In silico advancements in Peptide-MHC interaction: A molecular dynamics study of predicted glypican-3 peptides and HLA-A*11:01
Issued Date
2024-09-15
Resource Type
eISSN
24058440
Scopus ID
2-s2.0-85201760694
Journal Title
Heliyon
Volume
10
Issue
17
Rights Holder(s)
SCOPUS
Bibliographic Citation
Heliyon Vol.10 No.17 (2024)
Suggested Citation
Chieochansin T., Sanachai K., Darai N., Chiraphapphaiboon W., Choomee K., Yenchitsomanus P.t., Thuwajit C., Rungrotmongkol T. In silico advancements in Peptide-MHC interaction: A molecular dynamics study of predicted glypican-3 peptides and HLA-A*11:01. Heliyon Vol.10 No.17 (2024). doi:10.1016/j.heliyon.2024.e36654 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/100673
Title
In silico advancements in Peptide-MHC interaction: A molecular dynamics study of predicted glypican-3 peptides and HLA-A*11:01
Corresponding Author(s)
Other Contributor(s)
Abstract
Our study employed molecular dynamics (MD) simulations to assess the binding affinity between short peptides derived from the tumor-associated antigen glypican 3 (GPC3) and the major histocompatibility complex (MHC) molecule HLA-A*11:01 in hepatocellular carcinoma. We aimed to improve the reliability of in silico predictions of peptide-MHC interactions, which are crucial for developing targeted cancer therapies. We used five algorithms to discover four peptides (TTDHLKFSK, VINTTDHLK, KLIMTQVSK, and STIHDSIQY), demonstrating the substantial potential for HLA-A11:01 presentation. The Anchored Peptide-MHC Ensemble Generator (APE-Gen) was used to create the initial structure of the peptide-MHC complex. This was followed by a 200 ns molecular dynamics (MD) simulation using AMBER22, which verified the precise positioning of the peptides in the binding groove of HLA-A*11:01, specifically at the A and F pockets. Notably, the 2nd residue, which serves as a critical anchor within the 2nd pocket, played a pivotal role in stabilising the binding interactions.VINTTDHLK (ΔGSIE = −14.46 ± 0.53 kcal/mol and ΔGMM/GBSA = −30.79 ± 0.49 kcal/mol) and STIHDSIQY (ΔGSIE and ΔGMM/GBSA = −14.55 ± 0.16 and −23.21 ± 2.23 kcal/mol) exhibited the most effective binding potential among the examined peptides, as indicated by both their binding free energies and its binding affinity on the T2 cell line (VINTTDHLK: IC50 = 0.45 nM; STIHDSIQY: IC50 = 0.35 nM). The remarkable concordance between in silico and in vitro binding affinity results was of particular significance, indicating that MD simulation is a potent instrument capable of bolstering confidence in in silico peptide predictions. By employing MD simulation as a method, our study provides a promising avenue for improving the prediction of potential peptide-MHC interactions, thereby facilitating the development of more effective and targeted cancer therapies.