Inviting an author to review:
Find an author and click ‘Invite to review selected article’ near their name.
Search for authorsSearch for similar articles
12
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      APE-Gen: A Fast Method for Generating Ensembles of Bound Peptide-MHC Conformations

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The Class I Major Histocompatibility Complex (MHC) is a central protein in immunology as it binds to intracellular peptides and displays them at the cell surface for recognition by T-cells. The structural analysis of bound peptide-MHC complexes (pMHCs) holds the promise of interpretable and general binding prediction (i.e., testing whether a given peptide binds to a given MHC). However, structural analysis is limited in part by the difficulty in modelling pMHCs given the size and flexibility of the peptides that can be presented by MHCs. This article describes APE-Gen (Anchored Peptide-MHC Ensemble Generator), a fast method for generating ensembles of bound pMHC conformations. APE-Gen generates an ensemble of bound conformations by iterated rounds of (i) anchoring the ends of a given peptide near known pockets in the binding site of the MHC, (ii) sampling peptide backbone conformations with loop modelling, and then (iii) performing energy minimization to fix steric clashes, accumulating conformations at each round. APE-Gen takes only minutes on a standard desktop to generate tens of bound conformations, and we show the ability of APE-Gen to sample conformations found in X-ray crystallography even when only sequence information is used as input. APE-Gen has the potential to be useful for its scalability (i.e., modelling thousands of pMHCs or even non-canonical longer peptides) and for its use as a flexible search tool. We demonstrate an example for studying cross-reactivity.

          Related collections

          Most cited references37

          • Record: found
          • Abstract: found
          • Article: not found

          Reliable prediction of T-cell epitopes using neural networks with novel sequence representations.

          In this paper we describe an improved neural network method to predict T-cell class I epitopes. A novel input representation has been developed consisting of a combination of sparse encoding, Blosum encoding, and input derived from hidden Markov models. We demonstrate that the combination of several neural networks derived using different sequence-encoding schemes has a performance superior to neural networks derived using a single sequence-encoding scheme. The new method is shown to have a performance that is substantially higher than that of other methods. By use of mutual information calculations we show that peptides that bind to the HLA A*0204 complex display signal of higher order sequence correlations. Neural networks are ideally suited to integrate such higher order correlations when predicting the binding affinity. It is this feature combined with the use of several neural networks derived from different and novel sequence-encoding schemes and the ability of the neural network to be trained on data consisting of continuous binding affinities that gives the new method an improved performance. The difference in predictive performance between the neural network methods and that of the matrix-driven methods is found to be most significant for peptides that bind strongly to the HLA molecule, confirming that the signal of higher order sequence correlation is most strongly present in high-binding peptides. Finally, we use the method to predict T-cell epitopes for the genome of hepatitis C virus and discuss possible applications of the prediction method to guide the process of rational vaccine design.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Cardiovascular toxicity and titin cross-reactivity of affinity-enhanced T cells in myeloma and melanoma.

            An obstacle to cancer immunotherapy has been that the affinity of T-cell receptors (TCRs) for antigens expressed in tumors is generally low. We initiated clinical testing of engineered T cells expressing an affinity-enhanced TCR against HLA-A*01-restricted MAGE-A3. Open-label protocols to test the TCRs for patients with myeloma and melanoma were initiated. The first two treated patients developed cardiogenic shock and died within a few days of T-cell infusion, events not predicted by preclinical studies of the high-affinity TCRs. Gross findings at autopsy revealed severe myocardial damage, and histopathological analysis revealed T-cell infiltration. No MAGE-A3 expression was detected in heart autopsy tissues. Robust proliferation of the engineered T cells in vivo was documented in both patients. A beating cardiomyocyte culture generated from induced pluripotent stem cells triggered T-cell killing, which was due to recognition of an unrelated peptide derived from the striated muscle-specific protein titin. These patients demonstrate that TCR-engineered T cells can have serious and not readily predictable off-target and organ-specific toxicities and highlight the need for improved methods to define the specificity of engineered TCRs.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Present Yourself! By MHC Class I and MHC Class II Molecules.

              Since the discovery of MHC molecules, it has taken 40 years to arrive at a coherent picture of how MHC class I and MHC class II molecules really work. This is a story of the proteases and MHC-like chaperones that support the MHC class I and II molecules in presenting peptides to the immune system. We now understand that the MHC system shapes both the repertoire of presented peptides and the subsequent T cell response, with important implications ranging from transplant rejection to tumor immunotherapies. Here we present an illustrated review of the ins and outs of MHC class I and MHC class II antigen presentation.
                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Molecules
                Molecules
                molecules
                Molecules
                MDPI
                1420-3049
                02 March 2019
                March 2019
                : 24
                : 5
                : 881
                Affiliations
                [1 ]Department of Computer Science, Rice University, Houston, TX 77005, USA; j.abella@ 123456rice.edu (J.R.A.); dinler@ 123456rice.edu (D.A.A.)
                [2 ]Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA; cecilia@ 123456rice.edu
                [3 ]Department of Chemistry, Rice University, Houston, TX 77005, USA
                Author notes
                [* ]Correspondence: kavraki@ 123456rice.edu
                Author information
                https://orcid.org/0000-0002-8574-1144
                https://orcid.org/0000-0001-7947-6455
                https://orcid.org/0000-0001-9221-2358
                https://orcid.org/0000-0003-0699-8038
                Article
                molecules-24-00881
                10.3390/molecules24050881
                6429480
                30832312
                d8912333-8f5d-4688-bb59-c1d3f3cc05a8
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 15 January 2019
                : 27 February 2019
                Categories
                Article

                mhc class i,ensemble,molecular docking,peptide binding
                mhc class i, ensemble, molecular docking, peptide binding

                Comments

                Comment on this article