DockTope: a Web-based tool for automated pMHC-I modelling.
ABSTRACT: The immune system is constantly challenged, being required to protect the organism against a wide variety of infectious pathogens and, at the same time, to avoid autoimmune disorders. One of the most important molecules involved in these events is the Major Histocompatibility Complex class I (MHC-I), responsible for binding and presenting small peptides from the intracellular environment to CD8(+) T cells. The study of peptide:MHC-I (pMHC-I) molecules at a structural level is crucial to understand the molecular mechanisms underlying immunologic responses. Unfortunately, there are few pMHC-I structures in the Protein Data Bank (PDB) (especially considering the total number of complexes that could be formed combining different peptides), and pMHC-I modelling tools are scarce. Here, we present DockTope, a free and reliable web-based tool for pMHC-I modelling, based on crystal structures from the PDB. DockTope is fully automated and allows any researcher to construct a pMHC-I complex in an efficient way. We have reproduced a dataset of 135 non-redundant pMHC-I structures from the PDB (C? RMSD below 1?Å). Modelling of pMHC-I complexes is remarkably important, contributing to the knowledge of important events such as cross-reactivity, autoimmunity, cancer therapy, transplantation and rational vaccine design.
Project description:The interaction between the class I major histocompatibility complex (MHC), the peptide presented by the MHC and the T-cell receptor (TCR) is a key determinant of the cellular immune response. Here, we present TCRpMHCmodels, a method for accurate structural modelling of the TCR-peptide-MHC (TCR-pMHC) complex. This TCR-pMHC modelling pipeline takes as input the amino acid sequence and generates models of the TCR-pMHC complex, with a median C? RMSD of 2.31?Å. TCRpMHCmodels significantly outperforms TCRFlexDock, a specialised method for docking pMHC and TCR structures. TCRpMHCmodels is simple to use and the modelling pipeline takes, on average, only two minutes. Thanks to its ease of use and high modelling accuracy, we expect TCRpMHCmodels to provide insights into the underlying mechanisms of TCR and pMHC interactions and aid in the development of advanced T-cell-based immunotherapies and rational design of vaccines. The TCRpMHCmodels tool is available at http://www.cbs.dtu.dk/services/TCRpMHCmodels/ .
Project description:BACKGROUND: The adaptive immune response is antigen-specific and triggered by pathogen recognition through T cells. Although the interactions and mechanisms of TCR-peptide-MHC (TCR-pMHC) have been studied over three decades, the biological basis for these processes remains controversial. As an increasing number of high-throughput binding epitopes and available TCR-pMHC complex structures, a fast genome-wide structural modelling of TCR-pMHC interactions is an emergent task for understanding immune interactions and developing peptide vaccines. RESULTS: We first constructed the PPI matrices and iMatrix, using 621 non-redundant PPI interfaces and 398 non-redundant antigen-antibody interfaces, respectively, for modelling the MHC-peptide and TCR-peptide interfaces, respectively. The iMatrix consists of four knowledge-based scoring matrices to evaluate the hydrogen bonds and van der Waals forces between sidechains or backbones, respectively. The predicted energies of iMatrix are high correlated (Pearson's correlation coefficient is 0.6) to 70 experimental free energies on antigen-antibody interfaces. To further investigate iMatrix and PPI matrices, we inferred the 701,897 potential peptide antigens with significant statistic from 389 pathogen genomes and modelled the TCR-pMHC interactions using available TCR-pMHC complex structures. These identified peptide antigens keep hydrogen-bond energies and consensus interactions and our TCR-pMHC models can provide detailed interacting models and crucial binding regions. CONCLUSIONS: Experimental results demonstrate that our method can achieve high precision for predicting binding affinity and potential peptide antigens. We believe that iMatrix and our template-based method can be useful for the binding mechanisms of TCR-pMHC complexes and peptide vaccine designs.
