Computational and atomistic studies applied to the understanding of the structural and behavioral features of the immune checkpoint HLA-G molecule and gene.
Cinthia C AlvesThaís ArnsMaria L OliveiraPhilippe MoreauDinler A AntunesErick C CastelliCelso T Mendes-JuniorSilvana GiuliattiEduardo A DonadiPublished in: Human immunology (2023)
We took advantage of the increasingly evolving approaches for in silico studies concerning protein structures, protein molecular dynamics (MD), protein-protein and protein-DNA docking to evaluate: (i) the structure and MD characteristics of the HLA-G well-recognized isoforms, (ii) the impact of missense mutations at HLA-G receptor genes (LILRB1/2), and (iii) the differential binding of the hypoxia-inducible factor 1 (HIF1) to hypoxia-responsive elements (HRE) at the HLA-G gene. Besides reviewing these topics, they were revisited including the following novel results: (i) the HLA-G6 isoforms were unstable docked or not with β 2 -microglobulin or peptide, (ii) missense mutations at LILRB1/2 genes, exchanging amino acids at the intracellular domain, particularly those located within and around the ITIM motifs, may impact the HLA-G binding strength, and (iii) HREs motifs at the HLA-G promoter or exon 2 regions exhibiting a guanine at their third position present a higher affinity for HIF1 when compared to an adenine at the same position. These data shed some light into the functional aspects of HLA-G, particularly how polymorphisms may influence the role of the molecule. Computational and atomistic studies have provided alternative tools for experimental physical methodologies, which are time-consuming, expensive, demanding large quantities of purified proteins, and exhibit low output.
Keyphrases
- molecular dynamics
- protein protein
- small molecule
- genome wide
- amino acid
- molecular dynamics simulations
- endothelial cells
- binding protein
- mental health
- dna methylation
- gene expression
- physical activity
- genome wide identification
- copy number
- big data
- autism spectrum disorder
- density functional theory
- mass spectrometry
- drug delivery
- case control
- intellectual disability
- deep learning
- single molecule
- artificial intelligence
- machine learning
- reactive oxygen species