An integrated molecular modeling approach for in silico design of new tetracyclic derivatives as ALK inhibitors

Abstract

Anaplastic lymphoma kinase (ALK), a promising therapeutic target for treatment of human cancers, is a receptor tyrosine kinase that instigates the activation of several signal transduction pathways. In the present study, in silico methods have been employed in order to explore the structural features and functionalities of a series of tetracyclic derivatives displaying potent inhibitory activity toward ALK. Initially docking was performed using GLIDE 5.6 to probe the bioactive conformation of all the compounds and to understand the binding modes of inhibitors. The docking results revealed that ligand interaction with Met 1199 plays a crucial role in binding of inhibitors to ALK. Further to establish a robust 3D-QSAR model using CoMFA and CoMSIA methods, the whole dataset was divided into three splits. Model obtained from Split 3 showed high accuracy ( of 0.700 and 0.682, of 0.971 and 0.974, of 0.673 and 0.811, respectively for CoMFA and CoMSIA). The key structural requirements for enhancing the inhibitory activity were derived from CoMFA and CoMSIA contours in combination with site map analysis. Substituting small electronegative groups at Position 8 by replacing either morpholine or piperidine rings and maintaining hydrophobic character at Position 9 in tetracyclic derivatives can enhance the inhibitory potential. Finally, we performed molecular dynamics simulations in order to investigate the stability of protein ligand interactions and MM/GBSA calculations to compare binding free energies of co-crystal ligand and newly designed molecule N1. Based on the coherence of outcome of various molecular modeling studies, a set of 11 new molecules having potential predicted inhibitory activity were designed.

• Anaplastic lymphoma kinase
• molecular dynamics simulation
• site map analysis
• molecular docking
• 3D-QSAR

Acknowledgements

We greatly acknowledge Tripos Inc., USA and Schrödinger LLC, New York for providing the software. This research was made possible through grants from DST-SERB (SB/EMEQ-004/2013), UGC (42–233/2013(SR)), and UGC-UPE (UGC/UPE/FAR/OU/2014) New Delhi, India. The author Saikiran Reddy Peddi (IF150172) would like to thank DST for providing Inspire Fellowship.

Declaration of interest

The authors do not have any conflict of interest to declare.