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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 σ 1 receptor ligands
Author(s) -
QuesadaRomero Luisa,
MenaUlecia Karel,
Zuñiga Matias,
DelaTorre Pedro,
Rossi Daniela,
Tiznado William,
Collina Simona,
Caballero Julio
Publication year - 2015
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.2650
Subject(s) - correlation coefficient , molecular descriptor , graph , test set , molecular model , mathematics , biological system , chemistry , quantitative structure–activity relationship , stereochemistry , combinatorics , statistics , biology
In this investigation, an optimal description of the structure–activity relationship was done for 59 σ 1 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 σ 1 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 SSS k in the manuscript) includes only three SMILES elements SSS k 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 σ 1 receptor ligand affinity. Copyright © 2014 John Wiley & Sons, Ltd.