Project description:BACKGROUND: Identification of antigenic peptide epitopes is an essential prerequisite in T cell-based molecular vaccine design. Computational (sequence-based and structure-based) methods are inexpensive and efficient compared to experimental approaches in screening numerous peptides against their cognate MHC alleles. In structure-based protocols, suited to alleles with limited epitope data, the first step is to identify high-binding peptides using docking techniques, which need improvement in speed and efficiency to be useful in large-scale screening studies. We present pDOCK: a new computational technique for rapid and accurate docking of flexible peptides to MHC receptors and primarily apply it on a non-redundant dataset of 186 pMHC (MHC-I and MHC-II) complexes with X-ray crystal structures. RESULTS: We have compared our docked structures with experimental crystallographic structures for the immunologically relevant nonameric core of the bound peptide for MHC-I and MHC-II complexes. Primary testing for re-docking of peptides into their respective MHC grooves generated 159 out of 186 peptides with Cα RMSD of less than 1.00 Å, with a mean of 0.56 Å. Amongst the 25 peptides used for single and variant template docking, the Cα RMSD values were below 1.00 A for 23 peptides. Compared to our earlier docking methodology, pDOCK shows upto 2.5 fold improvement in the accuracy and is ~60% faster. Results of validation against previously published studies represent a seven-fold increase in pDOCK accuracy. CONCLUSIONS: The limitations of our previous methodology have been addressed in the new docking protocol making it a rapid and accurate method to evaluate pMHC binding. pDOCK is a generic method and although benchmarks against experimental structures, it can be applied to alleles with no structural data using sequence information. Our outcomes establish the efficacy of our procedure to predict highly accurate peptide structures permitting conformational sampling of the peptide in MHC binding groove. Our results also support the applicability of pDOCK for in silico identification of promiscuous peptide epitopes that are relevant to higher proportions of human population with greater propensity to activate T cells making them key targets for the design of vaccines and immunotherapies.
Project description:MHC class I peptide complexes (pMHC) are routinely used to enumerate T cell populations and are currently being evaluated as vaccines to tumors and specific pathogens. Herein, we describe the structures of three generations of single-chain pMHC progressively designed for the optimal presentation of covalently associated epitopes. Our ultimate design employs a versatile disulfide trap between an invariant MHC residue and a short C-terminal peptide extension. This general strategy is nondisruptive of native pMHC conformation and T cell receptor engagement. Indeed, cell-surface-expressed MHC complexes with disulfide-trapped epitopes are refractory to peptide exchange, suggesting they will make safe and effective vaccines. Furthermore, we find that disulfide-trap stabilized, recombinant pMHC reagents reliably detect polyclonal CD8 T cell populations as proficiently as conventional reagents and are thus well suited to monitor or modulate immune responses during pathogenesis.
Project description:The interaction of antigenic peptides (p) and major histocompatibility complexes (pMHC) with T-cell receptors (TCR) is one of the most important steps during the immune response. Here we present a molecular dynamics simulation study of bound and unbound TCR and pMHC proteins of the LC13-HLA-B*44:05-pEEYLQAFTY complex to monitor differences in relative orientations and movements of domains between bound and unbound states of TCR-pMHC. We generated local coordinate systems for MHC ?1- and MHC ?2-helices and the variable T-cell receptor regions TCR V? and TCR V? and monitored changes in the distances and mutual orientations of these domains. In comparison to unbound states, we found decreased inter-domain movements in the simulations of bound states. Moreover, increased conformational flexibility was observed for the MHC ?2-helix, the peptide, and for the complementary determining regions of the TCR in TCR-unbound states as compared to TCR-bound states.
Project description:Peptide exchange technologies are essential for the generation of pMHC-multimer libraries used to probe diverse, polyclonal TCR repertoires in various settings. Here, using the molecular chaperone TAPBPR, we develop a robust method for the capture of stable, empty MHC-I molecules comprising murine H2 and human HLA alleles, which can be readily tetramerized and loaded with peptides of choice in a high-throughput manner. Alternatively, catalytic amounts of TAPBPR can be used to exchange placeholder peptides with high affinity peptides of interest. Using the same system, we describe high throughput assays to validate binding of multiple candidate peptides on empty MHC-I/TAPBPR complexes. Combined with tetramer-barcoding via a multi-modal cellular indexing technology, ECCITE-seq, our approach allows a combined analysis of TCR repertoires and other T cell transcription profiles together with their cognate antigen specificities in a single experiment. The new approach allows TCR/pMHC interactions to be interrogated easily at large scale.
