Advances in Rational Drug Design: From Target Identification to Drug Lead Compounds
A special issue of Chemistry (ISSN 2624-8549). This special issue belongs to the section "Medicinal Chemistry".
Deadline for manuscript submissions: 20 January 2026 | Viewed by 1157
Special Issue Editors
Interests: drug discovery; molecular modeling; nutraceutical modeling; bioinformatics; medicinal chemistry
Special Issues, Collections and Topics in MDPI journals
Interests: drug discovery; medicinal chemistry; molecular modeling; polypharmacology; artificial intelligence; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The landscape of drug discovery is rapidly evolving through the integration of innovative computational and experimental approaches. Rational drug design, encompassing both structure-based and ligand-based strategies, has accelerated the identification of novel drug leads by leveraging insights into molecular targets, bioinformatics, and cheminformatics. Advances in artificial intelligence, machine learning, molecular dynamics, and virtual screening are reshaping how researchers predict drug–target interactions, optimize lead compounds, and evaluate pharmacokinetic properties. This Special Issue invites original research articles, reviews, and perspectives on recent developments in target identification, hit-to-lead optimization, computer-aided drug design (CADD), deep learning applications in medicinal chemistry, and the modeling of small molecules and biologics. Contributions exploring multidisciplinary approaches, including the use of big data, multi-omics integration, and innovative experimental validation techniques, are particularly encouraged. We aim to gather a diverse collection of studies to reflect the dynamic cross-disciplinary nature of modern drug discovery and foster knowledge exchange across computational and experimental domains.
Topics of interest include but are not limited to:
- computer-aided drug discovery (CADD);
- rational drug design;
- target identification;
- lead optimization;
- molecular modeling;
- virtual screening;
- deep learning in drug discovery;
- ADMET prediction;
- bioinformatics;
- artificial intelligence in medicinal chemistry.
We invite you to submit your work to this Special Issue. Full papers, communications, and reviews are all welcome.
Dr. Carmen Di Giovanni
Prof. Dr. Antonio Lavecchia
Guest Editors
Manuscript Submission Information
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Keywords
- computer aided-drug discovery
- drug development
- lead compounds
- drug candidates
- molecular modeling
- structure-based drug design
- ligand-based drug design
- artificial intelligence (AI)
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