Huan Rui

CHARMM-GUI Membrane Builder toward realistic biological membrane simulations.

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 simulations through an automated optimized process. In this work, we describe the new features and major improvements in Membrane Builder that allow users to robustly build realistic biological membrane systems, including (1) addition of new lipid types, such as phosphoinositides, cardiolipin (CL), 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: CL 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.

Cholesterol flip-flop: insights from free energy simulation studies.

The mechanism of lipid flip-flop motion is important for maintaining the asymmetric distribution of lipids in a biological membrane. To explore the energetics and mechanism of passive cholesterol flip-flop and its dependence on chain saturation, we performed two-dimensional umbrella sampling simulations in DPPC, POPC, and DAPC (dipalmitoyl-, palmitoyloleoyl-, and diarachidonylphosphatidylcholine) and used the string method to identify the most probable flip-flop paths based on the two-dimensional free energy maps. The resulting paths indicate that cholesterol prefers to tilt first and then move to the bilayer center where the free energy barrier exists. The barrier is lower in DAPC than in DPPC or POPC, and the calculated flip-flop rates show that cholesterol flip-flop in a poly-unsaturated bilayer is faster than in more saturated bilayers. The free energy barrier results from the unfavorable enthalpic contribution arising from cholesterol-water/lipid interactions and the favorable entropic contribution due to increased lipid dynamics. While the cholesterol-water interaction has similar contributions to the barrier due to desolvation of the cholesterol hydroxyl group in all lipids, the cholesterol-lipid interaction has a much lower barrier in DAPC than in DPPC or POPC, resulting in the lower free energy barrier in DAPC.

Brownian Dynamics Simulations of Ion Transport through the VDAC

It is important to gain a physical understanding of ion transport through the voltage-dependent anion channel (VDAC) because this channel provides primary permeation pathways for metabolites and electrolytes between the cytosol and mitochondria. We performed grand canonical Monte Carlo/Brownian dynamics (GCMC/BD) simulations to explore the ion transport properties of human VDAC isoform 1 (hVDAC1; PDB:2K4T) embedded in an implicit membrane. When the MD-derived, space-dependent diffusion constant was used in the GCMC/BD simulations, the current-voltage characteristics and ion number profiles inside the pore showed excellent agreement with those calculated from all-atom molecular-dynamics (MD) simulations, thereby validating the GCMC/BD approach. Of the 20 NMR models of hVDAC1 currently available, the third one (NMR03) best reproduces both experimental single-channel conductance and ion selectivity (i.e., the reversal potential). In addition, detailed analyses of the ion trajectories, one-dimensional multi-ion potential of mean force, and protein charge distribution reveal that electrostatic interactions play an important role in the channel structure and ion transport relationship. Finally, the GCMC/BD simulations of various mutants based on NMR03 show good agreement with experimental ion selectivity. The difference in ion selectivity between the wild-type and the mutants is the result of altered potential of mean force profiles that are dominated by the electrostatic interactions.

Web interface for brownian dynamics simulation of ion transport and its applications to beta‐barrel pores

Brownian dynamics (BD) based on accurate potential of mean force is an efficient and accurate method for simulating ion transport through wide ion channels. Here, a web‐based graphical user interface (GUI) is presented for carrying out grand canonical Monte Carlo (GCMC) BD simulations of channel proteins: http://www.charmm‐gui.org/input/gcmcbd. The webserver is designed to help users avoid most of the technical difficulties and issues encountered in setting up and simulating complex pore systems. GCMC/BD simulation results for three proteins, the voltage dependent anion channel (VDAC), α‐Hemolysin (α‐HL), and the protective antigen pore of the anthrax toxin (PA), are presented to illustrate the system setup, input preparation, and typical output (conductance, ion density profile, ion selectivity, and ion asymmetry). Two models for the input diffusion constants for potassium and chloride ions in the pore are compared: scaling of the bulk diffusion constants by 0.5, as deduced from previous all‐atom molecular dynamics simulations of VDAC, and a hydrodynamics based model (HD) of diffusion through a tube. The HD model yields excellent agreement with experimental conductances for VDAC and α‐HL, while scaling bulk diffusion constants by 0.5 leads to underestimates of 10–20%. For PA, simulated ion conduction values overestimate experimental values by a factor of 1.5–7 (depending on His protonation state and the transmembrane potential), implying that the currently available computational model of this protein requires further structural refinement.

