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3D-QSAR study of c-Src kinase inhibitors based on docking
1Key Laboratory of radiopharmaceuticals of Ministry of Education, College of Chemistry, Beijing Normal University, Beijing, China.
Abstract:
Cancer is a significant world health problem for which efficient therapies are in urgent demand. c-Src has emerged as an attractive target for drug discovery efforts toward antitumor therapies. Toward this target several series of c-Src inhibitors that showed activity in the assay have been reported. In this article, 3D-QSAR models have been built with 156 anilinoquinazoline and quinolinecarbonitrile derivative inhibitors by using CoMFA and CoMSIA methods. These studies indicated that the QSAR models were statistically significant with high predictabilities (CoMFA model, q(2) = 0.590, r(2) = 0.855; CoMSIA model, q(2) = 0.538, r(2) = 0.748). The details of c-Src kinase/inhibitor binding interactions in the crystal structure of complex provided new information for the design of new inhibitors. As a result, docking simulations were also conducted on the series of potent inhibitors. The flexible docking method, which was performed by the DOCK program, positioned all of the inhibitors into the active site to determine the probable binding conformation. The CoMFA and CoMSIA models based on the flexible docking conformations also yielded statistically significant and highly predictive QSAR models (CoMFA model, q(2) = 0.507, r(2) = 0.695; CoMSIA model, q(2) = 0.463, r(2) = 0.734). Our models would offer help to better comprehend the structure-activity relationships that exist for this class of compounds and also facilitate the design of novel inhibitors with good chemical diversity.
Insights
This study developed 3D-QSAR models for c-Src inhibitors, crucial for cancer therapy. The models accurately predict inhibitor activity, aiding in the design of novel anticancer drugs.
Area of Science:
- Medicinal Chemistry
- Computational Chemistry
- Drug Discovery
Background:
- Cancer remains a major global health challenge, necessitating novel therapeutic strategies.
- The c-Src kinase is a promising target for developing new anticancer drugs.
- Existing research has identified several series of c-Src inhibitors with demonstrated activity.
Purpose of the Study:
- To build and validate 3D-QSAR (Quantitative Structure-Activity Relationship) models for anilinoquinazoline and quinolinecarbonitrile derivative inhibitors of c-Src.
- To explore structure-activity relationships and guide the design of new, potent c-Src inhibitors.
Main Methods:
- Utilized Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) to develop 3D-QSAR models.
- Employed docking simulations, including a flexible docking approach with the DOCK program, to determine inhibitor binding conformations.
- Validated models using statistical parameters like q² (predictivity) and r² (goodness of fit).
Main Results:
- Developed statistically significant 3D-QSAR models with high predictive power (CoMFA: q²=0.590, r²=0.855; CoMSIA: q²=0.538, r²=0.748).
- Docking simulations provided insights into c-Src kinase-inhibitor binding interactions.
- QSAR models based on flexible docking conformations also showed significant predictive ability (CoMFA: q²=0.507, r²=0.695; CoMSIA: q²=0.463, r²=0.734).
Conclusions:
- The developed QSAR models effectively elucidate structure-activity relationships for c-Src inhibitors.
- These models serve as valuable tools for the rational design of novel anticancer agents with improved efficacy and diversity.
- The findings contribute to the ongoing efforts in discovering efficient therapies for cancer.
