Computational Design and Comparative Evaluation of Supramolecular Organic Nanocarriers for Targeted CRISPR-Cas12 Delivery in Triple - Negative Breast Cancer

Triple – Negative Breast Cancer (TNBC) is an aggressive, heterogeneous subtype with limited targeted therapies. Although CRISPR-Cas12a ribonucleoprotein (RNP) complexes offer a promising genome editing platform for precision oncology, its clinical translation is largely constrained by the absence of safe, efficient and tumor-specific delivery strategies. Supramolecular organic nanocarriers offer unique advantages including biocompatibility, tunable physicochemical properties and stimuli-responsive cargo release, making them attractive candidates for CRISPR delivery.

This study aims to present a reproducible computational pipeline to prioritize supramolecular organic nanocarriers for targeted delivery of CRISPR-Cas12a RNPs in TNBC.

An integrated computational workflow will be used that includes cancer bioinformatics, CRISPR guide RNA design, molecular modelling and molecular docking. Publicly available transcriptomic datasets will be mined to identify therapeutically relevant, tumor-enriched TNBC gene targets and generate high-specificity CRISPR-Cas12a gRNA using established design tools. Representative supramolecular organic nanocarriers with established potential for CRISPR delivery will be systematically compared based on structural compatibility, targeting potential, physicochemical characteristics and predicted delivery performance.

The study is expected to establish a computational framework for the rational selection of supramolecular organic nanocarriers for targeted delivery of CRISPR-Cas12a in TNBC. This workflow combines bioinformatics and molecular docking offering a reproducible computational strategy for the prioritization of supramolecular organic nanocarriers based on disease-specific genomic targets. This approach enables rational development of CRISPR-Cas12a mediated precision oncology and reduces the need for extensive experimental screening.