Dynamic characterization of HLA-B*44 Alleles: A comparative molecular dynamics simulation study

Human Leukocyte Antigens (HLA) are highly polymorphic proteins that play a key role in the immune system. HLA molecule is present on the cell membrane of antigen-presenting cells of the immune system and presents short peptides, originating from the proteins of invading pathogens or self-proteins, to the T-cell Receptor (TCR) molecule of the T-cells. In this study, peptide-binding characteristics of HLA-B*44:02, 44:03, 44:05 alleles bound to three nonameric peptides were studied using molecular dynamics simulations. Polymorphisms among these alleles (Asp116Tyr and Asp156Leu) result in major differences in the allele characteristics. While HLA-B*44:02 (Asp116, Asp156) and HLA-B*44:03 (Asp116, Leu156) depend on tapasin for efficient peptide loading, HLA-B*44:05 (Tyr116, Asp156) is tapasin independent. On the other hand, HLA-B*44:02 and HLA-B*44:03 mismatch is closely related to transplant rejection and acute-graft-versus-host disease. In order to understand the dynamic characteristics, the simulation trajectories were analyzed by applying Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) calculations and hydrogen bonding analysis. Binding dynamics of the three HLA-B*44 alleles and peptide sequences are comparatively discussed. In general, peptide binding stability is found to depend on the peptide rather than the allele type for HLA-B*44 alleles.     

Synthesis and biological evaluation of two chemically modified peptide epitopes for the class I MHC protein HLA-B*2705

The T-cell receptor of a CD8(+) T-cell recognises peptide epitopes bound by class I major histocompatibility complex (MHC) glycoproteins presented in a groove on their upper surface. Within the groove of the MHC molecule are 6 pockets, two of which mostly display a high degree of specificity for binding amino acids capable of making conserved and energetically favourable contacts with the MHC. One type of MHC molecule, HLA-B*2705, preferentially binds peptides containing an arginine at position 2. In an effort to increase the affinity of peptides for HLA-B*2705, potentially leading to better immune responses to such a peptide, we synthesised two modified epitopes where the amino acid at position 2 involved in anchoring the peptide to the class I molecule was replaced with the alpha-methylated beta,gamma-unsaturated arginine analogue 2-(S)-amino-5-guanidino-2-methyl-pent-3-enoic acid. The latter was prepared via a multi-step synthetic sequence, starting from alpha-methyl serine, and incorporated into dipeptides which were fragment-coupled to resin-bound heptameric peptides yielding the target nonameric sequences. Biological characterisation indicated that the modified peptides were poorer than the native peptides at stabilising empty class I MHC complexes, and cells sensitised with these peptides were not recognised as well by cognate CD8(+) T-cells, where available, compared to those sensitised with the native peptide. We suggest that the modifications made to the peptide have decreased its ability to bind to the peptide binding groove of HLA-B*2705 molecules which may explain the decrease in recognition by cytotoxic T-cells when compared to the native peptide.     

Molecular mechanism of the susceptibility difference between HLA-B*27:02/04/05 and HLA-B*27:06/09 to ankylosing spondylitis: substitution analysis,MD simulation,QSAR modelling,and in vitro assay

