scholarly journals Ambiguity of non-systematic chemical identifiers within and between small-molecule databases

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Saber A. Akhondi ◽  
Sorel Muresan ◽  
Antony J. Williams ◽  
Jan A. Kors
Keyword(s):  
Small Molecule ◽  
Small Molecule Databases

Toward a Comprehensive Treatment of Tautomerism in Chemoinformatics Including in InChI V2

2019 ◽  
Author(s):  
Devendra K. Dhaked ◽  
Wolf Ihlenfeldt ◽  
Hitesh Patel ◽  
Marc Nicklaus
Keyword(s):  
Small Molecule ◽  
Comprehensive Treatment ◽  
Experimental Literature ◽  
Web Tool ◽  
Valence Tautomerism ◽  
Standard Version ◽  
Small Molecule Databases

<p>We have collected 86 different transforms of tautomeric interconversions. Out of those, 54 are for prototropic (non-ring-chain) tautomerism; 21 for ring-chain tautomerism; and 11 for valence tautomerism. The majority of these rules have been extracted from experimental literature. Twenty rules – covering the most well-known types of tautomerism such as keto-enol tautomerism – were taken from the default handling of tautomerism by the chemoinformatics toolkit CACTVS. The rules were analyzed against nine differerent databases totaling over 400 million (non-unique) structures as to their occurrence rates, mutual overlap in coverage, and recapitulation of the rules’ enumerated tautomer sets by InChI V.1.05, both in InChI’s Standard and a Non-Standard version with the increased tautomer-handling options 15T and KET turned on. These results and the background of this study are discussed in the context of the IUPAC InChI Project tasked with the redesign of handling of tautomerism for an InChI version 2. Applying the rules presented in this paper would approximately triple the number of compounds in typical small-molecule databases that would be affected by tautomeric interconversion by InChI V2. A web tool has been created to test these rules at https://cactus.nci.nih.gov/tautomerizer.</p>

scholarly journals Tautomeric Conflicts in Forty Small-Molecule Databases

2021 ◽  
Author(s):  
Devendra Kumar Dhaked ◽  
Marc Nicklaus
Keyword(s):  
Small Molecule ◽  
Data Set ◽  
Almost All ◽  
Small Molecule Databases

We have analyzed forty different databases ranging in size from a few thousand to nearly 100 million molecules, comprising a total of over 200 million structures, for their tautomeric conflicts. A tautomeric conflict is defined as an occurrence of two or more structures within a data set identified by the tautomeric rules applied as being tautomers of each other. We tested a total of 119 detailed tautomeric transform rules expressed as SMIRKS, out of which 79 yielded at least one conflict. The databases analyzed spanned a wide variety of types including large aggregating databases, drug collections, and experimentally based structure collections. Almost all databases analyzed showed intra-database tautomeric conflicts. The conflict rates as percentage of the database were typically in the few tenths of a percent range, which for the largest databases amounts to more than 100,000 cases per database.

Processing of Small Molecule Databases for Automated Docking

2007 ◽  
Vol 3 (1) ◽  
pp. 107-113 ◽  
Author(s):  
Maxwell Cummings ◽  
Alan Maxwell ◽  
Renee DesJarlais
Keyword(s):  
Small Molecule ◽  
Automated Docking ◽  
Small Molecule Databases

Food bioactive small molecule databases: Deep boosting for the study of food molecular behaviors

2020 ◽  
Vol 66 ◽  
pp. 102499
Author(s):  
Zheng-Fei Yang ◽  
Ran Xiao ◽  
Fei-Jun Luo ◽  
Qin-Lu Lin ◽  
Defang Ouyang ◽  
...  
Keyword(s):  
Small Molecule ◽  
Small Molecule Databases

Toward a Comprehensive Treatment of Tautomerism in Chemoinformatics Including in InChI V2

2019 ◽  
Author(s):  
Devendra K. Dhaked ◽  
Wolf Ihlenfeldt ◽  
Hitesh Patel ◽  
Marc Nicklaus
Keyword(s):  
Small Molecule ◽  
Comprehensive Treatment ◽  
Experimental Literature ◽  
Web Tool ◽  
Valence Tautomerism ◽  
Standard Version ◽  
Small Molecule Databases

<p>We have collected 86 different transforms of tautomeric interconversions. Out of those, 54 are for prototropic (non-ring-chain) tautomerism; 21 for ring-chain tautomerism; and 11 for valence tautomerism. The majority of these rules have been extracted from experimental literature. Twenty rules – covering the most well-known types of tautomerism such as keto-enol tautomerism – were taken from the default handling of tautomerism by the chemoinformatics toolkit CACTVS. The rules were analyzed against nine differerent databases totaling over 400 million (non-unique) structures as to their occurrence rates, mutual overlap in coverage, and recapitulation of the rules’ enumerated tautomer sets by InChI V.1.05, both in InChI’s Standard and a Non-Standard version with the increased tautomer-handling options 15T and KET turned on. These results and the background of this study are discussed in the context of the IUPAC InChI Project tasked with the redesign of handling of tautomerism for an InChI version 2. Applying the rules presented in this paper would approximately triple the number of compounds in typical small-molecule databases that would be affected by tautomeric interconversion by InChI V2. A web tool has been created to test these rules at https://cactus.nci.nih.gov/tautomerizer.</p>

scholarly journals Advanced SPARQL querying in small molecule databases

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Jakub Galgonek ◽  
Tomáš Hurt ◽  
Vendula Michlíková ◽  
Petr Onderka ◽  
Jan Schwarz ◽  
...  
Keyword(s):  
Small Molecule ◽  
Small Molecule Databases

scholarly journals MolDiscovery: learning mass spectrometry fragmentation of small molecules

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Liu Cao ◽  
Mustafa Guler ◽  
Azat Tagirdzhanov ◽  
Yi-Yuan Lee ◽  
Alexey Gurevich ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Small Molecules ◽  
Small Molecule ◽  
Domain Knowledge ◽  
Mass Spectra ◽  
Molecular Structures ◽  
Mass Spectral Database ◽  
Mass Spectral ◽  
Tandem Mass Spectra ◽  
Small Molecule Databases

AbstractIdentification of small molecules is a critical task in various areas of life science. Recent advances in mass spectrometry have enabled the collection of tandem mass spectra of small molecules from hundreds of thousands of environments. To identify which molecules are present in a sample, one can search mass spectra collected from the sample against millions of molecular structures in small molecule databases. The existing approaches are based on chemistry domain knowledge, and they fail to explain many of the peaks in mass spectra of small molecules. Here, we present molDiscovery, a mass spectral database search method that improves both efficiency and accuracy of small molecule identification by learning a probabilistic model to match small molecules with their mass spectra. A search of over 8 million spectra from the Global Natural Product Social molecular networking infrastructure shows that molDiscovery correctly identify six times more unique small molecules than previous methods.

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