Dynamic flexibility of a peptide-binding groove of human HLA-DR1 class II MHC molecules: normal mode analysis of the antigen peptide-class II MHC complex

Class II major histocompatibility complex (MHC) has tolerance for binding longer antigen peptides than those bound by class I MHC. In this paper, a normal mode analysis on HLA-DR1 class II MHC involving an antigen peptide indicated that the peptide-binding groove had some different dynamic characteristics from that of HLA-A2 class I MHC. The dynamic changes in the class I groove with removal of the bound peptide were limited primarily to the central region and the C-terminal side (corresponding to the C-terminal side of the bound peptide) of the groove, while the dynamic changes in the class II groove with removal of the bound peptide extended to the whole of the groove, and were especially remarkable around a strand located in the N-terminal side (corresponding to the N-terminal side of the bound peptide) of the groove. These results suggest that the N-terminal side of the class II groove is more flexible than the same side of the class I groove, and this flexibility may allow some N-terminal residues of the bound peptide to extend outside the class II groove. Definite anti-correlative motions with removal of the bound peptide appeared between two alpha-helical regions of class II MHC as in the case of class I MHC. These motions of the class II groove may play an important role in obtaining "a flexible dynamic fit" against diverse longer peptides both of whose terminals extend outside the groove.     

Molecular and structural determinants of adamantyl susceptibility to HLA-DRs allelic variants: an in silico approach to understand the mechanism of MLEs

Class II major histocompatibility complex (MHC II) molecules as expressed by antigen-presenting cells are heterodimeric cell-surface glycoprotein receptors that are fundamental in initiating and propagating an immune response by presenting tumor-associated antigenic peptides to CD4⁺/T_H cells. The loading efficiency of such peptides can be improved by small organic compounds (MHC Loading Enhancers—MLEs), that convert the non-receptive peptide conformation of MHC II to a peptide-receptive conformation. In a reversible reaction, these compounds open up the binding site of MHC II molecules by specific interactions with a yet undefined pocket. Here, we performed molecular docking and molecular dynamics simulation studies of adamantyl compounds on the predicted cavity around the P1 pocket of 2 allelic variants of HLA-DRs. The purpose was to investigate the suitability of adamantyl compounds as MLEs at the dimorphic β86 position. Docking studies revealed that besides numerous molecular interactions formed by the adamantyl compounds, Asnβ82, Tyrβ83, and Thrβ90 are the crucial amino acid residues that are characterized as the “sensors” of peptide loading. Molecular dynamics simulation studies exposed the dynamical structural changes that HLA-DRs adopted as a response to binding of 3-(1-adamantyl)-5-hydrazidocarbonyl-1H-pyrazole (AdCaPy). The conformations of AdCaPy complexed with the Glyβ86 HLA-DR allelic variant are well correlated with the stabilized form of peptide-loaded HLA-DRs, further confirming the role of AdCaPy as a MLE. Hydrogen bonding interaction analysis clearly demonstrated that after making suitable contacts with AdCaPy, HLA-DR changes its local conformation. However, AdCaPy complexed with HLA-DR having Valβ86 at the dimorphic position did not accommodate AdCaPy as MLE due to steric hindrance caused by the valine.     

In silico designing breast cancer peptide vaccine for binding to MHC class I and II: A molecular docking study

Antigenic peptides or cancer peptide vaccines can be directly delivered to cancer patients to produce immunologic responses against cancer cells. Specifically, designed peptides can associate with Major Histocompatibility Complex (MHC) class I or II molecules on the cell surface of antigen presenting cells activating anti-tumor effector mechanisms by triggering helper T cell (Th) or cytotoxic T cells (CTL). In general, high binding to MHCs approximately correlates with in vivo immunogenicity. Consequently, a molecular docking technique was run on a library of novel discontinuous peptides predicted by PEPOP from Human epidermal growth factor receptor 2 (HER2 ECD) subdomain III. This technique is expected to improve the prediction accuracy in order to identify the best MHC class I and II binder peptides. Molecular docking analysis through GOLD identified the peptide 1412 as the best MHC binder peptide to both MHC class I and II molecules used in the study. The GOLD results predicted HLA-DR4, HLA-DP2 and TCR as the most often targeted receptors by the peptide 1412. These findings, based on bioinformatics analyses, can be exploited in further experimental analyses in vaccine design and cancer therapy to find possible proper approaches providing beneficial effects.     

