Special issue: Exploring the chemical compound space with cutting-edge research tools

Targeted and efficient exploration of the vast chemical space in search of new and improved molecules and materials with artificial intelligence and multiscale modeling at the forefront of research efforts in life and materials’ sciences.

At two recent meetings in Heidelberg, Germany, this year, leaders in this dynamic field met and discussed the latest developments: the 2nd SIMPLAIX Workshop on Machine Learning for Multiscale Molecular Modeling and the Chemical Compound Space Conference 2024 (CCSC2024).

To highlight the cutting-edge research presented at these meetings and disseminate the state-of-the-art achievements in chemical space exploration, Anya Gryn’ova, Rebecca Wade, Tristan Bereau, and Pascal Friederich from the SIMPLAIX initiative, have teamed up with the editors of the Journal of Chemical Information and Modeling (published by the American Chemical Society), to assemble a virtual special issue (VSI) on “Chemical Compound Space Exploration by Multiscale High-Throughput Screening and Machine Learning”.

More details on this VSI can be found in a recently published Editorial (https://pubs.acs.org/doi/10.1021/acs.jcim.4c01300 ).