The chemical space for non-target analysis

Abstract The review describes chemical space, i.e. the set of known and possible compounds, and presents the use of corresponding chemical data in non-target analysis. Its implementation is briefly considered. General and dedicated chemical databases are outlined. Citation and co-citation of chemical compounds in databases are considered. The data transfer from high resolution mass spectrometry to chemical databases is noted to be the key stage of modern non-target analysis. Searched structures are further filtered with the use of reference and computational data. Related issues are also addressed.

[1]  Wendy C. Andersen,et al.  Application of single-stage Orbitrap mass spectrometry and differential analysis software to nontargeted analysis of contaminants in dog food: detection, identification, and quantification of glycoalkaloids. , 2015, Journal of agricultural and food chemistry.

[2]  Masanori Arita,et al.  Identification of small molecules using accurate mass MS/MS search. , 2018, Mass spectrometry reviews.

[3]  Hong Wang,et al.  Non-Target Screening of Veterinary Drugs Using Tandem Mass Spectrometry on SmartMass , 2013, Journal of The American Society for Mass Spectrometry.

[4]  Ronghong Li,et al.  MyCompoundID MS/MS Search: Metabolite Identification Using a Library of Predicted Fragment-Ion-Spectra of 383,830 Possible Human Metabolites. , 2015, Analytical chemistry.

[5]  Adrian Covaci,et al.  Identification strategies for flame retardants employing time-of-flight mass spectrometric detectors along with spectral and spectra-less databases. , 2015, Journal of mass spectrometry : JMS.

[6]  Mohammad Goodarzi,et al.  Analysis of Volatile Compounds by Advanced Analytical Techniques and Multivariate Chemometrics. , 2017, Chemical reviews.

[7]  Jean-Louis Reymond,et al.  Fragment Database FDB-17 , 2017, J. Chem. Inf. Model..

[8]  J. Reymond.  The chemical space project. , 2015, Accounts of chemical research.

[9]  Merle M. Plassmann,et al.  Detecting a wide range of environmental contaminants in human blood samples—combining QuEChERS with LC-MS and GC-MS methods , 2015, Analytical and Bioanalytical Chemistry.

[10]  Valery Tkachenko,et al.  Identification of “Known Unknowns” Utilizing Accurate Mass Data and ChemSpider , 2011, Journal of The American Society for Mass Spectrometry.

[11]  Bertrand Rochat,et al.  Proposed Confidence Scale and ID Score in the Identification of Known-Unknown Compounds Using High Resolution MS Data , 2017, Journal of The American Society for Mass Spectrometry.

[12]  K. Kümmerer,et al.  General strategies to increase the repeatability in non-target screening by liquid chromatography-high resolution mass spectrometry. , 2016, Analytica chimica acta.

[13]  V. Havlíček,et al.  Structural Analysis of Natural Products. , 2016, Analytical chemistry.

[14]  Christian Brinch Mollerup,et al.  Targeted and non-targeted drug screening in whole blood by UHPLC-TOF-MS with data-independent acquisition. , 2017, Drug testing and analysis.

[15]  B. Milman.  Identification of chemical compounds , 2005 .

[16]  Miguel Valcárcel,et al.  Metrology of Qualitative Chemical Analysis: Project report EUR 20605 , 2002 .

[17]  M. Woldegebriel.  Novel Method for Calculating a Nonsubjective Informative Prior for a Bayesian Model in Toxicology Screening: A Theoretical Framework. , 2015, Analytical chemistry.

[18]  M. G. Gómez Ramos,et al.  Development of sample extraction and clean-up strategies for target and non-target analysis of environmental contaminants in biological matrices. , 2015, Journal of chromatography. A.

[19]  Juho Rousu,et al.  Critical Assessment of Small Molecule Identification 2016: automated methods , 2017, Journal of Cheminformatics.

[20]  Emma L. Schymanski,et al.  Suspect and nontarget screening approaches to identify organic contaminant records in lake sediments , 2014, Analytical and Bioanalytical Chemistry.

[21]  Shuzhao Li,et al.  Computational Metabolomics: A Framework for the Million Metabolome , 2022 .

[22]  V. Babushok.  Chromatographic retention indices in identification of chemical compounds , 2015 .

[23]  Nikolaos S. Thomaidis,et al.  Targeted and non-targeted liquid chromatography-mass spectrometric workflows for identification of transformation products of emerging pollutants in the aquatic environment , 2015 .

[24]  Xin Wang,et al.  Untargeted screening of unknown xenobiotics and potential toxins in plasma of poisoned patients using high-resolution mass spectrometry: Generation of xenobiotic fingerprint using background subtraction. , 2016, Analytica chimica acta.

[25]  Herbert Oberacher,et al.  Current status of non-targeted liquid chromatography-tandem mass spectrometry in forensic toxicology , 2016 .

