A comparative approach linking molecular dynamics of altered peptide ligands and MHC with in vivo immune responses

Effects of Two Distinct Psychoactive Microbes, Lacticaseibacillus rhamnosus JB-1 and Limosilactobacillus reuteri 6475, on Circulating and Hippocampal mRNA in Male Mice

Discovery of the microbiota-gut–brain axis has led to proposed microbe-based therapeutic strategies in mental health, including the use of mood-altering bacterial species, termed psychobiotics. However, we still have limited understanding of the key signaling pathways engaged by specific organisms in modulating brain function, and evidence suggests that bacteria with broadly similar neuroactive and immunomodulatory actions can drive different behavioral outcomes. We sought to identify pathways distinguishing two psychoactive bacterial strains that seemingly engage similar gut–brain signaling pathways but have distinct effects on behaviour. We used RNAseq to identify mRNAs differentially expressed in the blood and hippocampus of mice following Lacticaseibacillus rhamnosus JB-1, and Limosilactobacillus reuteri 6475 treatment and performed Gene Set Enrichment Analysis (GSEA) to identify enrichment in pathway activity. L. rhamnosus, but not L. reuteri treatment altered several pathways in the blood and hippocampus, and the rhamnosus could be clearly distinguished based on mRNA profile. In particular, L. rhamnosus treatment modulated the activity of interferon signaling, JAK/STAT, and TNF-alpha via NF-KB pathways. Our results highlight that psychobiotics can induce complex changes in host gene expression, andin understanding these changes, we may help fine-tune selection of psychobiotics for treating mood disorders.

Structure and dynamics of major histocompatibility class Ib molecule H2-M3 complexed with mitochondrial-derived peptides

Presentation of antigenic peptides to T-cell receptors is an essential step in the adaptive immune response. In the mouse the class Ib major histocompatibility complex molecule, H2-M3, presents bacterial- and mitochondrial-derived peptides to T-cell receptors on cytotoxic T cells. Four mitochondrial heptapeptides, differing only at residue 6, form complexes with H2-M3 which can be distinguished by T cells. No structures of relevant receptors are available. To investigate the structural basis for this distinction, crystal structures were determined and molecular dynamics simulations over one microsecond were done for each complex. In the crystal structures of the heptapeptide complexes with H2-M3, presented here, the side chains of the peptide residues at position 6 all point into the H2-M3 binding groove, and are thus inaccessible, so that the very similar structures do not suggest how recognition and initiation of responses by the T cells may occur. However, conformational differences, which could be crucial to T-cell discrimination, appear within one microsecond during molecular dynamics simulations of the four complexes. Specifically, the three C-terminal residues of peptide ligands with alanine or threonine at position 6 partially exit the binding groove; this does not occur in peptide ligands with isoleucine or valine at position 6. Structural changes associated with partial peptide exit from the binding groove, along with relevant peptide binding energetics and immunological results are discussed. Communicated by Ramaswamy H. Sarma.

Unraveling the Allosteric Communication Mechanisms in T-Cell Receptor-Peptide-Loaded Major Histocompatibility Complex Dynamics Using Molecular Dynamics Simulations: An Approach Based on Dynamic Cross Correlation Maps and Residue Interaction Energy Calculations

Antigen presentation by major histocompatibility complex (MHC) proteins to T-cell receptors (TCRs) plays a crucial role in triggering the adaptive immune response. Most of our knowledge on TCR-peptide-loaded major histocompatibility complex (pMHC) interaction stemmed from experiments yielding static structures, yet the dynamic aspects of this molecular interaction are equally important to understand the underlying molecular mechanisms and to develop treatment strategies against diseases such as cancer and autoimmune diseases. To this end, computational biophysics studies including all-atom molecular dynamics simulations have provided useful insights; however, we still lack a basic understanding of an overall allosteric mechanism that results in conformational changes in the TCR and subsequent T-cell activation. Previous hydrogen-deuterium exchange and nuclear magnetic resonance studies provided clues regarding these molecular mechanisms, including global rigidification and allosteric effects on the constant domain of TCRs away from the pMHC interaction site. Here, we show that molecular dynamics simulations can be used to identify how this overall rigidification may be related to the allosteric communication within TCRs upon pMHC interaction via essential dynamics and nonbonded residue-residue interaction energy analyses. The residues taking part in the rigidification effect are highlighted with an intricate analysis on residue interaction changes, which lead to a detailed outline of the complex formation event. Our results indicate that residues of the Cβ domain of TCRs show significant differences in their nonbonded interactions upon complex formation. Moreover, the dynamic cross correlations between these residues are also increased, in line with their nonbonded interaction energy changes. Altogether, our approach may be valuable for elucidating intramolecular allosteric changes in the TCR structure upon pMHC interaction in molecular dynamics simulations.

