Exploration of (Ultra)Big Chemical Spaces

Chemical space [1, 2], the abstract universe of all possible molecules, remains a central concept in cheminformatics [3], drug discovery, and several other research areas. With estimates extending far beyond 1060 compounds, its exploration represents both an opportunity and an outstanding challenge. The increasing availability of computational power, innovative algorithms, and constantly increasing, massive compound libraries are opening new avenues for navigating this vast space. However, the complexity of the task—from dataset curation and representation to the reliable prediction of bioactivity—requires a careful balance between scale, diversity, and feasibility. Ultralarge chemical spaces demand not only efficient algorithms for screening but also rigorous strategies to ensure that the generated or selected molecules are synthetically accessible and hold the desired property, for example, that are biologically relevant [4]. In this context, this special issue of Molecular Informatics brings together six contributions that showcase the current progress in the exploration of (ultra)big chemical spaces. The works range from comparative analyses of natural and synthetic compound collections to the definition and practical advances of ultralarge virtual screening. They further illustrate methodological innovations, including new approaches to address activity cliffs in large datasets, benchmarking of dimensionality reduction techniques for chemical space visualization, and generative algorithms for exploring unprecedented peptide–peptoid libraries comprising up to 1060 members. Importantly, the special issue also introduces novel chemical spaces explicitly designed to expand the reach of existing resources, such as the Freedom Space, a synthetically feasible compound set complementary to widely used commercial libraries. Together, these contributions reflect the diversity of approaches currently driving the exploration of chemical space, from fundamental methodological work to practical applications in drug discovery. Taken as a whole, the contributions in this special issue underscore both the vastness of chemical space and the ingenuity required to navigate it. They emphasize the importance of uniting theoretical frameworks with experimental feasibility, integrating data-driven machine learning with human-interpretable visualizations, and expanding the boundaries of accessible molecular libraries while maintaining synthetic plausibility. We anticipate that this special issue will serve as a timely snapshot of a dynamic and rapidly evolving field, and we hope it will inspire continued efforts to explore, map, and harness the immense potential of chemical space in the discovery of novel bioactive molecules. I would like to thank all the authors who contributed to this special issue, as well as the anonymous peer reviewers for their insightful and constructive comments on the submitted manuscripts. On behalf of all contributors, we hope that this special issue will advance the ongoing exploration and understanding of the ever-expanding chemical space.