Peptide binding prediction for the human class II MHC allele HLA-DP2:a molecular docking approach

MHC class II proteins bind oligopeptide fragments derived from proteolysis of pathogen antigens, presenting them at the cell surface for recognition by CD4+ T cells. Human MHC class II alleles are grouped into three loci: HLA-DP, HLA-DQ and HLA-DR. In contrast to HLA-DR and HLA-DQ, HLA-DP proteins have not been studied extensively, as they have been viewed as less important in immune responses than DRs and DQs. However, it is now known that HLA-DP alleles are associated with many autoimmune diseases. Quite recently, the X-ray structure of the HLA-DP2 molecule (DPA*0103, DPB1*0201) in complex with a self-peptide derived from the HLA-DR a-chain has been determined. In the present study, we applied a validated molecular docking protocol to a library of 247 modelled peptide-DP2 complexes, seeking to assess the contribution made by each of the 20 naturally occurred amino acids at each of the nine binding core peptide positions and the four flanking residues (two on both sides).

Peptide length significantly influences in vitro affinity for MHC class II molecules

Class II Major Histocompatibility Complex (MHC) molecules have an open-ended binding groove which can accommodate peptides of varying lengths. Several studies have demonstrated that peptide flanking residues (PFRs) which lie outside the core binding groove can influence peptide binding and T cell recognition. By using data from the AntiJen database we were able to characterise systematically the influence of PFRs on peptide affinity for MHC class II molecules.

Static energy analysis of MHC class I and class II peptide-binding affinity

Antigenic peptide is presented to a T-cell receptor (TCR) through the formation of a stable complex with a major histocompatibility complex (MHC) molecule. Various predictive algorithms have been developed to estimate a peptide's capacity to form a stable complex with a given MHC class II allele, a technique integral to the strategy of vaccine design. These have previously incorporated such computational techniques as quantitative matrices and neural networks. A novel predictive technique is described, which uses molecular modeling of predetermined crystal structures to estimate the stability of an MHC class II-peptide complex. The structures are remodeled, energy minimized, and annealed before the energetic interaction is calculated.

EpiTOP—a proteochemometric tool for MHC class II binding prediction

Motivation: T-cell epitope identification is a critical immunoinformatic problem within vaccine design. To be an epitope, a peptide must bind an MHC protein. Results: Here, we present EpiTOP, the first server predicting MHC class II binding based on proteochemometrics, a QSAR approach for ligands binding to several related proteins. EpiTOP uses a quantitative matrix to predict binding to 12 HLA-DRB1 alleles. It identifies 89% of known epitopes within the top 20% of predicted binders, reducing laboratory labour, materials and time by 80%. EpiTOP is easy to use, gives comprehensive quantitative predictions and will be expanded and updated with new quantitative matrices over time.

Predicting class II MHC-Peptide binding:a kernel based approach using similarity scores

Background - Modelling the interaction between potentially antigenic peptides and Major Histocompatibility Complex (MHC) molecules is a key step in identifying potential T-cell epitopes. For Class II MHC alleles, the binding groove is open at both ends, causing ambiguity in the positional alignment between the groove and peptide, as well as creating uncertainty as to what parts of the peptide interact with the MHC. Moreover, the antigenic peptides have variable lengths, making naive modelling methods difficult to apply. This paper introduces a kernel method that can handle variable length peptides effectively by quantifying similarities between peptide sequences and integrating these into the kernel. Results - The kernel approach presented here shows increased prediction accuracy with a significantly higher number of true positives and negatives on multiple MHC class II alleles, when testing data sets from MHCPEP [1], MCHBN [2], and MHCBench [3]. Evaluation by cross validation, when segregating binders and non-binders, produced an average of 0.824 AROC for the MHCBench data sets (up from 0.756), and an average of 0.96 AROC for multiple alleles of the MHCPEP database. Conclusion - The method improves performance over existing state-of-the-art methods of MHC class II peptide binding predictions by using a custom, knowledge-based representation of peptides. Similarity scores, in contrast to a fixed-length, pocket-specific representation of amino acids, provide a flexible and powerful way of modelling MHC binding, and can easily be applied to other dynamic sequence problems.

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).

