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4 results for “Sec61”
Simulations of Sec61 with a substrate-selective inhibitor
<p>Simulation inputs and outputs for manuscript "Signal peptide mimicry primes Sec61 for client-selective inhibition" by Rehan <em>et al</em>. Nature Chemical Biology 19, pages 1054–1062 (2023). DOI: 10.1038/s41589-023-01326-1.</p> <p>The Sec61 complex, embedded in a lipid bilayer mimicking ER in composition [1–4], was simulated in the presence ("Sec61_KZR8445", 5×1 µs) and absence ("Sec61_noinhibitor", 3×1 µs) of the cotransin KZR-8445 inhibitor. Additionally, a N300A mutant of Sec61α ("Sec61_KZR8445_N300A") was simulated in the presence of KZR-8445 for 1 µs. The replicas are labeled with "R". </p> <p>The GROMACS-compatible files include:</p> <ul> <li>Run input files (.tpr)</li> <li>Trajectory with coordinates written every 1 ns (.xtc)</li> <li>Energy file (.edr)</li> <li>Final coordinates after 1 µs of simulation (.gro)</li> <li>Continue points for extending the simulation (.cpt)</li> </ul> <p>Additionally, for each type of simulation (with KZR8445, without KZR8445, N300A mutation), common files are included:</p> <ul> <li>Index file (.ndx)</li> <li>Topology file (.top)</li> </ul> <p>The run parameter file (md.mdp) is common for all systems. The topologies (.itp) referred to by the top files are compressed into the TOP.tar archive.</p> <p><strong>Additional details on the methodology used in the simulations is described below:</strong></p> <p>We used the CHARMM36m protein force field [5,6], the CHARMM36 lipid force field [7], the CGenFF force field for the inhibitor with the ligand containing a positive dummy particle describing the bromobenzyl sigma hole [8,9], and CHARMM-specific TIP(S)3P model for water [10,11]. The systems were generated in CHARMM-GUI [12,13], including the protein positioning using PPM 2.0 [14] and the ligand parametrization within CHARMM-GUI [15].</p> <p>The leap-frog integrator was used with a time step of 2 fs. Buffered Verlet lists were used [16]. The Lennard-Jones forces were switched to zero between 1.0 and a cut-off distance of 1.2 nm. Long-range electrostatic interactions were included by the smooth particle mesh Ewald algorithm [17,18]. Temperatures of the protein (including the inhibitor), the lipids, and the solvent (water and ions) were separately coupled to a Nosé–Hoover thermostat [19,20] with a target temperature of 310 K and a relaxation time of 1 ps. The pressure was maintained at 1 bar with a semi-isotropic Parrinello–Rahman barostat [21]. The target pressure was set to 1 bar, the compressibility to 4.5 × 10<sup>–5</sup> bar<sup>–1</sup> and the relaxation time constant 5 ps. Bonds involving hydrogens were constrained with p-LINCS [22,23].</p> <p>[1] Bollen, I. C. & Higgins, J. A. Phospholipid asymmetry in rough- and smooth-endoplasmic-reticulum membranes of untreated and phenobarbital-treated rat liver. <em>Biochem. J</em> 189, 475–480 (1980).<br> [2] Colbeau, A., Nachbaur, J. & Vignais, P. M. Enzymac characterization and lipid composition of rat liver subcellular membranes. <em>Biochim. Biophys. Acta </em>249, 462–492 (1971).<br> [3] Davison, S. C. & Wills, E. D. Studies on the lipid composition of the rat liver endoplasmic reticulum after induction with phenobarbitone and 20-methylcholanthrene. <em>Biochem. J</em> 140, 461–468 (1974).<br> [4] Casares, D., Escribá, P. V. & Rosselló, C. A. Membrane Lipid Composition: Effect on Membrane and Organelle Structure, Function and Compartmentalization and Therapeutic Avenues. <em>Int. J. Mol.</em> Sci. 20, (2019).