Advances in Computer-Aided Drug Design Strategies
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".
Deadline for manuscript submissions: 30 August 2025 | Viewed by 315
Special Issue Editor
Interests: structural bioinformatics; bioinformatics; next-generation sequence; drug design; deep learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Computer-aided drug design has become a cornerstone of current scientific research and is of phenomenal importance in pharmacy, revolutionising the way we approach the understanding of biological phenomena and drug discovery as well as development. Over the last two decades, significant advances in the design of more efficient algorithms (such as new scoring and exploration functions), coupled with computing power and integration with experimental techniques, have accelerated the identification of ligands of interest and promising therapeutic candidates. This Special Issue is devoted to exploring the cutting-edge methodologies and innovations that are shaping the future of computer-aided drug design.
From virtual screening to molecular dynamics simulations of increasingly large and complex systems, and from structure-based to ligand-based approaches, computer-aided tools are streamlining processes that were once costly, laborious, and time-consuming. Recent developments in artificial intelligence and machine learning offer a new level of predictive accuracy, enabling researchers to model complex biological systems, predict drug interactions, and optimise pharmacokinetic properties with remarkable precision. These strategies not only improve efficacy, but also reduce the financial costs and potential ethical issues associated with large-scale in vivo and in vitro studies.
This Special Issue aims to bring together original research, analyses, and case studies that demonstrate how cutting-edge computational techniques are being used to address the pressing challenges of drug discovery. Topics of interest include, but are not limited to, the following:
- Innovations in molecular docking and scoring functions.
- Simulations of large biological systems.
- Computational strategies for designing drugs targeting druggable, but also undruggable, proteins.
- Integration of artificial intelligence (machine learning, deep learning, etc.) into CADD pipelines.
- Advances in quantum mechanics/molecular mechanics hybrid methods.
- The role of big data and bioinformatics in drug design.
- Case studies highlighting success stories in CADD.
Sincerely,
Dr. Alexandre G. De Brevern
Guest Editor
Manuscript Submission Information
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Keywords
- computer-aided drug design
- artificial intelligence in drug discovery
- molecular docking
- molecular dynamics simulations
- macromolecular systems
- quantum mechanics/molecular mechanics (QM/MM)
- big data analytics in drug development
- pharmacokinetics optimization
- structure-based drug design (SBDD)
- ligand-based drug design
- virtual screening techniques
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