23 DOI: https://doi.org/10.1016/j.jgeb.2026.100708 English eng Vimala, Poornima Baskar Contributor <p><span style="color: rgb(31, 31, 31); font-family: ElsevierGulliver, Georgia, "Times New Roman", Times, STIXGeneral, "Cambria Math", "Lucida Sans Unicode", "Microsoft Sans Serif", "Segoe UI Symbol", "Arial Unicode MS", serif, sans-serif; font-size: 16px;">Epithelial–mesenchymal transition (EMT) is a fundamental driver of cancer invasion, metastasis, and therapeutic resistance, mediated by dynamic switching between E-cadherin (CDH1) and N-cadherin (CDH2). Although cadherins are central regulators of EMT, current therapeutic strategies rarely exploit EMT-state–specific cadherin dependencies. In this study, we present a structure-driven, EMT-aware computational framework to repurpose and engineer colicins as cadherin-selective anti-metastatic biologics. Pan-cancer transcriptomic profiling across thirty-three tumor types revealed distinct CDH1- and CDH2-dominant EMT landscapes, providing a rational basis for receptor-informed targeting. stereo chemically validated structures of Colicin E1 and Colicin E2 were subjected to stability-guided mutagenesis using FoldX, followed by protein–protein docking and atomistic molecular dynamics simulations with E- and N-cadherin. Docking analyses demonstrated intrinsic cadherin preferences, with Colicin E2 exhibiting stronger affinity for CDH1 and Colicin E1 favouring CDH2, mirroring EMT-associated cadherin switching. Molecular dynamics simulations further confirmed these trends, revealing stable complex formation, reduced backbone deviation, sustained interfacial contacts, and distinct residue-level flexibility profiles in preferred colicin–cadherin pairs. Structure-guided mutations significantly enhanced binding stability and specificity, identifying Colicin E2 mutant A579E as the most optimized variant, characterized by improved docking scores, reduced conformational fluctuations, and persistent E-cadherin engagement throughout simulations. Compared with prior EMT-targeting approaches, this work uniquely integrates transcriptomic context with structure-guided protein engineering to achieve cadherin-state selectivity rather than broad inhibition. Collectively, this study establishes a novel computational paradigm for EMT-state-guided biologic design and provides a predictive foundation for future experimental validation, cadherin-resolved cancer stratification, and translational development of precision anti-metastatic protein therapeutics in diverse solid tumor contexts clinically.</span></p> Elsevier June 2026 pdf Journal of Genetic Engineering and Biotechnology Computational and Structure-Guided engineering of colicin E1 and E2 for EMT -driven cadherin selectivity in cancer mixed material Elsevier