In silico advancements in Peptide-MHC interaction: A molecular dynamics study of predicted glypican-3 peptides and HLA-A*11:01

被引:1
作者
Chieochansin, Thaweesak [1 ,2 ]
Sanachai, Kamonpan [3 ]
Darai, Nitchakan [4 ]
Chiraphapphaiboon, Wannasiri [1 ,2 ]
Choomee, Kornkan [1 ,2 ]
Yenchitsomanus, Pathai [1 ,2 ]
Thuwajit, Chanitra [5 ]
Rungrotmongkol, Thanyada [6 ,7 ]
机构
[1] Mahidol Univ, Fac Med, Siriraj Hosp, Res Dept,Siriraj Ctr Res Excellence Canc Immunothe, Bangkok, Thailand
[2] Mahidol Univ, Fac Med, Siriraj Hosp, Div Mol Med,Res Dept, Bangkok, Thailand
[3] Khon Kaen Univ, Fac Sci, Dept Biochem, Khon Kaen, Thailand
[4] Walailak Univ, Futurist Sci Res Ctr, Sch Sci, Nakhon Si Thammarat, Thailand
[5] Mahidol Univ, Fac Med, Siriraj Hosp, Dept Immunol, Bangkok, Thailand
[6] Chulalongkorn Univ, Fac Sci, Ctr Excellence Struct & Computat Biol, Dept Chem, Bangkok, Thailand
[7] Chulalongkorn Univ, Grad Sch, Program Bioinformat & Computat Biol, Bangkok, Thailand
关键词
Molecular dynamics simulation; Binding ability; Predicted glypican-3 peptides; Human leukocyte antigen-A*11:01; Hepatocellular carcinoma; COMPLEX; SIMULATIONS; RESOURCE; DATABASE; BINDING;
D O I
10.1016/j.heliyon.2024.e36654
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 (Delta G(SIE) = -14.46 +/- 0.53 kcal/mol and Delta G(MM/GBSA) = -30.79 +/- 0.49 kcal/mol) and STIHDSIQY (Delta G(SIE) and Delta G(MM/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.
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页数:14
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