The searching for agents for Alzheimer’s disease treatment via the system of self-consistent models

Abstract

Robust quantitative structure-activity relationships (QSARs) for hBACE-1 inhibitors (pIC50) for a large database (n = 1706) are established. New statistical criteria of the predictive potential of models are suggested and tested. These criteria are the index of ideality of correlation (IIC) and the correlation intensity index (CII). The system of self-consistent models is a new approach to validate the predictive potential of QSAR-models. The statistical quality of models obtained using the CORAL software (http://www.insilico.eu/coral) for the validation sets is characterized by the average determination coefficient R²_v= 0.923, and RMSE = 0.345. Three new promising molecular structures which can become inhibitors hBACE-1 are suggested.

Keywords:

• QSAR
• hBACE-1
• Alzheimer's disease
• CORAL software
• index of ideality of correlation
• correlation intensity index

Acknowledgments

AAT and APT are grateful to the EC project LIFE-CONCERT contract [LIFE17 GIE/IT/000461] for the financial support.

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability statement

The data used in this work and developed models are freely available Supplementary materials section.