Efficient estimation of binding free energies between peptides and an MHC class II molecule using coarse‐grained molecular dynamics simulations with a weighted histogram analysis method

We estimate the binding free energy between peptides and an MHC class II molecule using molecular dynamics (MD) simulations with the weighted histogram analysis method (WHAM). We show that, owing to its more thorough sampling in the available computational time, the binding free energy obtained by pulling the whole peptide using a coarse‐grained (CG) force field (MARTINI) is less prone to significant error induced by inadequate‐sampling than using an atomistic force field (AMBER). We further demonstrate that using CG MD to pull 3–4 residue peptide segments while leaving the remaining peptide segments in the binding groove and adding up the binding free energies of all peptide segments gives robust binding free energy estimations, which are in good agreement with the experimentally measured binding affinities for the peptide sequences studied. Our approach thus provides a promising and computationally efficient way to rapidly and reliably estimate the binding free energy between an arbitrary peptide and an MHC class II molecule. © 2017 Wiley Periodicals, Inc.     

Synthesis and biological evaluation of two chemically modified peptide epitopes for the class I MHC protein HLA-B*2705

The T-cell receptor of a CD8(+) T-cell recognises peptide epitopes bound by class I major histocompatibility complex (MHC) glycoproteins presented in a groove on their upper surface. Within the groove of the MHC molecule are 6 pockets, two of which mostly display a high degree of specificity for binding amino acids capable of making conserved and energetically favourable contacts with the MHC. One type of MHC molecule, HLA-B*2705, preferentially binds peptides containing an arginine at position 2. In an effort to increase the affinity of peptides for HLA-B*2705, potentially leading to better immune responses to such a peptide, we synthesised two modified epitopes where the amino acid at position 2 involved in anchoring the peptide to the class I molecule was replaced with the alpha-methylated beta,gamma-unsaturated arginine analogue 2-(S)-amino-5-guanidino-2-methyl-pent-3-enoic acid. The latter was prepared via a multi-step synthetic sequence, starting from alpha-methyl serine, and incorporated into dipeptides which were fragment-coupled to resin-bound heptameric peptides yielding the target nonameric sequences. Biological characterisation indicated that the modified peptides were poorer than the native peptides at stabilising empty class I MHC complexes, and cells sensitised with these peptides were not recognised as well by cognate CD8(+) T-cells, where available, compared to those sensitised with the native peptide. We suggest that the modifications made to the peptide have decreased its ability to bind to the peptide binding groove of HLA-B*2705 molecules which may explain the decrease in recognition by cytotoxic T-cells when compared to the native peptide.     

Toward prediction of class II mouse major histocompatibility complex peptide binding affinity: in silico bioinformatic evaluation using partial least squares, a robust multivariate statistical technique

The accurate identification of T-cell epitopes remains a principal goal of bioinformatics within immunology. As the immunogenicity of peptide epitopes is dependent on their binding to major histocompatibility complex (MHC) molecules, the prediction of binding affinity is a prerequisite to the reliable prediction of epitopes. The iterative self-consistent (ISC) partial-least-squares (PLS)-based additive method is a recently developed bioinformatic approach for predicting class II peptide-MHC binding affinity. The ISC-PLS method overcomes many of the conceptual difficulties inherent in the prediction of class II peptide-MHC affinity, such as the binding of a mixed population of peptide lengths due to the open-ended class II binding site. The method has applications in both the accurate prediction of class II epitopes and the manipulation of affinity for heteroclitic and competitor peptides. The method is applied here to six class II mouse alleles (I-Ab, I-Ad, I-Ak, I-As, I-Ed, and I-Ek) and included peptides up to 25 amino acids in length. A series of regression equations highlighting the quantitative contributions of individual amino acids at each peptide position was established. The initial model for each allele exhibited only moderate predictivity. Once the set of selected peptide subsequences had converged, the final models exhibited a satisfactory predictive power. Convergence was reached between the 4th and 17th iterations, and the leave-one-out cross-validation statistical terms--q2, SEP, and NC--ranged between 0.732 and 0.925, 0.418 and 0.816, and 1 and 6, respectively. The non-cross-validated statistical terms r2 and SEE ranged between 0.98 and 0.995 and 0.089 and 0.180, respectively. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made freely available online (http://www.jenner.ac.uk/MHCPred).     

