New horizons in mouse immunoinformatics: reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity

Quantitative structure-activity relationship (QSAR) analysis is a main cornerstone of modern informatic disciplines. Predictive computational models, based on QSAR technology, of peptide-major histocompatibility complex (MHC) binding affinity have now become a vital component of modern day computational immunovaccinology. Historically, such approaches have been built around semi-qualitative, classification methods, but these are now giving way to quantitative regression methods. The additive method, an established immunoinformatics technique for the quantitative prediction of peptide-protein affinity, was used here to identify the sequence dependence of peptide binding specificity for three mouse class I MHC alleles: H2-D(b), H2-K(b) and H2-K(k). As we show, in terms of reliability the resulting models represent a significant advance on existing methods. They can be used for the accurate prediction of T-cell epitopes and are freely available online ( http://www.jenner.ac.uk/MHCPred).     

Computational analysis on the binding of epitope peptide to human leukocyte antigen class I molecule A*2402 subtype

Immunological response induced by small amino peptide has attracted much recent attention in the field of immunotherapy. Wilms' tumor (WT1) protein is one of the potent tumor antigens inducing immunological response in mouse and human, because WT1 is over expressed in many types of leukemia and various kinds of solid tumors. A 9-mer peptide encoded in WT1 protein (CMTWNQMNL; amino acid 235-243) is known to serve as antigenic peptide for human leukocyte antigen (HLA)-A*2402 molecule. It was reported that the replacement of the second amino residue, which is deeply responsible for the peptide binding to HLA, induced strong immunological response compared to the natural peptide. In this study, 19 kinds of single amino substitutions were introduced at position 2 of this 9-mer WT1 peptide. We performed molecular dynamics simulation on the complex of each of WT1 epitope peptides and HLA-β2 micro globulin (β2m) molecule, and subsequently estimated the binding affinity using molecular mechanics/generalized-Born surface area method combined with normal mode analysis. Our computation indicated that the peptide containing M2Y or M2W mutation showed high binding affinity to the HLA-β2m molecule as well as the natural peptide. We have also examined the role of the residue at position 2 in peptide binding to HLA-β2m. The calculation showed that van der Waals interaction between the side chain of the residue at position 2 and hydrophobic residues inside B-pocket of HLA are important. These findings will be helpful to search other potent peptides that will enhance strong immunological response specific to HLA-A*2402 molecule.     

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).     

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.     

Dynamic interaction among the platform domain and two membrane-proximal immunoglobulin-like domains of class I major histocompatibility complex: normal mode analysis

Class I major histocompatibility complex (MHC) molecules have three domains, a platform domain and two membrane-proximal immunoglobulin-like domains, an alpha3 domain and a beta2-immunoglobulin (beta2m). To understand the dynamic interactions among the three domains, we simulated the behavior of a partial model deficient in beta2m and another model deficient in the alpha3 domain, by normal mode analysis. As a result, the partial model deficient in beta2m was more flexible in interdomain conformation than the other model. The lowest frequency modes (<2 cm(-1)) observed for the simulations of the partial model deficient in beta2m showed clear interdomain motions as if each domain moved like a rigid body. Such low frequencies and clear interdomain motions were not observed for the simulations of the other model, therefore the interdomain flexibility of the partial model deficient in beta2m may be due to the lowest frequency modes (<2 cm(-1)). These results suggest that beta2m contributes to maintaining the interdomain conformation of class I MHC molecules more than the alpha3 domain does, and may offer convincing evidence to support the notion that the alpha3 domain and beta2m do not have an equal influence on the structural stability of class I MHC molecules.     

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.     

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.     

Small molecule hydrogels based on a class of antiinflammatory agents

Here we report small molecule hydrogels formed by the combination of two N-(fluorenyl-methoxycarbonyl) amino acids, which belong to a novel class of antiinflammatory agents.     

Rational design of affinity peptide ligand by flexible docking simulation

Rational design of affinity peptide ligands of proteins by flexible docking simulation is performed using the SYBYL program package. This approach involves the use of experimental data to verify a scoring function that can be used to assess the affinity of a peptide for its target protein. The enzyme-linked immunosorbent assay (ELISA) data of several peptides displayed on phage surfaces for insulin and lysozyme, respectively, reported in literature are used for the purpose. It is found that the absolute values of the Dscore calculated from the docking correspond well to the ELISA data that relate to the affinity between the peptides and the target molecule. So, the Dscore function is used to assess the affinity of docked peptides in a pentapeptide library designed on the basis of protein (alpha-amylase) structure. As a result, a pentapeptide with a high Dscore value is selected and a hexapeptide (FHENWS) is built by linking serine to its C-terminal to lengthen the peptide. Molecular surface analysis with the MOLCAD program reveals that electrostatic interactions (including hydrogen bonds) and Van der Waals forces contribute to the affinity of the hexapeptide for alpha-amylase. Chromatographic experiments with the immobilized peptide have given further evidence for this observation. Adsorption isotherm described by the Langmuir equation indicates that the apparent binding constant of alpha-amylase to the immobilized hexapeptide was 2.5x10(5)L/mol. Finally, high affinity and specificity of the affinity adsorbent is exemplified by the purification of alpha-amylase from crude fermentation broth of Bacillus subtilis.     