The art of suicidal molecular seduction for targeting drug resistance

The development of drug resistance is one of the most significant challenges of the current century in the pharmaceutical industry. Superinfections, cancer chemoresistance, and resistance observed in many non-infectious diseases are nullifying the efforts and monetary supplies, put in the advent of new drug molecules. Millions of people die because of this drug resistance developed gradually through extensive use of the drugs. Inherently, some drugs are less prone to become ineffective by drug resistance than others. Covalent inhibitors bind to their targets via a biologically permanent bound with their cognate receptor and therefore display more potent inhibiting characteristics. Suicide inhibitors or mechanism-based inhibitors are one of the covalent inhibitors, which require a pre-activation step by their targeting enzyme. This step accrues their selectivity and specificity with respect to other covalent inhibitors. After that pre-activation step, they produce an analogue of the transition state of the catalytic enzyme, which is practically incapable of dissociating from the enzyme. Suicide inhibitors, due to their high intrinsic affinity toward the related enzyme, are resistant to many mechanisms involved in the development of drug resistance and can be regarded as one of the enemies of this scientific hurdle. These inhibitors compete even with monoclonal antibodies in terms of their cost-effectiveness and efficacy.

Exploring the different states of wild-type T-cell receptor and mutant conformational changes towards understanding the antigen recognition

Recognition of proteolytic peptide fragments presented by major histocompatibility complex (MHC) on target cells by T-cell receptor (TCR) is among the most important interactions in the adaptive immune system. Several computational studies have been performed to investigate conformational and dynamical properties of TCRs for enhanced immunogenicity. Here, we present the large-scale molecular dynamics (MD) simulation studies of the two comprehensive systems consisting of the wild-type and mutant IG4 TCR in complex with the tumor epitope NY-ESO peptide (SLLMWITQC) and analyzed for mapping conformational changes of TCR in the states prior to antigen binding, upon antigen binding and after the antigen was released. All of the simulations were performed with different states of TCRs for each 1000 ns of simulation time, providing six simulations for time duration of 6000 ns (6µs). We show that rather than undergoing most critical conformational changes upon antigen binding, the high proportion of complementarity-determining region (CDR) loops change by comparatively small amount. The hypervariable CDRα3 and CDRβ3 loops showed significant structural changes. Interestingly, the TCR β chain loops showed the least changes, which is reliable with recent implications that β domain of TCR may propel antigen interaction. The mutant shows higher rigidity than wild-type even in released state; expose an induced fit mechanism occurring from the re-structuring of CDRα3 loop and can allow enhanced binding affinity of the peptide antigen. Additionally, we show that CDRα3 loop and peptide contacts are an adaptive feature of affinity enhanced mutant TCR.Communicated by Ramaswamy H. Sarma.

