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      Structures of peptide-free and partially loaded MHC class I molecules reveal mechanisms of peptide selection

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          Abstract

          Major Histocompatibility Complex (MHC) class I molecules selectively bind peptides for presentation to cytotoxic T cells. The peptide-free state of these molecules is not well understood. Here, we characterize a disulfide-stabilized version of the human class I molecule HLA-A*02:01 that is stable in the absence of peptide and can readily exchange cognate peptides. We present X-ray crystal structures of the peptide-free state of HLA-A*02:01, together with structures that have dipeptides bound in the A and F pockets. These structural snapshots reveal that the amino acid side chains lining the binding pockets switch in a coordinated fashion between a peptide-free unlocked state and a peptide-bound locked state. Molecular dynamics simulations suggest that the opening and closing of the F pocket affects peptide ligand conformations in adjacent binding pockets. We propose that peptide binding is co-determined by synergy between the binding pockets of the MHC molecule.

          Abstract

          Major Histocompatibility Complex (MHC) class I molecules present tightly binding peptides on the cell surface for recognition by cytotoxic T cells. Here, the authors present the crystal structures of a disulfide-stabilized human MHC class I molecule in the peptide-free state and bound with dipeptides, and find that peptide binding is accompanied by concerted conformational switches of the amino acid side chains in the binding pockets.

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          Long-Time-Step Molecular Dynamics through Hydrogen Mass Repartitioning.

          Previous studies have shown that the method of hydrogen mass repartitioning (HMR) is a potentially useful tool for accelerating molecular dynamics (MD) simulations. By repartitioning the mass of heavy atoms into the bonded hydrogen atoms, it is possible to slow the highest-frequency motions of the macromolecule under study, thus allowing the time step of the simulation to be increased by up to a factor of 2. In this communication, we investigate further how this mass repartitioning allows the simulation time step to be increased in a stable fashion without significantly increasing discretization error. To this end, we ran a set of simulations with different time steps and mass distributions on a three-residue peptide to get a comprehensive view of the effect of mass repartitioning and time step increase on a system whose accessible phase space is fully explored in a relatively short amount of time. We next studied a 129-residue protein, hen egg white lysozyme (HEWL), to verify that the observed behavior extends to a larger, more-realistic, system. Results for the protein include structural comparisons from MD trajectories, as well as comparisons of pKa calculations via constant-pH MD. We also calculated a potential of mean force (PMF) of a dihedral rotation for the MTS [(1-oxyl-2,2,5,5-tetramethyl-pyrroline-3-methyl)methanethiosulfonate] spin label via umbrella sampling with a set of regular MD trajectories, as well as a set of mass-repartitioned trajectories with a time step of 4 fs. Since no significant difference in kinetics or thermodynamics is observed by the use of fast HMR trajectories, further evidence is provided that long-time-step HMR MD simulations are a viable tool for accelerating MD simulations for molecules of biochemical interest.
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            Building Water Models: A Different Approach

            Simplified classical water models are currently an indispensable component in practical atomistic simulations. Yet, despite several decades of intense research, these models are still far from perfect. Presented here is an alternative approach to constructing widely used point charge water models. In contrast to the conventional approach, we do not impose any geometry constraints on the model other than the symmetry. Instead, we optimize the distribution of point charges to best describe the “electrostatics” of the water molecule. The resulting “optimal” 3-charge, 4-point rigid water model (OPC) reproduces a comprehensive set of bulk properties significantly more accurately than commonly used rigid models: average error relative to experiment is 0.76%. Close agreement with experiment holds over a wide range of temperatures. The improvements in the proposed model extend beyond bulk properties: compared to common rigid models, predicted hydration free energies of small molecules using OPC are uniformly closer to experiment, with root-mean-square error <1 kcal/mol.
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              Extension to the weighted histogram analysis method: combining umbrella sampling with free energy calculations

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                Author and article information

                Contributors
                s.springer@jacobs-university.de
                rob.meijers@proteininnovation.org
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                11 March 2020
                11 March 2020
                2020
                : 11
                : 1314
                Affiliations
                [1 ]ISNI 0000 0000 9397 8745, GRID grid.15078.3b, Department of Life Sciences and Chemistry, , Jacobs University Bremen, ; Bremen, Germany
                [2 ]ISNI 0000 0004 0444 5410, GRID grid.475756.2, European Molecular Biology Laboratory, Hamburg Outstation, ; Hamburg, Germany
                [3 ]ISNI 0000 0001 0665 103X, GRID grid.418481.0, Heinrich Pette Institute, Leibniz Institute for Experimental Virology, ; Hamburg, Germany
                [4 ]ISNI 0000 0004 0590 2900, GRID grid.434729.f, European XFEL GmbH, ; Schenefeld, Germany
                [5 ]ISNI 0000000123222966, GRID grid.6936.a, Physics Department, , Technical University of Munich, ; Garching, Germany
                [6 ]Present Address: Institute for Protein Innovation, Boston, USA
                Author information
                http://orcid.org/0000-0001-9806-5352
                http://orcid.org/0000-0002-1991-7922
                http://orcid.org/0000-0002-5527-6149
                http://orcid.org/0000-0003-2872-6279
                Article
                14862
                10.1038/s41467-020-14862-4
                7066147
                32161266
                0c7d5309-f09a-4275-9c1b-b1202c59e91b
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 8 August 2019
                : 6 February 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000780, European Commission (EC);
                Award ID: 653706
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft (German Research Foundation);
                Award ID: SP583/12-1
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100001664, Leibniz-Gemeinschaft (Leibniz Association);
                Award ID: SAW-2014-HPI-4
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                biochemistry,protein design,mhc class i,molecular modelling,x-ray crystallography
                Uncategorized
                biochemistry, protein design, mhc class i, molecular modelling, x-ray crystallography

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