Towards the in silico identification of class II restricted T-cell epitopes:a partial least squares iterative self-consistent algorithm for affinity prediction

Motivation: The immunogenicity of peptides depends on their ability to bind to MHC molecules. MHC binding affinity prediction methods can save significant amounts of experimental work. The class II MHC binding site is open at both ends, making epitope prediction difficult because of the multiple binding ability of long peptides. Results: An iterative self-consistent partial least squares (PLS)-based additive method was applied to a set of 66 pep- tides no longer than 16 amino acids, binding to DRB1*0401. A regression equation containing the quantitative contributions of the amino acids at each of the nine positions was generated. Its predictability was tested using two external test sets which gave r pred =0.593 and r pred=0.655, respectively. Furthermore, it was benchmarked using 25 known T-cell epitopes restricted by DRB1*0401 and we compared our results with four other online predictive methods. The additive method showed the best result finding 24 of the 25 T-cell epitopes. Availability: Peptides used in the study are available from http://www.jenner.ac.uk/JenPep. The PLS method is available commercially in the SYBYL molecular modelling software package. The final model for affinity prediction of peptides binding to DRB1*0401 molecule is available at http://www.jenner.ac.uk/MHCPred. Models developed for DRB1*0101 and DRB1*0701 also are available in MHC- Pred

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.

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.

Major Histocompatibility Complex (MHC) Class II sequence polymorphism in long-finned pilot whale (Globicephala melas) from the North Atlantic

Funding Silvia S. Monteiro and Marisa Ferreira were supported by a Ph.D. grant from Fundação para a Ciência e Tecnologia (ref SFRH/BD/38735/2007 and SFRH/BD/30240/2006, respectively). Alfredo López was supported by a postdoctoral grant from Fundação para a Ciência e Tecnologia (ref SFRH/BPD/82407/2011). Catarina Eira is supported by CESAM (UID/AMB/50017), from FCT/MEC through national funds and FEDER (PT2020, Compete 2020). The work related with strandings and tissue collection in Portugal was partially supported by the SafeSea Project EEAGrants PT 0039 (supported by Iceland, Liechtenstein and Norway through the EEA Financial Mechanism), by the Project MarPro–Life09 NAT/PT/000038 (funded by the European Union–Program Life+) and by the project CetSenti FCT RECI/AAG-GLO/0470/2012; FCOMP-01-0124-FEDER-027472 (Funded by the Program COMPETE and Fundação para a Ciência e Tecnologia).

Two years survival rate of Class II ART restorations in primary molars using two ways to avoid saliva contamination

AIM To compare the survival rates of Class II Atraumatic Restorative Treatment (ART) restorations placed in primary molars using cotton rolls or rubber dam as isolation methods. METHODS A total of 232 children, 6-7 years old, both genders, were selected having one primary molar with proximal dentine lesion. The children were randomly assigned into two groups: control group with Class II ART restoration made using cotton rolls and experimental group using rubber dam. The restorations were evaluated by eight calibrated evaluators (Kappa > 0.8) after 6, 12, 18 and 24 months. RESULTS A total of 48 (20.7%) children were considered dropout, after 24 months. The cumulative survival rate after 6, 12, 18 and 24 months was 61.4%, 39.0%, 29.1% and 18.0%, respectively for the control group, and 64.1%, 55.1%, 40.1% and 32.1%, respectively for the rubber dam group. The log rank test for censored data showed no statistical significant difference between the groups (P = 0.07). The univariate Cox Regression showed no statistical significant difference after adjusting for independent variables (P > 0.05). CONCLUSION Both groups had similar survival rates, and after 2 years, the use of rubber dam does not increase the success of Class II ART restorations significantly.

Segmental LeFort I osteotomy for treatment of a class III malocclusion with temporomandibular disorder

This article reports the case of a 19-year-old young man with Class III malocclusion and posterior crossbite with concerns about temporomandibular disorder (TMD), esthetics and functional problems. Surgical-orthodontic treatment was carried out by decompensation of the mandibular incisors and segmentation of the maxilla in 4 pieces, which allowed expansion and advancement. Remission of the signs and symptoms occurred after surgical-orthodontic intervention. The maxillary dental arch presented normal transverse dimension. Satisfactory static and functional occlusion and esthetic results were achieved and remained stable. Three years after the surgical-orthodontic treatment, no TMD sign or symptom was observed and the occlusal results had not changed. When vertical or horizontal movements of the maxilla in the presence of moderate maxillary constriction are necessary, segmental LeFort I osteotomy can be an important part of treatment planning.