Prediction of small molecule binding property of protein domains with Bayesian classifiers based on Markov chains

Accurate computational methods that can help to predict biological function of a protein from its sequence are of great interest to research biologists and pharmaceutical companies. One approach to assume the function of proteins is to predict the interactions between proteins and other molecules. In this work, we propose a machine learning method that uses a primary sequence of a domain to predict its propensity for interaction with small molecules. By curating the Pfam database with respect to the small molecule binding ability of its component domains, we have constructed a dataset of small molecule binding and non-binding domains. This dataset was then used as training set to learn a Bayesian classifier, which should distinguish members of each class. The domain sequences of both classes are modelled with Markov chains. In a Jack-knife test, our classification procedure achieved the predictive accuracies of 77.2% and 66.7% for binding and non-binding classes respectively. We demonstrate the applicability of our classifier by using it to identify previously unknown small molecule binding domains. Our predictions are available as supplementary material and can provide very useful information to drug discovery specialists. Given the ubiquitous and essential role small molecules play in biological processes, our method is important for identifying pharmaceutically relevant components of complete proteomes. The software is available from the author upon request.     

Oxazole-based peptide macrocycles: a new class of G-quadruplex binding ligands

Herein we report on the synthesis and DNA binding properties of a new class of water soluble oxazole-based peptide macrocycles that bind selectively to quadruplex DNA, with no detectable binding to duplex DNA. We have recently identified one quadruplex in the proto-oncogene c-kit that is suspected to act as a regulatory element for the expression of the c-kit gene. Here we provide the first example of a ligand binding to and stabilizing the c-kit quadruplex. Moreover, we show that these macrocycles show a preference for the c-kit quadruplex as compared to the human telomeric quadruplex.     

Mapping and expression pattern analysis of key components of the major histocompatibility complex class I antigen processing and presentation pathway in a representative human renal cell carcinoma cell line.

Renal cell carcinoma (RCC) represent approximately 5% of all cancer deaths. At the time of presentation, over 50% of the patients have already developed locally advanced or metastatic disease with five-year survival rates of less than 20%. Although relative resistant to conventional regimens, RCC are partially susceptible to T cell-based immunotherapy. To further develop this treatment modality, two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) was applied for both the mapping of the key components of the major histocompatibility complex (MHC) class I antigen processing and presentation machinery (APM) and the characterization of the constitutive and cytokine-regulated protein expression profiles in a representative human RCC cell line. The latter aspect is based on the fact, that the expression level of some of the APM components can be altered in response to interferon (IFN)-gamma treatment. Total cell lysates from untreated and IFN-gamma-treated tumor cells were separated on 2-D PAGE gels using broad range immobilized pH gradient (IPG) strips. Serial Western blot analyses using sets of APM-specific antibodies were performed to target the relevant protein spots. Protein verification was mostly accomplished via peptide mass finger-printing using matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS). To date, the majority of the APM-related components have been identified and mapped. In addition, the different protein expression profiles of untreated and IFN-gamma-treated RCC cells are under investigation.     

Prediction of microscopic structure and physical properties of complex fluid mixtures based on molecular simulation

Molecular simulation calculations are presented for two types of complex fluid mixtures, namely elastomer polymer mixtures and water–1-octanol binary and ternary mixtures. Elastomer polymers are used widely as membrane materials for gas separation. In this respect, the solubility and diffusion coefficient of gases need to be known accurately. Predictions for both properties are presented here. Water–1-octanol mixture is a widely used prototype system used to assess the partitioning of various chemical compounds with applications to chemical industry, biotechnology, etc. The microscopic structure of the water–1-octanol mixture is examined and the Gibbs free energy of solvation of four organic solutes is calculated. In all cases, detailed atomistic force fields are used to account for inter- and intra-molecular interactions. Simulation results are shown to be in excellent agreement with literature experimental data.     

