Chemoinformatics in Drug Design: Achievements and Challenges
A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Computational and Theoretical Chemistry".
Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 817
Special Issue Editors
Interests: medicinal chemistry; computational chemistry; 3D-QSAR; machine learning; drug design; extraction of natural compounds; essential oil
Special Issues, Collections and Topics in MDPI journals
Interests: biochemistry; computer-aided drug design; cheminformatics; bioinformatics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Chemoinformatics is a general word implying the massive use of informatics and software engineering in the chemistry field. In particular, in this topic, the focus is on medicinal chemistry and all the methods and their assessment in developing bioactive molecules. Experimental data should always be used to assess the chemoinformatic application, whereas methodology manuscripts will be considered also in absence of experimental data, but deep comparison with state-of-the-art methods should be included.
Dr. Rino Ragno
Dr. Milan Mladenović
Guest Editors
Manuscript Submission Information
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Keywords
- Molecular descriptor development: Topological invariants as promising tools for determining structure-activity and structure-property relations in molecules and their predictive potentials
- Development of methods for qualities assessments of topological descriptors
- Current methods vs. artificial intelligence in: Ligand-based drug design
- Structure-based drug design
- Analysis of drug mixtures effects
- Artificial intelligence in: Development of molecular descriptors
- QSAR, QSPR, and proteochemometrics modeling
- Predicting the drug activity/property
- De novo drug design
- Plant medicinal chemistry application
- Drug toxicity prediction
- Drug bioavailability
- Prediction of retrosynthesis pathways, synthetic routes, reaction mechanisms, and reaction yields
- Polypharmacology drug design
- Design of selective drugs
- Design of drug mixture or combinations
- Automated workflows in drug design
- Automated workflows in chemical synthesis
- Teaching methods for the use of artificial intelligence for drug design
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