Structure-Based Design of Drugs and Biologically Active Molecules Based on Computer-Aided Drug Discovery
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 149
Special Issue Editor
Interests: drug design; virtual screening; molecular modeling; docking; molecular simulations; quantum chemistry
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Computer-Aided Drug Discovery (CADD) has advanced significantly, particularly with Structure-Based Drug Design (SBDD). SBDD uses three-dimensional models of biological targets, obtained by techniques such as X-ray crystallography and nuclear magnetic resonance (NMR), to guide the creation and optimization of bioactive molecules. SBDD allows the precise identification of ligands with high affinity and specificity, essential for therapeutic efficacy.
Computational tools, such as molecular docking and molecular dynamics, are employed to predict the conformation of ligands and their binding energies to the biological target. Molecular docking remains a vital tool in SBDD, allowing the prediction of the preferred orientation of a molecule in a protein target. Furthermore, the use of machine learning has improved the prediction of pharmacokinetic and toxicological properties, accelerating the development of safe and effective medicines.
CADD and SBDD not only significantly reduce the time and cost associated with developing new drugs but also increase the accuracy in identifying promising compounds. The integration of computational and experimental methods is crucial for successful drug discovery, facilitating the identification and optimization of new drug candidates.
These approaches have proven essential for advances in medicine, promoting the discovery of innovative and personalized therapies that better meet patients’ needs.
Dr. Cleydson Breno Rodrigues dos Santos
Guest Editor
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Keywords
- drug design
- virtual screening
- bioinformatics
- chemoinformatics
- quantum chemistry
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