Double focus in the modelling of anti-influenza properties of 2-iminobenzimidazolines: pharmacology and toxicology

ABSTRACT

Influenza affects millions of people globally and the appearance of drug-resistant strains is an ongoing problem. Therefore, this work reports the development of quantitative structure-activity relationship (QSAR) models to predict some biological properties of new 2-iminobenzimidazoline candidates for the treatment of the flu. A series of 2-iminobenzimidazoline derivatives with experimentally available values for cytotoxicity (pCC₅₀) and anti-influenza activity (pIC₅₀) was used for multivariate image analysis applied to QSAR (MIA-QSAR). The models were vigorously validated according to the best practices in QSAR and the chemical features responsible for the response variables were analysed based on MIA-plots, which assess the PLS regression coefficients and variable importance in projection scores. MIA descriptors encoding atomic properties (van der Waals radius and electronegativity) were capable of properly modelling the pCC₅₀ and pIC₅₀ data. The internally and externally validated models were used to predict the selectivity indexes (SI = pCC₅₀/pIC₅₀) of unprecedented analogues, which were designed upon analysis of the MIA-plots that show the substituent groups most affecting the biological data and by the combination of substructures of selected molecules. At least three promising anti-influenza candidates could be proposed from the predictive MIA-QSAR models.

KEYWORDS:

• MIA-qsar
• influenza
• 2-iminobenzimidazolines
• antiviral activity
• cytotoxicity

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental data for this article can be accessed at: https://doi.org/10.1080/1062936X.2021.1950832

Additional information

Funding

The authors are thankful to Coordenação de Aperfeiçoamento de Pessoal de Nível Superior CAPES [funding code 001]; Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq [grant number 301371/2017-2]; and Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG) for financial support of this research.