NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction

Nielsen, Morten; Lund, Ole

doi:10.1186/1471-2105-10-296

Cited by 471 publications

(439 citation statements)

References 32 publications

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“…[3][4][5][6][7] However, because these algorithms are based on a limited amount of experimental peptide-binding data, prediction is only possible for a small fraction of known MHC proteins. Many groups have conducted sequencing analyses of naturally presented MHC peptides from both native membrane-bound molecules 8 and recombinant membrane-bound or secreted molecules.…”

Section: Introductionmentioning

confidence: 99%

The impact of human leukocyte antigen (HLA) micropolymorphism on ligand specificity within the HLA-B*41 allotypic family

Bade‐Doeding¹,

Theodossis²,

Gras³

et al. 2010

Haematologica

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The online version of this article has a Supplementary Appendix. BackgroundPolymorphic differences between human leukocyte antigen (HLA) molecules affect the specificity and conformation of their bound peptides and lead to differential selection of the T-cell repertoire. Mismatching during allogeneic transplantation can, therefore, lead to immunological reactions. Design and MethodsWe investigated the structure-function relationships of six members of the HLA-B*41 allelic group that differ by six polymorphic amino acids, including positions 80, 95, 97 and 114 within the antigen-binding cleft. Peptide-binding motifs for B*41:01, *41:02, *41:03, *41:04, *41:05 and *41:06 were determined by sequencing self-peptides from recombinant B*41 molecules by electrospray ionization tandem mass spectrometry. The crystal structures of HLA-B*41:03 bound to a natural 16-mer self-ligand (AEMYGSVTEHPSPSPL) and HLA-B*41:04 bound to a natural 11-mer self-ligand (HEEAVSVDRVL) were solved. ResultsPeptide analysis revealed that all B*41 alleles have an identical anchor motif at peptide position 2 (glutamic acid), but differ in their choice of C-terminal pΩ anchor (proline, valine, leucine). Additionally, B*41:04 displayed a greater preference for long peptides (>10 residues) when compared to the other B*41 allomorphs, while the longest peptide to be eluted from the allelic group (a 16mer) was obtained from B*41:03. The crystal structures of HLA-B*41:03 and HLA-B*41:04 revealed that both alleles interact in a highly conserved manner with the terminal regions of their respective ligands, while micropolymorphism-induced changes in the steric and electrostatic properties of the antigen-binding cleft account for differences in peptide repertoire and auxiliary anchoring. ConclusionsDifferences in peptide repertoire, and peptide length specificity reflect the significant functional evolution of these closely related allotypes and signal their importance in allogeneic transplantation, especially B*41:03 and B*41:04, which accommodate longer peptides, creating structurally distinct peptide-HLA complexes.

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Section: Introductionmentioning

confidence: 99%

The impact of human leukocyte antigen (HLA) micropolymorphism on ligand specificity within the HLA-B*41 allotypic family

Bade‐Doeding¹,

Theodossis²,

Gras³

et al. 2010

Haematologica

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“…In this study, for MHC Class II peptide prediction, we used artificial neural network based method NN-align, which was evaluated by 26 human MHC Class II alleles. 17 IC50 is a measure of half of a compound's concentration that would be required to inhibit biological effectiveness. Lower IC50 calculation refl ects a drug's effectiveness in a lower concentration.…”

Section: Discussionmentioning

confidence: 99%

“…In case of MHC Class II prediction, artifi cial neural network alignment method was used. 17 For selection of all the MHC binding peptides, MHC IC50 score was below 250 nM. The B cell epitopes that were situated in the conserved domain region of alpha-delta-bungarotoxin-4 were selected by analyzing Kolaskar and Tangaonkar antigenicity scale.…”

Section: Prediction Of Mhc Binding Peptide and B-cell Epitopesmentioning

confidence: 99%

An immunoinformatics approach toward epitope-based vaccine design through computational tools from Bungarus caeruleus’s neurotoxin

Ashraf¹,

Barua²,

Saha³

et al. 2014

J Young Pharm.