Imprinting and Editing of the Human CD4 T Cell Response to Influenza Virus

Immunity to influenza is unique among pathogens, in that immune memory is established both via intermittent lung localized infections with highly variable influenza virus strains and by intramuscular vaccinations with inactivated protein-based vaccines. Studies in the past decades have suggested that the B cell responses to influenza infection and vaccination are highly biased by an individual's early history of influenza infection. This reactivity likely reflects both the competitive advantage that memory B cells have in an immune response and the relatively limited diversity of epitopes in influenza hemagglutinin that are recognized by B cells. In contrast, CD4 T cells recognize a wide array of epitopes, with specificities that are heavily influenced by the diversity of influenza antigens available, and a multiplicity of functions that are determined by both priming events and subsequent confrontations with antigens. Here, we consider the events that prime and remodel the influenza-specific CD4 T cell response in humans that have highly diverse immune histories and how the CD4 repertoire may be edited in terms of functional potential and viral epitope specificity. We discuss the consequences that imprinting and remodeling may have on the potential of different human hosts to rapidly respond with protective cellular immunity to infection. Finally, these issues are discussed in the context of future avenues of investigation and vaccine strategies.

How peptide/MHC presence affects the dynamics of the LC13 T-cell receptor

The interaction between T-cell receptors (TCRs) of T-cells and potentially immunogenic peptides presented by MHCs of antigen presenting cells is one of the most important mechanisms of the adaptive human immune system. A large number of structural simulations of the TCR/peptide/MHC system have been carried out. However, to date no study has investigated the differences of the dynamics between free TCRs and pMHC bound TCRs on a large scale. Here we present a study totalling 37 100 ns investigating the LC13 TCR in its free form as well as in complex with HLA-B*08:01 and different peptides. Our results show that the dynamics of the bound and unbound LC13 TCR differ significantly. This is reflected in (a) expected results such as an increased flexibility and increased solvent accessible surface of the CDRs of unbound TCR simulations but also in (b) less expected results such as lower CDR distances and compactness as well as alteration in the hydrogen bond network around CDR3α of unbound TCR simulations. Our study further emphasises the structural flexibility of TCRs and confirms the importance of the CDR3 loops for the adoption to MHC.

Spatiotemporal multistage consensus clustering in molecular dynamics studies of large proteins

The aim of this work is to find semi-rigid domains within large proteins as reference structures for fitting molecular dynamics trajectories. We propose an algorithm, multistage consensus clustering, MCC, based on minimum variation of distances between pairs of Cα-atoms as target function. The whole dataset (trajectory) is split into sub-segments. For a given sub-segment, spatial clustering is repeatedly started from different random seeds, and we adopt the specific spatial clustering with minimum target function: the process described so far is stage 1 of MCC. Then, in stage 2, the results of spatial clustering are consolidated, to arrive at domains stable over the whole dataset. We found that MCC is robust regarding the choice of parameters and yields relevant information on functional domains of the major histocompatibility complex (MHC) studied in this paper: the α-helices and β-floor of the protein (MHC) proved to be most flexible and did not contribute to clusters of significant size. Three alleles of the MHC, each in complex with ABCD3 peptide and LC13 T-cell receptor (TCR), yielded different patterns of motion. Those alleles causing immunological allo-reactions showed distinct correlations of motion between parts of the peptide, the binding cleft and the complementary determining regions (CDR)-loops of the TCR. Multistage consensus clustering reflected functional differences between MHC alleles and yields a methodological basis to increase sensitivity of functional analyses of bio-molecules. Due to the generality of approach, MCC is prone to lend itself as a potent tool also for the analysis of other kinds of big data.

Major Histocompatibility Complex (MHC) Class I and MHC Class II Proteins: Conformational Plasticity in Antigen Presentation

Antigen presentation by major histocompatibility complex (MHC) proteins is essential for adaptive immunity. Prior to presentation, peptides need to be generated from proteins that are either produced by the cell's own translational machinery or that are funneled into the endo-lysosomal vesicular system. The prolonged interaction between a T cell receptor and specific pMHC complexes, after an extensive search process in secondary lymphatic organs, eventually triggers T cells to proliferate and to mount a specific cellular immune response. Once processed, the peptide repertoire presented by MHC proteins largely depends on structural features of the binding groove of each particular MHC allelic variant. Additionally, two peptide editors-tapasin for class I and HLA-DM for class II-contribute to the shaping of the presented peptidome by favoring the binding of high-affinity antigens. Although there is a vast amount of biochemical and structural information, the mechanism of the catalyzed peptide exchange for MHC class I and class II proteins still remains controversial, and it is not well understood why certain MHC allelic variants are more susceptible to peptide editing than others. Recent studies predict a high impact of protein intermediate states on MHC allele-specific peptide presentation, which implies a profound influence of MHC dynamics on the phenomenon of immunodominance and the development of autoimmune diseases. Here, we review the recent literature that describe MHC class I and II dynamics from a theoretical and experimental point of view and we highlight the similarities between MHC class I and class II dynamics despite the distinct functions they fulfill in adaptive immunity.

