Searching for Potential Novel BCR-ABL Tyrosine Kinase Inhibitors Through G-QSAR and Docking Studies of Some Novel 2-Phenazinamine Derivatives

Abstract

Background: The computational studies on 2-phenazinamines with their protein targets have been carried out to design compounds with potential anticancer activity and selectivity over specific BCR-ABL Tyrosine kinase. Methods: This has been achieved through G-QSAR and molecular docking studies. Computational chemistry was done by using VLife MDS 4.3 and Autodock 4.2. 2D and structures of ligands were drawn by using Chemdraw 2D Ultra 8.0 and were converted into 3D. These were optimized by using semi-empirical method called MOPAC. The protein structure was downloaded as PDB file from RCSC protein data bank. PYMOL was used for studying the binding interactions. The G-QSAR models generated were found to possess training (r2=0.8074), cross-validation (q2=0.6521), and external validation (pred_r2=0.5892) which proved their statistical significance. Accordingly, the newly designed series of 2-phenazinamines viz., 3-chloro-4-aryl-1-(phenazin-7-yl) azetidin-2-ones (4a-4e) were subjected to wet lab synthesis. Alternatively, docking st udies were also conducted which showed binding interactions of some derivatives with > 30% higher binding energy values than the standard anticancer drug imatinib. The lower energy values obtained for these derivatives indicate energetically favorable interaction with protein binding site as compared to standard imatinib. Results: G-QSAR and molecular docking studies predicted better anticancer activity for the synthesized azitidine derivatives of 2-phenazinamines (4a-4e) as compared to standard drug. Conclusion: It is therefore surmised that the molecular manipulations at appropriate sites of these derivatives suggested by structure activity relationship data will prove to be beneficial in raising anticancer potential.

Deciphering a Pharmacophore Network: A Case Study Using BCR-ABL Data

“…Classical approaches to this type of structure−activity relationship (SAR) study typically begin with the definition of physicochemical, topological, or topographical descriptors associated with the chemical dataset of interest. This type of analysis has been performed using a BCR-ABL dataset, as described by Kyaw Zin et al 5 in their study of imatinib derivatives and Kale et al 6 who reported on interactions with 2-phenazinamine derivatives. The descriptors can also be encoded into molecular fingerprints.…”

Advances in Phenazines over the Past Decade: Review of Their Pharmacological Activities, Mechanisms of Action, Biosynthetic Pathways and Synthetic Strategies

“…In addition, the score of imatinib was −8.7 kcal/mol. All the computational data showed 2-phenazinamine derivatives would be inhibitors against BCR-ABL tyrosine kinase and needed to be further investigated [25]. 4.4.7.…”

“…According to reports in recent years, phenazine derivatives possessed antiproliferative activities against various cancer cell lines [18][19][20][21]. Additionally, phenazine derivatives were candidates to be developed as inhibitors of disease-related targets and reported to show activity of inhibition to multiple enzymes [22][23][24][25]. Although phenazine derivatives possessed a broad activity spectrum, the in-depth study was hindered due to the limited resource.…”