CHARMM-GUI Membrane Builder for Mixed Bilayers and Its Application to Yeast Membranes

This is the publisher's version. Copyright 2009 by Elsevier.Most biological membranes are composed of many different kinds of lipid, and can be characterized by the composition of the lipids. Although more and more researchers have shown their interests in molecular dynamics simulation of lipid bilayer or protein-membrane complex system, the setup of such system remains quite challenging for even relatively experienced researchers. In the previous work [1], we have shown that the setup of molecular dynamics simulation for protein-membrane complex can be dramatically simplified by automating the process and providing intuitive and straightforward user interface. In this work, we have further elaborated the process to include 25 different kinds of lipid, which makes it possible to build more biologically relevant lipid bilayers, and we also added the facility to make a lipid bilayer system alone. The efficacy of the web interface at the CHARMM-GUI website [2] has been tested by building and simulating lipid bilayer systems that resemble yeast membrane, which is composed of cholesterol, DPPC, DOPC, POPE, POPA, and POPS. In this work, we will present the usages of the mixed bilayer generation in Membrane Builder and the simulation results of the yeast membrane systems

Orientation of Fluorescent Lipid Analog BODIPY-PC to Probe Lipid Membrane Properties: Insights from Molecular Dynamics Simulations

Single-molecule fluorescence measurements have been used to characterize membrane properties, and recently showed a linear evolution of the fluorescent lipid analog BODIPY-PC towards small tilt angles in Langmuir-Blodgett monolayers as the lateral surface pressure is increased. In this work, we have performed comparative molecular dynamics (MD) simulations of BODIPY-PC in DPPC (dipalmitoylphosphatidylcholine) monolayers and bilayers at three surface pressures (3, 10, and 40 mN/m) to explore 1) the microscopic correspondence between monolayer and bilayer structures, 2) the fluorophore’s position within the membrane, and 3) the microscopic driving forces governing the fluorophore’s tilting. The MD simulations reveal very close agreement between the monolayer and bilayer systems in terms of the fluorophore’s orientation and lipid chain order, suggesting that monolayer experiments can be used to approximate bilayer systems. The simulations capture the trend of reduced tilt angle of the fluorophore with increasing surface pressure as seen in the experimental results, and provide detailed insights into fluorophore location and orientation, not obtainable in the experiments. The simulations also reveal that the enthalpic contribution is dominant at 40 mN/m resulting in smaller tilt angles of the fluorophore, and the entropy contribution is dominant at lower pressures resulting in larger tilt angles

Membrane permeability of small molecules from unbiased molecular dynamics simulations

Permeation of many small molecules through lipid bilayers can be directly observed in molecular dynamics simulations on the nano- and microsecond timescale. While unbiased simulations provide an unobstructed view of the permeation process, their feasibility for computing permeability coefficients depends on various factors that differ for each permeant. The present work studies three small molecules for which unbiased simulations of permeation are feasible within less than a microsecond, one hydrophobic (oxygen), one hydrophilic (water), and one amphiphilic (ethanol). Permeabilities are computed using two approaches: counting methods and a maximum-likelihood estimation for the inhomogeneous solubility diffusion (ISD) model. Counting methods yield nearly model-free estimates of the permeability for all three permeants. While the ISD-based approach is reasonable for oxygen, it lacks precision for water due to insufficient sampling and results in misleading estimates for ethanol due to invalid model assumptions. It is also demonstrated that simulations using a Langevin thermostat with collision frequencies of 1/ps and 5/ps yield oxygen permeabilities and diffusion constants that are lower than those using Nose-Hoover by statistically significant margins. In contrast, permeabilities from trajectories generated with Nose-Hoover and the microcanonical ensemble do not show statistically significant differences. As molecular simulations become more affordable and accurate, calculation of permeability for an expanding range of molecules will be feasible using unbiased simulations. The present work summarizes theoretical underpinnings, identifies pitfalls, and develops best practices for such simulations

