Generalized molecular descriptors derived from event-based discrete derivative
In the present study, a generalized approach for molecular structure characterization is introduced, based on the relation frequency matrix (F) representation of the molecular graph and the subsequent calculation of the corresponding discrete derivative (finite difference) over a pair of elements (a...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2016
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
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- eng
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- https://hdl.handle.net/20.500.12585/9005
- Palabra clave:
- Atom-based derivative index
Discrete derivative
DIVATI
Event criterion
Fingerprint
Frequency matrix
PCA
QSAR/QSPR
TOMOCOMD-CARDD
Carbon
Halogen
Furan derivative
Algorithm
Atom
Chemical structure
Computer interface
Controlled study
Factor analysis
Hydrophobicity
Molecular biology
Priority journal
Quantitative structure property relation
Review
Algorithm
Chemical model
Chemistry
Software
Algorithms
Furans
Models, Chemical
Software
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|
dc.title.none.fl_str_mv |
Generalized molecular descriptors derived from event-based discrete derivative |
title |
Generalized molecular descriptors derived from event-based discrete derivative |
spellingShingle |
Generalized molecular descriptors derived from event-based discrete derivative Atom-based derivative index Discrete derivative DIVATI Event criterion Fingerprint Frequency matrix PCA QSAR/QSPR TOMOCOMD-CARDD Carbon Halogen Furan derivative Algorithm Atom Chemical structure Computer interface Controlled study Factor analysis Hydrophobicity Molecular biology Priority journal Quantitative structure property relation Review Algorithm Chemical model Chemistry Software Algorithms Furans Models, Chemical Software |
title_short |
Generalized molecular descriptors derived from event-based discrete derivative |
title_full |
Generalized molecular descriptors derived from event-based discrete derivative |
title_fullStr |
Generalized molecular descriptors derived from event-based discrete derivative |
title_full_unstemmed |
Generalized molecular descriptors derived from event-based discrete derivative |
title_sort |
Generalized molecular descriptors derived from event-based discrete derivative |
dc.subject.keywords.none.fl_str_mv |
Atom-based derivative index Discrete derivative DIVATI Event criterion Fingerprint Frequency matrix PCA QSAR/QSPR TOMOCOMD-CARDD Carbon Halogen Furan derivative Algorithm Atom Chemical structure Computer interface Controlled study Factor analysis Hydrophobicity Molecular biology Priority journal Quantitative structure property relation Review Algorithm Chemical model Chemistry Software Algorithms Furans Models, Chemical Software |
topic |
Atom-based derivative index Discrete derivative DIVATI Event criterion Fingerprint Frequency matrix PCA QSAR/QSPR TOMOCOMD-CARDD Carbon Halogen Furan derivative Algorithm Atom Chemical structure Computer interface Controlled study Factor analysis Hydrophobicity Molecular biology Priority journal Quantitative structure property relation Review Algorithm Chemical model Chemistry Software Algorithms Furans Models, Chemical Software |
description |
In the present study, a generalized approach for molecular structure characterization is introduced, based on the relation frequency matrix (F) representation of the molecular graph and the subsequent calculation of the corresponding discrete derivative (finite difference) over a pair of elements (atoms). In earlier publications (22-24), an unique event, named connected subgraphs, (based on the Kier-Hall’s subgraphs) was systematically employed for the computation of the matrix F. The present report is a generalization of this notion, in which eleven additional events are introduced, classified in three categories, namely, topological (terminal paths, vertex path incidence, quantum subgraphs, walks of length k, Sach’s subgraphs), fingerprints (MACCs, E-state and substructure fingerprints) and atomic contributions (Ghose and Crippen atom-types for hydrophobicity and refractivity) for F generation. The events are intended to capture diverse information by the generation or search of different kinds of substructures from the graph representation of a molecule. The discrete derivative over duplex atom relations are calculated for each event, and