Molecular dynamics simulations in the paper "High-resolution structures with bound Mn2+ and Cd2+ map the metal import pathway in an Nramp transporter". performed by Eric Wilson under the supervision of Abhishek Singharoy analyzed by Sam Berry under the supervision of Rachelle Gaudet --- ## Description of the Data and file structure This directory contains six simulations in .dcd format, zipped and tarred (you can extract them with tar -zvf [filename]), along with corresponding system files for each simulation in .pdb and .psf formats. (See "Usage information" below for notes on what to do with these files) The simulations are as follows: 1) S1a and S1b: two replicates of a simulation starting in the outward-open conformation of DraNramp (PDB code 6BU5) 2) S2a and S2b: two replicates of a simulation starting in the occluded conformation of DraNramp (PDB code 8E5S) 3) S3a and S3b: two replicates of a simulation starting in the inward-open conformation of DraNramp (PDB code 8E6M) Additionally, there is a contained folder with water occupancy data, generated via the water_occupancy.py script in the GitHub repository: https://github.com/samberry19/nramp-md. These files are all text files of two kinds: 1) water_occupancy files, either _t2.0, _t2.5, or t_3.0 (referring to what cutoff threshold in Å was used to determine proximity of the water to the residue of interest in the protein), are text files of 1s and 0s corresponding to whether the site defined by the residues mentioned in the name of the file is occupied by a water 2) closest_waters: tells you *which* water in the system file is closest to that residue, which can then be used to calculate lifetimes of particular waters in a given site (note that this information is not actually used in the paper) All other analysis scripts used in the paper are also contained in the GitHub repository, and all figures can be exactly reproduced using these simulations and the code in the Jupyter notebook contained in the GitHub. ## Detailed simulation methods From our paper: "Molecular dynamics (MD) simulations were initialized from three high-resolution structures of DraNramp: the outward-open G223W•Mn2+ structure (6BU5) with Mn2+ removed and W223 mutated back to the native glycine residue in silico, the inward-open WT•Cd2+ structure with Cd2+ removed, and the inward-occluded WT structure. Crystallographic waters were retained, and protonation states of key titratable residues were selected with PROPKA (M. H. Olsson, Sondergaard, Rostkowski, & Jensen, 2011; Sondergaard, Olsson, Rostkowski, & Jensen, 2011) assuming a pH of 5.0 for residues exposed to external solvent and a pH of 7.0 for residues exposed to cytosol, a condition under which DraNramp exhibits high activity. All structures were oriented in the membrane with the PPM web server and membrane systems were prepared with CHARMM-GUI (Jo, Kim, Iyer, & Im, 2008; Lee et al., 2016). A POPC membrane of surface area 99 x 99 Å was constructed in the XY plane around the protein (Wu et al., 2014), the system was solvated in a 100 x 100 x 100 Å3 rectangular box using TIP3 waters and electronically neutralized using potassium and chlorine ions at an overall concentration of 150 mM. The overall system size was approximately 103,000 atoms. All-atom simulations were run using GPU-accelerated NAMD (Phillips, Stone, & Schulten, 2008) and the CHARMM36m forcefield (Huang et al., 2017). Prior to simulation, the energy of each system was minimized for 10,000 steps using a conjugate gradient and line search algorithm native to NAMD. To improve simulation stability, the system was initially equilibrated using an NVT-ensemble with harmonic restraints placed on protein and lipid heavy atoms. The harmonic restraints were then incrementally relaxed over a period of 675 ps according to established CHARMM-GUI protocols (Lee et al., 2016). The system was then simulated at a constant pressure, utilizing the Langevin piston method to maintain 1 atm at 303.15 K, from anywhere between 617 to 1176 ns depending on the starting conformation. Simulations were performed using periodic boundary conditions and a time step of 3.0 fs with all bonds to hydrogens being constrained. Large integration timesteps were enabled by employing hydrogen mass repartitioning (Hopkins, Le Grand, Walker, & Roitberg, 2015). Long-range electrostatic interactions were calculated using the particle mesh Ewald (PME) method with nonbonded interactions being cut off at 12 Å. Each simulation was performed in duplicate resulting in approximately 2 µs of total sampling for each system. Simulations are summarized in Supplementary Table 11." ## Usage inforamtion The raw simulations can be loaded into PyMOL or VMD (first load the system file and then load the .dcd trajectory into it). Because these simulations are quite large, some users may wish to first stride them. We personally do this using catdcd: https://www.ks.uiuc.edu/Development/MDTools/catdcd/. ## Sharing/access Information We release our data into the public domain under a CC0 1.0 Universal (CC0 1.0) license (https://creativecommons.org/publicdomain/zero/1.0/). All data within this submission is freely available for reuse and adaptation by any individual for any purpose.