Overview
Computer-aided drug design (CADD) is the use of computational methods and modelling to discover and optimise new medicines. Rather than relying solely on trial-and-error laboratory screening, CADD applies algorithms, molecular modelling, and simulation to predict how candidate molecules will interact with biological targets such as proteins, helping researchers identify promising compounds and refine their structures before synthesis and testing. It includes structure-based approaches, which use the three-dimensional structure of a target to guide molecular docking and design, and ligand-based approaches, which infer the features required for activity from known active molecules. By prioritising the most promising candidates and predicting properties such as binding affinity, selectivity, and pharmacological behaviour, CADD aims to make drug discovery faster, cheaper, and more efficient. Within pharmaceutical science and technology, it has become an integral part of modern drug development, complementing experimental methods and drawing on advances in computing and bioinformatics. Research relevant to this topic includes reviews of progress in in silico, in vitro, and in vivo drug design research and of drug design through the application of computers, which survey the methods and impact of computational approaches in pharmaceutical development. This page gathers peer-reviewed, open-access research relevant to computer-aided drug design.
Research published in this journal
3 peer-reviewed articles, ranked by relevance. Each links to its DOI.
How this research is being cited
The 3 articles above have been cited 7 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.
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2022 · JURNAL BIOLOGI TROPIS
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2022 · SSRN Electronic Journal
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2021 · Springer eBooks
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2020 · Human Immunology
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2020 · Human Immunology
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2018 · Journal of Biotechnology and Biomedical Science
A sample of recent works citing this journal's research on Computer-Aided Drug Design, linking to each citing work.