CHARMM-GUI PDB Manipulator for Advanced Modeling and Simulations of Proteins Containing Nonstandard Residues

CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface to prepare molecular simulation systems and input files to facilitate the usage of common and advanced simulation techniques. Since it is originally developed in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to setup a broad range of simulations including free energy calculation and large-scale coarse-grained representation. Here, we describe functionalities that have recently been integrated into CHARMM-GUI PDB Manipulator, such as ligand force field generation, incorporation of methanethiosulfonate spin labels and chemical modifiers, and substitution of amino acids with unnatural amino acids. These new features are expected to be useful in advanced biomolecular modeling and simulation of proteins.

Probing the U-shaped conformation of caveolin-1 in a bilayer.

Caveolin induces membrane curvature and drives the formation of caveolae that participate in many crucial cell functions such as endocytosis. The central portion of caveolin-1 contains two helices (H1 and H2) connected by a three-residue break with both N- and C-termini exposed to the cytoplasm. Although a U-shaped configuration is assumed based on its inaccessibility by extracellular matrix probes, caveolin structure in a bilayer remains elusive. This work aims to characterize the structure and dynamics of caveolin-1 (D82-S136; Cav182-136) in a DMPC bilayer using NMR, fluorescence emission measurements, and molecular dynamics simulations. The secondary structure of Cav182-136 from NMR chemical shift indexing analysis serves as a guideline for generating initial structural models. Fifty independent molecular dynamics simulations (100 ns each) are performed to identify its favorable conformation and orientation in the bilayer. A representative configuration was chosen from these multiple simulations and simulated for 1 μs to further explore its stability and dynamics. The results of these simulations mirror those from the tryptophan fluorescence measurements (i.e., Cav182-136 insertion depth in the bilayer), corroborate that Cav182-136 inserts in the membrane with U-shaped conformations, and show that the angle between H1 and H2 ranges from 35 to 69°, and the tilt angle of Cav182-136 is 27 ± 6°. The simulations also reveal that specific faces of H1 and H2 prefer to interact with each other and with lipid molecules, and these interactions stabilize the U-shaped conformation.

Novel free energy calculations to explore mechanisms and energetics of membrane protein structure and function

Understanding the delicate balance of forces governing helix or β‐hairpin interactions in transmembrane (TM) proteins is central to understanding membrane structure and function. These membrane constituent interactions play an essential role in determining the structure and function of membrane proteins, and protein interactions in membranes, and thus form the basis for many vital processes, including TM signaling, transport of ions and small molecules, energy transduction, and cell–cell recognition. “Why does a single‐pass TM helix or β‐hairpin have specific orientations in membranes?” “What are the roles of hydrogen bonds, close packing, and helix‐lipid or β‐hairpin‐lipid interactions in helix or β‐hairpin associations in membranes?” “How do these interactions change the membrane structures?” “How do TM domains transmit signals across membranes?” These are important membrane biophysical questions that can be addressed by understanding the delicate balance of forces governing helix or β‐hairpin interactions with/in membranes. In this work, we summarize a series of helix/β‐hairpin restraint potentials that we have developed, and illustrate their applications that begin to address the complicated energetics and molecular mechanisms of these interactions at the atomic level by calculating the potentials of mean force (PMFs) along reaction coordinates relevant to helix/β‐hairpin motions in membranes and dissecting the total PMF into the contributions arising from physically important microscopic forces.

Protegrin-1 orientation and physicochemical properties in membrane bilayers studied by potential of mean force calculations.