[26]  Boris L. Milman.  Literature-Based Generation of Hypotheses on Chemical Composition Using Database Co-occurrence of Chemical Compounds , 2005, J. Chem. Inf. Model..

[27]  J. Reymond,et al.  Chemical Space Travel , 2007, ChemMedChem.

[28]  Sebastian Böcker,et al.  Mining molecular structure databases: Identification of small molecules based on fragmentation mass spectrometry data. , 2017, Mass spectrometry reviews.

[29]  Emma L. Schymanski,et al.  MetFrag relaunched: incorporating strategies beyond in silico fragmentation , 2016, Journal of Cheminformatics.

[30]  Sebastian Böcker,et al.  Fragmentation trees reloaded , 2014, Journal of Cheminformatics.

[31]  M. A. Kovrizhnych,et al.  Identification of chemical substances by testing and screening of hypotheses II. Determination of impurities in n-hexane and naphthalene , 2000, Fresenius' journal of analytical chemistry.

[32]  M. Krauss.  Chapter 15 - High-Resolution Mass Spectrometry in the Effect-Directed Analysis of Water Resources , 2016 .

[33]  T. Croley,et al.  Nontargeted Screening of Food Matrices: Development of a Chemometric Software Strategy To Identify Unknowns in Liquid Chromatography-Mass Spectrometry Data. , 2016, Analytical chemistry.

[34]  Dieter Jahn,et al.  Comprehensive comparison of in silico MS/MS fragmentation tools of the CASMI contest: database boosting is needed to achieve 93% accuracy , 2017, Journal of Cheminformatics.

[35]  I. Ferrer,et al.  Identification of imidacloprid metabolites in onion (Allium cepa L.) using high-resolution mass spectrometry and accurate mass tools. , 2013, Rapid communications in mass spectrometry : RCM.

[36]  A. Kaufmann,et al.  Semi-targeted residue screening in complex matrices with liquid chromatography coupled to high resolution mass spectrometry: current possibilities and limitations. , 2011, The Analyst.

[37]  R. Khaiwal.  Determination of Atmospheric Volatile and Semi-volatile Compounds , 2011 .

[38]  Thomas Letzel,et al.  Non-target screening with high-resolution mass spectrometry: critical review using a collaborative trial on water analysis , 2015, Analytical and Bioanalytical Chemistry.

[39]  Boris L. Milman,et al.  Chemical Identification and its Quality Assurance , 2011 .

[40]  R. Friedman,et al.  Mass spectral metabonomics beyond elemental formula: chemical database querying by matching experimental with computational fragmentation spectra. , 2008, Analytical chemistry.

[41]  Shenghong Hu,et al.  Rapid Identification of Unknown Organic Iodine in Small-Volume Complex Biological Samples Based on Nanospray Mass Spectrometry Coupled with in-Tube Solid Phase Microextraction. , 2017, Analytical chemistry.

[42]  Steffen Neumann,et al.  Solving CASMI 2013 with MetFrag, MetFusion and MOLGEN-MS/MS. , 2014, Mass spectrometry.

[43]  Emma L. Schymanski,et al.  Open Science for Identifying "Known Unknown" Chemicals. , 2017, Environmental science & technology.

[44]  Syam S Andra,et al.  Trends in the application of high-resolution mass spectrometry for human biomonitoring: An analytical primer to studying the environmental chemical space of the human exposome. , 2017, Environment international.

[45]  B. Milman.  A procedure for decreasing uncertainty in the identification of chemical compounds based on their literature citation and cocitation. Two case studies. , 2002, Analytical chemistry.

[46]  Félix Hernández,et al.  Rapid non-target screening of organic pollutants in water by ultraperformance liquid chromatography coupled to time-of-light mass spectrometry , 2008 .

[47]  B L Milman,et al.  Identification of chemical substances by testing and screening of hypotheses I. General , 2000, Fresenius' journal of analytical chemistry.

[48]  G. Vivó-Truyols,et al.  A New Bayesian Approach for Estimating the Presence of a Suspected Compound in Routine Screening Analysis. , 2016, Analytical chemistry.

[49]  K. Magnus Åberg,et al.  Non-target time trend screening: a data reduction strategy for detecting emerging contaminants in biological samples , 2016, Analytical and Bioanalytical Chemistry.

[50]  Katharina M. Rentsch,et al.  Knowing the unknown – State of the art of LCMS in toxicology , 2016 .

[51]  T. Croley,et al.  Non-targeted screening approaches for contaminants and adulterants in food using liquid chromatography hyphenated to high resolution mass spectrometry. , 2016, Journal of chromatography. A.

[52]  Emma L. Schymanski,et al.  Mass spectral databases for LC/MS- and GC/MS-based metabolomics: state of the field and future prospects , 2016 .

[53]  K. Levsen.  Chapter 22 Sample preparation for water analysis , 2002 .