Dimensões dos arcos dentários na má oclusão Classe II, divisão 1, com deficiência mandibular

OBJETIVO: identificar alterações dimensionais nos arcos dentários superior e inferior na má oclusão Classe II, divisão 1, com deficiência mandibular (Padrão esquelético II). MÉTODOS: 48 pacientes com má oclusão Classe II, igualmente divididos quanto ao gênero, foram comparados com 51 indivíduos com oclusão normal, sendo 22 do gênero masculino e 29 do gênero feminino. Todos os 99 indivíduos estavam no estágio de dentadura permanente, com os segundos molares permanentes irrompidos ou em irrupção, com idade média de 12 anos e 5 meses (desvio-padrão de 1 ano e 3 meses), numa faixa etária oscilando entre 11 anos e 4 meses e 20 anos. CONCLUSÃO: os resultados permitem concluir que, na má oclusão Classe II, divisão 1 com deficiência mandibular, o arco dentário superior encontra-se alterado, mostrando-se atrésico e mais longo, enquanto o arco dentário inferior é pouco influenciado pela discrepância sagital de Classe II.

MHC class I and II expression in juvenile dermatomyositis skeletal muscle

Objective To assess MHC I and II expressions in muscle fibres of juvenile dermatomyositis (JDM) and compare with the expression in polymyositis (PM), dermatomyositis (DM) and dystrophy. Patients and methods Forty-eight JDM patients and 17 controls (8 PM, 5 DM and 4 dystrophy) were studied. The mean age at disease onset was 7.1 +/- 3.0 years and the mean duration of weakness before biopsy was 9.4 +/- 12.9 months. Routine histochemistry and immunohistochemistry (StreptABComplex/HRP) for MHC I and II (Dakopatts) were performed on serial frozen muscle sections in all patients. Mann-Whitney, Kruskal Wallis, chi-square and Fisher`s exact statistical methods were used. Results MHC I expression was positive in 47 (97.9%) JDM cases. This expression was observed independent of time of disease corticotherapy previous to muscle biopsy and to the grading of inflammation observed in clinical, laboratorial and histological parameters. The expression of MHC I was similar on JDM, PM and DM, and lower in dystrophy. On the other hand, MHC II expression was positive in just 28.2% of JDM cases was correlated to histological features as inflammatory infiltrate, increased connective tissue and VAS for global degree of abnormality (p < 0.05). MCH II expression was similar in DM/PM and lower in JDM and dystrophy, and it was based on the frequency of positive staining rather than to the degree of the MCH II expression. Conclusions MHC I expression in muscle fibres is a premature and late marker of JDM patient independent to corticotherapy, and MHC II expression was lower in JDM than in PM and DM.

Immunolocalization and pathological alterations following Strongyloides venezuelensis infection in the lungs and the intestine of MHC class I or II deficient mice

The present study, investigated the mechanisms involved in the immune responses of Major Histocompatibility Complex class I or class II knockout mice, following Strongyloides venezuelensis infection. Wild-type C57BL/6 (WT), MHC II(-/-) and MHC I(-/-) mice were individually inoculated with 3000 larvae (U) of S. venezuelensis and sacrificed on days 1, 3, 5, 8, 13 and 21 post-infection (p.i.). Samples of blood, lungs and small intestines were collected. The tissue samples were stained with hematoxylineosin for the pathological analysis. The presence of the parasite was demonstrated by immunoperoxidase analysis. MHC II(-/-) mice presented a significantly higher number of adult worms recovered from the small intestine on day 5 p.i. and presented elevated numbers of eggs in the feces. The infection by S. venezuelensis was completely eliminated 13 days after infection in WT as well as in MHC I(-/-) mice. In MHC II(-/-) mice, eggs and adult worms were still found on day 21 p.i., however, there was a significant reduction in their numbers. In the lung, the parasite was observed in MHC I(-/-) on day 1 p.i. and in MHC II(-/-) mice on days 1 and 5 p.i. In the small intestine of WT mice, a larger number of parasites were observed on day 8 p.i. and their absence was observed after day 13 p.i. Through immunohistochemistry analysis, the parasite was detected in the duodenum of WT on days 5 and 8 p.i., and in knockout mice on days 5, 8 and 13 p.i.; as well as in posterior portions of the small intestine in MHC I(-/-) and MHC II(-/-) on day 13 p.i., a finding which was not observed in WT mice. We concluded that immunohistochemistry analysis contributed to a more adequate understanding of the parasite localization in immunodeficient hosts and that the findings aid in the interpretation of immunopathogenesis in Strongyloides infection. (C) 2008 Elsevier B.V. All rights reserved.