CHARMM-GUI Membrane Builder Toward Realistic Biological Membrane Simulations

This is the peer reviewed version of the following article: Wu, E. L., Cheng, X., Jo, S., Rui, H., Song, K. C., Dávila-Contreras, E. M., … Im, W. (2014). CHARMM-GUI Membrane Builder Toward Realistic Biological Membrane Simulations. Journal of Computational Chemistry, 35(27), 1997–2004. http://doi.org/10.1002/jcc.23702, which has been published in final form at http://doi.org/10.1002/jcc.23702. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.CHARMM-GUI Membrane Builder, http://www.charmm-gui.org/input/membrane, is a web-based user interface designed to interactively build all-atom protein/membrane or membrane-only systems for molecular dynamics simulation through an automated optimized process. In this work, we describe the new features and major improvements in Membrane Builderthat allow users to robustly build realistic biological membrane systems, including (1) addition of new lipid types such as phosphoinositides, cardiolipin, sphingolipids, bacterial lipids, and ergosterol, yielding more than 180 lipid types, (2) enhanced building procedure for lipid packing around protein, (3) reliable algorithm to detect lipid tail penetration to ring structures and protein surface, (4) distance-based algorithm for faster initial ion displacement, (5) CHARMM inputs for P21 image transformation, and (6) NAMD equilibration and production inputs. The robustness of these new features is illustrated by building and simulating a membrane model of the polar and septal regions of E. coli membrane, which contains five lipid types: cardiolipin lipids with two types of acyl chains and phosphatidylethanolamine lipids with three types of acyl chains. It is our hope that CHARMM-GUI Membrane Builder becomes a useful tool for simulation studies to better understand the structure and dynamics of proteins and lipids in realistic biological membrane environments

Modeling Plasma Membranes and Proteins that Transport Small Molecules and Membrane Components

Presented on March 13, 2013 from 4-5 pm in room G011 of the Molecular Science and Engineering Building.Dr. Jeffery B. Klauda is an Assistant Professor, Department of Chemical and Biomolecular Engineering A. James Clark School of Engineering at the University of Maryland. Dr. Klauda's research interests encompass thermodynamic modeling and molecular simulations with applications in energy, gas separation, and biomolecular systems.Runtime: 54:01 minutesLipid membranes protect cells from unwanted compounds and proteins control the transport of substrates between and across cellular membranes. The composition of these membranes varies significantly between organisms and organelles within an organism, which ultimately plays an important role in membrane structure and interaction with membrane-associated proteins. Our studies on the cytoplasmic membrane of E. coli with its unique lipid containing a cyclopropane moiety on its chain demonstrate the importance of lipid diversity to membrane structure and rigidity. Our E. coli membrane model agrees with known hydrophobic thicknesses of transmembrane proteins and is thinner than existing simple models for the cytoplasmic membrane. With accurate model membranes, simulations on membrane-associated proteins can provide insight on how proteins transport substrate across the membrane or between membranes. Lactose permease (LacY) of E. coli is a model for secondary active transporters (SATs) but most SATs have crystal structures in a single state in the transport cycle. To study substrate transport mechanism, we have developed a simulation technique to enhance conformational sampling of SAT proteins. This method was successful in obtaining the unknown periplasmic-open state of LacY and our simulations agree with a multitude of experimental measurements (FRET, DEER, accessibility studies, etc.). With a crystal structure in a single conformational state, our method can probe other states in the substrate transport cycle. While SAT proteins span the lipid bilayer, peripheral membrane proteins transiently bind to membranes and are involved in membrane signaling and transport. Our multiple ms all-atom simulations of the peripheral membrane protein of yeast (Osh4) have clarified how this protein binds to membranes. Previous experimental mutation studies suggested that Osh4 contained 2-3 distinct membrane binding domains. However, our simulations on similar model membranes used in experiments demonstrate a single membrane binding region. Since the membrane binding region on Osh4 agrees with previous experiments, it appears that Osh4 has a single large membrane binding domain. Ultimately, our goal is to probe how Osh4 transports sterols and an important signaling lipid between organelles in yeast