ArticleJournal of cheminformatics2024
One chiral fingerprint to find them all.
Article in Journal of cheminformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Count your bits: fingerprint benchmarking to assess broad chemical space representation.Journal of cheminformatics · 2026Article
- Assigning the stereochemistry of natural products by machine learning.Journal of cheminformatics · 2026Article
- A unified multi-scale deep learning framework for molecular property prediction that bridges molecular structures and fingerprinting.Communications chemistry · 2026Article
- Chirobiophore: A Novel Framework for Quantifying Biochirality in Macromolecular Systems.Biomolecules · 2026Article
- PepFoundry: A Pipeline for Building Machine-Learning Ready Representations of Nonstandard Peptides Containing Cycles, Non-natural Residues, Polymer Units, and More.Journal of chemical information and modeling · 2026Article
- Exploring and expanding the chemical multiverse of peptides.Chemical science · 2026Review
- Beyond natural amino acids: extending immunogenicity risk assessment to modified peptides through chemical feature encoding. A case study on citrullination.Frontiers in immunology · 2026Article
- From Deep-Sea Natural Product to Optimized Therapeutics: Computational Design of Marizomib Analogs.International journal of molecular sciences · 2025Article
- Rescuing Verubecestat: An Integrative Molecular Modeling and Simulation Approach for Designing Next-Generation BACE1 Inhibitors.International journal of molecular sciences · 2025Article
- Structural Isomer Cumulative molecular fingerprinting method (SIC) for standardizing structural isomeric relationships.Communications chemistry · 2025Article
- DiaNat-DB-v2: A Molecular Database of Antidiabetic Compounds from Medicinal Plants and Functional Foods.ACS omega · 2025Article
- ELECTRUM: an electron configuration-based universal metal fingerprint for transition metal compounds.Digital discovery · 2025Article
- How to build machine learning models able to extrapolate from standard to modified peptides.Journal of cheminformatics · 2025Article
- A View on Molecular Complexity from the GDB Chemical Space.Journal of chemical information and modeling · 2025Review
- Merging the computational design of chimeric type I polyketide synthases with enzymatic pathways for chemical biosynthesis.Nature communications · 2025Article
- A Machine Learning Approach for Predicting the Pure-Component Surface Tension of Atmospherically Relevant Organic Compounds.ACS ES&T air · 2025Article
- Navigating a 1E+60 Chemical Space of Peptide/Peptoid Oligomers.Molecular informatics · 2025Article
- Chemoinformatic Characterization of NAPROC-13: A Database for Natural ProductJournal of natural products · 2024Article
- AutoPeptideML: a study on how to build more trustworthy peptide bioactivity predictors.Bioinformatics (Oxford, England) · 2024Article
- Can large language models predict antimicrobial peptide activity and toxicity?RSC medicinal chemistry · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Molecular fingerprints are indispensable tools in cheminformatics. However, stereochemistry is generally not considered, which is problematic for large molecules which are almost all chiral. Herein we report MAP4C, a chiral version of our previously reported fingerprint MAP4, which lists MinHashes computed from character strings containing the SMILES of all pairs of circular substructures up to a diameter of four bonds and the shortest topological distance between their central atoms. MAP4C includes the Cahn-Ingold-Prelog (CIP) annotation (R, S, r or s) whenever the chiral atom is the center of a circular substructure, a question mark for undefined stereocenters, and double bond cis-trans information if specified. MAP4C performs slightly better than the achiral MAP4, ECFP and AP fingerprints in non-stereoselective virtual screening benchmarks. Furthermore, MAP4C distinguishes between stereoisomers in chiral molecules from small molecule drugs to large natural products and peptides comprising thousands of diastereomers, with a degree of distinction smaller than between structural isomers and proportional to the number of chirality changes. Due to its excellent performance across diverse molecular classes and its ability to handle stereochemistry, MAP4C is recommended as a generally applicable chiral molecular fingerprint. SCIENTIFIC CONTRIBUTION: The ability of our chiral fingerprint MAP4C to handle stereoisomers from small molecules to large natural products and peptides is unprecedented and opens the way for cheminformatics to include stereochemistry as an important molecular parameter across all fields of molecular design.
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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.