Editorial Board Members’ Collection Series: QSAR and Computational Approaches to Drug Discovery

Dear Colleagues,

Currently, a great effort exists to understand better and treat improvingly diseases. Computational modelling and simulation are critical in biomedical research. Computer-aided drug design and development allow understanding biomolecular interactions and the molecular mechanisms of diseases. In their applications in xenobiotics, computational methods are fundamental for drug discovery and development. This is because of their multiple uses in the collection, processing, analysis and modelling of data. In addition, they are central in associated risk assessment: Less animal testing (a currently compromised issue) is necessary. Drug design and development are multi-faceted processes in which a number of characteristics (e.g., efficacy, pharmacokinetics, safety) must be optimised. Therefore, advances in computational knowledge, artificial knowledge, machine learning and deep learning provide a basis for more effective searches of chemical spaces and the prediction of bioproperties based on molecular structure. In addition, to assess carefully the validity of the results is the most important matter. This issue aims to show different approaches and technologies that could be implemented in drug design and assessing the validity of the results, in the near future.

Dr. Francisco Torrens
Prof. Dr. Jesús Vicente de Julián-Ortiz
Guest Editors

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• molecular modelling
• molecular simulation
• drug design
• drug development
• molecular mechanism
• mathematical chemistry
• structure-activity relationship
• molecular descriptor
• pharmacokinetics
• toxicity