The human leukocyte antigen HLA-B27 is directly involved in the disease pathogenesis of ankylosing spondylitis (AS). HLA-B27 has a high degree of genetic polymorphism, with 105 currently known subtypes; the presence of aspartic acid at residue 116 (Asp116) has been found to play an essential role in AS susceptibility. Here, we systematically investigated the molecular mechanism of the susceptibility difference between the AS-associated subtypes HLA-B*27:02/04/05 and AS-unassociated subtypes HLA-B*27:06/09 to AS at sequence, structure, energetic and dynamic levels. In total seven variable residues were identified among the five studied HLA-B27 subtypes, in which Asp116 can be largely stabilized by a spatially vicinal, positively charged His114 through a salt bridge, while five other variable residues seem to have only a marginal effect on AS susceptibility. We also employed a quantitative structure–activity relationship approach to model the statistical correlation between peptide structure and affinity to HLA-B*27:05, a genetic ancestor of all other HLA-B27 subtypes and associated strongly with AS. The built regression predictor was verified rigorously through both internal cross-validation and external blind validation, and was then employed to identify potential HLA-B*27:05 binders from >20,000 cartilage-derived self-peptides. Subsequently, the binding potency of the top five antigenic peptides to HLA-B*27:05 was assayed in vitro using a FACS-based MHC stabilization experiment. Consequently, two (QRVGSDEFK and LRGAGTNEK) out of the five peptides were determined to have high affinity (BL₅₀ = 5.5 and 15.8 nM, respectively) and, as expected, both of them possess positively charged Lys at the C-terminus.     

Computational investigation of peptide binding stabilities of HLA-B*27 and HLA-B*44 alleles

Major Histocompatibility Complex (MHC) is a cell surface glycoprotein that binds to foreign antigens and presents them to T lymphocyte cells on the surface of Antigen Presenting Cells (APCs) for appropriate immune recognition. Recently, studies focusing on peptide-based vaccine design have allowed a better understanding of peptide immunogenicity mechanisms, which is defined as the ability of a peptide to stimulate CTL-mediated immune response. Peptide immunogenicity is also known to be related to the stability of peptide-loaded MHC (pMHC) complex. In this study, ENCoM server was used for structure-based estimation of the impact of single point mutations on pMHC complex stabilities. For this purpose, two human MHC molecules from the HLA-B*27 group (HLA-B*27:05 and HLA-B*27:09) in complex with four different peptides (GRFAAAIAK, RRKWRRWHL, RRRWRRLTV and IRAAPPPLF) and three HLA-B*44 molecules (HLA-B*44:02, HLA-B*44:03 and HLA-B*44:05) in complex with two different peptides (EEYLQAFTY and EEYLKAWTF) were analyzed. We found that the stability of pMHC complexes is dependent on both peptide sequence and MHC allele. Furthermore, we demonstrate that allele-specific peptide-binding preferences can be accurately revealed using structure-based computational methods predicting the effect of mutations on protein stability.     

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.     

The HLA-A2-supermotif: a QSAR definition

Identification of epitopes capable of binding multiple HLA types will significantly rationalise the development of epitope-based vaccines. A quantitative method assessing the contribution of each amino acid at each position was applied to over 500 nonamer peptides binding to 5 MHC alleles--A*0201, A*0202, A*0203, A*0206 and A*6802--which together define the HLA-A2-like supertype. FXIGXI (L)IFV was identified as a supermotif for the A2-supertype based on the contributions of the common preferred amino acids at each of the nine positions. The results indicate that HLA-A*6802 is an intermediate allele standing between A2 and A3 supertypes: at anchor position 2 it is closer to A3 and at anchor position 9 it is nearer to A2. Models are available free on-line at http://www.jenner.ac.uk/MHCPred and can be used for binding affinity prediction.     

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.     

A novel class of small functional peptides that bind and inhibit human alpha-thrombin isolated by mRNA display

Here we report the in vitro selection of novel small peptide motifs that bind to human alpha-thrombin. We have applied mRNA display to select for thrombin binding peptides from an unbiased library of 1.2 x 10(11) different 35-mer peptides, each containing a random sequence of 15 amino acids. Two clones showed binding affinities ranging from 166 to 520 nM. A conserved motif of four amino acids, DPGR, was identified. Clot formation of human plasma is inhibited by the selected clones, and they downregulate the thrombin-mediated activation of protein C. The identified peptide motifs do not share primary sequence similarities to any of the known natural thrombin binding motifs. As new inhibitors for human thrombin open interesting possibilities in thrombosis research, our newly identified peptides may provide further insights into this field of investigation and may be possible candidates for the development of new anti-thrombotic agents.     

