Modeling MHC class II molecules and their bound peptides as expressed at the cell surface

Homology modelling of frequent HLA class-II alleles: A perspective to improve prediction of HLA binding peptide and understand the HLA associated disease susceptibility

Human leukocyte antigen (HLA) plays significant role via the regulation of immune system and contribute in the progression and protection of many diseases. HLA molecules bind and present peptides to T- cell receptors which generate the immune response. HLA peptide interaction and molecular function of HLA molecule is the key to predict peptide binding and understanding its role in different diseases. The availability of accurate three dimensional (3D) structures is the initial step towards this direction. In the present work, homology modelling of important and frequent HLA-DRB1 alleles (07:01, 11:01 and 09:01) was done and acceptable models were generated. These modelled alleles were further refined and cross validated by using several methods including Ramachandran plot, Z-score, ERRAT analysis and root mean square deviation (RMSD) calculations. It is known that numbers of allelic variants are related to the susceptibility or protection of various infectious diseases. Difference in amino acid sequences and structures of alleles were also studied to understand the association of HLA with disease susceptibility and protection. Susceptible alleles showed more amino acid variations than protective alleles in three selected diseases caused by different pathogens. Amino acid variations at binding site were found to be more than other part of alleles. RMSD values were also higher at variable positions within binding site. Higher RMSD values indicate that mutations occurring at peptide binding site alter protein structure more than rest of the protein. Hence, these findings and modelled structures can be used to design HLA-DRB1 binding peptides to overcome low prediction accuracy of HLA class II binding peptides. Furthermore, it may help to understand the allele specific molecular mechanisms involved in susceptibility/resistance against pathogenic diseases.

Molecular dynamics simulations to provide insights into epitopes coupled to the soluble and membrane-bound MHC-II complexes

Epitope recognition by major histocompatibility complex II (MHC-II) is essential for the activation of immunological responses to infectious diseases. Several studies have demonstrated that this molecular event takes place in the MHC-II peptide-binding groove constituted by the α and β light chains of the heterodimer. This MHC-II peptide-binding groove has several pockets (P1-P11) involved in peptide recognition and complex stabilization that have been probed through crystallographic experiments and in silico calculations. However, most of these theoretical calculations have been performed without taking into consideration the heavy chains, which could generate misleading information about conformational mobility both in water and in the membrane environment. Therefore, in absence of structural information about the difference in the conformational changes between the peptide-free and peptide-bound states (pMHC-II) when the system is soluble in an aqueous environment or non-covalently bound to a cell membrane, as the physiological environment for MHC-II is. In this study, we explored the mechanistic basis of these MHC-II components using molecular dynamics (MD) simulations in which MHC-II was previously co-crystallized with a small epitope (P₇) or coupled by docking procedures to a large (P₂₂) epitope. These MD simulations were performed at 310 K over 100 ns for the water-soluble (MHC-II_w, MHC-II-P_7w, and MHC-II-P_22w) and 150 ns for the membrane-bound species (MHC-II_m, MHC-II-P_7m, and MHC-II-P_22m). Our results reveal that despite the different epitope sizes and MD simulation environments, both peptides are stabilized primarily by residues lining P1, P4, and P6-7, and similar noncovalent intermolecular energies were observed for the soluble and membrane-bound complexes. However, there were remarkably differences in the conformational mobility and intramolecular energies upon complex formation, causing some differences with respect to how the two peptides are stabilized in the peptide-binding groove.

Towards universal structure-based prediction of class II MHC epitopes for diverse allotypes

