Machine learning: Python tools for studying biomolecules and drug design

Machine learning: Python tools for studying biomolecules and drug design Review

Journal

Molecular Diversity
ISSN: 1573-501X , E-ISSN: 1381-1991

Output data

Year: 2025, Volume: 29, Pages: 3789–3824 Pages count : DOI: 10.1007/s11030-025-11199-2

Authors

Ryzhkov Fedor V ¹ , Ryzhkova Yuliya E ¹ , Elinson Michail N ¹

Affiliations

1	N. D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences, 47 Leninsky Prospekt, 119991, Moscow, Russia. ryzhkovfv@ioc.ac.ru.

The increasing adoption of computational methods and artificial intelligence in scientific research has led to a growing interest in versatile tools like Python. In the fields of medical chemistry, biochemistry, and bioinformatics, Python has emerged as a key language for tackling complex challenges. It is used to solve various tasks, such as drug discovery, high-throughput and virtual screening, protein and genome analysis, and predicting drug efficacy. This review presents a list of tools for these tasks, including scripts, libraries, and ready-made programs, and serves as a starting point for scientists wishing to apply automation or optimization to routine tasks in medical chemistry and bioinformatics.

Ryzhkov F.V. , Ryzhkova Y.E. , Elinson M.N.
Machine learning: Python tools for studying biomolecules and drug design
Molecular Diversity. 2025. V.29. P.3789–3824. DOI: 10.1007/s11030-025-11199-2 WOS Scopus OpenAlex

≡ Web of science:	WOS:001478387300001
≡ Scopus:	2-s2.0-105003847514
≡ OpenAlex:	W4409919598