Predicting class I major histocompatibility complex (MHC) binders using multivariate statistics:comparison of discriminant analysis and multiple linear regression

The accurate in silico identification of T-cell epitopes is a critical step in the development of peptide-based vaccines, reagents, and diagnostics. It has a direct impact on the success of subsequent experimental work. Epitopes arise as a consequence of complex proteolytic processing within the cell. Prior to being recognized by T cells, an epitope is presented on the cell surface as a complex with a major histocompatibility complex (MHC) protein. A prerequisite therefore for T-cell recognition is that an epitope is also a good MHC binder. Thus, T-cell epitope prediction overlaps strongly with the prediction of MHC binding. In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for binding affinity prediction. We apply these methods to peptides which bind the well-studied human MHC allele HLA-A*0201. A matrix which results from combining results of the two methods proved powerfully predictive under cross-validation. The new matrix was also tested on an external set of 160 binders to HLA-A*0201; it was able to recognize 135 (84%) of them.

Class I T-cell epitope prediction:improvements using a combination of proteasome cleavage, TAP affinity, and MHC binding

Cleavage by the proteasome is responsible for generating the C terminus of T-cell epitopes. Modeling the process of proteasome cleavage as part of a multi-step algorithm for T-cell epitope prediction will reduce the number of non-binders and increase the overall accuracy of the predictive algorithm. Quantitative matrix-based models for prediction of the proteasome cleavage sites in a protein were developed using a training set of 489 naturally processed T-cell epitopes (nonamer peptides) associated with HLA-A and HLA-B molecules. The models were validated using an external test set of 227 T-cell epitopes. The performance of the models was good, identifying 76% of the C-termini correctly. The best model of proteasome cleavage was incorporated as the first step in a three-step algorithm for T-cell epitope prediction, where subsequent steps predicted TAP affinity and MHC binding using previously derived models.

Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models

Background - The binding between peptide epitopes and major histocompatibility complex proteins (MHCs) is an important event in the cellular immune response. Accurate prediction of the binding between short peptides and the MHC molecules has long been a principal challenge for immunoinformatics. Recently, the modeling of MHC-peptide binding has come to emphasize quantitative predictions: instead of categorizing peptides as "binders" or "non-binders" or as "strong binders" and "weak binders", recent methods seek to make predictions about precise binding affinities. Results - We developed a quantitative support vector machine regression (SVR) approach, called SVRMHC, to model peptide-MHC binding affinities. As a non-linear method, SVRMHC was able to generate models that out-performed existing linear models, such as the "additive method". By adopting a new "11-factor encoding" scheme, SVRMHC takes into account similarities in the physicochemical properties of the amino acids constituting the input peptides. When applied to MHC-peptide binding data for three mouse class I MHC alleles, the SVRMHC models produced more accurate predictions than those produced previously. Furthermore, comparisons based on Receiver Operating Characteristic (ROC) analysis indicated that SVRMHC was able to out-perform several prominent methods in identifying strongly binding peptides. Conclusion - As a method with demonstrated performance in the quantitative modeling of MHC-peptide binding and in identifying strong binders, SVRMHC is a promising immunoinformatics tool with not inconsiderable future potential.

Quantitative structure-activity relationships and the prediction of MHC supermotifs

The underlying assumption in quantitative structure–activity relationship (QSAR) methodology is that related chemical structures exhibit related biological activities. We review here two QSAR methods in terms of their applicability for human MHC supermotif definition. Supermotifs are motifs that characterise binding to more than one allele. Supermotif definition is the initial in silico step of epitope-based vaccine design. The first QSAR method we review here—the additive method—is based on the assumption that the binding affinity of a peptide depends on contributions from both amino acids and the interactions between them. The second method is a 3D-QSAR method: comparative molecular similarity indices analysis (CoMSIA). Both methods were applied to 771 peptides binding to 9 HLA alleles. Five of the alleles (A*0201, A* 0202, A*0203, A*0206 and A*6802) belong to the HLA-A2 superfamily and the other four (A*0301, A*1101, A*3101 and A*6801) to the HLA-A3 superfamily. For each superfamily, supermotifs defined by the two QSAR methods agree closely and are supported by many experimental data.

