DOI: 10.5281/zenodo.7303652
title: Simulations of Sec61 with a substrate-selective inhibitor

description: 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. 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". The GROMACS-compatible files include: Run input files (.tpr) Trajectory with coordinates written every 1 ns (.xtc) Energy file (.edr) Final coordinates after 1 µs of simulation (.gro) Continue points for extending the simulation (.cpt) Additionally, for each type of simulation (with KZR8445, without KZR8445, N300A mutation), common files are included: Index file (.ndx) Topology file (.top) 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. <strong>Additional details on the methodology used in the simulations is described below:</strong> 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]. 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]. [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).