In Silico Design and Computational Characterization of a Multi-Epitope Immunotherapeutic Candidate Targeting MYC and CTNNB1 for Hepatocellular Carcinoma
Kushal Wangdale *
Department of Bioinformatics, Amplikon Biosystems, Hyderabad, Telangana, India.
Nannaparaju Vaishnavi
Department of Biochemistry, Aurora’s Degree & PG College, Chikkadpally, Hyderabad, Telangana, India.
*Author to whom correspondence should be addressed.
Abstract
Aims: To design, validate, and partially express a novel large molecule immunotherapeutic candidate targeting MYC and CTNNB1, key oncogenes implicated in hepatocellular carcinoma (HCC), using in silico computational approaches.
Study Design: In Silico Studies using Computational tools in bioinformatics.
Place and Duration of Study: Amplikon Biosystems and Aurora’s Degree&PG College, Hyderabad, Telangana, India; April–June 2025.
Methodology: The methodology involved retrieving MYC and β-catenin protein sequences from UniProt, followed by prediction and prioritization of B- and T-cell epitopes using IEDB and NetMHCpan. Selected epitopes were linked with suitable adjuvants and modeled into a 3D structure using SWISS-MODEL, with validation through Ramachandran plot analysis. Codon optimization was carried out for expression in E. coli using the pET-28a vector. The designed construct was then assessed for allergenicity, toxicity, aggregation, and physicochemical properties, while molecular docking with ClusPro confirmed binding interactions with the target oncogenic proteins.
Results: The designed large molecule immunotherapeutic candidate showed promising characteristics in silico. Structural validation through the Ramachandran plot confirmed that most residues occupied favorable regions, indicating reliable folding and stereochemical quality. Safety assessments revealed the protein to be non-toxic, non-allergenic, and soluble, suggesting suitability for therapeutic use. Physicochemical evaluation predicted reasonable stability with an acceptable half-life across biological systems. Immunogenicity analysis classified the construct as a probable antigen, supporting its potential to elicit an immune response. Furthermore, molecular docking demonstrated strong and stable interactions with MYC and β-catenin, confirming the intended binding efficacy. Collectively, these results highlight the construct’s potential as a candidate therapeutic for hepatocellular carcinoma, warranting further in vitro validation.
Conclusion: This study successfully designed a novel large molecule immunotherapeutic candidate targeting MYC and β-catenin, two critical oncogenic drivers of hepatocellular carcinoma, using in silico approaches. The construct demonstrated favorable properties, including proper structural stability, non-toxicity, non-allergenicity, and strong immunogenic potential. Docking studies further confirmed its ability to form stable interactions with the target proteins, supporting its therapeutic relevance. While experimental validation --in HCC cell lines remains the next step, the computational findings provide a strong proof-of-concept and establish a reliable workflow for rational design of targeted biologics against complex cancer pathways.
Keywords: Hepatocellular carcinoma (HCC), large molecule therapeutics, In silico drug design, MYC oncogene, β-catenin (CTNNB1), molecular docking, codon optimization