Transporter associated with antigen processing preselection of peptides binding to the MHC:a bioinformatic evaluation

TAP is responsible for the transit of peptides from the cytosol to the lumen of the endoplasmic reticulum. In an immunological context, this event is followed by the binding of peptides to MHC molecules before export to the cell surface and recognition by T cells. Because TAP transport precedes MHC binding, TAP preferences may make a significant contribution to epitope selection. To assess the impact of this preselection, we have developed a scoring function for TAP affinity prediction using the additive method, have used it to analyze and extend the TAP binding motif, and have evaluated how well this model acts as a preselection step in predicting MHC binding peptides. To distinguish between MHC alleles that are exclusively dependent on TAP and those exhibiting only a partial dependence on TAP, two sets of MHC binding peptides were examined: HLA-A*0201 was selected as a representative of partially TAP-dependent HLA alleles, and HLA-A*0301 represented fully TAP-dependent HLA alleles. TAP preselection has a greater impact on TAP-dependent alleles than on TAP-independent alleles. The reduction in the number of nonbinders varied from 10% (TAP-independent) to 33% (TAP-dependent), suggesting that TAP preselection is an important component in the successful in silico prediction of T cell epitopes.

Coupling in silico and in vitro analysis of peptide-MHC binding:a bioinformatic approach enabling prediction of superbinding peptides and anchorless epitopes

The ability to define and manipulate the interaction of peptides with MHC molecules has immense immunological utility, with applications in epitope identification, vaccine design, and immunomodulation. However, the methods currently available for prediction of peptide-MHC binding are far from ideal. We recently described the application of a bioinformatic prediction method based on quantitative structure-affinity relationship methods to peptide-MHC binding. In this study we demonstrate the predictivity and utility of this approach. We determined the binding affinities of a set of 90 nonamer peptides for the MHC class I allele HLA-A*0201 using an in-house, FACS-based, MHC stabilization assay, and from these data we derived an additive quantitative structure-affinity relationship model for peptide interaction with the HLA-A*0201 molecule. Using this model we then designed a series of high affinity HLA-A2-binding peptides. Experimental analysis revealed that all these peptides showed high binding affinities to the HLA-A*0201 molecule, significantly higher than the highest previously recorded. In addition, by the use of systematic substitution at principal anchor positions 2 and 9, we showed that high binding peptides are tolerant to a wide range of nonpreferred amino acids. Our results support a model in which the affinity of peptide binding to MHC is determined by the interactions of amino acids at multiple positions with the MHC molecule and may be enhanced by enthalpic cooperativity between these component interactions.

Identifiying human MHC supertypes using bioinformatic methods

Classification of MHC molecules into supertypes in terms of peptide-binding specificities is an important issue, with direct implications for the development of epitope-based vaccines with wide population coverage. In view of extremely high MHC polymorphism (948 class I and 633 class II HLA alleles) the experimental solution of this task is presently impossible. In this study, we describe a bioinformatics strategy for classifying MHC molecules into supertypes using information drawn solely from three-dimensional protein structure. Two chemometric techniques–hierarchical clustering and principal component analysis–were used independently on a set of 783 HLA class I molecules to identify supertypes based on structural similarities and molecular interaction fields calculated for the peptide binding site. Eight supertypes were defined: A2, A3, A24, B7, B27, B44, C1, and C4. The two techniques gave 77% consensus, i.e., 605 HLA class I alleles were classified in the same supertype by both methods. The proposed strategy allowed “supertype fingerprints” to be identified. Thus, the A2 supertype fingerprint is Tyr9/Phe9, Arg97, and His114 or Tyr116; the A3-Tyr9/Phe9/Ser9, Ile97/Met97 and Glu114 or Asp116; the A24-Ser9 and Met97; the B7-Asn63 and Leu81; the B27-Glu63 and Leu81; for B44-Ala81; the C1-Ser77; and the C4-Asn77. action fields calculated for the peptide binding site. Eight supertypes were defined: A2, A3, A24, B7, B27, B44, C1, and C4. The two techniques gave 77% consensus, i.e., 605 HLA class I alleles were classified in the same supertype by both methods. The proposed strategy allowed “supertype fingerprints” to be identified. Thus, the A2 supertype fingerprint is Tyr9/Phe9, Arg97, and His114 or Tyr116; the A3-Tyr9/Phe9/Ser9, Ile97/Met97 and Glu114 or Asp116; the A24-Ser9 and Met97; the B7-Asn63 and Leu81; the B27-Glu63 and Leu81; for B44-Ala81; the C1-Ser77; and the C4-Asn77.

