Non-communicable diseases (NCDs) impose a significant burden on healthcare systems in both developed and developing countries. Indeed, the incidence of NCDs (e.g., diabetes, cancers, chronic respiratory diseases, and cardiovascular diseases) has increased in epidemic proportions worldwide. According to estimates made by the WHO, about 41 million people die annually worldwide, equivalent to 71% of all deaths, because of NCDs. 37% of those who died with NCDs are between the ages 30 and 69 years old. Lack of access to essential medicines for NCDs is a major challenge, especially in developing countries. Regrettably, the national drug policies in low- and middle-income countries do not include essential medicines for NCDs.

Utilising medicinal plants in drug discovery provides important leads against various pharmacological targets. A large number of plants used in traditional medicine have now become a part of the modern world healthcare system. Discovering novel natural drugs is now more achievable thanks to modern techniques for separation, structure elucidation, screening, and bio- and chemo-informatics. With the drastically increasing amount of biological data and the intensive time and human resources allocated to the discovery of new drugs, the need for computational methods has substantially increased. This can be achieved by filtering a large number of leads at the early stage of drug development before launching the drug into the costly and difficult phases of experimental lab tests as well as preclinical and clinical testing. Thanks to computer-aided drug design (CADD), new and potent natural hits can be mined. As a result, the time and cost requirements for the discovery of new drugs can be substantially lowered.

The aim of this Special Issue is to collate original research and review articles dealing with computer-aided drug design. We are interested in articles that explore aspects of medicinal plants and their active compounds in treating non-communicable diseases, with the concentration on in silico methods of drug discovery pipelines. Research articles that combine experimental evidence with computer-based methods of drug discovery are highly welcomed.

Potential topics include but are not limited to the following:

• Ligand-based drug design, including quantitative structure-activity relationship (QSAR) methods, pharmacophore mapping, or ligand-based virtual screening, and chemical similarity
• Structure- based drug design, including fragment- based drug design, docking approaches, molecular dynamics as well as pharmacophore modelling
• The combination of ligand- and structure- based filtering methods
• Isolation and characterisation of novel medicinal plants active compounds treating NCDs
• Recent advances in drug discovery from medicinal plants with anti- NCDs disorders potentials