Optimal graph-based and simplified molecular input line entry system-based descriptors for quantitative structure-activity relationship analysis of arylalkylaminoalcohols, arylalkenylamines, and arylalkylamines as σ1 receptor ligands

Luisa Quesada-Romero, Karel Mena-Ulecia, Matias Zuñiga, Pedro De-la-Torre, Daniela Rossi, William Tiznado, Simona Collina, Julio Caballero

Resultado de la investigación: Article

2 Citas (Scopus)

Resumen

In this investigation, an optimal description of the structure-activity relationship was done for 59 σ1 receptor ligands including arylalkylaminoalcohols, arylalkenylamines, and arylalkylamines (denoted as RC-33 analogs in this manuscript). We used optimal graph-based (GBD) and Simplified Molecular Input Line Entry System (SMILES)-based (SBD) descriptors as molecular characteristics of the structures to explain the differences in σ1 receptor affinity between the ligands. The best graph-based descriptor model (named HFG-EC0 in the manuscript) included hydrogen-filled molecular graphs using the extended connectivity of zero order (EC0). This model has an average correlation coefficient value for external test set of 0.786 with a better statistics when comparing with the best SBD model. The best SBD model (named SSSk in the manuscript) includes only three SMILES elements SSSk and has an average correlation coefficient value for external test set of 0.726. These models identified the molecular features that contribute to a high σ1 receptor ligand affinity.

Idioma originalEnglish
Páginas (desde-hasta)13-20
Número de páginas8
PublicaciónJournal of Chemometrics
Volumen29
N.º1
DOI
EstadoPublished - 1 ene 2015

Huella dactilar

Quantitative Structure-activity Relationship
Receptor
Descriptors
Ligands
Line
Graph in graph theory
Test Set
Correlation coefficient
Affine transformation
Structure-activity Relationship
Molecular Graph
Model
Hydrogen
Connectivity
Statistics
Analogue
Zero

ASJC Scopus subject areas

  • Analytical Chemistry
  • Applied Mathematics

Citar esto

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abstract = "In this investigation, an optimal description of the structure-activity relationship was done for 59 σ1 receptor ligands including arylalkylaminoalcohols, arylalkenylamines, and arylalkylamines (denoted as RC-33 analogs in this manuscript). We used optimal graph-based (GBD) and Simplified Molecular Input Line Entry System (SMILES)-based (SBD) descriptors as molecular characteristics of the structures to explain the differences in σ1 receptor affinity between the ligands. The best graph-based descriptor model (named HFG-EC0 in the manuscript) included hydrogen-filled molecular graphs using the extended connectivity of zero order (EC0). This model has an average correlation coefficient value for external test set of 0.786 with a better statistics when comparing with the best SBD model. The best SBD model (named SSSk in the manuscript) includes only three SMILES elements SSSk and has an average correlation coefficient value for external test set of 0.726. These models identified the molecular features that contribute to a high σ1 receptor ligand affinity.",
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author = "Luisa Quesada-Romero and Karel Mena-Ulecia and Matias Zu{\~n}iga and Pedro De-la-Torre and Daniela Rossi and William Tiznado and Simona Collina and Julio Caballero",
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Optimal graph-based and simplified molecular input line entry system-based descriptors for quantitative structure-activity relationship analysis of arylalkylaminoalcohols, arylalkenylamines, and arylalkylamines as σ1 receptor ligands. / Quesada-Romero, Luisa; Mena-Ulecia, Karel; Zuñiga, Matias; De-la-Torre, Pedro; Rossi, Daniela; Tiznado, William; Collina, Simona; Caballero, Julio.

En: Journal of Chemometrics, Vol. 29, N.º 1, 01.01.2015, p. 13-20.

Resultado de la investigación: Article

TY - JOUR

T1 - Optimal graph-based and simplified molecular input line entry system-based descriptors for quantitative structure-activity relationship analysis of arylalkylaminoalcohols, arylalkenylamines, and arylalkylamines as σ1 receptor ligands

AU - Quesada-Romero, Luisa

AU - Mena-Ulecia, Karel

AU - Zuñiga, Matias

AU - De-la-Torre, Pedro

AU - Rossi, Daniela

AU - Tiznado, William

AU - Collina, Simona

AU - Caballero, Julio

PY - 2015/1/1

Y1 - 2015/1/1

N2 - In this investigation, an optimal description of the structure-activity relationship was done for 59 σ1 receptor ligands including arylalkylaminoalcohols, arylalkenylamines, and arylalkylamines (denoted as RC-33 analogs in this manuscript). We used optimal graph-based (GBD) and Simplified Molecular Input Line Entry System (SMILES)-based (SBD) descriptors as molecular characteristics of the structures to explain the differences in σ1 receptor affinity between the ligands. The best graph-based descriptor model (named HFG-EC0 in the manuscript) included hydrogen-filled molecular graphs using the extended connectivity of zero order (EC0). This model has an average correlation coefficient value for external test set of 0.786 with a better statistics when comparing with the best SBD model. The best SBD model (named SSSk in the manuscript) includes only three SMILES elements SSSk and has an average correlation coefficient value for external test set of 0.726. These models identified the molecular features that contribute to a high σ1 receptor ligand affinity.

AB - In this investigation, an optimal description of the structure-activity relationship was done for 59 σ1 receptor ligands including arylalkylaminoalcohols, arylalkenylamines, and arylalkylamines (denoted as RC-33 analogs in this manuscript). We used optimal graph-based (GBD) and Simplified Molecular Input Line Entry System (SMILES)-based (SBD) descriptors as molecular characteristics of the structures to explain the differences in σ1 receptor affinity between the ligands. The best graph-based descriptor model (named HFG-EC0 in the manuscript) included hydrogen-filled molecular graphs using the extended connectivity of zero order (EC0). This model has an average correlation coefficient value for external test set of 0.786 with a better statistics when comparing with the best SBD model. The best SBD model (named SSSk in the manuscript) includes only three SMILES elements SSSk and has an average correlation coefficient value for external test set of 0.726. These models identified the molecular features that contribute to a high σ1 receptor ligand affinity.

KW - Arylalkylamine derivates

KW - Optimal descriptors

KW - Quantitative structure-activity relationships

KW - Sigma-1 ligands

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