Revisiting the structural basis and energetic landscape of susceptibility difference between HLA isotypes to allergic rhinitis

The human leukocyte antigen class II (HLA II) molecules are implicated in the immunopathogenesis of allergic rhinitis (AR). The HLA II contains three allelic isotypes HLA-DR, -DQ, and -QP that exhibit considerably different susceptibility to AR. Here, we investigated the structural basis and energetic landscape of the susceptibility difference between the three HLA II isotypes to AR by combining computational analysis and experimental assay. Multiple sequence alignment revealed a low conservation among the three subtypes with sequence identity of ∼10% between them, suggesting that the peptide repertoires presented by HLA-DR, -DP and -DQ are not overlapped to each other, and they may be involved in different immune functions and dysfunctions. Structural analysis imparted that the antigenic peptides are rooted on the peptide-binding groove of HLA molecules and hold in a PPII-like helical conformation. Subsequently, the interaction behavior of 17 AR allergen-derived peptides with HLA-DR, −DP and −DQ was investigated using a statistics-based quantitative structure-activity relationship (QSAR) predictor. It was found a significant difference between the binding capabilities of these antigenic peptides to HLA-DR and to HLA-DP/-DQ; the former showed a generally higher affinity than the latter with p-value of 0.02 obtained from 2-tailed Student’s t-test. The computational findings were then confirmed by HLA II–peptide stability assay, which demonstrated that the AR allergen-derived peptides have a high in vitro selectivity for HLA-DR over HLA-DP/-DQ. Thus, the HLA-DR isotype, rather than HLA-DP and −DQ, is expected to associate with the pathological process of AR.     

Complex Formation between the Lumenal Domain of Adenovirus E3–19k Protein and the Extracellular Domain of Class I MHC Molecule In Vitro

The Ad2 E3–19k protein inhibits the transport of newly synthesized class I MHC molecules to the cell surface, thereby interfering with antigen presentation. The details of the interaction between E3–19k protein and class I MHC molecules have not been well‐defined. In this present study, we describe the use of gel filtration HPLC for confirming the binding interaction of two domain proteins, E3–19k and MHC class I antigen, and subsequently the characterization of protein complex by SDS‐PAGE. Our results demonstrate the complex formation between Ad2 lumenal E3–19k (108 amino acids, wt 108) and HLA‐A*0201 molecule in vitro. Titration experiments will be employed in the future to determine stoichiometry and verify the specific interactions.     

Predicting sequences and structures of MHC-binding peptides: a computational combinatorial approach

Peptides bound to MHC molecules on the surface of cells convey critical information about the cellular milieu to immune system T cells. Predicting which peptides can bind an MHC molecule, and understanding their modes of binding, are important in order to design better diagnostic and therapeutic agents for infectious and autoimmune diseases. Due to the difficulty of obtaining sufficient experimental binding data for each human MHC molecule, computational modeling of MHC peptide-binding properties is necessary. This paper describes a computational combinatorial design approach to the prediction of peptides that bind an MHC molecule of known X-ray crystallographic or NMR-determined structure. The procedure uses chemical fragments as models for amino acid residues and produces a set of sequences for peptides predicted to bind in the MHC peptide-binding groove. The probabilities for specific amino acids occurring at each position of the peptide are calculated based on these sequences, and these probabilities show a good agreement with amino acid distributions derived from a MHC-binding peptide database. The method also enables prediction of the three-dimensional structure of MHC-peptide complexes. Docking, linking, and optimization procedures were performed with the XPLOR program [1].     