MHCPred : a server for quantitative prediction of peptide-MHC binding

Accurate T-cell epitope prediction is a principal objective of computational vaccinology. As a service to the immunology and vaccinology communities at large, we have implemented, as a server on the World Wide Web, a partial least squares-base multivariate statistical approach to the quantitative prediction of peptide binding to major histocom-patibility complexes (MHC), the key checkpoint on the antigen presentation pathway within adaptive,cellular immunity. MHCPred implements robust statistical models for both Class I alleles (HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203,HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3301, HLA-A*6801, HLA-A*6802 and HLA-B*3501) and Class II alleles (HLA-DRB*0401, HLA-DRB*0401and HLA-DRB* 0701).

Do little embryos make big decisions? How maternal dietary protein restriction can permanently change an embryo's potential, affecting adult health

Periconceptional environment may influence embryo development, ultimately affecting adult health. Here, we review the rodent model of maternal low-protein diet specifically during the preimplantation period (Emb-LPD) with normal nutrition during subsequent gestation and postnatally. This model, studied mainly in the mouse, leads to cardiovascular, metabolic and behavioural disease in adult offspring, with females more susceptible. We evaluate the sequence of events from diet administration that may lead to adult disease. Emb-LPD changes maternal serum and/or uterine fluid metabolite composition, notably with reduced insulin and branched-chain amino acids. This is sensed by blastocysts through reduced mammalian target of rapamycin complex 1 signalling. Embryos respond by permanently changing the pattern of development of their extra-embryonic lineages, trophectoderm and primitive endoderm, to enhance maternal nutrient retrieval during subsequent gestation. These compensatory changes include stimulation in proliferation, endocytosis and cellular motility, and epigenetic mechanisms underlying them are being identified. Collectively, these responses act to protect fetal growth and likely contribute to offspring competitive fitness. However, the resulting growth adversely affects long-term health because perinatal weight positively correlates with adult disease risk. We argue that periconception environmental responses reflect developmental plasticity and 'decisions' made by embryos to optimise their own development, but with lasting consequences.

EpiDOCK:a molecular docking-based tool for MHC class II binding prediction

Cellular peptide vaccines contain T-cell epitopes. The main prerequisite for a peptide to act as a T-cell epitope is that it binds to a major histocompatibility complex (MHC) protein. Peptide MHC binder identification is an extremely costly experimental challenge since human MHCs, named human leukocyte antigen, are highly polymorphic and polygenic. Here we present EpiDOCK, the first structure-based server for MHC class II binding prediction. EpiDOCK predicts binding to the 23 most frequent human, MHC class II proteins. It identifies 90% of true binders and 76% of true non-binders, with an overall accuracy of 83%. EpiDOCK is freely accessible at http://epidock.ddg-pharmfac. net. © The Author 2013. Published by Oxford University Press. All rights reserved.