Project description:Current approaches for generating major histocompatibility complex (MHC) Class-I proteins with desired bound peptides (pMHC-I) for research, diagnostic and therapeutic applications are limited by the inherent instability of empty MHC-I molecules. Using the properties of the chaperone TAP-binding protein related (TAPBPR), we have developed a robust method to produce soluble, peptide-receptive MHC-I molecules in Chinese Hamster Ovary cells at high yield, completely bypassing the requirement for laborious refolding from inclusion bodies expressed in E.coli. Purified MHC-I/TAPBPR complexes can be prepared for multiple human allotypes, and exhibit complex glycan modifications at the conserved Asn 86 residue. As a proof of concept, we demonstrate both HLA allele-specific peptide binding and MHC-restricted antigen recognition by T cells for two relevant tumor-associated antigens. Our system provides a facile, high-throughput approach for generating pMHC-I antigens to probe and expand TCR specificities present in polyclonal T cell repertoires.
Project description:One of the most adaptive immune responses is triggered by specific T-cell receptors (TCR) binding to peptide-major histocompatibility complexes (pMHC). Despite the availability of many prediction servers to identify peptides binding to MHC, these servers are often lacking in peptide-TCR interactions and detailed atomic interacting models. PAComplex is the first web server investigating both pMHC and peptide-TCR interfaces to infer peptide antigens and homologous peptide antigens of a query. This server first identifies significantly similar TCR-pMHC templates (joint Z-value???4.0) of the query by using antibody-antigen and protein-protein interacting scoring matrices for peptide-TCR and pMHC interfaces, respectively. PAComplex then identifies the homologous peptide antigens of these hit templates from complete pathogen genome databases (?10(8) peptide candidates from 864,628 protein sequences of 389 pathogens) and experimental peptide databases (80,057 peptides in 2287 species). Finally, the server outputs peptide antigens and homologous peptide antigens of the query and displays detailed interacting models (e.g. hydrogen bonds and steric interactions in two interfaces) of hitTCR-pMHC templates. Experimental results demonstrate that the proposed server can achieve high prediction accuracy and offer potential peptide antigens across pathogens. We believe that the server is able to provide valuable insights for the peptide vaccine and MHC restriction. The PAComplex sever is available at http://PAcomplex.life.nctu.edu.tw.
Project description:The ?? T-cell receptor (TCR) on each T lymphocyte mediates exquisite specificity for a particular foreign peptide bound to a major histocompatibility complex molecule (pMHC) displayed on the surface of altered cells. This recognition stimulates protection in the mammalian host against intracellular pathogens, including viruses, and involves piconewton forces that accompany pMHC ligation. Physical forces are generated by T-lymphocyte movement during immune surveillance as well as by cytoskeletal rearrangements at the immunological synapse following cessation of cell migration. The mechanistic explanation for how TCRs distinguish between foreign and self-peptides bound to a given MHC molecule is unclear: peptide residues themselves comprise few of the TCR contacts on the pMHC, and pathogen-derived peptides are scant among myriad self-peptides bound to the same MHC class arrayed on infected cells. Using optical tweezers and DNA tether spacer technology that permit piconewton force application and nanometer scale precision, we have determined how bioforces relate to self versus nonself discrimination. Single-molecule analyses involving isolated ??-heterodimers as well as complete TCR complexes on T lymphocytes reveal that the FG loop in the ?-subunit constant domain allosterically controls both the variable domain module's catch bond lifetime and peptide discrimination via force-driven conformational transition. In contrast to integrins, the TCR interrogates its ligand via a strong force-loaded state with release through a weakened, extended state. Our work defines a key element of TCR mechanotransduction, explaining why the FG loop structure evolved for adaptive immunity in ?? but not ??TCRs or immunoglobulins.