Pharmacoinformatics Approaches for Target Fishing and Modulation of Non-Small Cell Lung Carcinoma (NSCLC)

Abstract

Lung cancer is one of the leading causes of cancer death in the world and overall, NSCLC accounts for the 85% of all lung cancer cases. However, overexpression of certain nodes gene products such as EGFR, AKT, RAS, and NEU3 in lungs cancer has been known to promote cell proliferation and cell motility. It has been reported recently that overexpression of NEU3 plays a crucial role in NSCLC through activation of RAS in ERK pathway which results in apoptosis suppression and cell motility and also enhances EGFR activity thus, activating EGFR downstream pathways leading towards that may leads to NSCLC. However, the Akt pathway is also hyper-activated upon NEU3 overexpression, but already existing inhibitors of EGFR such as gefitinib only decreases the (and not to abolish) activation of AKT pathway. Hence, NEU3 can act directly on the ERK pathway and indirectly on the Akt pathway through EGFR. Therefore, NEU3 could be one of the potential targets for the treatment of NSLC. Therefore, in present study pharmacoinformatics approaches has been applied to elucidate the 3D structural features of NEU3 and EGFR modulators their probable binding conformation for NSCLC therapy. In the current project, binding hypothesis of NEU3 and EGFR has been proposed by already known inhibitors of NEU3 and EGFR through molecular docking studies. The SAR study of NEU3 (class A) compounds revealed, acetamide dihydropyran carboxylic acid derivatives s important for achieving the basic interaction/activity of the compound, whereas, benzoic acid derivatives is responsible for differences in activity. Moreover, strong hydrogen bond and weak hydrophobic interactions with Glu410 and Trp126 for NEU3 modulators are critical and mainly responsible for the high inhibitory potency of the compounds. For EGFR, the strong hydrogen bond interactions with Asp831, Asn818 and Lys702, these interactions were consistently present and contribute positively towards the inhibitory activity. Moreover, for EGFR, compounds with smaller molecular weight shows optimal fit into the binding cavity. Whereas, least inhibitory potency is due to the presence of bulky groups that are exposed to the side chain of the protein and may cause steric hindrance. In addition, the interactions for the highly active compounds of NEU3 and EGFR remain stable after MD simulations. In addition, predictive models (decision tree and ANN) have been developed against EGFR with accuracy of greater than 80%. Thus, the results suggested that Hueckel theory, partial Abstract xii charge and radius are identified as the most critical feature for accuracy of the predicted model. Overall, the project could pave the way towards the identification of new leads with improved pharmacological profiles against NSCLC.