Insertion of X-ray structures of proteins in membranes

UNILIPID, a Methodology for Energetically Accurate Prediction of Protein Insertion into Implicit Membranes of Arbitrary Shape

The insertion of proteins into membranes is crucial for understanding their function in many biological processes. In this work, we present UNILIPID, a universal implicit lipid-protein description as a methodology for dealing with implicit membranes. UNILIPID is independent of the scale of representation and can be applied at the level of all atoms, coarse-grained particles down to the level of a single bead per amino acid. We provide example implementations for these scales and demonstrate the versatility of our approach by accurately reflecting the free energy of transfer for each amino acid. In addition to single membranes, we describe the analytical implementation of double membranes and show that UNILIPID is well suited for modeling at multiple scales. We generalize to membranes of arbitrary shape. With UNILIPID, we provide a methodological framework for a simple and general parameterization tuned to reproduce a selected reference hydrophobicity scale. The software we provide along with the methodological description is optimized for specific user features such as real-time response, live visual analysis, and virtual reality experiences.

Optimized Data Set and Feature Construction for Substrate Prediction of Membrane Transporters

α-Helical transmembrane proteins termed membrane transporters mediate the passage of small hydrophilic substrate molecules across biological lipid bilayer membranes. Annotating the specific substrates of the dozens to hundreds of individual transporters of an organism is an important task. In the past, machine learning classifiers have been successfully trained on pan-organism data sets to predict putative substrates of transporters. Here, we critically examine the selection of an optimal data set of protein sequence features for the classification task. We focus on membrane transporters of the three model organisms Escherichia coli, Arabidopsis thaliana, and Saccharomyces cerevisiae, as well as human. We show that organism-specific classifiers can be robustly trained if at least 20 samples are available for each substrate class. If information from position-specific scoring matrices is included, such classifiers have F1 scores between 0.85 and 1.00. For the largest data set (A. thaliana), a 4-class classifier yielded an F-score of 0.97. On a pan-organism data set composed of transporters of all four organisms, amino acid and sugar transporters were predicted with an F1 score of 0.91.

Determination of Hydrophobic Lengths of Membrane Proteins with the HDGB Implicit Membrane Model

A protocol for predicting the hydrophobic length of membrane proteins using the heterogeneous dielectric generalized Born (HDGB) implicit membrane model is presented. The method involves optimal positioning in the membrane and identification of lipid-facing and inward-facing residues, followed by energy optimization of the implicit membrane model to obtain the hydrophobic length from the optimal membrane width. The latest HDGB version 3 (HDGBv3) and HDGB van der Waals (HDGBvdW) models were applied to a test set containing 15 proteins (seven β-barrel and eight α-helical proteins), for which matching membrane widths are available from experiment, and an additional set contains ten α-helical and ten β-barrel proteins without any experimental data. The results with the HDGB model compare favorably with predictions from methods used in the Orientations of Proteins in Membranes (OPM) and Protein Data Bank of Transmembrane Proteins (PDB-TM) databases.

Molecular Modelling, Dynamics, and Docking of Membrane Proteins

Computational tools and techniques are now most popular and promising to progress the research at rapid rate. Molecular modelling studies contribute their maximum role in wide variety of disciplines especially in proteomics and drug discovery strategies. Molecular dynamics and molecular docking algorithms are now became an essential part in daily research activities of every laboratory throughout the world. These strategies are now well established and standardised to study any specific protein of interest and drug molecule. But still there exist considerable drawbacks in a special concern with membrane proteins as the presently available tools and methods cannot be applied directly to them. Modelling, dynamics and docking studies of membrane proteins need a special care and attention as several challenges are to be crossed with an intensive care to produce a reliable result. This chapter is aimed to discuss such challenges and solutions to handle membrane proteins.

