Advanced Research on Computer-Aided Drug Design
A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Medicinal Chemistry".
Deadline for manuscript submissions: 31 January 2027 | Viewed by 145
Editors
Interests: computer-aided drug design; molecular docking; molecular dynamics simulations; molecular ecotoxicology; in silico toxicology; nanotoxicology; DNA damage and repair mechanisms; genotoxicity and antigenotoxicity; oxidative stress; phytochemicals and natural products; enzyme inhibition studies; protein–ligand interactions; structure-based virtual screening; ADMET and pharmacokinetic prediction; environmental mutagenesis and toxicogenomics
Interests: molecular dynamics; docking; drug design; nucleic acids; complex fluids; water anomalies
2. Koc University Research Center for Translational Medicine (KUTTAM), School of Medicine, Koc University, Istanbul, Türkiye
Interests: computer-aided drug design; respiratory diseases; environmental lung disease; pulmonary fibrosis; precision medicine
Special Issue Information
Dear Colleagues,
Computer-aided drug design (CADD) has evolved from a supportive screening strategy into a central framework for modern molecular discovery. The increasing cost, duration, and attrition rate of experimental drug development have created a strong need for approaches that can prioritize chemical matter before synthesis, reduce unproductive wet-lab cycles, and generate mechanistic hypotheses at molecular and atomic resolution. Within this context, structure-based and ligand-based CADD methods, including molecular docking, molecular dynamics simulations, QSAR, pharmacophore modeling, virtual screening, free energy calculations, ADMET prediction, and machine-learning-guided molecular design, provide complementary information that is often inaccessible from endpoint experimental assays alone.
The impact of CADD is particularly evident during hit identification and hit-to-lead optimization, where computational models can evaluate binding modes, interaction networks, conformational flexibility, selectivity determinants, resistance-associated mutations, and physicochemical liabilities before experimental validation. Its scope now extends beyond classical small-molecule drug discovery into chemical biology, toxicology, molecular medicine, enzyme inhibition, host–pathogen interactions, and the interpretation of disease-related variants. Recent advances in structural biology, ultra-large chemical libraries, artificial intelligence, and protein-complex prediction further expand the applicability of CADD to targets with limited or absent experimental structural information, enabling rational exploration of proteins, nucleic acids, membranes, cofactors, and multi-component biomolecular systems.
This Special Issue, Advanced Research on Computer-Aided Drug Design, aims to collect high-quality studies that integrate computational rigor with biological relevance. We particularly welcome research combining validated in silico protocols with experimental or translational insight, thereby advancing CADD as a mechanistic, predictive, and interdisciplinary platform for next-generation therapeutic discovery.
Dr. Erman Salih İstifli
Prof. Dr. Paulo Augusto Netz
Dr. Özgecan Kayalar
Guest Editors
Manuscript Submission Information
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Keywords
- computer-aided drug design
- structure-based drug design
- molecular docking
- molecular dynamics simulations
- virtual screening
- hit-to-lead optimization
- binding free energy
- ADMET prediction
- machine learning in drug discovery
- protein–ligand interactions
- mutation-driven drug resistance
- computational medicinal chemistry
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