Cited by 763Computational Drug Discovery MethodsCholinesterase and Neurodegenerative DiseasesSynthesis and Characterization of Heterocyclic Compounds

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Role of computer-aided drug design in modern drug discovery

Macalino, Stephani Joy Y., Gosu, Vijayakumar, Hong, Sunhye, Choi, Sun·2015·Archives of Pharmacal Research

DOI 10.1007/s12272-015-0640-5

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Abstract

Drug discovery utilizes chemical biology and computational drug design approaches for the efficient identification and optimization of lead compounds. Chemical biology is mostly involved in the elucidation of the biological function of a target and the mechanism of action of a chemical modulator. On the other hand, computer-aided drug design makes use of the structural knowledge of either the target (structure-based) or known ligands with bioactivity (ligand-based) to facilitate the determination of promising candidate drugs. Various virtual screening techniques are now being used by both pharmaceutical companies and academic research groups to reduce the cost and time required for the discovery of a potent drug. Despite the rapid advances in these methods, continuous improvements are critical for future drug discovery tools. Advantages presented by structure-based and ligand-based drug design suggest that their complementary use, as well as their integration with experimental routines, has a powerful impact on rational drug design. In this article, we give an overview of the current computational drug design and their application in integrated rational drug development to aid in the progress of drug discovery research.

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Authors: Macalino, S. J. Y., Gosu, V., Hong, S., & Choi, S.
Affiliations: Ewha Womans University (KR)
Corresponding author: Choi, Sun
ORCID: Macalino, Stephani Joy Y.
Gosu, Vijayakumar
Choi, Sun
Venue: Archives of Pharmacal Research
Publisher: Springer Science and Business Media LLC
Published: 2015-07-25
Volume: 38
Issue: 9
Pages: 1686-1701
ISSN: 0253-6269 (ISSN-L)
1976-3786
DOI: 10.1007/s12272-015-0640-5
OpenAlex: W1854810044
Cited by: 762
References: 156
Citations by year: 2026: 65 · 2025: 80 · 2024: 109 · 2023: 146 · 2022: 105 · 2021: 96 · 2020: 60 · 2019: 41 · 2018: 31 · 2017: 15 · 2016: 10 · 2015: 2
FWCI: 2.08
Type: journal article
Language: en
Open access: closed
Licence: www.springernature.com/gp/researchers/text-and-data-mining (tdm)
www.springernature.com/gp/researchers/text-and-data-mining (vor)
Locations: Archives of Pharmacal Research (publishedVersion)
PubMed (publishedVersion)
Funders: The Ministry of Science, ICT & Future Planning (MSIP) and National Research Foundation of Korea (2011-0028885)
Topics: Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
Health Sciences › Medicine › Pharmacology (medical) › Cholinesterase and Neurodegenerative Diseases
Physical Sciences › Chemistry › Organic Chemistry › Synthesis and Characterization of Heterocyclic Compounds
Keywords: computer-aided drug design, drug discovery, structure-based drug design, ligand-based drug design, virtual screening, chemical biology, lead optimization, rational drug design
MeSH terms: Animals, Pharmaceutical Preparations, Humans, Drug Design, Computer-Aided Design, Protein Structure, Secondary, Protein Structure, Tertiary, Quantitative Structure-Activity Relationship, Drug Discovery

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