[54]  Hartmut Laatsch,et al.  Dereplication of Natural Products Using Databases , 2015 .

[55]  Igor V. Tetko,et al.  BIGCHEM: Challenges and Opportunities for Big Data Analysis in Chemistry , 2016, Molecular informatics.

[56]  C. Junot,et al.  Development and validation of a multiresidue method for the analysis of more than 500 pesticides and drugs in water based on on-line and liquid chromatography coupled to high resolution mass spectrometry. , 2016, Water research.

[57]  Jesús Martín,et al.  Combined LC/UV/MS and NMR Strategies for the Dereplication of Marine Natural Products , 2016, Planta Medica.

[58]  Evan Bolton,et al.  PUG-SOAP and PUG-REST: web services for programmatic access to chemical information in PubChem , 2015, Nucleic Acids Res..

[59]  Steven J. Lehotay,et al.  Current issues involving screening and identification of chemical contaminants in foods by mass spectrometry , 2015 .

[60]  Takaaki Nishioka,et al.  Winners of CASMI2013: Automated Tools and Challenge Data. , 2014, Mass spectrometry.

[61]  Y. Russkikh,et al.  An approach to the mass spectrometry identification of cyanobacterial peptides. The case of demethylmicrocystin-LR , 2011 .

[62]  Jianying Hu,et al.  Evaluating a Tap Water Contamination Incident Attributed to Oil Contamination by Nontargeted Screening Strategies. , 2016, Environmental science & technology.

[63]  Boris L. Milman,et al.  Mass spectral libraries: A statistical review of the visible use , 2016 .

[64]  Bertrand Rochat,et al.  From targeted quantification to untargeted metabolomics: Why LC-high-resolution-MS will become a key instrument in clinical labs , 2016 .

[65]  Y. Picó,et al.  Last trends in pesticide residue determination by liquid chromatography–mass spectrometry , 2014 .

[66]  Shunji Hashimoto,et al.  Nontarget approach for environmental monitoring by GC × GC-HRTOFMS in the Tokyo Bay basin. , 2016, Chemosphere.

[67]  Boris L. Milman,et al.  General principles of identification by mass spectrometry , 2015 .

[68]  Reza Aalizadeh,et al.  Extended Suspect and Non-Target Strategies to Characterize Emerging Polar Organic Contaminants in Raw Wastewater with LC-HRMS/MS. , 2015, Environmental science & technology.

[69]  Ann M Richard,et al.  Linking high resolution mass spectrometry data with exposure and toxicity forecasts to advance high-throughput environmental monitoring. , 2016, Environment international.

[70]  Oliver Fiehn,et al.  Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry , 2007, BMC Bioinformatics.

[71]  Tracey Thomas,et al.  Review of chemical signature databases , 2010, Analytical and bioanalytical chemistry.

[72]  A. Fernández-Alba,et al.  Matching unknown empirical formulas to chemical structure using LC/MS TOF accurate mass and database searching: example of unknown pesticides on tomato skins. , 2005, Journal of Chromatography A.

[73]  Sebastian Böcker,et al.  Searching molecular structure databases using tandem MS data: are we there yet? , 2017, Current opinion in chemical biology.

[74]  Lars Ruddigkeit,et al.  The enumeration of chemical space , 2012 .

[75]  Jon R. Sobus,et al.  Identifying known unknowns using the US EPA’s CompTox Chemistry Dashboard , 2017, Analytical and Bioanalytical Chemistry.

[76]  Stacy D. Brown,et al.  Identification of “Known Unknowns” Utilizing Accurate Mass Data and Chemical Abstracts Service Databases , 2011, Journal of the American Society for Mass Spectrometry.

[77]  Antony J. Williams,et al.  ChemTrove: Enabling a Generic ELN To Support Chemistry through the Use of Transferable Plug-ins and Online Data Sources , 2015, J. Chem. Inf. Model..

[78]  R. Breitling,et al.  Toward global metabolomics analysis with hydrophilic interaction liquid chromatography-mass spectrometry: improved metabolite identification by retention time prediction. , 2011, Analytical chemistry.

[79]  J. Wolff,et al.  Identification of the 'wrong' active pharmaceutical ingredient in a counterfeit Halfan drug product using accurate mass electrospray ionisation mass spectrometry, accurate mass tandem mass spectrometry and liquid chromatography/mass spectrometry. , 2003, Rapid communications in mass spectrometry : RCM.

[80]  S. Böcker,et al.  Searching molecular structure databases with tandem mass spectra using CSI:FingerID , 2015, Proceedings of the National Academy of Sciences of the United States of America.

[81]  Emma L. Schymanski,et al.  Nontarget Analysis of Environmental Samples Based on Liquid Chromatography Coupled to High Resolution Mass Spectrometry (LC-HRMS) , 2016 .