A comparative molecular similarity index analysis (CoMSIA) study identifies an HLA-A2 binding supermotif

The 3D-QSAR CoMSIA technique was applied to a set of 458 peptides binding to the five most widespread HLA-A2-like alleles: A^*0201, A^*0202, A^*0203, A^*0206 and A^*6802. Models comprising the main physicochemical properties (steric bulk, electron density, hydrophobicity and hydrogen-bond formation abilities) were obtained with acceptable predictivity (q ² ranged from 0.385 to 0.683). The use of coefficient contour maps allowed an A2-supermotif to be identified based on common favoured and disfavoured areas. The CoMSIA definition for the best HLA-A2 binder is as follows: hydrophobic aromatic amino acid at position 1; hydrophobic bulky side chains at positions 2, 6 and 9; non-hydrogen-bond-forming amino acids at position 3; small aliphatic hydrogen-bond donors at position 4; aliphatic amino acids at position 5; small aliphatic side chains at position 7; and small aliphatic hydrophilic and hydrogen-bond forming amino acids at position 8.     

A general method for designing combinatorial peptide libraries decodable by amino acid analysis

Herein we describe an algorithm for designing combinatorial peptide libraries for split-and-mix synthesis on solid support that are decodable by amino acid analysis (AAA) of the beads. AAA is a standard service analysis available in most biochemical laboratories, and it allows one to control the quality of the peptide on each bead, an important feature that is missing from most library decoding protocols. In the algorithm, each AA is assigned to two variable positions in the sequence grouped in a "unique pair". This arrangement limits sequence design because both the number of unique pairs U (setting the maximum number of variable AA) and the maximum number S of different AA per variable position depend on the peptide length N (U=N(N-1)/2), S=N-1). The method is therefore only suitable for focused libraries. An application example is shown for the selection of peptides with N-terminal proline or hydroxyproline catalyzing an aldol reaction from a combinatorial library of 65536 octapeptides. A simple enumeration program is available to help design combinatorial libraries decodable by amino acid analysis. The method applies to linear and cyclic peptides, can be used for nonnatural building blocks, including beta-amino acids, and should help to explore the vast chemistry of linear and cyclic peptide for catalysis and bioactivity.     

PepPro: A Nonredundant Structure Data Set for Benchmarking Peptide–Protein Computational Docking

We present a nonredundant benchmark, coined PepPro, for testing peptide–protein docking algorithms. Currently, PepPro contains 89 nonredundant experimentally determined peptide–protein complex structures, with peptide sequence lengths ranging from 5 to 30 amino acids. The benchmark covers peptides with distinct secondary structures, including helix, partial helix, a mixture of helix and β-sheet, β-sheet formed through binding, β-sheet formed through self-folding, and coil. In addition, unbound proteins' structures are provided for 58 complexes and can be used for testing the ability of a docking algorithm handling the conformational changes of proteins during the binding process. PepPro should benefit the docking community for the development and improvement of peptide docking algorithms. The benchmark is available at http://zoulab.dalton.missouri.edu/PepPro_benchmark . © 2019 Wiley Periodicals, Inc.     

基于定量序效模型的计算机辅助虚拟疫苗库设计

给出了基于定量序效模型(QSAM)的计算机辅助虚拟疫苗库设计方案, 并以此为基础成功组建了一个合理规模的HLA-A*0201限制性CTL表位库, 其实现流程如下: (1)从天然氨基酸516种理化性质经主成分分析(PCA)得到一种新的氨基酸描述子: 氨基酸综合性质得分(SP-score); (2)基于SP-score结合遗传-偏最小二乘(GA-PLS)技术建立QSAM模型; (3)利用QSAM模型作为评价工具采用遗传算法(GA)优化CTL表位种群; (4)统计优秀种群中20种氨基酸分别在抗原肽序列不同位置出现频率f; (5)保留f＞F (F为平均出现概率, 对于任意氨基酸为1/20)的氨基酸作为该位置的有利残基类型参与虚拟组合库的构建.     

