Evaluating the 3D structure prediction tools to identify optimal MEBPVC structure models

• Published in: Computational and Structural Biotechnology Reports Vol. 1; p. 100010
• Main Authors: Sahoo, Partha Sarathi, Burra, V.L.S. Prasad
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2024
• Subjects: AlphaFold2; ESMFold; I-TASSER; MEBPVCs; MVP; PEA; Protein Modelling; Protein Modelling; MEBPVCs; MVP; AlphaFold2; PEA; I-TASSER; ESMFold
• ISSN: 2950-3639
• DOI: 10.1016/j.csbr.2024.100010

Multi-Epitope based Peptide Vaccines Candidates (MEBPVCs) are peptide sequences with the immunogenic epitopes interspersed with linkers, adjuvants and other components. The optimization of one of the components of MEBPVCs, epitope order, resulted in a unique epitope ordered MEBPVC showing improved vaccine potency. In addition to the above combinatorial optimization task, predicting the 3D structure of these MEBPVCs presents a significant challenge owing to the diverse modeling approaches employed by the modeling tools. Here we embarked on evaluating the performance of the threading based ab initio modeling tool: I-TASSER, Large Language Model (LLM) based tool: ESMFold and the MSA based artificial intelligence based tool: AlphaFold2. Our investigation employed RMSD, PEA, SASA, Solubility, Globularity, secondary structure analysis, Docking, MDS and MVP. I-TASSER emerged as the superior performer. The analysis revealed a strong correlation between predicted tertiary structure and secondary structure composition, especially the β-turns and random coils. It appears that accurate secondary structure identification to be a pivotal step, dictating the propagation of accuracy (or inaccuracy). This finding highlights the critical importance of secondary structure prediction/assignment algorithms for enhanced protein structure modeling accuracy especially to integrate predictions where evolutionary information is minimal and or lacking. Small sample size is attributed to the low significance of the parameters though Globularity and SASA have shown good p-values. Overall, the results support the need and utilization of the LLMs in biological research, underscoring their potential to revolutionize protein structure prediction and advance diverse biomolecular applications, accelerating Synthetic Biology research. [Display omitted] •PEA, a new descriptor, ranks MEBPVC models based on total epitope exposure, offering benefits in MEBPV design & development.•The study found a strong correlation between 3D structure accuracy & SSEs, underscoring their critical role in model fidelity.•Enhanced awareness and discretion in tool selection enables readers to make more informed decisions in MEBP Vaccine design.