QSAR and Chemoinformatics in Drug Design and Discovery
A special issue of Pharmaceuticals (ISSN 1424-8247). This special issue belongs to the section "Medicinal Chemistry".
Deadline for manuscript submissions: 15 December 2025 | Viewed by 63
Special Issue Editors
Interests: GPCR-targeting compounds; enzymes; QSAR; virtual screening; computational methods; drug design; pharmacophore modeling
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The use of information resources and computers in search for novel bioactive compounds is a well-established practice in the field of pharmaceutical sciences. Chemoinformatics significantly contributes to the efficiency and quality of hit finding, as well as to candidate optimization, in early drug development. Virtual screening, QSAR, and machine learning models are only a few examples of the chemoinformatics techniques that have relevance to the drug design process. In addition, toxicoinformatics is devoted to the prediction of compounds’ toxicity and adverse effects. The most relevant advantages of computational techniques are the cost and time reduction resulting from the prioritization of only a subset of most probable hits. Today, these methods are widely applied and have allowed for advances in the clinics of several candidates. These techniques are constantly evolving, allowing for to perform molecular simulations on a larger scale and with improved performance. In this vibrant scenario, this Special Issue invites authors to submit original papers that exploit QSAR and chemoinformatics for the design of new bioactive molecules. Review articles reporting the state of the art and future perspectives are welcome as long as they align with the scope of this Special Issue. Topics of interest include (but are not limited to) advanced QSAR modeling, machine learning applications in drug discovery, ligand-based virtual screening and design, computer-aided drug repurposing, and toxicology- and pharmacokinetic-related predictive studies using computational methods.
Dr. Elena Cichero
Dr. Naomi Scarano
Guest Editors
Manuscript Submission Information
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Keywords
- QSAR modeling
- machine learning
- ligand-based virtual screening and design
- computer-aided drug repurposing
- computational methods
- molecular modeling
- molecular dynamics
- drug design
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