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).     

Substrate specificity and novel selective inhibitors of TNF-alpha converting enzyme (TACE) from two-dimensional substrate mapping

We report a systematic analysis of the P1' and P2' substrate specificity of TNF-alpha converting enzyme (TACE) using a peptide library and a novel analytical method, and we use the substrate specificity information to design novel reverse hydroxamate inhibitors. Initial truncation studies, using the amino acid sequence around the cleavage site in precursor-TNF-alpha, showed that good turnover was obtained with the peptide DNP-LAQAVRSS-NH2. Based on this result, 1000 different peptide substrates of the form Biotin-LAQA-P1'-P2'-SSK(DNP)-NH2 were prepared, with 50 different natural and unnatural amino acids at P1' in combination with 20 different amino acids at P2'. The peptides were pooled, treated with purified microsomal TACE, and the reaction mixtures were passed over a streptavidin affinity column to remove unreacted substrate and the N-terminal biotinylated product. C-terminal cleavage products not binding to streptavidin were subjected to liquid chromatography/mass spectrometry analysis where individual products were identified and semiquantitated. 25 of the substrates were resynthesized as discrete peptides and assayed with recombinant TACE. The experiments show that recombinant TACE prefers lipophilic amino acids at the P1' position, such as phenylglycine, homophenylalanine, leucine and valine. At the P2' position, TACE can accommodate basic amino acids, such as arginine and lysine, as well as certain non-basic amino acids such as citrulline, methionine sulfoxide and threonine. These substrate preferences were used in the design of novel reverse hydroxamate TACE inhibitors with phenethyl and 5-methyl-thiophene-methyl side-chains at P1', and threonine and nitro-arginine at P2'.     

Peptide reagent design based on physical and chemical properties of amino acid residues

It has tremendous values for both drug discovery and basic research to develop a solid bioinformatical tool for guiding peptide reagent design. Based on the physical and chemical properties of amino acids, a new strategy for peptide reagent design, the so-called AABPD (amino acid based-peptide design), is proposed. The peptide samples in a training dataset are described by a series of HMLP (heuristic molecular lipophilicity potential) parameters and other physicochemical properties of amino acid residues that form a three-dimensional data matrix where each component is defined by three indexes: the first index refers to the peptide samples, the second to the amino acid positions, and the third to the amino acid parameters. The binding free energy between a peptide ligand and its protein receptor is calculated by a linear free energy equation through the physicochemical parameters, resulting in a set of simultaneous linear equations between the bioactivity of the peptides and the physicochemical properties of amino acids. An iterative double least square technique is developed for the solution of the three-dimensional simultaneous linear equation set to determine the amino acid position coefficients of peptide sequence and the physicochemical parameter coefficients of amino acid residues alternately. The two sets of coefficients thus obtained are used for predicting the bioactivity of other query peptide reagents. Two calculation examples, the peptide substrate specificity of the SARS coronavirus 3C-like proteinase and the affinity prediction for epitope-peptides with Class I MHC molecules are studied by using the peptide reagent design strategy.     

Biologically-Inspired Peptide Reagents for Enhancing IMS-MS Analysis of Carbohydrates