Protegrin‐1 (PG‐1) belongs to the family of antimicrobial peptides. It interacts specifically with the membrane of a pathogen and kills the pathogen by releasing its cellular contents. To fully understand the energetics governing the orientation of PG‐1 in different membrane environments and its effects on the physicochemical properties of the peptide and membrane bilayers, we have performed the potential of mean force (PMF) calculations as a function of its tilt angle at four distinct rotation angles in explicit membranes composed of either DLPC (1,2‐dilauroylphosphatidylcholine) or POPC (1‐palmitoyl‐2‐oleoylphosphatidylcholine) lipid molecules. The resulting PMFs in explicit lipid bilayers were then used to search for the optimal hydrophobic thickness of the EEF1/IMM1 implicit membrane model in which a two‐dimensional PMF in the tilt and rotation space was calculated. The PMFs in explicit membrane systems clearly reveal that the energetically favorable tilt angle is affected by both the membrane hydrophobic thickness and the PG‐1 rotation angle. Local thinning of the membrane around PG‐1 is observed upon PG‐1 tilting. The thinning is caused by both hydrophobic mismatch and arginine‐lipid head group interactions. The two‐dimensional PMF in the implicit membrane is in good accordance with those from the explicit membrane simulations. The ensemble‐averaged Val16 15N and 13CO chemical shifts weighted by the two‐dimensional PMF agree fairly well with the experimental values, suggesting the importance of peptide dynamics in calculating such ensemble properties for direct comparison with experimental observables.

Comparative Molecular Dynamics Simulation Studies of Protegrin-1 Monomer and Dimer in Two Different Lipid Bilayers

Antimicrobial peptides interact specifically with the membrane of a pathogen and kill the pathogen by releasing its cellular contents. Protegrin-1 (PG-1), a beta-hairpin antimicrobial peptide, is known to exist as a transmembrane monomer in a 1,2-dilauroylphosphatidylcholine (DLPC) bilayer and shows concentration-dependent oligomerization in a 1-palmitoyl-2-oleoylphosphatidylcholine (POPC) bilayer. To examine its structure, dynamics, orientation, and interaction in membranes, we performed comparative molecular dynamics simulations of PG-1 monomer and dimer in DLPC and POPC bilayers for a total of 840 ns. The PG-1 monomer exhibits larger tilting in DLPC than in POPC due to a hydrophobic mismatch. PG-1 tilting is dependent on its rotation angle. The specific orientation of PG-1 in membranes is governed by the interactions of its aromatic residues with lipid headgroups. The calculated (15)N and (13)CO chemical shifts of Val(16) in DLPC reveal that there are different sets of tilt and rotation angles that satisfy the experimental values reasonably, suggesting that more experiments are needed to determine its orientation. The dimer simulations show that the dimer interface is better preserved in POPC than in DLPC because POPCs greater hydrophobic thickness causes reduced flexibility of the C-terminal strands. Both monomer and dimer simulations show membrane thinning around PG-1, largely due to arginine-lipid interactions.

CHARMM-GUI 10 years for biomolecular modeling and simulation.

CHARMM‐GUI, http://www.charmm-gui.org, is a web‐based graphical user interface that prepares complex biomolecular systems for molecular simulations. CHARMM‐GUI creates input files for a number of programs including CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Since its original development in 2006, CHARMM‐GUI has been widely adopted for various purposes and now contains a number of different modules designed to set up a broad range of simulations: (1) PDB Reader & Manipulator, Glycan Reader, and Ligand Reader & Modeler for reading and modifying molecules; (2) Quick MD Simulator, Membrane Builder, Nanodisc Builder, HMMM Builder, Monolayer Builder, Micelle Builder, and Hex Phase Builder for building all‐atom simulation systems in various environments; (3) PACE CG Builder and Martini Maker for building coarse‐grained simulation systems; (4) DEER Facilitator and MDFF/xMDFF Utilizer for experimentally guided simulations; (5) Implicit Solvent Modeler, PBEQ‐Solver, and GCMC/BD Ion Simulator for implicit solvent related calculations; (6) Ligand Binder for ligand solvation and binding free energy simulations; and (7) Drude Prepper for preparation of simulations with the CHARMM Drude polarizable force field. Recently, new modules have been integrated into CHARMM‐GUI, such as Glycolipid Modeler for generation of various glycolipid structures, and LPS Modeler for generation of lipopolysaccharide structures from various Gram‐negative bacteria. These new features together with existing modules are expected to facilitate advanced molecular modeling and simulation thereby leading to an improved understanding of the structure and dynamics of complex biomolecular systems. Here, we briefly review these capabilities and discuss potential future directions in the CHARMM‐GUI development project.