Emilia L. Wu

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.

Molecular Dynamics and NMR Spectroscopy Studies of E. coli Lipopolysaccharide Structure and Dynamics

Lipopolysaccharide (LPS), a component of Gram-negative bacterial outer membranes, comprises three regions: lipid A, core oligosaccharide, and O-antigen polysaccharide. Using the CHARMM36 lipid and carbohydrate force fields, we have constructed a model of an Escherichia coli R1 (core) O6 (antigen) LPS molecule. Several all-atom bilayers are built and simulated with lipid A only (LIPA) and varying lengths of 0 (LPS0), 5 (LPS5), and 10 (LPS10) O6 antigen repeating units; a single unit of O6 antigen contains five sugar residues. From (1)H,(1)H-NOESY experiments, cross-relaxation rates are obtained from an O-antigen polysaccharide sample. Although some experimental deviations are due to spin-diffusion, the remaining effective proton-proton distances show generally very good agreement between NMR experiments and molecular dynamics simulations. The simulation results show that increasing the LPS molecular length has an impact on LPS structure and dynamics and also on LPS bilayer properties. Terminal residues in a LPS bilayer are more flexible and extended along the membrane normal. As the core and O-antigen are added, per-lipid area increases and lipid bilayer order decreases. In addition, results from mixed LPS0/5 and LPS0/10 bilayer simulations show that the LPS O-antigen conformations at a higher concentration of LPS5 and LPS10 are more orthogonal to the membrane and less flexible. The O-antigen concentration of mixed LPS bilayers does not have a significant effect on per-lipid area and hydrophobic thickness. Analysis of ion and water penetration shows that water molecules can penetrate inside the inner core region, and hydration is critical to maintain the integrity of the bilayer structure.

BamA POTRA Domain Interacts with a Native Lipid Membrane Surface

The outer membrane of Gram-negative bacteria is an asymmetric membrane with lipopolysaccharides on the external leaflet and phospholipids on the periplasmic leaflet. This outer membrane contains mainly β-barrel transmembrane proteins and lipidated periplasmic proteins (lipoproteins). The multisubunit protein β-barrel assembly machine (BAM) catalyzes the insertion and folding of the β-barrel proteins into this membrane. In Escherichia coli, the BAM complex consists of five subunits, a core transmembrane β-barrel with a long periplasmic domain (BamA) and four lipoproteins (BamB/C/D/E). The BamA periplasmic domain is composed of five globular subdomains in tandem called POTRA motifs that are key to BAM complex formation and interaction with the substrate β-barrel proteins. The BAM complex is believed to undergo conformational cycling while facilitating insertion of client proteins into the outer membrane. Reports describing variable conformations and dynamics of the periplasmic POTRA domain have been published. Therefore, elucidation of the conformational dynamics of the POTRA domain in full-length BamA is important to understand the function of this molecular complex. Using molecular dynamics simulations, we present evidence that the conformational flexibility of the POTRA domain is modulated by binding to the periplasmic surface of a native lipid membrane. Furthermore, membrane binding of the POTRA domain is compatible with both BamB and BamD binding, suggesting that conformational selection of different POTRA domain conformations may be involved in the mechanism of BAM-facilitated insertion of outer membrane β-barrel proteins.

Dynamics and Interactions of OmpF and LPS: Influence on Pore Accessibility and Ion Permeability

The asymmetric outer membrane of Gram-negative bacteria is formed of the inner leaflet with phospholipids and the outer leaflet with lipopolysaccharides (LPS). Outer membrane protein F (OmpF) is a trimeric porin responsible for the passive transport of small molecules across the outer membrane of Escherichia coli. Here, we report the impact of different levels of heterogeneity in LPS environments on the structure and dynamics of OmpF using all-atom molecular dynamics simulations. The simulations provide insight into the flexibility and dynamics of LPS components that are highly dependent on local environments, with lipid A being the most rigid and O-antigen being the most flexible. Increased flexibility of O-antigen polysaccharides is observed in heterogeneous LPS systems, where the adjacent O-antigen repeating units are weakly interacting and thus more dynamic, compared to homogeneous LPS systems in which LPS interacts strongly with each other with limited overall flexibility due to dense packing. The model systems were validated by comparing molecular-level details of interactions between OmpF surface residues and LPS core sugars with experimental data, establishing the importance of LPS core oligosaccharides in shielding OmpF surface epitopes recognized by monoclonal antibodies. There are LPS environmental influences on the movement of bulk ions (K(+) and Cl(-)), but the ion selectivity of OmpF is mainly affected by bulk ion concentration.