The Use of Reverse Vaccinology and Molecular Modeling Associated with Cell Proliferation Stimulation Approach to Select Promiscuous Epitopes from <Emphasis Type="Italic">Schistosoma mansoni</Emphasis>

Schistosomiasis remains an important parasitic disease that affects millions of individuals worldwide. Despite the availability of chemotherapy, the occurrence of constant reinfection demonstrates the need for additional forms of intervention and the development of a vaccine represents a relevant strategy to control this disease. With the advent of genomics and bioinformatics, new strategies to search for vaccine targets have been proposed, as the reverse vaccinology. In this work, computational analyses of Schistosoma mansoni membrane proteins were performed to predict epitopes with high affinity for different human leukocyte antigen (HLA)-DRB1. Ten epitopes were selected and along with murine major histocompatibility complex (MHC) class II molecule had their three-dimensional structures optimized. Epitope interactions were evaluated against murine MHC class II molecule through molecular docking, electrostatic potential, and molecular volume. The epitope Sm141290 and Sm050890 stood out in most of the molecular modeling analyses. Cellular proliferation assay was performed to evaluate the ability of these epitopes to bind to murine MHC II molecules and stimulate CD4+ T cells showing that the same epitopes were able to significantly stimulate cell proliferation. This work showed an important strategy of peptide selection for epitope-based vaccine design, achieved by in silico analyses that can precede in vivo and in vitro experiments, avoiding excessive experimentation.     

Determination of Allosteric Effects and Interstrand Bidentate Interactions in DNA‐Peptide Molecular Recognition

To study DNA allostery, quantitative DNase I footprinting studies were carried out on a newly designed peptide His‐Hyp‐Lys‐Lys‐(Py)₄‐Lys‐Lys‐NH₂ (HypKK‐10) containing the XHypKK (Hyp = hydroxyproline) and polyamide motifs. The interconnection of DNA footprints of peptides HypKK‐10 and the parent peptide PyPro‐12 supports the proposal that interaction network cooperativity is preferred in DNA‐peptide interactions between multiple recognition sites. A simple method of determining interstrand bidentate interactions between the peptide moieties and DNA bases is introduced. It is envisaged that interstrand bidentate interactions also participate in the relay of conformational changes to recognition sites on the complementary strands. Circular dichroism studies of the titration of peptide HypKK‐10 with an oligonucleotide duplex indicate that this peptide binds in a dimeric fashion to DNA in the minor groove. This work may prompt the design of new DNA binding ligands for the study of DNA‐peptide allosteric interactions and DNA interaction network.     

Fine specificity of antigen binding to two class I major histocompatibility proteins (B*2705 and B*2703) differing in a single amino acid residue

Starting from the X-ray structure of a class I majorhistocompatibility complex (MHC)-encoded protein (HLA-B*2705), a naturallypresented self-nonapeptide and two synthetic analogues were simulated in thebinding groove of two human leukocyte antigen (HLA) alleles (B*2703 andB*2705) differing in a single amino acid residue. After 200 ps moleculardynamics simulations of the solvated HLA–peptide pairs, some molecularproperties of the complexes (distances between ligand and protein center ofmasses, atomic fluctuations, buried versus accessible surface areas,hydrogen-bond frequencies) allow a clear discrimination of potent from weakMHC binders. The binding specificity of the three nonapeptides for the twoHLA alleles could be explained by the disruption of one hydrogen-bondingnetwork in the binding pocket of the HLA-B*2705 protein where the singlemutation occurs. Rearrangements of interactions in the B pocket, which bindsthe side chain of peptidic residue 2, and a weakening of interactionsinvolving the C-terminal end of the peptide also took place. In addition,extension of the peptide backbone using a -Ala analogue did notabolish binding to any of the two HLA-B27 subtypes, but increased theselectivity for B*2703, as expected from the larger peptide binding groovein this subtype. A better understanding of the atomic details involved inpeptide selection by closely related HLA alleles is of crucial importancefor unraveling the molecular features linking particular HLA alleles toautoimmune diseases, and for the identification of antigenic peptidestriggering such pathologies.     

