ArticleACS omega2021
Exploring Chemical Reaction Space with Reaction Difference Fingerprints and Parametric t-SNE.
Article in ACS omega, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Efficient visualization of chemical space.Chemical science · 2026Article
- Antitarget profiling of mycotoxins via molecular docking.Molecular diversity · 2026Article
- Chemical space visualization at scale: a survey of end-to-end pipelines and dataset-size archetypes.Journal of cheminformatics · 2026Review
- Integrating AlphaFold2, RoseTTAFold2, and HADDOCK to refine Protein-Protein Interaction (PPI) candidate selection: A case study with ZWINT.Biochemistry and biophysics reports · 2026Article
- From In Silico Hypothesis to Validation: The Role of Real-World Evidence in the Preliminary Verification of AI-Generated Drug-Repositioning Candidates: A Comprehensive Review.Journal of clinical medicine · 2026Review
- Analysis of the Toxicological Profile ofPlants (Basel, Switzerland) · 2025Article
- Computational discovery of novel FYN kinase inhibitors: a cheminformatics and machine learning-driven approach to targeted cancer and neurodegenerative therapy.Molecular diversity · 2024Article
- MolCompass: multi-tool for the navigation in chemical space and visual validation of QSAR/QSPR models.Journal of cheminformatics · 2024Article
- Using slisemap to interpret physical data.PloS one · 2024Article
- Machine learning-guided strategies for reaction conditions design and optimization.Beilstein journal of organic chemistry · 2024Review
- Alchemical analysis of FDA approved drugs.Digital discovery · 2023Article
- Revolutionizing Medicinal Chemistry: The Application of Artificial Intelligence (AI) in Early Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2023Review
- Sampling and Mapping Chemical Space with Extended Similarity Indices.Molecules (Basel, Switzerland) · 2023Article
- Reagent prediction with a molecular transformer improves reaction data quality.Chemical science · 2023Article
- Cheminformatics and artificial intelligence for accelerating agrochemical discovery.Frontiers in chemistry · 2023Review
- MetChem: a new pipeline to explore structural similarity across metabolite modules.Bioinformatics advances · 2023Article
- Navigating chemical reaction space - application to DNA-encoded chemistry.Chemical science · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Humans prefer visual representations for the analysis of large databases. In this work, we suggest a method for the visualization of the chemical reaction space. Our technique uses the t-SNE approach that is parameterized using a deep neural network (parametric t-SNE). We demonstrated that the parametric t-SNE combined with reaction difference fingerprints could provide a tool for the projection of chemical reactions on a low-dimensional manifold for easy exploration of reaction space. We showed that the global reaction landscape projected on a 2D plane corresponds well with the already known reaction types. The application of a pretrained parametric t-SNE model to new reactions allows chemists to study these reactions in a global reaction space. We validated the feasibility of this approach for two commercial drugs, darunavir and montelukast. We believe that our method can help to explore reaction space and will inspire chemists to find new reactions and synthetic ways.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.