Coupling protein complex analysis to peptide based proteomics

Proteolysis is a central component of most proteomics methods. Unfortunately much of the information relating to the structural diversity of proteins is lost during digestion. This paper describes a method in which the native proteome of yeast was subjected to preliminary fractionation by size exclusion chromatography (SEC) prior to trypsin digestion of SEC fractions and reversed phase chromatography-mass spectral analysis to identify tryptic peptides thus generated. Through this approach proteins associated with other proteins in high molecular mass complexes were recognized and identified. A focus of this work was on the identification of Hub proteins that associate with multiple interaction partners. A critical component of this strategy is to choose methods and conditions that maximize retention of native structure during the various stages of analysis prior to proteolysis, especially during cell lysis. Maximum survival of protein complexes during lysis was obtained with the French press and bead-beater methods of cell disruption at approximately pH 8 with 200 mM NaCl in the lysis buffer. Structure retention was favored by higher ionic strength, suggesting that hydrophobic effects are important in maintaining the structure of protein complexes. Recovery of protein complexes declined substantially with storage at any temperature, but storage at -20°C was best when low temperature storage was necessary. Slightly lower recovery was obtained with storage at -80°C while lowest recovery was achieved at 4°C. It was concluded that initial fractionation of native proteins in cell lysates by SEC prior to RPC-MS/MS of tryptic digests can be used to recognize and identify proteins in complexes along with their interaction partners in known protein complexes.     

Identification of major histocompatibility complex class II-associated peptides derived from freshly prepared rat Langerhans cells using MALDI-PSD and Edman degradation

The isolation and identification is described of MHC class II-bound peptides derived from Langerhans cells. A combination of preparative micro-HPLC, MALDI-MS, Edman degradation was used for determining the amino acid sequence of MHC-associated peptides. Sample handling was crucial because fractions containing trace amounts of material require immediate storage at -80 degrees C to prevent peptide losses.     

Human topoisomerase I poisoning: docking protoberberines into a structure-based binding site model

Summary Using the X-ray crystal structure of the human topoisomerase I (top1) – DNA cleavable complex and the Sybyl software package, we have developed a general model for the ternary cleavable complex formed with four protoberberine alkaloids differing in the substitution on the terminal phenyl rings and covering a broad range of the top1-poisoning activities. This model has the drug intercalated with its planar chromophore between the −1 and +1 base pairs flanking the cleavage site, with the nonplanar portion pointing into the minor groove. The ternary complexes were geometry-optimized and relative interaction energies, computed by using the Tripos force field, were found to rank in correct order the biological potency of the compounds; in addition, the model is also consistent with the top1-poisoning inactivity of berberine, a major prototype of the protoberberine alkaloids. The model might serve as a rational basis for elaboration of the most active compound as a lead structure, in order to develop more potent top1 poisons as next generation anti-cancer drugs.     

Molecular modeling of class I and II alleles of the major histocompatibility complex in <Emphasis Type="Italic">Salmo salar</Emphasis>

Knowledge of the 3D structure of the binding groove of major histocompatibility (MHC) molecules, which play a central role in the immune response, is crucial to shed light into the details of peptide recognition and polymorphism. This work reports molecular modeling studies aimed at providing 3D models for two class I and two class II MHC alleles from Salmo salar (Sasa), as the lack of experimental structures of fish MHC molecules represents a serious limitation to understand the specific preferences for peptide binding. The reliability of the structural models built up using bioinformatic tools was explored by means of molecular dynamics simulations of their complexes with representative peptides, and the energetics of the MHC-peptide interaction was determined by combining molecular mechanics interaction energies and implicit continuum solvation calculations. The structural models revealed the occurrence of notable differences in the nature of residues at specific positions in the binding groove not only between human and Sasa MHC proteins, but also between different Sasa alleles. Those differences lead to distinct trends in the structural features that mediate the binding of peptides to both class I and II MHC molecules, which are qualitatively reflected in the relative binding affinities. Overall, the structural models presented here are a valuable starting point to explore the interactions between MHC receptors and pathogen-specific interactions and to design vaccines against viral pathogens.     

Effect of mutated transporters associated with antigen-processing 2 on characteristic major histocompatibility complex binding peptides: analysis using electrospray ionization tandem mass spectrometry

A novel allele of transporters associated with the antigen-processing (TAP) 2 gene, TAP2*Bky2 (Val(577)), is significantly increased in Japanese patients with Sj?gren's syndrome (SS), and has a strong association with SS-A/Ro autoantibody production in SS and autoantibody including anti-SS-A/Ro and anti-U1 RNP antibody in systemic lupus erythematosus (SLE). To determine the influence of this natural mutated TAP on peptides loaded onto MHC class I, we analyzed the repertoire of peptides loaded onto MHC class I on transfectants with TAP1 and TAP2 or mutated TAP2 by electrospray ionization tandem mass spectrometry (ESI-MS/MS). After comparison of the peptide profiles we identified three peptides from only mutated TAP transfectants. Moreover, one of these peptides is derived from snRNP A, which is a target for anti-U1 RNP antibody. To our knowledge this is the first report to show that the natural mutation of TAP2 changes the peptide profile loaded onto MHC class I molecules.