New Computational Methodologies for Computer-Aided Drug Design and Chemoinformatics

Dear Colleagues,

Chemoinformatics is a multidisciplinary area of research primarily engaged with the collection, deposition, retrieval, and analysis of information in order to address chemistry-related problems. The analysis of chemistry-related data can take many forms, with one of the most important ones being quantitative structure–activity relationship (QSAR). QSAR can be broadly defined as the usage of mathematical models to find correlations between molecular activities (defined in the broadest possible sense) and a set of structure-based descriptors. Starting with early studies by Hansch and co-workers, the field has rapidly evolved through many significant advances, including data curation, descriptor calculation, regression and classification algorithms (e.g., Machine Learning algorithms), and evaluation metrics. Over the years, QSAR models have been widely and successfully used in many research areas, including chemistry, biology, toxicology, and material sciences, to both analyse the factors affecting molecular properties and design new compounds.

The purpose of this Special Issue is to provide an overview of the state of the art in current chemoinformatics methodologies, with an emphasis on the QSAR, and to describe how these methodologies are used in molecular modeling and drug design. We welcome original research articles, review articles, and short communications on one or more of the following topics:

• The development, implementation, and application of chemoinformatics databases;
• The development and application of new chemoinformatics tools;
• The development and application of new molecular descriptors;
• The construction and visualization of, and navigation through the chemical space;
• The development of new QSAR algorithms and workflows;
• The application of chemoinformatics and QSAR methodologies in molecular modeling and drug design.

We hope that this Special Issue will serve as an entry point for newcomers into the exciting world of chemoinformatics/QSAR, as well as a valuable reference for more experienced practitioners in the field.

Prof. Dr. Hanoch Senderowitz
Guest Editor

Manuscript Submission Information

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• chemoinformatics
• machine learning
• data mining
• quantitative structure activity relationship (QSAR)
• quantitative structure property relationship (QSPR)
• computer aided drug design (CADD)
• molecular descriptors
• databases
• chemical space
• data visualization

• QSAR and Chemoinformatics in Molecular Modeling and Drug Design in International Journal of Molecular Sciences (10 articles)
• QSAR and Chemoinformatics in Molecular Modeling and Drug Design 2.0 in International Journal of Molecular Sciences (9 articles)
• QSAR and Chemoinformatics in Molecular Modeling and Drug Design 3.0 in International Journal of Molecular Sciences (22 articles)
• QSAR and Chemoinformatics in Molecular Modeling and Drug Design 4.0 in International Journal of Molecular Sciences (6 articles)