Preferred Orientations of Phosphoinositides in Bilayers and Their Implications in Protein Recognition Mechanisms

Phosphoinositides (PIPs), phosphorylated derivatives of phosphatidylinositol (PI), are essential regulatory lipids involved in various cellular processes, including signal transduction, membrane trafficking, and cytoskeletal remodeling. To gain insight into the protein-PIPs recognition process, it is necessary to study the inositol ring orientation (with respect to the membrane) of PIPs with different phosphorylation states. In this study, 8 PIPs (3 PIP, 2 PIP2, and 3 PIP3) with different phosphorylation and protonation sites have been separately simulated in two mixed bilayers (one with 20% phosphatidylserine (PS) lipids and another with PS lipids switched to phosphatidylcholine (PC) lipids), which roughly correspond to yeast membranes. Uniformity of the bilayer properties including hydrophobic thickness, acyl chain order parameters, and heavy atom density profiles is observed in both PS-contained and PC-enriched membranes due to the same hydrophobic core composition. The relationship between the inositol ring orientation (tilt and rotation angles) and its solvent-accessible surface area indicates that the orientation is mainly determined by its solvation energy. Different PIPs exhibit a clear preference in the inositol ring rotation angle. Surprisingly, a larger proportion of PIPs inositol rings stay closer to the surface of PS-contained membranes compared to PC-enriched ones. Such a difference is rationalized with the formation of more hydrogen bonds between the PS/PI headgroups and the PIPs inositol rings in PS-contained membranes. This hydrogen bond network could be functionally important; thus, the present results can potentially add important and detailed features into the existing protein-PIPs recognition mechanism.

Lipopolysaccharide Membrane Building and Simulation

While membrane simulations are widely employed to study the structure and dynamics of various lipid bilayers and membrane proteins in the bilayers, simulations of lipopolysaccharides (LPS) in membrane environments have been limited due to their structural complexity, difficulties in building LPS-membrane systems, and lack of the appropriate molecular force fields. In this work, as a first step to extend CHARMM-GUI Membrane Builder to incorporate LPS molecules and to explore their structures and dynamics in membrane environments using molecular dynamics simulations, we describe step-by-step procedures to build LPS bilayer systems using CHARMM and the recently developed CHARMM carbohydrate and lipid force fields. Such procedures are illustrated by building various bilayers of Escherichia coli R1.O6 LPS and the presentation of preliminary simulation results in terms of per-LPS area and density distributions of various components along the membrane normal.

Insight into Early-Stage Unfolding of GPI-Anchored Human Prion Protein

Prion diseases are fatal neurodegenerative disorders, which are characterized by the accumulation of misfolded prion protein (PrPSc) converted from a normal host cellular prion protein (PrPC). Experimental studies suggest that PrPC is enriched with α-helical structure, whereas PrPSc contains a high proportion of β-sheet. In this study, we report the impact of N-glycosylation and the membrane on the secondary structure stability utilizing extensive microsecond molecular dynamics simulations. Our results reveal that the HB (residues 173 to 194) C-terminal fragment undergoes conformational changes and helix unfolding in the absence of membrane environments because of the competition between protein backbone intramolecular and protein-water intermolecular hydrogen bonds as well as its intrinsic instability originated from the amino acid sequence. This initiation of the unfolding process of PrPC leads to a subsequent increase in the length of the HB-HC loop (residues 195 to 199) that may trigger larger rigid body motions or further unfolding around this region. Continuous interactions between prion protein and the membrane not only constrain the protein conformation but also decrease the solvent accessibility of the backbone atoms, thereby stabilizing the secondary structure, which is enhanced by N-glycosylation via additional interactions between the N-glycans and the membrane surface.

ST-analyzer: A web-based user interface for simulation trajectory analysis

Molecular dynamics (MD) simulation has become one of the key tools to obtain deeper insights into biological systems using various levels of descriptions such as all‐atom, united‐atom, and coarse‐grained models. Recent advances in computing resources and MD programs have significantly accelerated the simulation time and thus increased the amount of trajectory data. Although many laboratories routinely perform MD simulations, analyzing MD trajectories is still time consuming and often a difficult task. ST‐analyzer, http://im.bioinformatics.ku.edu/st‐analyzer, is a standalone graphical user interface (GUI) toolset to perform various trajectory analyses. ST‐analyzer has several outstanding features compared to other existing analysis tools: (i) handling various formats of trajectory files from MD programs, such as CHARMM, NAMD, GROMACS, and Amber, (ii) intuitive web‐based GUI environment—minimizing administrative load and reducing burdens on the user from adapting new software environments, (iii) platform independent design—working with any existing operating system, (iv) easy integration into job queuing systems—providing options of batch processing either on the cluster or in an interactive mode, and (v) providing independence between foreground GUI and background modules—making it easier to add personal modules or to recycle/integrate pre‐existing scripts utilizing other analysis tools. The current ST‐analyzer contains nine main analysis modules that together contain 18 options, including density profile, lipid deuterium order parameters, surface area per lipid, and membrane hydrophobic thickness. This article introduces ST‐analyzer with its design, implementation, and features, and also illustrates practical analysis of lipid bilayer simulations.