Designing of Peptide Based Multi-Epitope Vaccine Construct against Gallbladder Cancer Using Immunoinformatics and Computational Approaches

Abstract

Gallbladder cancer (GBC) is an aggressive and difficult to treat biliary tract carcinoma with a poor survival rate. The aim of this study was to design a peptide-based multi-epitope vaccine construct against GBC using immunoinformatics approaches. Three proteins implicated in the progression of GBC were selected for B and T cell epitope prediction and the designing of the potential vaccine construct. Seven CTL, four HTL and six Bcell epitopes along with a suitable adjuvant were selected and connected using linkers for designing the vaccine construct. The secondary and tertiary models of the designed vaccine were generated and satisfactorily validated. A Ramachandran plot of the final 3D model showed more than 90% of the residues in allowed regions and only 0.4% in disallowed regions. The binding affinity of a vaccine construct with TLR 2, 3 and 4 receptors was assessed through molecular docking and simulation. The average numbers of hydrogen bonds for vaccine-TLR 2, 3 and 4 complexes in the simulation were 15.36, 16.45, and 11.98, respectively, and remained consistent over a 100ns simulation period, which is critical for their function. The results of this study provide a strong basis for further evaluation through in vitro/in vivo experimental validation of the safety and efficacy of the designed vaccine construct.

AutoEpiCollect, a Novel Machine Learning-Based GUI Software for Vaccine Design: Application to Pan-Cancer Vaccine Design Targeting PIK3CA Neoantigens

“…Due to the limited success of PIK3CA-directed treatments, patients with the cancers discussed above could potentially experience improved clinical outcomes through a pancancer epitope vaccine targeting prevalent PIK3CA point mutations. Our study considered various clinical variables based on prior studies that served as primary benchmarks when developing our novel epitope selection process [6,7,26,27]. These variables confirmed that AutoEpiCollect's top predicted epitopes were immunogenic, safe, and stable.…”

Advancing Tolerogenic Immunotherapy: A Multi-Epitope Vaccine Design Targeting the CYP2D6 Autoantigen in Autoimmune Hepatitis Through Immuno-Informatics

“…These tools enable epitope mapping, structural design, and molecular interaction studies critical for effective vaccine development. Leveraging immunoinformatic approaches, numerous vaccines have been successfully developed against various infections and cancers [16][17][18][19][20][21].…”

Design and In Silico Validation of a Novel MZF-1-Based Multi-Epitope Vaccine to Combat Metastatic Triple Negative Breast Cancer

“…In another study, Kumar et al (2022) incorporated the epitopes from L1, E5, E6, and E7 oncoproteins of HPV 16 and HPV 18 to formulate a chimeric peptide-based vaccine to combat cervical cancer [ 18 ]. Dar et al (2022) implemented a reverse vaccinology approach to determine the immunogenic B, CTL, and HTL epitopes from NT5E, ANPEP, and MME proteins, the putative targets for gallbladder cancer (GBC), and developed a robust peptide-based vaccine against GBC [ 19 ]. Importantly, our team successfully developed an immunoinformatics-based peptide vaccine targeting SOX9, a transcription factor that has been reported as a major regulator of TNBC metastasis [ 20 ].…”