Major Histocompatibility Complex (MHC) Class I and MHC Class II Proteins: Conformational Plasticity in Antigen Presentation

Antigen presentation by major histocompatibility complex (MHC) proteins is essential for adaptive immunity. Prior to presentation, peptides need to be generated from proteins that are either produced by the cell’s own translational machinery or that are funneled into the endo-lysosomal vesicular system. The prolonged interaction between a T cell receptor and specific pMHC complexes, after an extensive search process in secondary lymphatic organs, eventually triggers T cells to proliferate and to mount a specific cellular immune response. Once processed, the peptide repertoire presented by MHC proteins largely depends on structural features of the binding groove of each particular MHC allelic variant. Additionally, two peptide editors—tapasin for class I and HLA-DM for class II—contribute to the shaping of the presented peptidome by favoring the binding of high-affinity antigens. Although there is a vast amount of biochemical and structural information, the mechanism of the catalyzed peptide exchange for MHC class I and class II proteins still remains controversial, and it is not well understood why certain MHC allelic variants are more susceptible to peptide editing than others. Recent studies predict a high impact of protein intermediate states on MHC allele-specific peptide presentation, which implies a profound influence of MHC dynamics on the phenomenon of immunodominance and the development of autoimmune diseases. Here, we review the recent literature that describe MHC class I and II dynamics from a theoretical and experimental point of view and we highlight the similarities between MHC class I and class II dynamics despite the distinct functions they fulfill in adaptive immunity.

Energetic and flexibility properties captured by long molecular dynamics simulations of a membrane-embedded pMHCII-TCR complex

Although crystallographic data have provided important molecular insight into the interactions in the pMHC-TCR complex, the inherent features of this structural approach cause it to only provide a static picture of the interactions. While unbiased molecular dynamics simulations (UMDSs) have provided important information about the dynamic structural behavior of the pMHC-TCR complex, most of them have modeled the pMHC-TCR complex as soluble, when in physiological conditions, this complex is membrane bound; therefore, following this latter UMDS protocol might hamper important dynamic results. In this contribution, we performed three independent 300 ns-long UMDSs of the pMHCII-TCR complex anchored in two opposing membranes to explore the structural and energetic properties of the recognition of pMHCII by the TCR. The conformational ensemble generated through UMDSs was subjected to clustering and Cartesian principal component analyses (cPCA) to explore the dynamical behavior of the pMHCII-TCR association. Furthermore, based on the conformational population sampled through UMDSs, the effective binding free energy, per-residue free energy decomposition, and alanine scanning mutations were explored for the native pMHCII-TCR complex, as well as for 12 mutations (p1-p12MHCII-TCR) introduced in the native peptide. Clustering analyses and cPCA provide insight into the rocking motion of the TCR onto pMHCII, together with the presence of new electrostatic interactions not observed through crystallographic methods. Energetic results provide evidence of the main contributors to the pMHC-TCR complex formation as well as the key residues involved in this molecular recognition process.

