easily druggable targets with a well-defined structure and well-understood interactions within the cell. However, due to the complexity of cellular interactions and a lack of understanding of intricate cellular pathways, these methods are severely limited. By detecting novel associations and inferring the functional significance of various components of a cellular pathway, AI will conquer these obstacles. It extracts useful knowledge from a broad dataset using complex algorithms and machine learning techniques. QSAR modeling based on structure, de-novo drug design, automated synthesis planning is just a few of the cutting-edge applications available. Screening of the compounds along with optimizing the lead compound, goal validation and selection, nonclinical research and studies, and clinical drug trials are all places where AI is used extensively.