Histidine hydrogen bonding in MHC at pH 5 and pH 7 modeled by molecular docking and molecular dynamics simulations

Hydrogen bonds play important roles in maintaining the structure of proteins and in the formation of most biomolecular protein-ligand complexes. All amino acids can act as hydrogen bond donors and acceptors. Among amino acids, Histidine is unique, as it can exist in neutral or positively charged forms within the physiological pH range of 5.0 to 7.0. Histidine can thus interact with other aromatic residues as well as forming hydrogen bonds with polar and charged residues. The ability of His to exchange a proton lies at the heart of many important functional biomolecular interactions, including immunological ones. By using molecular docking and molecular dynamics simulation, we examine the influence of His protonation/deprotonation on peptide binding affinity to MHC class II proteins from locus HLA-DP. Peptide-MHC interaction underlies the adaptive cellular immune response, upon which the next generation of commercially-important vaccines will depend. Consistent with experiment, we find that peptides containing protonated His residues bind better to HLA-DP proteins than those with unprotonated His. Enhanced binding at pH 5.0 is due, in part, to additional hydrogen bonds formed between peptide His+ and DP proteins. In acidic endosomes, protein His79β is predominantly protonated. As a result, the peptide binding cleft narrows in the vicinity of His79β, which stabilizes the peptide - HLA-DP protein complex. © 2014 Bentham Science Publishers.

Can hydrogen sulfide prevent preeclampsia and fetal growth restriction?

The exact aetiology of preeclampsia is unknown, but there is a good association with an imbalance in angiogenic growth factors and abnormal placentation [1]. Hydrogen sulphide (H2S), a gaseous messenger produced mainly by cystathionine γ-lyase (CSE), is pro-angiogenic vasodilator [2] and [3]. We hypothesized that a reduction in CSE activity may alter the angiogenic balance in pregnancy and induce abnormal placentation and maternal hypertension. Plasma levels of H2S were significantly decreased in preeclamptic women (p < 0.01), which was associated with reduced CSE message and protein expression in human placenta as determined by real-time PCR and immunohistochemistry. Inhibition of CSE activity by DL-propargylglycine (PAG) in first trimester (8–12 weeks gestation) human placental explants had reduced placenta growth factor (PlGF) production as assessed by ELISA and inhibited trophoblast invasion in vitro. Endothelial CSE knockdown by siRNA transfection increased the endogenous release of soluble fms-Like tyrosine kinase-1 (sFlt-1) and soluble endoglin, (sEng) from human umbilical vein endothelial cells while adenoviral-mediated CSE overexpression inhibited their release. Administration of PAG to pregnant mice induced hypertension, liver damage, and promoted abnormal labyrinth vascularisation in the placenta and decreased fetal growth. Finally, a slow releasing, H2S-generating compound, GYY4137, inhibited circulating sFlt-1 and sEng levels and restored fetal growth that was compromised by PAG-treatment demonstrating that the effect of CSE inhibitor was due to inhibition of H2S production. These results imply that endogenous H2S is required for healthy placental vasculature and a decrease in of CSE/H2S activity may contribute to the pathogenesis of preeclampsia. References [1] S. Ahmad, A. Ahmed, Elevated placental soluble vascular endothelial growth factor receptor-1 inhibits angiogenesis in preeclampsia, Circ Res., 95 (2004), pp. 884–891. [2] G. Yang, et al., H2S as a physiologic vasorelaxant: hypertension in mice with deletion of cystathionine gamma-lyase, Science, 322 (2008), pp. 587–590. [3] A. Papapetropoulos, et al., Hydrogen sulfide is an endogenous stimulator of angiogenesis, Proc Natl Acad Sci USA, 106 (2009), pp. 21972–21977.