T-Cell Receptor Binding Affects the Dynamics of the Peptide/MHC-I Complex

The recognition of peptide/MHC by T-cell receptors is one of the most important interactions in the adaptive immune system. A large number of computational studies have investigated the structural dynamics of this interaction. However, to date only limited attention has been paid to differences between the dynamics of peptide/MHC with the T-cell receptor bound and unbound. Here we present the first large-scale molecular dynamics simulation study of this type investigating HLA-B*08:01 in complex with the Epstein-Barr virus peptide FLRGRAYGL and all possible single-point mutations (n = 172). All of the simulations were performed with and without the LC 13 T-cell receptor for a simulation time of 100 ns, yielding 344 simulations and a total simulation time of 34 400 ns. Our study is 2 orders of magnitude larger than the average T-cell receptor/peptide/MHC molecular dynamics simulation study. This data set provides reliable insights into alterations of the peptide/MHC-I dynamics caused by the presence of the T-cell receptor. We found that simulations in the presence of T-cell receptors have more hydrogen bonds between the peptide and MHC, altered flexibility patterns in the MHC helices and the peptide, a lower MHC groove width range, and altered solvent-accessible surface areas. This indicates that without a T-cell receptor the MHC binding groove can open and close, while the presence of the T-cell receptor inhibits these breathing-like motions.

TCR triggering by pMHC ligands tethered on surfaces via poly(ethylene glycol) depends on polymer length

Antigen recognition by T cells relies on the interaction between T cell receptor (TCR) and peptide-major histocompatibility complex (pMHC) at the interface between the T cell and the antigen presenting cell (APC). The pMHC-TCR interaction is two-dimensional (2D), in that both the ligand and receptor are membrane-anchored and their movement is limited to 2D diffusion. The 2D nature of the interaction is critical for the ability of pMHC ligands to trigger TCR. The exact properties of the 2D pMHC-TCR interaction that enable TCR triggering, however, are not fully understood. Here, we altered the 2D pMHC-TCR interaction by tethering pMHC ligands to a rigid plastic surface with flexible poly(ethylene glycol) (PEG) polymers of different lengths, thereby gradually increasing the ligands' range of motion in the third dimension. We found that pMHC ligands tethered by PEG linkers with long contour length were capable of activating T cells. Shorter PEG linkers, however, triggered TCR more efficiently. Molecular dynamics simulation suggested that shorter PEGs exhibit faster TCR binding on-rates and off-rates. Our findings indicate that TCR signaling can be triggered by surface-tethered pMHC ligands within a defined 3D range of motion, and that fast binding rates lead to higher TCR triggering efficiency. These observations are consistent with a model of TCR triggering that incorporates the dynamic interaction between T cell and antigen-presenting cell.

Large scale characterization of the LC13 TCR and HLA-B8 structural landscape in reaction to 172 altered peptide ligands: a molecular dynamics simulation study

The interplay between T cell receptors (TCRs) and peptides bound by major histocompatibility complexes (MHCs) is one of the most important interactions in the adaptive immune system. Several previous studies have computationally investigated their structural dynamics. On the basis of these simulations several structural and dynamical properties have been proposed as effectors of the immunogenicity. Here we present the results of a large scale Molecular Dynamics simulation study consisting of 100 ns simulations of 172 different complexes. These complexes consisted of all possible point mutations of the Epstein Barr Virus peptide FLRGRAYGL bound by HLA-B*08:01 and presented to the LC13 TCR. We compare the results of these 172 structural simulations with experimental immunogenicity data. We found that simulations with more immunogenic peptides and those with less immunogenic peptides are in fact highly similar and on average only minor differences in the hydrogen binding footprints, interface distances, and the relative orientation between the TCR chains are present. Thus our large scale data analysis shows that many previously suggested dynamical and structural properties of the TCR/peptide/MHC interface are unlikely to be conserved causal factors for peptide immunogenicity.

Antigenic peptide molecular recognition by the DRB1–DQB1 haplotype modulates multiple sclerosis susceptibility

DRB1–DQB1 binding affinities in peptide molecular recognition process. (A) In protective haplotype DRB1 allele displays a preferential affinity for MBP peptide, while (B) in predisposing haplotype DQB1 allele displays a preferential affinity for EBNA1 peptide.

Early relaxation dynamics in the LC 13 T cell receptor in reaction to 172 altered peptide ligands: a molecular dynamics simulation study

The interaction between the T cell receptor and the major histocompatibility complex is one of the most important events in adaptive immunology. Although several different models for the activation process of the T cell via the T cell receptor have been proposed, it could not be shown that a structural mechanism, which discriminates between peptides of different immunogenicity levels, exists within the T cell receptor. In this study, we performed systematic molecular dynamics simulations of 172 closely related altered peptide ligands in the same T cell receptor/major histocompatibility complex system. Statistical evaluations yielded significant differences in the initial relaxation process between sets of peptides at four different immunogenicity levels.

