Molecular docking studies shows tivozanib and lapatinib as potential inhibitors of EML4-ALK translocation mediated fusion protein in non small cell lung cancer



Vijayalakshmi Ramshankar1*, Subha Yegnaswamy2, Kumarasamy P2 & Krishnamurthy Arvind3



1Department of Preventive Oncology, Cancer Institute (WIA), Adyar, Chennai; 2Department of Bioinformatics, Madras Veterinary College, Vepery, Chennai; 3Department of Surgical Oncology, Cancer Institute (WIA), Adyar, Chennai


Email; *Corresponding authors


Article Type




Received October 03, 2014; Revised October 22, 2014; Accepted October 22, 2014; Published October 30, 2014



Identification of activating mutations in non-small cell lung cancers (NSCLC) has been a focus in recent years. This led to successful evidence of using tyrosine kinase inhibitors (TKIs) over the standard platinum doublet based chemotherapy as the first line treatment in the metastatic setting.The rearrangements of fusion protein EML4-ALK in NSCLC lead to the use of crizotinib for this class of tumors. Preclinical and Phase 1 clinical studies show that ceritinib is more effective against both crizotinib sensitive and resistant tumors. Although robust responses to crizotinib are observed in NSCLC harboring ALK mutations, majority of tumors eventually become resistant, posing a major challenge in treatment course. Thus, there is a need for the identification and development of second-generation of ALK inhibitors. Computer aided molecular docking data show Tivozanib and Lapatinib bind EML4-ALK with high score. Tivozanib is in clinical trials for renal cell cancer and Lapatinib is a known dual tyrosine kinase inhibitor effective in breast cancer patients with HER2 over-expression. Additional data on these compounds for use in EML4-ALK positive NSCLC will provide evidence for use in patients treated with crizotinib. Data shows the importance of computer aided molecular docking in developing candidates with improved activity for further consideration in vitro and in vivo validation.



Ramshankar  et al. Bioinformation 10(10): 658-663 (2014)

Edited by

P Kangueane






Biomedical Informatics



This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.