MULTIPRED: A computational system for prediction of promiscuous HLA binding peptides

MULTIPRED is a web-based computational system for the prediction of peptide binding to multiple molecules ( proteins) belonging to human leukocyte antigens (HLA) class I A2, A3 and class II DR supertypes. It uses hidden Markov models and artificial neural network methods as predictive engines. A novel data representation method enables MULTIPRED to predict peptides that promiscuously bind multiple HLA alleles within one HLA supertype. Extensive testing was performed for validation of the prediction models. Testing results show that MULTIPRED is both sensitive and specific and it has good predictive ability ( area under the receiver operating characteristic curve A(ROC) > 0.80). MULTIPRED can be used for the mapping of promiscuous T-cell epitopes as well as the regions of high concentration of these targets termed T-cell epitope hotspots. MULTIPRED is available at http:// antigen.i2r.a-star.edu.sg/ multipred/.

Prediction of HLA-DQ3.2 beta ligands: evidence of multiple registers in class II binding peptides

Motivation: While processing of MHC class II antigens for presentation to helper T-cells is essential for normal immune response, it is also implicated in the pathogenesis of autoimmune disorders and hypersensitivity reactions. Sequence-based computational techniques for predicting HLA-DQ binding peptides have encountered limited success, with few prediction techniques developed using three-dimensional models. Methods: We describe a structure-based prediction model for modeling peptide-DQ3.2 beta complexes. We have developed a rapid and accurate protocol for docking candidate peptides into the DQ3.2 beta receptor and a scoring function to discriminate binders from the background. The scoring function was rigorously trained, tested and validated using experimentally verified DQ3.2 beta binding and non-binding peptides obtained from biochemical and functional studies. Results: Our model predicts DQ3.2 beta binding peptides with high accuracy [area under the receiver operating characteristic (ROC) curve A(ROC) > 0.90], compared with experimental data. We investigated the binding patterns of DQ3.2 beta peptides and illustrate that several registers exist within a candidate binding peptide. Further analysis reveals that peptides with multiple registers occur predominantly for high-affinity binders.

Predictive vaccinology: Optimisation of predictions using support vector machine classifiers

Promiscuous human leukocyte antigen (HLA) binding peptides are ideal targets for vaccine development. Existing computational models for prediction of promiscuous peptides used hidden Markov models and artificial neural networks as prediction algorithms. We report a system based on support vector machines that outperforms previously published methods. Preliminary testing showed that it can predict peptides binding to HLA-A2 and -A3 super-type molecules with excellent accuracy, even for molecules where no binding data are currently available.

Inhibition of protein interactions with the beta(2) sliding clamp of Escherichia coli DNA polymerase III by peptides from beta(2)-binding proteins

The sliding clamp of the Escherichia coli replisome is now understood to interact with many proteins involved in DNA synthesis and repair. A universal interaction motif is proposed to be one mechanism by which those proteins bind the E. coli sliding clamp, a homodimer of the beta subunit, at a single site on the dimer. The numerous beta(2)-binding proteins have various versions of the consensus interaction motif, including a related hexameric sequence. To determine if the variants of the motif could contribute to the competition of the beta-binding proteins for the beta(2) site, synthetic peptides derived from the putative beta(2)-binding motifs were assessed for their abilities to inhibit protein-beta(2) interactions, to bind directly to beta(2), and to inhibit DNA synthesis in vitro. A hierarchy emerged, which was consistent with sequence similarity to the pentameric consensus motif, QL(S/D)LF, and peptides containing proposed hexameric motifs were shown to have activities comparable to those containing the consensus sequence. The hierarchy of peptide binding may be indicative of a competitive hierarchy for the binding of proteins to beta(2) in various stages or circumstances of DNA replication and repair.