Membrane-bound ARF1 peptide: interpretation of neutron diffraction data by molecular dynamics simulation methods

Adenosine diphosphate ribosylation factor-1 (ARF1) is activated by cell membrane binding of a self-folding N-terminal domain. We have previously presented four possible conformations of the membrane bound, human ARF1 N-terminal peptide in planar lipid bilayers of DOPC and DOPG (7:3 molar ratio), determined from lamellar neutron diffraction and circular dichroism data. In this paper we analyse the four possible conformations by molecular dynamics simulations. The aim of these simulations was to use MD to distinguish which of the four possible membrane bound structures was the most likely. The most likely conformation was determined according to the following criteria: (a) location of label positions on the peptide in relation to the bilayer, (b) lowest mean square displacement from the initial structure, (c) lowest system energy, (d) most peptide-lipid headgroup hydrogen bonding, (e) analysis of phi/psi angles of the peptide. These findings demonstrate the application of molecular dynamics simulations to explore neutron diffraction data.

Coarse-grained MD simulations of membrane protein-bilayer self-assembly

Complete determination of a membrane protein structure requires knowledge of the protein position within the lipid bilayer. As the number of determined structures of membrane proteins increases so does the need for computational methods which predict their position in the lipid bilayer. Here we present a coarse-grained molecular dynamics approach to lipid bilayer self-assembly around membrane proteins. We demonstrate that this method can be used to predict accurately the protein position in the bilayer for membrane proteins with a range of different sizes and architectures.

Method To Assess Packing Quality of Transmembrane α-Helices in Proteins. 1. Parametrization Using Structural Data

Integral membrane proteins (MPs) are pharmaceutical targets of exceptional importance. Modern methods of three-dimensional protein structure determination often fail to supply the fast growing field of structure-based drug design with the requested MPs' structures. That is why computational modeling techniques gain a special importance for these objects. Among the principal difficulties limiting application of these methods is the low quality of the MPs' models built in silico. In this series of two papers we present a computational approach to the assessment of the packing "quality" of transmembrane (TM) alpha-helical domains in proteins. The method is based on the concept of protein environment classes, whereby each amino acid residue is described in terms of its environment polarity and accessibility to the membrane. In the first paper we analyze a nonredundant set of 26 TM alpha-helical domains and compute the residues' propensities to five predefined classes of membrane-protein environments. Here we evaluate the proposed approach only by various test sets, cross-validation protocols and ability of the method to delimit the crystal structure of visual rhodopsin, and a number of its erroneous theoretical models. More advanced validation of the method is given in the second article of this series. We assume that the developed "membrane score" method will be helpful in optimizing computer models of TM domains of MPs, especially G-protein coupled receptors.

-Barrel transmembrane proteins: Geometric modelling, detection of transmembrane region, and structural properties

The location of the membrane lipid bilayer relative to a transmembrane protein structure is important in protein engineering. Since it is not present on the determined structures, it is essential to automatically define the membrane embedded protein region in order to test mutation effects or to design potential drugs. beta-Barrel transmembrane proteins, present in nature as outer membrane proteins (OMPs), comprise one of the two transmembrane protein fold classes. Lately, the number of their determined structures has increased and this enables the implementation and evaluation of structure-based annotation methods and their more comprehensive study. In this paper, we propose two new algorithms for (i) the geometric modelling of beta-barrels and (ii) the detection of the transmembrane region of a beta-barrel transmembrane protein. The geometric modelling algorithm combines a non-linear least square minimization method and a genetic algorithm in order to find the characteristics (axis, radius) of a shape with axial symmetry which best models a beta-barrel. The transmembrane region is detected by profiling the external residues of the beta-barrel along its axis in terms of hydrophobicity and existence of aromatic and charged residues. TbB-Tool implements these algorithms and is available in . A non-redundant set of 22 OMPs is used in order to evaluate the algorithms implemented and the results are very satisfying. In addition, we quantify the abundance of all amino acids and the average hydrophobicity for external and internal beta-stranded residues along the axis of beta-barrel, thus confirming and extending other researchers' results.