Differential geometric analysis of alterations in MH α-helices

Antigen presenting cells present processed peptides via their major histocompatibility (MH) complex to the T cell receptors (TRs) of T cells. If a peptide is immunogenic, a signaling cascade can be triggered within the T cell. However, the binding of different peptides and/or different TRs to MH is also known to influence the spatial arrangement of the MH α-helices which could itself be an additional level of T cell regulation. In this study, we introduce a new methodology based on differential geometric parameters to describe MH deformations in a detailed and comparable way. For this purpose, we represent MH α-helices by curves. On the basis of these curves, we calculate in a first step the curvature and torsion to describe each α-helix independently. In a second step, we calculate the distribution parameter and the conical curvature of the ruled surface to describe the relative orientation of the two α-helices. On the basis of four different test sets, we show how these differential geometric parameters can be used to describe changes in the spatial arrangement of the MH α-helices for different biological challenges. In the first test set, we illustrate on the basis of all available crystal structures for (TR)/pMH complexes how the binding of TRs influences the MH helices. In the second test set, we show a cross evaluation of different MH alleles with the same peptide and the same MH allele with different peptides. In the third test set, we present the spatial effects of different TRs on the same peptide/MH complex. In the fourth test set, we illustrate how a severe conformational change in an α-helix can be described quantitatively. Taken together, we provide a novel structural methodology to numerically describe subtle and severe alterations in MH α-helices for a broad range of applications.

Structural and dynamical insights on HLA-DR2 complexes that confer susceptibility to multiple sclerosis in Sardinia: a molecular dynamics simulation study

Sardinia is a major Island in the Mediterranean with a high incidence of multiple sclerosis, a chronic autoimmune inflammatory disease of the central nervous system. Disease susceptibility in Sardinian population has been associated with five alleles of major histocompatibility complex (MHC) class II DRB1 gene. We performed 120 ns of molecular dynamics simulation on one predisposing and one protective alleles, unbound and in complex with the two relevant peptides: Myelin Basic Protein and Epstein Barr Virus derived peptide. In particular we focused on the MHC peptide binding groove dynamics. The predisposing allele was found to form a stable complex with both the peptides, while the protective allele displayed stability only when bound with myelin peptide. The local flexibility of the MHC was probed dividing the binding groove into four compartments covering the well known peptide anchoring pockets. The predisposing allele in the first half cleft exhibits a narrower and more rigid groove conformation in the presence of myelin peptide. The protective allele shows a similar behavior, while in the second half cleft it displays a narrower and more flexible groove conformation in the presence of viral peptide. We further characterized these dynamical differences by evaluating H-bonds, hydrophobic and stacking interaction networks, finding striking similarities with super-type patterns emerging in other autoimmune diseases. The protective allele shows a defined preferential binding to myelin peptide, as confirmed by binding free energy calculations. All together, we believe the presented molecular analysis could help to design experimental assays, supports the molecular mimicry hypothesis and suggests that propensity to multiple sclerosis in Sardinia could be partly linked to distinct peptide-MHC interaction and binding characteristics of the antigen presentation mechanism.

Relaxation estimation of RMSD in molecular dynamics immunosimulations

Molecular dynamics simulations have to be sufficiently long to draw reliable conclusions. However, no method exists to prove that a simulation has converged. We suggest the method of "lagged RMSD-analysis" as a tool to judge if an MD simulation has not yet run long enough. The analysis is based on RMSD values between pairs of configurations separated by variable time intervals Δt. Unless RMSD(Δt) has reached a stationary shape, the simulation has not yet converged.