Structural basis for the specificity of bipartite nuclear localization sequence binding by importin-α

Importin-alpha is the nuclear import receptor that recognizes cargo proteins carrying conventional basic monopartite and bipartite nuclear localization sequences (NLSs) and facilitates their transport into the nucleus. Bipartite NLSs contain two clusters of basic residues, connected by linkers of variable lengths. To determine the structural basis of the recognition of diverse bipartite NLSs by mammalian importin-alpha, we co-crystallized a non-autoinhibited mouse receptor protein with peptides corresponding to the NLSs from human retinoblastoma protein and Xenopus laevis phosphoprotein N1N2, containing diverse sequences and lengths of the linker. We show that the basic clusters interact analogously in both NLSs, but the linker sequences adopt different conformations, whereas both make specific contacts with the receptor. The available data allow us to draw general conclusions about the specificity of NLS binding by importin-alpha and facilitate an improved definition of the consensus sequence of a conventional basic/bipartite NLS (KRX10-12KRRK) that can be used to identify novel nuclear proteins.

Potent T cell response to a class I-binding 13-mer viral epitope and the influence of HLA micropolymorphism in controlling epitope length

The BZLF1 antigen of Epstein-Barr virus includes three overlapping sequences of different lengths that conform to the binding motif of human leukocyte antigen (HLA) B*3501. These 9-mer ((56)LPOGQLTAy(64)), 11-mer ((54)EPLPQGQLTAy(64)), and 13-mer ((52)LPEPLPQGQLTAY(64)) peptides all bound well to B*3501; however, the CTL response in individuals expressing this HILA allele was directed strongly and exclusively towards the 11-mer peptide. In contrast, EBV-exposed donors expressing HLA B*3503 showed no significant CTL response to these peptides because the single amino acid difference between B*3501 and B*3503 within the F pocket inhibited HLA binding by these peptides. The extraordinarily long 13-mer peptide was the target for the CTL response in individuals expressing B*3508, which differs from B*3501 at a single position within the D pocket (B*3501, 156 Leucine; B*3508, 156 Arginine). This minor difference was shown to enhance binding of the 13-mer peptide, presumably through a stabilizing interaction between the negatively charged glutamate at position 3 of the peptide and the positively charged arginine at HLA position 156. The 13-mer epitope defined in this study represents the longest class I-binding viral epitope identified to date as a minimal determinant. Furthermore, the potency of the response indicates that peptides of this length do not present a major structural barrier to CTL recognition.

Determination of alpha-conotoxin binding modes on neuronal nicotinic acetylcholine receptors

alpha-Conotoxins, from cone snails, and alpha-neurotoxins, from snakes, are competitive inhibitors of nicotinic acetylcholine receptors (nAChRs) that have overlapping binding sites in the ACh binding pocket. These disulphide-rich peptides are used extensively as tools to localize and pharmacologically characterize specific nAChRs subtypes. Recently, a homology model based on the high-resolution structure of an ACh binding protein (AChBP) allowed the three-fingered alpha-neurotoxins to be docked onto the alpha7 nAChR. To investigate if alpha-conotoxins interact with the nAChR in a similar manner, we built homology models of human alpha7 and alpha3beta2 nAChRs, and performed docking simulations of alpha-conotoxins ImI, PnIB, PnIA and MII using the program GOLD. Docking revealed that alpha-conotoxins have a different mode of interaction compared with alpha-neurotoxins, with surprisingly few nAChR residues in common between their overlapping binding sites. These docking experiments show that Imi and PnIB bind to the ACh binding pocket via a small cavity located above the beta9/beta10 hairpin of the (+)alpha7 nAChR subunit. Interestingly, PnIB, PnIA and MII were found to bind in a similar location on alpha7 or alpha3beta2 receptors mostly through hydrophobic interactions, while ImI bound further from the ACh binding pocket, mostly through electrostatic interactions. These findings, which distinguish alpha-conotoxin and alpha-neurotoxin binding modes, have implications for the rational design of selective nAChR antagonists. Copyright (C) 2004 John Wiley Sons, Ltd.

Novel natriuretic peptides from the venom of the inland taipan (Oxyuranus microlepidotus): isolation, chemical and biological characterisation