Positioning of proteins in membranes: a computational approach

A new computational approach has been developed to determine the spatial arrangement of proteins in membranes by minimizing their transfer energies from water to the lipid bilayer. The membrane hydrocarbon core was approximated as a planar slab of adjustable thickness with decadiene-like interior and interfacial polarity profiles derived from published EPR studies. Applicability and accuracy of the method was verified for a set of 24 transmembrane proteins whose orientations in membranes have been studied by spin-labeling, chemical modification, fluorescence, ATR FTIR, NMR, cryo-microscopy, and neutron diffraction. Subsequently, the optimal rotational and translational positions were calculated for 109 transmembrane, five integral monotopic and 27 peripheral protein complexes with known 3D structures. This method can reliably distinguish transmembrane and integral monotopic proteins from water-soluble proteins based on their transfer energies and membrane penetration depths. The accuracies of calculated hydrophobic thicknesses and tilt angles were approximately 1 A and 2 degrees, respectively, judging from their deviations in different crystal forms of the same proteins. The hydrophobic thicknesses of transmembrane proteins ranged from 21.1 to 43.8 A depending on the type of biological membrane, while their tilt angles with respect to the bilayer normal varied from zero in symmetric complexes to 26 degrees in asymmetric structures. Calculated hydrophobic boundaries of proteins are located approximately 5 A lower than lipid phosphates and correspond to the zero membrane depth parameter of spin-labeled residues. Coordinates of all studied proteins with their membrane boundaries can be found in the Orientations of Proteins in Membranes (OPM) database:http://opm.phar.umich.edu/.

The N-terminal 12 Residue Long Peptide of HIV gp41 is the Minimal Peptide Sufficient to Induce Significant T-cell-like Membrane Destabilization in Vitro

Here, we predicted the minimal N-terminal fragment of gp41 required to induce significant membrane destabilization using IMPALA. This algorithm is dedicated to predict peptide interaction with a membrane. We based our prediction of the minimal fusion peptide on the tilted peptide theory. This theory proposes that some protein fragments having a peculiar distribution of hydrophobicity adopt a tilted orientation at a hydrophobic/hydrophilic interface. As a result of this orientation, tilted peptides should disrupt the interface. We analysed in silico the membrane-interacting properties of gp41 N-terminal peptides of different length derived from the isolate BRU and from an alignment of 710 HIV strains available on the Los Alamos National Laboratory. Molecular modelling results indicated that the 12 residue long peptide should be the minimal fusion peptide. We then assayed lipid-mixing and leakage of T-cell-like liposomes with N-terminal peptides of different length as first challenge of our predictions. Experimental results confirmed that the 12 residue long peptide is necessary and sufficient to induce membrane destabilization to the same extent as the 23 residue long fusion peptide. In silico analysis of some fusion-incompetent mutants presented in the literature further revealed that they cannot insert into a modelled membrane correctly tilted. According to this work, the tilted peptide model appears to explain at least partly the membrane destabilization properties of HIV fusion peptide.

OPM: Orientations of Proteins in Membranes database

SUMMARY

The Orientations of Proteins in Membranes (OPM) database provides a collection of transmembrane, monotopic and peripheral proteins from the Protein Data Bank whose spatial arrangements in the lipid bilayer have been calculated theoretically and compared with experimental data. The database allows analysis, sorting and searching of membrane proteins based on their structural classification, species, destination membrane, numbers of transmembrane segments and subunits, numbers of secondary structures and the calculated hydrophobic thickness or tilt angle with respect to the bilayer normal. All coordinate files with the calculated membrane boundaries are available for downloading.

AVAILABILITY

http://opm.phar.umich.edu.

Evaluating tilt angles of membrane-associated helices: comparison of computational and NMR techniques

A computational method to calculate the orientation of membrane-associated alpha-helices with respect to a lipid bilayer has been developed. It is based on a previously derived implicit membrane representation, which was parameterized using the structures of 46 alpha-helical membrane proteins. The method is validated by comparison with an independent data set of six transmembrane and nine antimicrobial peptides of known structure and orientation. The minimum energy orientations of the transmembrane helices were found to be in good agreement with tilt and rotation angles known from solid-state NMR experiments. Analysis of the free-energy landscape found two types of minima for transmembrane peptides: i), Surface-bound configurations with the helix long axis parallel to the membrane, and ii), inserted configurations with the helix spanning the membrane in a perpendicular orientation. In all cases the inserted configuration also contained the global energy minimum. Repeating the calculations with a set of solution NMR structures showed that the membrane model correctly distinguishes native transmembrane from nonnative conformers. All antimicrobial peptides investigated were found to orient parallel and bind to the membrane surface, in agreement with experimental data. In all cases insertion into the membrane entailed a significant free-energy penalty. An analysis of the contributions of the individual residue types confirmed that hydrophobic residues are the main driving force behind membrane protein insertion, whereas polar, charged, and aromatic residues were found to be important for the correct orientation of the helix inside the membrane.

