3D-QSAR study on the DYRK1A inhibitors and design of new compounds by CoMFA and CoMSIA methods

In recent years, drug design for specific diseases has been of great importance for researchers. In this study, 3D-QSAR modeling was used on a series of 1,5-naphthyridine derivatives in order to design new DYRK1A inhibitors as anti-diabetes. After dividing the data set to the training and test sets, the training set was used to generate statistically significant CoMFA (r2cv = 0.376, r2ncv = 0.980) and CoMSIA (r2cv = 0.365, r2ncv = 0.783) models based on the common substructure-based alignment. Furthermore, a set of 9 compounds was created for testing the ability of the CoMFA and CoMSIA models to accurately predict compound activity. Also, the application of the CoMFA focus model provided better results (r2cv = 0.566, r2ncv = 0.988). The design of new analogues based on naphthyridines as DYRK1A inhibitors was carried out using the knowledge obtained from the contours of the CoMFA focus model. Contours were used to identify structural features of this series of analogs that are related to biological activity. Six new designed compounds, in this group of substances, showed stronger DYRK1A inhibitory activity.

3D-QSAR study on the DYRK1A inhibitors and design of new compounds by CoMFA and CoMSIA methods Keywords:

3D-QSAR , CoMFA , CoMSIA , DYRK1A , Anti-diabetes