Association of HLA-DR1 with the allergic response to the major mugwort pollen allergen: molecular background

BACKGROUND

Mugwort pollen allergens represent the main cause of pollinosis in late summer. The major allergen, Art v 1, contains only one single immunodominant, solely HLA-DR-restricted T cell epitope (Art v 125-36). The frequency of HLA-DRB1*01 is highly increased in mugwort-allergic individuals and HLA-DR1 serves as restriction element for Art v 125-36. However, Art v 125-36 also binds to HLA-DR4 with high affinity and DR1-restricted Art v 125-36 -specific T cell receptors can be activated by HLA-DR4 molecules. To understand the predominance of HLA-DR1 in mugwort allergy in spite of the degeneracy in HLA/peptide-binding and TCR-recognition, we investigated the molecular background of Art v 125-36 /MHC/TCR interactions in the context of HLA-DR1 compared to -DR4.

RESULTS

The majority of Art v 125-36 -specific T cell lines and clones from HLA-DR1 carrying, mugwort pollen-allergic donors reacted to synthetic and naturally processed Art v 1-peptides when presented by HLA-DR1 or HLA-DR4 expressing antigen presenting cells. However, at limiting peptide concentrations DR1 was more effective in T cell stimulation. In addition, the minimal epitope for 50% of Art v 125-36 -specific T cells was shorter for DR1 than for DR4. In vitro binding assays of Art v 125-36 mutant peptides to isolated DR1- and DR4-molecules indicated similar binding capacities and use of the same register. In silico simulation of Art v 125-36 binding to HLA-DR1 and -DR4 suggested similar binding of the central part of the peptide to either molecule, but a higher flexibility of the N- and C-terminal amino acids and detachment at the C-terminus in HLA-DR1.

CONCLUSIONS

The predominance of HLA-DR1 in the response to Art v 125-36 may be explained by subtle conformation changes of the peptide bound to DR1 compared to DR4. Computer simulation supported our experimental data by demonstrating differences in peptide mobility within the HLA-DR complex that may influence TCR-binding. We suggest that the minor differences observed in vitro may be more relevant in the microenvironment in vivo, so that only presentation by HLA-DR1, but not -DR4 permits successful T cell activation.

MH2c: Characterization of major histocompatibility α-helices - an information criterion approach

Major histocompatibility proteins share a common overall structure or peptide binding groove. Two binding groove domains, on the same chain for major histocompatibility class I or on two different chains for major histocompatibility class II, contribute to that structure that consists of two α-helices ("wall") and a sheet of eight anti-parallel beta strands ("floor"). Apart from the peptide presented in the groove, the major histocompatibility α-helices play a central role for the interaction with the T cell receptor. This study presents a generalized mathematical approach for the characterization of these helices. We employed polynomials of degree 1 to 7 and splines with 1 to 2 nodes based on polynomials of degree 1 to 7 on the α-helices projected on their principal components. We evaluated all models with a corrected Akaike Information Criterion to determine which model represents the α-helices in the best way without overfitting the data. This method is applicable for both the stationary and the dynamic characterization of α-helices. By deriving differential geometric parameters from these models one obtains a reliable method to characterize and compare α-helices for a broad range of applications.

PROGRAM SUMMARY

Program title: MH²c (MH helix curves) Catalogue identifier: AELX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AELX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 327 565 No. of bytes in distributed program, including test data, etc.: 17 433 656 Distribution format: tar.gz Programming language: Matlab Computer: Personal computer architectures Operating system: Windows, Linux, Mac (all systems on which Matlab can be installed) RAM: Depends on the trajectory size, min. 1 GB (Matlab) Classification: 2.1, 4.9, 4.14 External routines: Curve Fitting Toolbox and Statistic Toolbox of Matlab Nature of problem: Major histocompatibility (MH) proteins share a similar overall structure. However, identical MH alleles which present different peptides differ by subtle conformational alterations. One hypothesis is that such conformational differences could be another level of T cell regulation. By this software package we present a reliable and systematic way to compare different MH structures to each other. Solution method: We tested several fitting approaches on all available experimental crystal structures of MH to obtain an overall picture of how to describe MH helices. For this purpose we transformed all complexes into the same space and applied splines and polynomials of several degrees to them. To draw a general conclusion which method fits them best we employed the "corrected Akaike Information Criterion". The software is applicable for all kinds of helices of biomolecules. Running time: Depends on the data, for a single stationary structure the runtime should not exceed a few seconds.

