Molecular Diversity, volume 25, issue 3, pages 1439-1460
Evolving scenario of big data and Artificial Intelligence (AI) in drug discovery
Manish Kumar Tripathi
1
,
Abhigyan Nath
2
,
Tej P. Singh
1
,
A S Ethayathulla
1
,
Punit Kaur
1
2
Department of Biochemistry, Pt. Jawahar Lal Nehru Memorial Medical College, Raipur, India
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Publication type: Journal Article
Publication date: 2021-06-23
Journal:
Molecular Diversity
scimago Q2
wos Q2
SJR: 0.585
CiteScore: 7.3
Impact factor: 3.9
ISSN: 13811991, 1573501X
Catalysis
Organic Chemistry
Drug Discovery
Inorganic Chemistry
Physical and Theoretical Chemistry
Molecular Biology
General Medicine
Information Systems
Abstract
The accumulation of massive data in the plethora of Cheminformatics databases has made the role of big data and artificial intelligence (AI) indispensable in drug design. This has necessitated the development of newer algorithms and architectures to mine these databases and fulfil the specific needs of various drug discovery processes such as virtual drug screening, de novo molecule design and discovery in this big data era. The development of deep learning neural networks and their variants with the corresponding increase in chemical data has resulted in a paradigm shift in information mining pertaining to the chemical space. The present review summarizes the role of big data and AI techniques currently being implemented to satisfy the ever-increasing research demands in drug discovery pipelines.
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