A polymorphic pocket at the P10 position contributes to peptide binding specificity in class II MHC proteins

Peptides bind to class II major histocompatibility complex (MHC) proteins in an extended conformation. Pockets in the peptide binding site spaced to accommodate peptide side chains at the P1, P4, P6, and P9 positions have been previously characterized and help to explain the obtained peptide binding specificity. However, two peptides differing only at P10 have significantly different binding affinities for HLA-DR1. The structure of HLA-DR1 in complex with the tighter binding peptide shows that the peptide binds in the usual polyproline type II conformation, but with the P10 residue accommodated in a shallow pocket at the end of the binding groove. HLA-DR1 variants with polymorphic residues at these positions were produced and found to exhibit different side chain specificity at the P10 position. These results define a new specificity position in HLA-DR proteins.     

Prediction of peptide binding to a major histocompatibility complex class I molecule based on docking simulation

Binding between major histocompatibility complex (MHC) class I molecules and immunogenic epitopes is one of the most important processes for cell-mediated immunity. Consequently, computational prediction of amino acid sequences of MHC class I binding peptides from a given sequence may lead to important biomedical advances. In this study, an efficient structure-based method for predicting peptide binding to MHC class I molecules was developed, in which the binding free energy of the peptide was evaluated by two individual docking simulations. An original penalty function and restriction of degrees of freedom were determined by analysis of 361 published X-ray structures of the complex and were then introduced into the docking simulations. To validate the method, calculations using a 50-amino acid sequence as a prediction target were performed. In 27 calculations, the binding free energy of the known peptide was within the top 5 of 166 peptides generated from the 50-amino acid sequence. Finally, demonstrative calculations using a whole sequence of a protein as a prediction target were performed. These data clearly demonstrate high potential of this method for predicting peptide binding to MHC class I molecules.     

Dynamic characteristics of a peptide-binding groove of human HLA-A2 class I MHC molecules: normal mode analysis of the antigen peptide-class I MHC complex

Class I major histocompatibility complex (MHC) binds antigen peptides with various sequences. We performed a normal mode analysis of HLA-A2 MHC that binds three peptides with different affinity. HLA-A2 MHC has a peptide-binding groove composed of two alpha-helices (residue 49-84, residue 140-179). Some residues in the center of the groove showed an increase in fluctuations and some residue pairs between two helix groups showed a negative change in correlations by removing the antigen peptide. The extent of the fluctuation and correlation changes correlated well with the experimental ranking of the three peptides in binding affinity. Some definite anti-correlative motions were found between two helix groups in low frequency modes (<50 cm(-1)) by removing the antigen peptide. We propose that the above anti-correlative motions play an important role to bind the antigen peptide, especially in obtaining a "dynamic fit."     

Effect of chain length on the conformation and T cell recognition of synthetic hemagglutinin fragments

Circular dichroism and Fourier-transform infrared spectroscopies were used to compare the conformational mobility of 13-mer peptides covering the 317-329 region of the envelope protein hemagglutinin of human influenza A virus subtypes H1, H2 and H3 with that of their truncated deca- and nonapeptide analogs. These peptides were demonstrated to bind to the murine I-Ed major histocompatibility complex encoded class II and human HLA-B*2705 class I molecules. Despite the amino acid substitutions in the three 13-mer subtype sequences, no significant differences in the conformational properties could be shown. Deletion of the N-terminal three residues resulted in a shift to an increased alpha-helical conformer population in the 317-329 H1 peptide and the breakage of the 3(10) or weakly H-bonded (nascent) alpha-helix in the H2 and H3 peptides. The conformational change observed upon deletion did not influence the efficiency of I-Ed peptide interaction, however, the C-terminal Arg had a beneficial effect both on MHC class II and class I binding without causing any remarkable change in solution conformation.     