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.

(E)-alkene and ethylene isosteres substantially alter the hydrogen-bonding network in class II MHC A(q)/glycopeptide complexes and affect T-cell recognition

The structural basis for antigen presentation by class II major histocompatibility complex (MHC) proteins to CD4(+) T-cells is important for understanding and possibly treating autoimmune diseases. In the work described in this paper, (E)-alkene and ethylene amide-bond isosteres were used to investigate the effect of removing hydrogen-bonding possibilities from the CII259-270 glycopeptide, which is bound by the arthritis-associated murine A(q) class II MHC protein. The isostere-modified glycopeptides showed varying and unexpectedly large losses of A(q) binding that could be linked to the dynamics of the system. Molecular dynamics (MD) simulations revealed that the backbone of CII259-270 and the A(q) protein are able to form up to 11 hydrogen bonds, but fewer than this number are present at any one time. Most of the strong hydrogen-bond interactions were formed by the N-terminal part of the glycopeptide, i.e., in the region where the isosteric replacements were made. The structural dynamics also revealed that hydrogen bonds were strongly coupled to each other; the loss of one hydrogen-bond interaction had a profound effect on the entire hydrogen-bonding network. The A(q) binding data revealed that an ethylene isostere glycopeptide unexpectedly bound more strongly to A(q) than the corresponding (E)-alkene, which is in contrast to the trend observed for the other isosteres. Analysis of the MD trajectories revealed that the complex conformation of this ethylene isostere was structurally different and had an altered molecular interaction pattern compared to the other A(q)/glycopeptide complexes. The introduced amide-bond isosteres also affected the interactions of the glycopeptide/A(q) complexes with T-cell receptors. The dynamic variation of the patterns and strengths of the hydrogen-bond interactions in the class II MHC system is of critical importance for the class II MHC/peptide/TCR signaling system.

Is an intuitive convergence definition of molecular dynamics simulations solely based on the root mean square deviation possible?

Molecular dynamics is a commonly used technique in computational biology. One key issue of each molecular dynamics simulation is: When does this simulation reach equilibrium state? A widely used way to determine this is the visual and intuitive inspection of root mean square deviation (RMSD) plots of the simulation. Although this technique has been criticized several times, it is still often used. Therefore, we present a study proving that this method is not reliable at all. We conducted a survey with participants from the field in which we illustrated different RMSD plots to scientists in the field of molecular dynamics. These plots were randomized and repeated, using a statistical model and different variants of the plots. We show that there is no mutual consent about the point of equilibrium. The decisions are severely biased by different parameters. Therefore, we conclude that scientists should not discuss the equilibration of a molecular dynamics simulation on the basis of a RMSD plot.

PeptX: using genetic algorithms to optimize peptides for MHC binding

Background

The binding between the major histocompatibility complex and the presented peptide is an indispensable prerequisite for the adaptive immune response. There is a plethora of different in silico techniques for the prediction of the peptide binding affinity to major histocompatibility complexes. Most studies screen a set of peptides for promising candidates to predict possible T cell epitopes. In this study we ask the question vice versa: Which peptides do have highest binding affinities to a given major histocompatibility complex according to certain in silico scoring functions?

Results

Since a full screening of all possible peptides is not feasible in reasonable runtime, we introduce a heuristic approach. We developed a framework for Genetic Algorithms to optimize peptides for the binding to major histocompatibility complexes. In an extensive benchmark we tested various operator combinations. We found that (1) selection operators have a strong influence on the convergence of the population while recombination operators have minor influence and (2) that five different binding prediction methods lead to five different sets of "optimal" peptides for the same major histocompatibility complex. The consensus peptides were experimentally verified as high affinity binders.

Conclusion

We provide a generalized framework to calculate sets of high affinity binders based on different previously published scoring functions in reasonable runtime. Furthermore we give insight into the different behaviours of operators and scoring functions of the Genetic Algorithm.