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NameRxn

Version 3.2.0 [May 2021]

Expert System for Named Reaction Identification and Classification

NextMove Software's NameRxn software, part of the HazELNut suite of tools, allows the recognition and categorization of reactions from their connection tables. Using a large rule-base of known reaction mechanisms/transformations, NameRXN is able to categorize reactions (such as those in pharmaceutical ELNs or extracted from the literature) to a NameRxn code, such as "3.1.1 Bromo Suzuki coupling" and an RXNO ontology identifier, such as "RXNO:0000140". RXNO is an ontology of named reactions maintained by the Royal Society of Chemistry. The three-level NameRxn code is based upon the hierarchy proposed by Carey, Laffan, Thomson and Williams 2006, and used again by Roughley and Jordan 2011. For example, "3.5.3 Negishi coupling" is an member of the class "3.5 Palladium-catalyzed C-C bond formation", which is a member of the super-class "3 Carbon-carbon bond formation".

  • A presentation mentioning NameRXN presented at the American Chemical Society (ACS) National Meeting in Boston, August 2015

References

1. J.S Carey, D. Laffan, C. Thomson and M.T. Williams, "Analysis of the Reactions used for the Preparation of Drug Candidate Molecules", Organic & Biomolecular Chemistry, 4: 2337-2347, May 2006.

2. Stephen D. Roughley and Allan M. Jordan, "The Medicinal Chemist's Toolbox: An Analysis of Reactions used in the Pusuit of Drug Candidates". Journal of Medicinal Chemistry. 54: 3451-79, May 2011.

3. Nadine Schneider, Daniel N. Lowe, Roger Sayle, Michael Tarselli and Gregory Landrum, "Big Data from Pharmaceutical Patents: A Computational Analysis of Medicinal Chemists' Bread and Butter", Journal of Medicinal Chemistry. 59(9): 4385-4402, Mar 2016.

4. Nadine Schneider, Daniel M. Lowe, Roger Sayle and Greg Landrum, Development of a Novel Fingerprint for Chemical Reactions and Its Application to Large-Scale Reaction Classification and Similarity. Journal of Chemical Information and Modeling. 55(1): 39-53. Jan 2015

Arthor provides fast state-of-the-art substructure and chemical similarity search capabilities for ultra-large databases of hundreds of millions of compounds, using SMARTS optimization, Just-In-Time compilation and/or GPUs.
CaffeineFix is used to rapidly match chemical names or terms against a dictionary or grammar (e.g. a grammar for IUPAC names). As well as use in text-mining, it can be used to provide autocomplete functionality and spell-correction.
Casandra is a server for delivering real time safety warnings of experimental hazards straight to the pharmaceutical electronic laboratory notebooks (ELNs).
HazELNut is a suite of tools used to extract, normalize and analyse information in Electronic Lab Notebooks (ELNs). This can be used to implement a search interface, find/eliminate duplicates, find similar reactions and so on.
LeadMine extracts chemical names and terms from text. It incorporates NextMove's CaffeineFix technology to find terms that match appropriate dictionaries or grammars. It has enhanced functionality to handle the patent literature.
Matsy is a set of tools for creating and analysing Matched Molecular Series (the general form of Matched Molecular Pairs). In particular, it can be used to suggest what compound to make next in a Medicinal Chemistry program.
MPSearch rapidly searches a database to find Matched Pairs related to a query molecule. This type of search is used to explore previous medicinal chemistry strategies.
NameRXN is used to classify and name reactions. It is particular useful in the context of ELN analysis but also as a plugin to chemical drawing software. NameRXN builds on NextMove Software's Patsy technology.
Patsy is used to speed up SMARTS pattern matching by creating optimized SMARTS patterns or source code. Speed gains are particularly large when multiple SMARTS patterns are matched against a single structure.
Pistachio is a reaction dataset browser providing loading, querying, and analytics of chemical reactions. With over 9 million chemical reactions extracted from US & EPO patents, it demonstrates an AI interface to faceted (structure) search
SmallWorld is an index of chemical space based on more than 230 billion molecular substructures. It can be used to measure similarity based on graph-edit distance, find the MCS of two or more molecules, analyse HTS results and much more.
Sugar & Splice can be used to perceive and depict biopolymer structure. It makes it easy to interconvert between small-molecule representations (e.g. SMILES, MOL) and biopolymer representations (HELM, IUPAC line notation).
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