Natural Compounds against Alzheimer’s Disease: Molecular Recognition of Aβ1–42 Peptide by Salvia sclareoides Extract and its Major Component,Rosmarinic Acid,as Investigated by NMR

Amyloid peptides, Aβ1–40 and Aβ1–42, represent major molecular targets to develop potential drugs and diagnostic tools for Alzheimer’s Disease (AD). In fact, oligomeric and fibrillar aggregates generated by these peptides are amongst the principal components of amyloid plaques found post mortem in patients suffering from AD. Rosmarinic acid has been demonstrated to be effective in preventing the aggregation of amyloid peptides in vitro and to delay the progression of the disease in animal models. Nevertheless, no information is available about its molecular mechanism of action. Herein, we report the NMR characterization of the interaction of Salvia sclareoides extract and that of its major component, rosmarinic acid, with Aβ1–42 peptide, whose oligomers have been described as the most toxic Aβ species in vivo. Our data shed light on the structural determinants of rosmarinic acid–Aβ1–42 oligomers interaction, thus allowing the elucidation of its mechanism of action. They also provide important information for the rational design of new compounds with higher affinity for Aβ peptides to generate new anti‐amyloidogenic molecules and/or molecular tools for the specific targeting of amyloid aggregates in vivo. In addition, we identified methyl caffeate, another natural compound present in different plants and human diet, as a good ligand of Aβ1–42 oligomers, which also shows anti‐amyloidogenic activity. Finally, we demonstrated the possibility to exploit STD‐NMR and trNOESY experiments to screen extracts from natural sources for the presence of Aβ peptide ligands.     

Recovery of known T-cell epitopes by computational scanning of a viral genome

A new computational method (EpiDock) is proposed for predicting peptide binding to class I MHC proteins, from the amino acid sequence of any protein of immunological interest. Starting from the primary structure of the target protein, individual three-dimensional structures of all possible MHC-peptide (8-, 9- and 10-mers) complexes are obtained by homology modelling. A free energy scoring function (Fresno) is then used to predict the absolute binding free energy of all possible peptides to the class I MHC restriction protein. Assuming that immunodominant epitopes are usually found among the top MHC binders, the method can thus be applied to predict the location of immunogenic peptides on the sequence of the protein target. When applied to the prediction of HLA-A^*0201-restricted T-cell epitopes from the Hepatitis B virus, EpiDock was able to recover 92% of known high affinity binders and 80% of known epitopes within a filtered subset of all possible nonapeptides corresponding to about one tenth of the full theoretical list.The proposed method is fully automated and fast enough to scan a viral genome in less than an hour on a parallel computing architecture. As it requires very few starting experimental data, EpiDock can be used: (i) to predict potential T-cell epitopes from viral genomes (ii) to roughly predict still unknown peptide binding motifs for novel class I MHC alleles.     

Adding energy minimization strategy to peptide‐design algorithm enables better search for RNA‐binding peptides: Redesigned λ N peptide binds boxB RNA

Our previously developed peptide‐design algorithm was improved by adding an energy minimization strategy which allows the amino acid sidechains to move in a broad configuration space during sequence evolution. In this work, the new algorithm was used to generate a library of 21‐mer peptides which could substitute for λ N peptide in binding to boxB RNA. Six potential peptides were obtained from the algorithm, all of which exhibited good binding capability with boxB RNA. Atomistic molecular dynamics simulations were then conducted to examine the ability of the λ N peptide and three best evolved peptides, viz. Pept01, Pept26, and Pept28, to bind to boxB RNA. Simulation results demonstrated that our evolved peptides are better at binding to boxB RNA than the λ N peptide. Sequence searches using the old (without energy minimization strategy) and new (with energy minimization strategy) algorithms confirm that the new algorithm is more effective at finding good RNA‐binding peptides than the old algorithm. © 2016 Wiley Periodicals, Inc.