3D-QSAR analysis of pyrimidine derivatives as AXL kinase inhibitors as anticancer agents

4Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.

Abstract

AXL kinase receptor belongs to the TAM family of receptor tyrosine kinases (RTKs). Different types of cancer namely breast cancer, osteosarcoma, acute myeloid leukemia, colorectal cancer and non-small cell lung cancer (NSCLC) manifest overexpression of AXL receptor. Moreover, AXL kinase overexpression leads to tumor angiogenesis & resistance to chemotherapeutic agents and reduces the antitumor immune response. Therefore, AXL kinase has emerged as the potential and attractive target for the treatment of cancer. The present study is based on the correlation between the structural parameter and biological activity of the compounds using the 3D-QSAR technique. In this technique, pyrimidine derivatives and their inhibitory activity against AXL kinase receptor were chosen as independent and dependent variables respectively. Based on the investigation, the structural requirements for AXL kinase inhibition were recognized. Here, CoMFA and CoMSIA analysis were used for the execution of the 3D-QSAR model. The training and the test set pyrimidine derivatives were used for the generation and validation of QSAR model respectively. Dataset alignment was performed using the lowest energy conformer of the most active compound. CoMFA, as well as CoMSIA, model have encouraging values of the cross-validation coefficient (q2) 0.700 and 0.622 and conventional correlation coefficient (r2) 0.911 and 0.875 independently. Furthermore, values of rpred2 were obtained as 0.709 and 0.668 respectively. Outcomes of the QSAR models and contour maps may be used for discovery of new AXL kinase inhibitors as potent anticancer agents.

Cite

CITATION STYLE

APA

Modi, S. J., & Kulkarni, V. M. (2018). 3D-QSAR analysis of pyrimidine derivatives as AXL kinase inhibitors as anticancer agents. Journal of Applied Pharmaceutical Science, 8(11), 15–27. https://doi.org/10.7324/JAPS.2018.81103

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free