Articles producció científica> Enginyeria Química

Ligand-based virtual screening using graph edit distance as molecular similarity measure

  • Datos identificativos

    Identificador: imarina:5133313
    Autores:
    Garcia-Hernandez C, Fernández A, Serratosa F
    Resumen:
    Copyright © 2019 American Chemical Society. Extended reduced graphs provide summary representations of chemical structures using pharmacophore-type node descriptions to encode the relevant molecular properties. Commonly used similarity measures using reduced graphs convert these graphs into 2D vectors like fingerprints, before chemical comparisons are made. This study investigates the effectiveness of a graph-only driven molecular comparison by using extended reduced graphs along with graph edit distance methods for molecular similarity calculation as a tool for ligand-based virtual screening applications, which estimate the bioactivity of a chemical on the basis of the bioactivity of similar compounds. The results proved to be very stable and the graph editing distance method performed better than other methods previously used on reduced graphs. This is exemplified with six publicly available data sets: DUD-E, MUV, GLL&GDD, CAPST, NRLiSt BDB, and ULS-UDS. The screening and statistical tools available on the ligand-based virtual screening benchmarking platform and the RDKit were also used. In the experiments, our method performed better than other molecular similarity methods which use array representations in most cases. Overall, it is shown that extended reduced graphs along with graph edit distance is a combination of methods that has numerous applications and can identify bioactivity similarities in a structurally diverse group of molecules.
  • Otros:

    Autor según el artículo: Garcia-Hernandez C, Fernández A, Serratosa F
    Departamento: Enginyeria Informàtica i Matemàtiques Enginyeria Química
    Autor/es de la URV: Fernández Sabater, Alberto / GARCIA HERNANDEZ, CARLOS JESÚS / Serratosa Casanelles, Francesc d'Assís
    Palabras clave: Validation Sets Metrics Diversity analysis Design Descriptor Chemistry Chemical-structures
    Resumen: Copyright © 2019 American Chemical Society. Extended reduced graphs provide summary representations of chemical structures using pharmacophore-type node descriptions to encode the relevant molecular properties. Commonly used similarity measures using reduced graphs convert these graphs into 2D vectors like fingerprints, before chemical comparisons are made. This study investigates the effectiveness of a graph-only driven molecular comparison by using extended reduced graphs along with graph edit distance methods for molecular similarity calculation as a tool for ligand-based virtual screening applications, which estimate the bioactivity of a chemical on the basis of the bioactivity of similar compounds. The results proved to be very stable and the graph editing distance method performed better than other methods previously used on reduced graphs. This is exemplified with six publicly available data sets: DUD-E, MUV, GLL&GDD, CAPST, NRLiSt BDB, and ULS-UDS. The screening and statistical tools available on the ligand-based virtual screening benchmarking platform and the RDKit were also used. In the experiments, our method performed better than other molecular similarity methods which use array representations in most cases. Overall, it is shown that extended reduced graphs along with graph edit distance is a combination of methods that has numerous applications and can identify bioactivity similarities in a structurally diverse group of molecules.
    Áreas temáticas: Química Medicina ii Medicina i Materiais Library and information sciences Interdisciplinar General chemistry General chemical engineering Farmacia Ensino Engenharias ii Computer science, interdisciplinary applications Computer science, information systems Computer science applications Ciencias sociales Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência da computação Chemistry, multidisciplinary Chemistry, medicinal Chemistry (miscellaneous) Chemistry (all) Chemical engineering (miscellaneous) Chemical engineering (all) Biotecnología Astronomia / física
    Acceso a la licencia de uso: thttps://creativecommons.org/licenses/by/3.0/es/
    ISSN: 15499596
    Direcció de correo del autor: francesc.serratosa@urv.cat alberto.fernandez@urv.cat
    Identificador del autor: 0000-0001-6112-5913 0000-0002-1241-1646
    Página final: 1421
    Fecha de alta del registro: 2023-02-18
    Volumen de revista: 59
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.8b00820#
    Referencia al articulo segun fuente origial: Journal Of Chemical Information And Modeling. 59 (4): 1410-1421
    Referencia de l'ítem segons les normes APA: Garcia-Hernandez C, Fernández A, Serratosa F (2019). Ligand-based virtual screening using graph edit distance as molecular similarity measure. Journal Of Chemical Information And Modeling, 59(4), 1410-1421. DOI: 10.1021/acs.jcim.8b00820
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    DOI del artículo: 10.1021/acs.jcim.8b00820
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2019
    Página inicial: 1410
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Chemical Engineering (Miscellaneous),Chemistry (Miscellaneous),Chemistry, Medicinal,Chemistry, Multidisciplinary,Computer Science Applications,Computer Science, Information Systems,Computer Science, Interdisciplinary Applications,Library and Information Sciences
    Validation
    Sets
    Metrics
    Diversity analysis
    Design
    Descriptor
    Chemistry
    Chemical-structures
    Química
    Medicina ii
    Medicina i
    Materiais
    Library and information sciences
    Interdisciplinar
    General chemistry
    General chemical engineering
    Farmacia
    Ensino
    Engenharias ii
    Computer science, interdisciplinary applications
    Computer science, information systems
    Computer science applications
    Ciencias sociales
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência da computação
    Chemistry, multidisciplinary
    Chemistry, medicinal
    Chemistry (miscellaneous)
    Chemistry (all)
    Chemical engineering (miscellaneous)
    Chemical engineering (all)
    Biotecnología
    Astronomia / física
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