MHC class II binding prediction by molecular docking

Proteins of the Major Histocompatibility Complex (MHC) bind self and nonself peptide antigens or epitopes within the cell and present them at the cell surface for recognition by T cells. All T-cell epitopes are MHC binders but not all MCH binders are T-cell epitopes. The MHC class II proteins are extremely polymorphic. Polymorphic residues cluster in the peptide-binding region and largely determine the MHC's peptide selectivity. The peptide binding site on MHC class II proteins consist of five binding pockets. Using molecular docking, we have modelled the interactions between peptide and MHC class II proteins from locus DRB1. A combinatorial peptide library was generated by mutation of residues at peptide positions which correspond to binding pockets (so called anchor positions). The binding affinities were assessed using different scoring functions. The normalized scoring functions for each amino acid at each anchor position were used to construct quantitative matrices (QM) for MHC class II binding prediction. Models were validated by external test sets comprising 4540 known binders. Eighty percent of the known binders are identified in the best predicted 15% of all overlapping peptides, originating from one protein. © 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dysregulation of placental cystathionine-β-synthase promotes fetal growth restriction

Fetal growth restriction (FGR) is characterized by the birth weight and body mass below the tenth percentile for gestational age. FGR is a major cause of perinatal morbidity and mortality and babies born with FGR are prone to develop cardiovascular diseases later in life. The underlying pathology of FGR is inadequate placental transfer of nutrients from mother to fetus, which can be caused by placental insufficiency. Hydrogen sulfide (H2S), a gaseous messenger is produced endogenously by cystathionine-lyase (Cth), cystathionine-β-synthase (CBS) and 3-mercaptopyruvate sulfurtransferase (3-MST), which are present in human placenta. Recently, we demonstrated that the dysregulation of H2S/Cth pathway is associated with preeclampsia and blockade of CSE activity induces preeclampsia-like condition in pregnant mice. We hypothesized that defect in H2S pathways promote FGR and H2S donor restores fetal growth in mice where CBS or CSE activity has been compromised. Western blotting and qPCR revealed that placental CBS expressions were significantly reduced in women with FGR. ELISA analysis showed reduced placental growth factor production (PlGF) from first trimester (8–12 weeks gestation) human placental explants following inhibition of CBS activity by aminooxyacetic acid (AOA). Administration of AOA to pregnant mice had no effects on blood pressure, but caused fetal growth restriction. This was associated with reduced PlGF production. Histological analysis revealed a reduction in the placental junction zone, within which trophoblast giant cells and glycogen cells were less prominent in CBS inhibitor treated mice. These results imply that placental CBS is required for placental development and that dysregulation of CBS activity may contribute to the pathogenesis of FGR but not preeclampsia.

Dysregulation of placental cystathionine-β-synthase impact on fetal growth restriction

INTRODUCTION: Fetal growth restriction (FGR), which causes perinatal morbidity and mortality, is characterized by birth weight and body mass being below 10th percentile for gestational age. FGR babies are prone to develop cardiovascular diseases later in life. Inadequate placental transfer of nutrients from mother to fetus due to placental insufficiency is considered the underlying cause of FGR. Recently, we demonstrated that blockade of cystathionine-γ-lyase (CSE) activity induces preeclampsia-like condition in pregnant mice. We hypothesized that defect in cystathionine-β-synthase (CBS) / H2S pathway may promote FGR. METHODS: Placental CBS expressions were determined in women with FGR (n=9) and normal controls (n=14) by Western blotting and real-time qPCR. ELISA was used to determine angiogenic factors levels in plasma and first-trimester (8–12 weeks gestation) human placental explants. Time pregnant mice were treated with CBS inhibitor, aminooxyacetic acid (AOA). Mean arterial blood pressure (MBP), histological assessments of placenta and embryos were performed. RESULTS: Placental CBS expressions were significantly reduced in women with FGR. Inhibition of CBS activity by AOA reduced PlGF production from first-trimester human placental explants, Administration of AOA to pregnant mice had no effects on blood pressure, but caused fetal growth restriction, which was associated with reduced placental PlGF production. Histological analysis revealed a reduction in the placental junction zone, within which trophoblast giant cells and glycogen cells were less prominent in CBS inhibitor-treated animals. Furthermore, H2S donor GYY4137 treatment restored fetal growth in pregnant mice exposed to high level of sFlt-1. CONCLUSIONS: These results imply that placental CBS is required for placental development and that dysregulation of CBS activity may contribute to the pathogenesis of FGR but not preeclampsia opening up the therapeutic potentials of H2S therapy in this condition.