In silico prediction of the mutagenicity of nitroaromatic compounds using correlation weights of fragments of local symmetry

Copyright © 2023 Elsevier B.V. All rights reserved..

Most quantitative structure-property/activity relationships (QSPRs/QSARs) techniques involve using different programs separately for generating molecular descriptors and separately for building models based on available descriptors. Here, the capabilities of the CORAL program are evaluated. A user of the program should apply as the basis for models the representation of the molecular structure by means of the simplified molecular input-line entry system (SMILES) as well as experimental data on the endpoint of interest. The local symmetry of SMILES is a novel composition of symmetrically represented symbols, which are three 'xyx', four 'xyyx', or five symbols 'xyzyx'. We updated our CORAL software using this optimal, new flexible descriptor, sensitive to the symmetric composition of a specific part of the molecule. Computational experiments have shown that taking account of these attributes of SMILES can improve the predictive potential of models for the mutagenicity of nitroaromatic compounds. In addition, the above computational experiments have confirmed the advantage of using the index of ideality of correlation (IIC) and the correlation intensity index (CII) for Monte Carlo optimization of the correlation weights for various attributes of SMILES, including the local symmetry. The average value of the coefficient of determination for the validation set (five different models) without fragments of local symmetry is 0.8589 ± 0.025, whereas using fragments of local symmetry improves this criterion of the predictive potential up to 0.9055 ± 0.010.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:891

Enthalten in:

Mutation research. Genetic toxicology and environmental mutagenesis - 891(2023) vom: 07. Okt., Seite 503684

Sprache:

Englisch

Beteiligte Personen:

Toropov, Andrey A [VerfasserIn]
Toropova, Alla P [VerfasserIn]
Roncaglioni, Alessandra [VerfasserIn]
Benfenati, Emilio [VerfasserIn]

Links:

Volltext

Themen:

CORAL software
Journal Article
Local symmetry
Monte Carlo method
Mutagenicity TA98
QSAR
SMILES

Anmerkungen:

Date Revised 28.09.2023

published: Print-Electronic

Citation Status Publisher

doi:

10.1016/j.mrgentox.2023.503684

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM362663637