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Objective:This study aims to analyze and predict the possibility of designing a vaccine that could make humans immune to krait toxin. Materials and Methods: Bungarus caeruleus or common Indian krait is a member of the venomous big four snake species. Its venom contains a neurotoxic protein alpha-delta-bungarotoxin-4 and is found to be responsible for human death 4-8 h after the snake bite. Antigenicity of this protein was determined by Hopp and Woods and Kolaskar and Tangaonkar method. We predicted major histocompatibility complex (MHC) Class I and MHC Class II binding peptides of antigenic protein from alpha-deltabungarotoxin-4, which are an important determinant for protection of host from snake bite. Fragments selected through this study revealed higher effi ciency binders. Result: Higher percentages of their atoms are directly involved in binding in comparison with larger molecules. These potential fragments, therefore can be a novel tool in the arena of cross protection to develop host specifi c antibodies in different objectives. We operated AllerHunter for predicting allergenicity based on the structural and physiochemical properties of whole alpha-delta-bungarotoin-4, and it was found to be nonallergen. The potential epitopes of alpha-delta-bungarotoxin-4 were found to be located at sequences "GENLCYTKM" and "FCSSRGKVI" and these were found to be suffi cient for eliciting the desired immune response. In this study, a hypothetical immunization is developed, which demands more validation and study. It can be emphasized that such predictive in silico study requires an in vivo experiments comprehensibly, which must be assured to validate such approaches. Hence, our goal was to identify a conformationally biased epitope sequence, which aims to provide a new paradigm to design epitope-based peptide vaccines in order to alleviate immunological infections from Krait neurotoxin. Conclusion: Computational techniques manifest the attention of Krait neurotoxin as crucial immunodiagnostic tool for fatal venom proved that most snake venoms are in poorly characterized although they are biologically important proteins with therapeutic potentialities.

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“…To our knowledge, there are only two servers for peptide HLA-DP2 binding prediction: NetMHCII 32 and IEDB. 29 Using our test set of 457 known binders, we compared the performance of these two servers to that of MD-QMnap (anchors þ cross terms).…”

Section: Comparison To Existing Servers For Hla-dp2 Binding Predictionmentioning

confidence: 99%

HLA‐DP2 binding prediction by molecular dynamics simulations

et al. 2011

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Major histocompatibility complex (MHC) II proteins bind peptide fragments derived from pathogen antigens and present them at the cell surface for recognition by T cells. MHC proteins are divided into Class I and Class II. Human MHC Class II alleles are grouped into three loci: HLA-DP, HLA-DQ, and HLA-DR. They are involved in many autoimmune diseases. In contrast to HLA-DR and HLA-DQ proteins, the X-ray structure of the HLA-DP2 protein has been solved quite recently. In this study, we have used structure-based molecular dynamics simulation to derive a tool for rapid and accurate virtual screening for the prediction of HLA-DP2-peptide binding. A combinatorial library of 247 peptides was built using the ''single amino acid substitution'' approach and docked into the HLA-DP2 binding site. The complexes were simulated for 1 ns and the short range interaction energies (Lennard-Jones and Coulumb) were used as binding scores after normalization. The normalized values were collected into quantitative matrices (QMs) and their predictive abilities were validated on a large external test set. The validation shows that the best performing QM consisted of Lennard-Jones energies normalized over all positions for anchor residues only plus cross terms between anchor-residues.

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NN-align. An artificial neural network-based alignment algorithm for MHC class II peptide binding prediction

Cited by 471 publications

References 32 publications

The impact of human leukocyte antigen (HLA) micropolymorphism on ligand specificity within the HLA-B*41 allotypic family

The impact of human leukocyte antigen (HLA) micropolymorphism on ligand specificity within the HLA-B*41 allotypic family

An immunoinformatics approach toward epitope-based vaccine design through computational tools from Bungarus caeruleus’s neurotoxin

HLA‐DP2 binding prediction by molecular dynamics simulations

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