In Silico Prediction of Eye Irritation Using Hansen Solubility Parameters and Predicted pKa Values.
Altern Lab Anim
; 51(3): 204-209, 2023 May.
Article
em En
| MEDLINE
| ID: mdl-37184299
ABSTRACT
An in silico method has been developed that permits the binary differentiation between pure liquids causing serious eye damage or eye irritation, and pure liquids with no need for such classification, according to the UN GHS system. The method is based on the finding that the Hansen Solubility Parameters (HSP) of a liquid are collectively important predictors for eye irritation. Thus, by applying a two-tier approach in which in silico-predicted pKa values (firstly) and a trained model based solely on in silico-predicted HSP data (secondly) were used, we have developed, and validated, a fully in silico approach for predicting the outcome of a Draize test (in terms of UN GHS Cat. 1/Cat. 2A/Cat. 2B or UN GHS No Cat.) with high validation set performance (sensitivity = 0.846, specificity = 0.818, balanced accuracy = 0.832) using SMILES only. The method is applicable to pure non-ionic liquids with molecular weight below 500 g/mol, fewer than six hydrogen bond donors (e.g. nitrogen-hydrogen or oxygen-hydrogen bonds) and fewer than eleven hydrogen bond acceptors (e.g. nitrogen or oxygen atoms). Due to its fully in silico characteristics, this method can be applied to pure liquids that are still at the desktop design stage and not yet in production.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Testes de Toxicidade
/
Olho
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Animals
Idioma:
En
Revista:
Altern Lab Anim
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Suécia