The binding of peptide fragments of antigens to class II MHC proteins is a crucial step in initiating a helper T cell immune response. The discovery of these peptide epitopes is important for understanding the normal immune response and its misregulation in autoimmunity and allergies and also for vaccine design. In spite of their biomedical importance, the high diversity of class II MHC proteins combined with the large number of possible peptide sequences make comprehensive experimental determination of epitopes for all MHC allotypes infeasible. Computational methods can address this need by predicting epitopes for a particular MHC allotype. We present a structure-based method for predicting class II epitopes that combines molecular mechanics docking of a fully flexible peptide into the MHC binding cleft followed by binding affinity prediction using a machine learning classifier trained on interaction energy components calculated from the docking solution. Although the primary advantage of structure-based prediction methods over the commonly employed sequence-based methods is their applicability to essentially any MHC allotype, this has not yet been convincingly demonstrated. In order to test the transferability of the prediction method to different MHC proteins, we trained the scoring method on binding data for DRB1*0101 and used it to make predictions for multiple MHC allotypes with distinct peptide binding specificities including representatives from the other human class II MHC loci, HLA-DP and HLA-DQ, as well as for two murine allotypes. The results showed that the prediction method was able to achieve significant discrimination between epitope and non-epitope peptides for all MHC allotypes examined, based on AUC values in the range 0.632-0.821. We also discuss how accounting for peptide binding in multiple registers to class II MHC largely explains the systematically worse performance of prediction methods for class II MHC compared with those for class I MHC based on quantitative prediction performance estimates for peptide binding to class II MHC in a fixed register.

A comparative study of MHC Class-II HLA-DRβ1*0401-Col II and HLA-DRβ1*0101-HA complexes: a theoretical point of view

A study was performed on the HLA-DRbeta1*0401-collagen II peptide complex using the computation of electronic multipolar variables proposed by us previously. Furthermore, these results were compared with those obtained for the HLA-DRbeta1*0101-haemaglutinin peptide complex studied by us with the same tools, confirming that Pocket 1 for this new complex is also the most important pocket for the interaction between the presenting molecule and the presented peptide. The pocket hierarchy established for HLA-DRbeta1*0401 allele was P1 >> P9 approximately P7 > P6 > P4, whilst a P1 >> P4 > P9 approximately P7>P6 pocket hierarchy was found for HLA-DRbeta1*0101, showing how the relative importance of the pockets distinguishes the two alleles. There are high correlation levels with experimental results (when possible), again confirming the validity of using calculated values for electronic multipolar variables as a useful tool for studying interactions between immune system molecules and peptides.

Cyclothiazide binding to functionally active AMPA receptor reveals genuine allosteric interaction with agonist binding sites

The agonist, [3H](-)[S]-1-(2-amino-2-carboxyethyl)-5-fluoro-pyrimidine-2,4-dione ([3H](S)F-Willardiine) binding to functional alpha-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) receptors of resealed plasma membrane vesicles and nerve endings freshly isolated from the rat cerebral cortex displayed two binding sites (K(D1)=33+/-7 nM, B(MAX1)=1.6+/-0.3 pmol/mg protein, K(D2)=720+/-250 nM and B(MAX2)=7.8+/-4.0 pmol/mg protein). The drug which impairs AMPA receptor desensitisation, 6-chloro-3,4-dihydro-3-(2-norbornene-5-yl)-2H-1,2,4-benzothiadiazine-7-sulphonamide-1,1-dioxide (cyclothiazide, CTZ) fully displaced the [3H](S)F-Willardiine binding at a concentration of 500 microM. In the presence of 100 microM CTZ (K(I(CTZ))=60+/-6 microM), both the antagonist [3H]-1,2,3,4-tetrahydro-6-nitro-2,3-dioxo-benzo(F)quinoxaline-7-sulfonamide ([3H]NBQX: K(D)=24+/-4 nM, B(MAX)=12.0+/-0.1 pmol/mg protein) and the high-affinity agonist binding showed similar affinity reduction ([3H](S)F-Willardiine: K(D)=140+/-19 nM, B(MAX)=2.9+/-0.5 pmol/mg protein; [3H]NBQX: K(D)=111+/-34 nM, B(MAX)=12+/-3 pmol/mg protein). To disclose structural correlates underlying genuine allosteric binding interactions, molecular mechanics calculations of CTZ-induced structural changes were performed with the use of PDB data on extracellular GluR2 binding domain dimeric crystals available by now. Hydrogen-bonding and root mean square (rms) values of amino acid residues recognising receptor agonists showed minor alterations in the agonist binding sites itself. Moreover, CTZ binding did not affect dimeric subunit structures significantly. These findings indicated that the structural changes featuring the non-desensitised state could possibly occur to a further site of the extracellular GluR2 binding domain. The increase of agonist efficacy on allosteric CTZ binding may be interpreted in terms of a mechanism involving AMPA receptor desensitisation sequential to activation.