Three natriuretic-like peptides (TNP-a, TNP-b, and TNP-c) were isolated from the venom of Oxyuranus microlepidotus (inland taipan) and were also present in the venoms of Oxyuranus scutellatus canni (New Guinea taipan) and Oxyuranus scutellatus scutellatus (coastal taipan). They were isolated by HPLC, characterised by mass spectrometry and Edman analysis, and consist of 35-39 amino acid residues. These molecules differ from ANP/BNP through replacement of invariant residues within the 17-membered ring structure and by inclusion of proline residues in the C-terminal tail. TNP-c was equipotent to ANP in specific GC-A assays or aortic ring assays whereas TNP-a and TNP-b were either inactive (GC-A over-expressing cells and endothelium-denuded aortic rings) or weakly active (endothelium-in tact aortic rings). TNP-a and TNP-b were also unable to competitively inhibit the binding of TNP-c in endothelium-denuded aortae (GC-A) or endothelium-in tact aortae (NPR-C). Thus, these naturally occurring isoforms provide a new platform for further investigation of structure-function relationships of natriuretic peptides. (C) 2004 Elsevier Inc. All rights reserved.

Comparative agonist/antagonist responses in mutant human C5a receptors define the ligand binding site

The C terminus is responsible for all of the agonist activity of C5a at human C5a receptors (C5aRs). In this report we have mapped the ligand binding site on the C5aR using a series of agonist and antagonist peptide mimics of the C terminus of C5a as well as receptors mutated at putative interaction sites ( Ile(116), Arg(175), Arg(206), Glu(199), Asp(282), and Val(286)). Agonist peptide 1 (Phe-Lys-Pro-D-cyclohexylalanine-cyclohexylalanine-D-Arg) can be converted to an antagonist by substituting the bulkier Trp for cyclohexylalanine at position 5 ( peptide 2). Conversely, mutation of C5aR transmembrane residue Ile(116) to the smaller Ala (I116A) makes the receptor respond to peptide 2 as an agonist (Gerber, B. O., Meng, E. C., Dotsch, V., Baranski, T. J., and Bourne, H. R. (2001) J. Biol. Chem. 276, 3394 - 3400). However, a potent cyclic hexapeptide antagonist, Phe-cyclo-[Orn-Pro-D-cyclohexylalanine-Trp-Arg] ( peptide 3), derived from peptide 2 and which binds to the same receptor site, remains a full antagonist at I116AC5aR. This suggests that although the residue at position 5 might bind near to Ile(116), the latter is not essential for either activation or antagonism. Arg(206) and Arg(175) both appear to interact with the C-terminal carboxylate of C5a agonist peptides, suggesting a dynamic binding mechanism that may be a part of a receptor activation switch. Asp(282) has been previously shown to interact with the side chain of the C-terminal Arg residue, and Glu(199) may also interact with this side chain in both C5a and peptide mimics. Using these interactions to orient NMR-derived ligand structures in the binding site of C5aR, a new model of the interaction between peptide antagonists and the C5aR is presented.

Extreme learning machine for predicting HLA-peptide binding

Machine learning techniques have been recognized as powerful tools for learning from data. One of the most popular learning techniques, the Back-Propagation (BP) Artificial Neural Networks, can be used as a computer model to predict peptides binding to the Human Leukocyte Antigens (HLA). The major advantage of computational screening is that it reduces the number of wet-lab experiments that need to be performed, significantly reducing the cost and time. A recently developed method, Extreme Learning Machine (ELM), which has superior properties over BP has been investigated to accomplish such tasks. In our work, we found that the ELM is as good as, if not better than, the BP in term of time complexity, accuracy deviations across experiments, and most importantly - prevention from over-fitting for prediction of peptide binding to HLA.

Site-specific labelling of proteins with a rigid lanthanide-binding tag

This paper describes a generic method for the site-specific attachment of lathanide complexes to proteins through a disulfide bond. The method is demonstrated by the attachment of a lanthanide-binding peptide tag to the single cysteine residue present in the N-terminal DNA-binding domain of the Echerichia coli arginine repressor. Complexes with Y3+, Tb3+, Dy3+, Ho3+, Er3+, Tm3+ and Yb3+ ions were formed and analysed by NMR spectroscopy. Large pseudocontact shifts and residual dipolar couplings were induced by the lanthanide-binding tag in the protein NMR spectrum, a result indicating that the tag was rigidly attached to the protein. The axial components of the magnetic susceptibility anisostropy tensors determined for the different lanthanide ions were similarly but not identically oriented. A single tag with a single protein attachment site can provide different pseudocontact shifts from different magnetic susceptibility tensors and thus provide valuable nondegenerate long-range structure information in the determination of 3D protein structures by NMR spectroscopy.