The binding properties of a peptidoglycan recognition protein are translated via combinatorial chemistry into short peptides. Non-adjacent histidine, tyrosine, and arginine residues in the protein’s binding cleft that associate specifically with the glycan moiety of a peptidoglycan substrate are incorporated into linear sequences creating a library of 27 candidate tripeptide reagents (three possible residues permutated across three positions). Upon electrospraying the peptide library and carbohydrate mixtures, some noncovalent complexes are observed. The binding efficiencies of the peptides vary according to their amino acid composition as well as the disaccharide linkage and carbohydrate ring-type. In addition to providing a charge-carrier for the carbohydrate, peptide reagents can also be used to differentiate carbohydrate isomers by ion mobility spectrometry. The utility of these peptide reagents as a means of enhancing ion mobility analysis of carbohydrates is illustrated by examining four glucose-containing disaccharide isomers, including a pair that is not resolved by ion mobility alone. The specificity and stoichiometry of the peptide–carbohydrate complexes are also investigated. Trihistidine demonstrates both suitable binding efficiency and successful resolution of disaccharides isomers, suggesting it may be a useful reagent in IMS analyses of carbohydrates.     

Prediction of peptide binding to a major histocompatibility complex class I molecule based on docking simulation

Binding between major histocompatibility complex (MHC) class I molecules and immunogenic epitopes is one of the most important processes for cell-mediated immunity. Consequently, computational prediction of amino acid sequences of MHC class I binding peptides from a given sequence may lead to important biomedical advances. In this study, an efficient structure-based method for predicting peptide binding to MHC class I molecules was developed, in which the binding free energy of the peptide was evaluated by two individual docking simulations. An original penalty function and restriction of degrees of freedom were determined by analysis of 361 published X-ray structures of the complex and were then introduced into the docking simulations. To validate the method, calculations using a 50-amino acid sequence as a prediction target were performed. In 27 calculations, the binding free energy of the known peptide was within the top 5 of 166 peptides generated from the 50-amino acid sequence. Finally, demonstrative calculations using a whole sequence of a protein as a prediction target were performed. These data clearly demonstrate high potential of this method for predicting peptide binding to MHC class I molecules.     

Solid-phase synthesis of DOTA-peptides

A general synthetic route to two DOTA-linked N-Fmoc amino acids (DOTA-F and DOTA-K) is described that allows insertion of DOTA at any endo-position within a peptide sequence. Three model pentapeptides were prepared to test the general utility of these derivatives in solid-phase peptide synthesis. Both DOTA derivatives reacted smoothly by means of standard HBTU activation chemistry to the point of insertion of the DOTA amino acid, but extension of the peptide chain beyond the DOTA-amino acid insertion required the use of pre-activated C-pentafluorophenyl ester N-alpha-Fmoc amino acids. Three Gal-80 binding peptides (12-mers) were then prepared by using this methodology with DOTA positioned either at the N terminus or at one of two different internal positions;the binding of the resulting GdDOTA-12-mers to Gal-80 were compared. The methodology described here allows versatile, controlled introduction of DOTA into any location within a peptide sequence. This provides a potential method for the screening of libraries of DOTA-linked peptides for optimal targeting properties.     

Controlled peptide solvation in portion-mixing libraries of FRET peptides: improved specificity determination for Dengue 2 virus NS2B-NS3 protease and human cathepsin S

The solubility of peptides in aqueous buffers used for the enzyme assays is a common limitation for all peptide libraries. In principle, the more water-soluble peptides are, the more susceptible they will be to peptidase hydrolysis. We have demonstrated that this bias can be circumvented in a portion-mixing fluorescence resonance energy transfer (FRET) peptide library by introducing k (lysine in the D-form) in both termini of the peptides. This more solvated library and another one without the k were assayed using trypsin and chymotrypsin as standard peptidases with high selectivity for R and K and for hydrophobic F and Y, respectively. Significantly improved consistency of the information on substrate profiles was obtained from the solvated library. The influence of improved solvation on substrate specificity determination was successfully demonstrated by the difference in specificity observed between the two libraries employing the human cathepsin S (accepts acidic, basic, or neutral amino acids at P1 position) and Dengue 2 virus NS2B-NS3 protease (high specificity to the pair of basic amino acids K-R, R-R, or Q-R/K at P2-P1 positions). In conclusion, hydration of the peptides has a major influence on protease processing, and this bias can be reduced in bound peptide libraries, improving reliability.