CRISPR-CAS 9 Modeling of ALK Resistance Mutations Harbouring the G1202R/L1196M

Anaplastic lymphoma kinase (ALK) is a clinically important therapeutic target in ALK-positive cancers, particularly non-small cell lung cancer (NSCLC). Although ALK tyrosine kinase inhibitors (ALK-TKIs) initially produce substantial clinical benefit, long-term efficacy is frequently compromised by the emergence of resistance mutations within the kinase domain. Among these, the solvent-front mutation G1202R and the gatekeeper mutation L1196M, especially when present as a compound mutation, pose significant challenges by markedly reducing inhibitor binding and therapeutic response. The present study aims to systematically investigate the structural and functional consequences of ALK G1202R and G1202R/L1196M resistance mutations using an integrated computational structural biology and CRISPR-Cas9 genome-editing framework. High-resolution crystal structures of mutant ALK in complex with the next-generation inhibitor NVL-655 (PDB ID: 9GBE) were analysed using PyMOL-based visualisation, B-factor analysis to assess conformational flexibility, MMDB annotations, and COSMIC-3D mutation mapping to identify mutation hotspots near ligand-binding regions. In parallel, allele-specific CRISPR-Cas9 single-guide RNAs were designed using E-CRISP and CHOPCHOP to enable precise modeling of these resistance mutations with minimal off-target effects. Structural analyses revealed that the G1202R mutation induces substantial steric hindrance and electrostatic alterations at the ATP-binding pocket, while the L1196M mutation stabilizes an active kinase conformation. Together, these changes destabilize inhibitor interactions and significantly impair binding of earlier-generation ALK-TKIs. In contrast, next-generation inhibitors such as NVL-655 and TPX-0131 demonstrate improved accommodation of the altered binding pocket, consistent with emerging preclinical and clinical observations. Overall, this study provides mechanistic insight into ALK resistance evolution by integrating structural modeling with genome-editing strategies. The proposed framework provides a robust platform for studying compound resistance mutations and supports the rational design and validation of next-generation ALK inhibitors and CRISPR-based therapeutic strategies for ALK-driven cancers that are resistant to these agents.