the resulting derivatives, local vertex invariants (LOVIs) are finally obtained. These LOVIs are subsequently employed as the basis for the calculation of global and local indices over groups of atoms (heteroatoms, halogens, methyl carbons, etc.), by using norms, means, statistics and classical algorithms as aggregator (fusion) operators. These indices were implemented in our house software DIVATI (Derivative Type Indices, a new module of TOMOCOMDCARDD system). DIVATI provides a friendly and cross-platform graphical user interface, developed in the Java programming language and is freely available at: http: //www.tomocomd.com. Factor analysis shows that the presented events are rather orthogonal and collect diverse information about the chemical structure. Finally, QSPR models were built to describe the logP and logK of 34 furylethylenes derivatives using the eleven events. Generally, the equations obtained according to these events showed high correlations, with the Sach’s sub-graphs and Multiplicity events showing the best behavior in the description of logK (Q2LOO value of 99.06%) and logP (Q2LOO value of 98.1%), respectively. These results show that these new eventbased indices constitute a powerful approach for chemoinformatics studies. © 2016 Bentham Science Publishers. |
publishDate |
2016 |
dc.date.issued.none.fl_str_mv |
2016 |
dc.date.accessioned.none.fl_str_mv |
2020-03-26T16:32:45Z |
dc.date.available.none.fl_str_mv |
2020-03-26T16:32:45Z |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_efa0 |
dc.type.driver.none.fl_str_mv |
info:eu-repo/semantics/review |
dc.type.hasversion.none.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.spa.none.fl_str_mv |
Artículo de revisión |
status_str |
publishedVersion |
dc.identifier.citation.none.fl_str_mv |
Current Pharmaceutical Design; Vol. 22, Núm. 33; pp. 5095-5113 |
dc.identifier.issn.none.fl_str_mv |
13816128 |
dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/9005 |
dc.identifier.doi.none.fl_str_mv |
10.2174/1381612822666160610114148 |
dc.identifier.instname.none.fl_str_mv |
Universidad Tecnológica de Bolívar |
dc.identifier.reponame.none.fl_str_mv |
Repositorio UTB |
dc.identifier.orcid.none.fl_str_mv |
24824951000 56506611500 55665599200 55363486500 36454896800 16025887100 14040865600 57192014301 7801534311 57192013138 57192004534 7004872108 |
identifier_str_mv |
Current Pharmaceutical Design; Vol. 22, Núm. 33; pp. 5095-5113 13816128 10.2174/1381612822666160610114148 Universidad Tecnológica de Bolívar Repositorio UTB 24824951000 56506611500 55665599200 55363486500 36454896800 16025887100 14040865600 57192014301 7801534311 57192013138 57192004534 7004872108 |
url |
https://hdl.handle.net/20.500.12585/9005 |
dc.language.iso.none.fl_str_mv |
eng |
language |
eng |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_16ec |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ |
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Atribución-NoComercial 4.0 Internacional |
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http://creativecommons.org/licenses/by-nc-nd/4.0/ Atribución-NoComercial 4.0 Internacional http://purl.org/coar/access_right/c_16ec |
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Recurso electrónico |
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application/pdf |
dc.publisher.none.fl_str_mv |
Bentham Science Publishers B.V. |
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Bentham Science Publishers B.V. |
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2020-03-26T16:32:45Z2020-03-26T16:32:45Z2016Current Pharmaceutical Design; Vol. 22, Núm. 33; pp. 5095-511313816128https://hdl.handle.net/20.500.12585/900510.2174/1381612822666160610114148Universidad Tecnológica de BolívarRepositorio UTB2482495100056506611500556655992005536348650036454896800160258871001404086560057192014301780153431157192013138571920045347004872108In the present study, a generalized approach for molecular structure characterization is introduced, based on the relation frequency matrix (F) representation of the molecular graph and the subsequent calculation of the corresponding discrete derivative (finite difference) over a pair of elements (atoms). In earlier publications (22-24), an unique event, named connected subgraphs, (based on the Kier-Hall’s subgraphs) was systematically employed for the computation of the matrix F. The present report is a generalization of this notion, in which eleven