Computational Methods in the Design of Anticancer Drugs

Dear Colleagues,

Cancer is still a major threat to human health and one of the leading causes of death worldwide. In recent years, advances in the development of new anticancer drugs have been continuous, and several compounds (small molecules, engineered antibodies, immunomodulators, etc.) have been approved for the treatment of cancer. 

In recent decades, computational methods have become an essential tool in the drug design process as they are able to reduce research costs and accelerate the development process. The application of computational methods in the design of anticancer drugs has proved to be very effective. Given the wide variety of very different tumor forms and the multiplicity of possible pharmacological targets, this research area is very fruitful.

This Special Issue on "Computational methods in the design of anticancer drugs" aims to collect the most recent discoveries in the field of anticancer drug design with the aid of computational methods, such as structure-based drug discovery and ligand-based drug discovery classical or de novo drug design (molecular docking, virtual screening, pharmacophore mapping, similarity searching, QSAR modeling), molecular dynamics and the development of machine learning methods. These are some types of computational approaches that we would like to highlight in this Special Issue.

We are looking forward to your contribution.

Dr. Marialuigia Fantacuzzi
Dr. Mariangela Agamennone
Guest Editors

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