Drug Design and Virtual Screening 3.0
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 November 2024 | Viewed by 333
Special Issue Editor
Interests: drug design; molecular simulations; molecular modeling; network pharmacology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Since the end of the 19th century when aspirin was synthesized by modifying the structure of a natural product, scientists have been engaged in drug design and discovery. The emergence of quantitative structure–activity relationship (QSAR) methods in the 1960s represented a new era of rational drug design. With the development of computational methods and large databases, various drug design and in silico screening technologies have been devised. Researchers can identify the molecular structures essential for pharmacological activity more readily and screen large libraries of compounds with a high degree of specificity. From genes to proteins to drugs, computer-aided drug design methodology plays an increasingly important role in modern drug discovery.
This Special Issue of International Journal Molecular Sciences focuses on drug design, in silico screening, and pharmacogenomic approaches. All articles relating to drug design and discovery are welcomed, including but not limited to the following aspects: CADD methodology, virtual screening of compound libraries by computational methods, structural optimization of lead compounds, modelling studies on the interaction between small molecules and macromolecules, and pharmacogenomics/transcriptomics. Cell-based or animal experiments are also encouraged involving any disease model, but not essential.
Dr. Jia-Zhong Li
Guest Editor
Manuscript Submission Information
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Keywords
- CADD methodology
- QSAR
- pharmacophore modelling
- molecular docking
- virtual screening
- lead optimization
- de novo drug design
- molecular dynamics
- network pharmacology
- pharmacogenomics
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