additional events are introduced, classified in three categories, namely, topological (terminal paths, vertex path incidence, quantum subgraphs, walks of length k, Sach’s subgraphs), fingerprints (MACCs, E-state and substructure fingerprints) and atomic contributions (Ghose and Crippen atom-types for hydrophobicity and refractivity) for F generation. The events are intended to capture diverse information by the generation or search of different kinds of substructures from the graph representation of a molecule. The discrete derivative over duplex atom relations are calculated for each event, and the resulting derivatives, local vertex invariants (LOVIs) are finally obtained. These LOVIs are subsequently employed as the basis for the calculation of global and local indices over groups of atoms (heteroatoms, halogens, methyl carbons, etc.), by using norms, means, statistics and classical algorithms as aggregator (fusion) operators. These indices were implemented in our house software DIVATI (Derivative Type Indices, a new module of TOMOCOMDCARDD system). DIVATI provides a friendly and cross-platform graphical user interface, developed in the Java programming language and is freely available at: http: //www.tomocomd.com. Factor analysis shows that the presented events are rather orthogonal and collect diverse information about the chemical structure. Finally, QSPR models were built to describe the logP and logK of 34 furylethylenes derivatives using the eleven events. Generally, the equations obtained according to these events showed high correlations, with the Sach’s sub-graphs and Multiplicity events showing the best behavior in the description of logK (Q2LOO value of 99.06%) and logP (Q2LOO value of 98.1%), respectively. These results show that these new eventbased indices constitute a powerful approach for chemoinformatics studies. © 2016 Bentham Science Publishers.carbon, 7440-44-0; FuransRecurso electrónicoapplication/pdfengBentham Science Publishers B.V.http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/restrictedAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_16echttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84995975328&doi=10.2174%2f1381612822666160610114148&partnerID=40&md5=32f7bc1daa4fe35762dd2b97589470b4Generalized molecular descriptors derived from event-based discrete derivativeinfo:eu-repo/semantics/reviewinfo:eu-repo/semantics/publishedVersionArtículo de revisiónhttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_efa0Atom-based derivative indexDiscrete derivativeDIVATIEvent criterionFingerprintFrequency matrixPCAQSAR/QSPRTOMOCOMD-CARDDCarbonHalogenFuran derivativeAlgorithmAtomChemical structureComputer interfaceControlled studyFactor analysisHydrophobicityMolecular biologyPriority journalQuantitative structure property relationReviewAlgorithmChemical modelChemistrySoftwareAlgorithmsFuransModels, ChemicalSoftwareMartínez-Santiago O.Cabrera R.M.Marrero-Ponce Y.Barigye S.J.Le-Thi-Thu H.Torres, JavierZambrano C.H.Yaber Goenaga, IvánCruz-Monteagudo, M.López Y.M.Giménez F.P.Torrens, F.Todeschini, R., (2009) Consonni, 5. , Molecular Descriptors for Chemoinformatics. 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Modeling Dispersive and Hydrophobic Interactions (1987) J Chem Inf Comput Sci, 27, pp. 21-35Diudea, M.V., (2001) QSPR/QSAR Studies by Molecular Descriptors, , Huntington, N.Y: Nova ScienceMoldovan, C.D., Diudea, M.V., Costescu, A., Katona, G., Applicationt o QSAR studies of 2-furylethylene derivatives (2008) J Math ChemEstrada, E., (2001) 3D Connectivity Indices in QSPR/QSAR Studies. J Chem Inf Comput Sci, 41, pp. 791-797(2004) Mobydigs, , 1.0 ed. Milano, ItalyTulsa, I., STATISTICA. Version. 8.0 Ed: StatsoftMarrero-Ponce, Y., Martinez-Albelo, E.R., Casanola-Martin, G.M., Bond-based linear indices of the non-stochasitic and stochastic edge-adjacency matrix. 1. Theory and modeling of chemphys properties of organic molecules (2009) Mol Divers, 14, pp. 731-753Basilevsky, A., (1994) Statistical Factor Analysis and Related MethodsFrank, I.E., Friedman, J.H., (1993) Technometrics, 35, pp. 109-135http://purl.org/coar/resource_type/c_dcae04bcTHUMBNAILMiniProdInv.pngMiniProdInv.pngimage/png23941https://repositorio.utb.edu.co/bitstream/20.500.12585/9005/1/MiniProdInv.png0cb0f101a8d16897fb46fc914d3d7043MD5120.500.12585/9005oai:repositorio.utb.edu.co:20.500.12585/90052023-05-26 13:49:18.217Repositorio Institucional UTBrepositorioutb@utb.edu.co |