<br> [5] Huang, J. & MacKerell, A. D., Jr. CHARMM36 all-atom additive protein force field: validation based on comparison to NMR data. <em>J. Comput. Chem.</em> 34, 2135–2145 (2013).<br> [6] Huang, J. et al. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. <em>Nat. Methods</em> 14, 71–73 (2017).<br> [7] Klauda, J. B. et al. Update of the CHARMM all-atom additive force field for lipids: validation on six lipid types. <em>J. Phys. Chem. B</em> 114, 7830–7843 (2010).<br> [8] Vanommeslaeghe, K. et al. CHARMM general force field: A force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. <em>J. Comput. Chem.</em> 31, 671–690 (2010).<br> [9] Soteras Gutiérrez, I. et al. Parametrization of halogen bonds in the CHARMM general force field: Improved treatment of ligand-protein interactions. <em>Bioorg. Med. Chem.</em> 24, 4812–4825 (2016).<br> [10] Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W. & Klein, M. L. Comparison of simple potential functions for simulating liquid water. <em>J. Chem. Phys.</em> 79, 926–935 (1983).<br> [11] Durell, S. R., Brooks, B. R. & Ben-Naim, A. Solvent-Induced Forces between Two Hydrophilic Groups.<em> J. Phys. Chem.</em> 98, 2198–2202 (1994).<br> [12] Jo, S., Kim, T., Iyer, V. G. & Im, W. CHARMM-GUI: a web-based graphical user interface for CHARMM. <em>J. Comput. Chem</em>. 29, 1859–1865 (2008).<br> [13] Wu, E. L. et al. CHARMM-GUI Membrane Builder toward realistic biological membrane simulations. <em>J. Comput. Chem.</em> 35, 1997–2004 (2014).<br> [14] Lomize, M. A., Pogozheva, I. D., Joo, H., Mosberg, H. I. & Lomize, A. L. OPM database and PPM web server: resources for positioning of proteins in membranes. <em>Nucleic Acids Res. 40</em>, D370–6 (2012).<br> [15] Kim, S. et al. CHARMM-GUI ligand reader and modeler for CHARMM force field generation of small molecules. <em>J. Comput. Chem.</em> 38, 1879–1886 (2017).<br> [16] Páll, S. & Hess, B. A flexible algorithm for calculating pair interactions on SIMD architectures. <em>Comput. Phys. Commun.</em> 184, 2641–2650 (2013).<br> [17] Darden, T., York, D. & Pedersen, L. Particle mesh Ewald: An N⋅log(N) method for Ewald sums in large systems. <em>J. Chem. Phys.</em> 98, 10089–10092 (1993).<br> [18] Essmann, U. et al. A smooth particle mesh Ewald method. <em>J. Chem. Phys.</em> 103, 8577–8593 (1995).<br> [19] Nosé, S. A unified formulation of the constant temperature molecular dynamics methods. <em>J. Chem. Phys.</em> 81, 511–519 (1984).<br> [20] Hoover, W. G. Canonical dynamics: Equilibrium phase-space distributions. <em>Phys. Rev. A Gen. Phys.</em> 31, 1695–1697 (1985).<br> [21] Parrinello, M. & Rahman, A. Polymorphic transitions in single crystals: A new molecular dynamics method. <em>J. Appl. Phys.</em> 52, 7182–7190 (1981).<br> [22] Hess, B. P-LINCS: A Parallel Linear Constraint Solver for Molecular Simulation. <em>J. Chem. Theory Comput.</em> 4, 116–122 (2008).<br> [23] Hess, B., Bekker, H., Berendsen, H. J. C. & Fraaije, J. G. E. M. LINCS: A linear constraint solver for molecular simulations. <em>J. Comput. Chem.</em> 18, 1463–1472 (1997).</p>
Coarse-grained simulations of the Sec61 and TRAP complexes in a multi-component membrane
<p>to be added</p>
Simulations of Sec61 with a substrate-selective inhibitor, conformation 1
<p>Simulations for an alternative conformation of KZR-8445 bound to Sec61. Data for the conformation used in Rehan <em>et al.</em>, Nature Chemical Biology 19, pages 1054–1062 (2023) are available at <a href="https://zenodo.org/record/7303653">https://zenodo.org/record/7303653</a></p>
Coarse-grained simulations of the Sec61 and TRAP complexes in a POPC membrane
<p>to be added</p>
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