Meta-analysis and review of in silico methods in drug discovery - part 1: technological evolution and trends from big data to chemical space

被引：0
作者：
Uzundurukan, Arife [1 ,2 ]
Nelson, Mark [3 ]
Teske, Christopher [4 ]
Islam, Mohamed Shahidul [5 ]
Mohamed, Elzagheid [6 ]
Christy, John Victor [7 ]
Martin, Holli-Joi [8 ]
Muratov, Eugene [9 ]
Glover, Samantha [10 ]
Fuoco, Domenico [2 ]
机构：
[1] Univ Sherbrooke, Ctr Rech Acoust Signal Humain, 2500 Bd Univ, Sherbrooke, PQ J1K 2R1, Canada
[2] Ecole Polytech Montreal, Dept Chem Engn, 2500 Chem Polytech, Montreal, PQ H3T 1J4, Canada
[3] Piramal Pharm Solut Inc, Altoris Inc, 18655 Krause St,Riverview, San Diego, CA 48193 USA
[4] Trinity Hlth, Oncol Res Fac, Ann Arbor, MI USA
[5] BIOVANTEK Global, Qual & Compliance Dept, 10149 Chemin Cote Deliesse, Montreal, PQ, Canada
[6] Royal Commiss Jubail & Yanbu, Jubail Ind City, Saudi Arabia
[7] Novacab, R&D Dept, Ottawa, ON, Canada
[8] Univ North Carolina, UNC Eshelman Sch Pharm, Div Chem Biol & Med Chem, Lab Mol Modeling, Chapel Hill, NC 27599 USA
[9] Univ North Carolina, UNC Eshelman Sch Pharm, Chapel Hill, NC USA
[10] Quantum Business Solut, Beverly Hills, Los Angeles, CA USA
来源：
PHARMACOGENOMICS JOURNAL | 2025年 / 25卷 / 03期
关键词：
CAMBRIDGE STRUCTURAL DATABASE; HUMAN METABOLOME DATABASE; SELECTION; QSAR; CLASSIFICATION; PHARMACOLOGY; INFORMATION; CHEMISTRY; BIOLOGY; SYSTEM;
D O I：
10.1038/s41397-025-00368-z
中图分类号：
Q3 [遗传学];
学科分类号：
071007 ; 090102 ;
摘要：
This review offers an overview of advanced in silico methods crucial for drug discovery, emphasizing their integration with data science, and investigates the effectiveness of data science, machine learning, and artificial intelligence via a thorough meta-analysis of existing technologies. This meta-analysis aims to rank these technologies based on their applications and accessibility of knowledge. Initially, a search strategy yielded 900 papers, which were then refined into two subsets: the top 300 most-cited papers since 2000 and papers selected for systematic review based on high impact. From these, 97 articles were identified for discussion, categorized by their influence on society. The focus remains on the qualitative impact of these disciplines rather than solely on metrics like new drug approvals. Ultimately, the review underscores the role of big data in enhancing our comprehension of drug candidate trajectories from development to commercialization, utilizing information stored in publicly available databases to chemical space.Graphical extrapolation of some keywords (Drug Discovery; Big Data; Database; Metadata) discussed in this article and their evolution (in terms of absolute items that are available) by time.
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页数：13
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