Cheminformatics applications in drug discovery, materials science and the environment underpinned by artificial intelligence and machine learning methods

Cheminformatics is an interface science that combines, among others, Chemistry, Biology,
Mathematics, Biochemistry, Physics, Statistics, and informatics. Cheminformatics has so far
significantly contributed to a wide range of applications within several research areas,
including drug discovery, computational toxicology, and, quite recently, nanomaterials risk
The in silico analysis of large datasets of compounds with their corresponding
properties/activities and the virtual screening of novel chemical structures is a demanding
procedure that needs to be automated. In this context, various tools must be combined to
facilitate multiple important tasks and construct workflows that simplify the handling,
processing, and modeling of cheminformatics data and provide time and cost-efficient
solutions, reproducible and easier to maintain.
Emerging methods and tools underpinned by machine learning and artificial intelligence,
as well as cloud solutions developed, significantly facilitate the dissemination of results
and knowledge gained and stimulate advancements in cheminformatics that is currently
expanding and growing with increasing pace. Specific examples and workflows leading to
significant results as alternatives to experimental procedures, by reducing the timescale
and cost required, will be presented.