Role of the Lid Hydrophobicity Pattern in Pancreatic Lipase Activity

Pancreatic lipase is a soluble globular protein that must undergo structural modifications before it can hydrolyze oil droplets coated with bile salts. The binding of colipase and movement of the lipase lid open access to the active site. Mechanisms triggering lid mobility are unclear. The *KNILSQIVDIDGI* fragment of the lid of the human pancreatic lipase is predicted by molecular modeling to be a tilted peptide. Tilted peptides are hydrophobicity motifs involved in membrane fusion and more globally in perturbations of hydrophobic/hydrophilic interfaces. Analysis of this lid fragment predicts no clear consensus of secondary structure that suggests that its structure is not strongly sequence determined and could vary with environment. Point mutations were designed to modify the hydrophobicity profile of the [240-252] fragment and their consequences on the lipase-mediated catalysis were tested. Two mutants, in which the tilted peptide motif was lost, also have poor activity on bile salt-coated oil droplets and cannot be reactivated by colipase. Conversely, one mutant in which a different tilted peptide is created retains colipase dependence. These results suggest that the tilted hydrophobicity pattern of the [240-252] fragment is neither important for colipase binding to lipase, nor for interfacial binding but is important to trigger the maximal catalytic efficiency of lipase in the presence of bile salt.

Rational design of complementary peptides to the betaAmyloid 29-42 fusion peptide: an application of PepDesign

Peptides in solution currently exist under several conformations; an equilibrium which varies with solvent polarity. Despite or because of this structure versatility, peptides can be selective biological tools: they can adapt to a target, vary conformation with solvents and so on. These capacities are crucial for cargo carriers. One promising way of using peptides in biotechnologies is to decipher their medium-sequence-structure-function relationships and one approach is molecular modelling. Only few "in silico" methods of peptide design are described in the literature. Most are used in support of experimental screening of peptide libraries. However, the way they are made does not teach us much for future researches. In this paper, we describe an "in silico" method (PepDesign) which starts by analysing the native interaction of a peptide with a target molecule in order to define which points are important. From there, a modelling protocol for the design of 'better' peptides is set. The PepDesign procedure calculates new peptides fulfilling the hypothesis, tests the conformational space of these peptides in interaction with the target by angular dynamics and goes up to the selection of the best peptide based on the analysis of complex structure properties. Experimental biological assays are finally used to test the selected peptides, hence to validate the approach. Applications of PepDesign are wide because the procedure will remain similar irrespective of the target which can be a protein, a drug or a nucleic acid. In this paper, we describe the design of peptides which binds to the fusogenic helical form of the C-terminal domain of the Abeta peptide (Abeta29-42).

Positioning Membrane Proteins by Novel Protein Engineering and Biophysical Approaches

Membrane proteins are unique, in that they can function properly only when they are bound to cellular membranes in a distinct manner. Therefore, positioning of membrane proteins with respect to the membrane is required in addition to the three-dimensional structures in order to understand their detailed molecular mechanisms. Atomic-resolution structures of membrane proteins that have been determined to date provide the atom coordinates in arbitrary coordinate systems with no relation to the membrane and therefore provide little or no information on how the protein would interact with the membrane. This is especially true for peripheral membrane proteins, because they, unlike integral proteins, are devoid of well-defined hydrophobic transmembrane domains. Here, we present a novel technique for determination of the configuration of a protein-membrane complex that involves protein ligation, segmental isotope labeling, polarized infrared spectroscopy, membrane depth-dependent fluorescence quenching, and analytical geometry algorithms. We have applied this approach to determine the structure of a membrane-bound phospholipase A2. Our results provide an unprecedented structure of a membrane-bound protein in which the z-coordinate of each atom is the distance from the membrane center and therefore allows precise location of each amino acid relative to the membrane. Given the functional significance of the orientation and location of membrane-bound proteins with respect to the membrane, we propose to specify this structural feature as the "quinary" structure of membrane proteins.