Toward high-resolution prediction and design of transmembrane helical protein structures

Structural basis for gating charge movement in the voltage sensor of a sodium channel

Voltage-dependent gating of ion channels is essential for electrical signaling in excitable cells, but the structural basis for voltage sensor function is unknown. We constructed high-resolution structural models of resting, intermediate, and activated states of the voltage-sensing domain of the bacterial sodium channel NaChBac using the Rosetta modeling method, crystal structures of related channels, and experimental data showing state-dependent interactions between the gating charge-carrying arginines in the S4 segment and negatively charged residues in neighboring transmembrane segments. The resulting structural models illustrate a network of ionic and hydrogen-bonding interactions that are made sequentially by the gating charges as they move out under the influence of the electric field. The S4 segment slides 6-8 Å outward through a narrow groove formed by the S1, S2, and S3 segments, rotates ∼30°, and tilts sideways at a pivot point formed by a highly conserved hydrophobic region near the middle of the voltage sensor. The S4 segment has a 3(10)-helical conformation in the narrow inner gating pore, which allows linear movement of the gating charges across the inner one-half of the membrane. Conformational changes of the intracellular one-half of S4 during activation are rigidly coupled to lateral movement of the S4-S5 linker, which could induce movement of the S5 and S6 segments and open the intracellular gate of the pore. We confirmed the validity of these structural models by comparing with a high-resolution structure of a NaChBac homolog and showing predicted molecular interactions of hydrophobic residues in the S4 segment in disulfide-locking studies.

Structure determination of membrane proteins in five easy pieces

Rotational Alignment (RA) solid-state NMR provides the basis for a general method for determining the structures of membrane proteins in phospholipid bilayers under physiological conditions. Membrane proteins are high priority targets for structure determination, and are challenging for existing experimental methods. Because membrane proteins reside in liquid crystalline phospholipid bilayer membranes it is important to study them in this type of environment. The RA solid-state NMR approach we have developed can be summarized in five steps, and incorporates methods of molecular biology, biochemistry, sample preparation, the implementation of NMR experiments, and structure calculations. It relies on solid-state NMR spectroscopy to obtain high-resolution spectra and residue-specific structural restraints for membrane proteins that undergo rotational diffusion around the membrane normal, but whose mobility is otherwise restricted by interactions with the membrane phospholipids. High resolution spectra of membrane proteins alone and in complex with other proteins and ligands set the stage for structure determination and functional studies of these proteins in their native, functional environment.

Gating charge interactions with the S1 segment during activation of a Na+ channel voltage sensor

Voltage-gated Na(+) channels initiate action potentials during electrical signaling in excitable cells. Opening and closing of the pore of voltage-gated ion channels are mechanically linked to voltage-driven outward movement of the positively charged S4 transmembrane segment in their voltage sensors. Disulfide locking of cysteine residues substituted for the outermost T0 and R1 gating-charge positions and a conserved negative charge (E43) at the extracellular end of the S1 segment of the bacterial Na(+) channel NaChBac detects molecular interactions that stabilize the resting state of the voltage sensor and define its conformation. Upon depolarization, the more inward gating charges R2 and R3 engage in these molecular interactions as the S4 segment moves outward to its intermediate and activated states. The R4 gating charge does not disulfide-lock with E43, suggesting an outer limit to its transmembrane movement. These molecular interactions reveal how the S4 gating charges are stabilized in the resting state and how their outward movement is catalyzed by interaction with negatively charged residues to effect pore opening and initiate electrical signaling.

Computational studies of membrane proteins: models and predictions for biological understanding

We discuss recent progresses in computational studies of membrane proteins based on physical models with parameters derived from bioinformatics analysis. We describe computational identification of membrane proteins and prediction of their topology from sequence, discovery of sequence and spatial motifs, and implications of these discoveries. The detection of evolutionary signal for understanding the substitution pattern of residues in the TM segments and for sequence alignment is also discussed. We further discuss empirical potential functions for energetics of inserting residues in the TM domain, for interactions between TM helices or strands, and their applications in predicting lipid-facing surfaces of the TM domain. Recent progresses in structure predictions of membrane proteins are also reviewed, with further discussions on calculation of ensemble properties such as melting temperature based on simplified state space model. Additional topics include prediction of oligomerization state of membrane proteins, identification of the interfaces for protein-protein interactions, and design of membrane proteins. This article is part of a Special Issue entitled: Protein Folding in Membranes.

Computational design of membrane proteins

This article reviews the recent successes of computational protein design techniques applied to integral membrane proteins. This emerging area is still handicapped by significant difficulties in the experimental characterization of the stability and structure of the designed proteins. Nevertheless, by focusing on oligomeric complexes of single-span transmembrane (TM) peptides with detectable activity, the computational design of membrane proteins has already produced very exciting results. The 'take-home message' is that optimization of van der Waals packing and hydrogen bonding (both 'canonical' and weak Cα-H⋯O bonds) can produce functional structures of remarkable stability and specificity in the membrane.

Optimal mutation sites for PRE data collection and membrane protein structure prediction

Nuclear magnetic resonance paramagnetic relaxation enhancement (PRE) measures long-range distances to isotopically labeled residues, providing useful constraints for protein structure prediction. The method usually requires labor-intensive conjugation of nitroxide labels to multiple locations on the protein, one at a time. Here a computational procedure, based on protein sequence and simple secondary structure models, is presented to facilitate optimal placement of a minimum number of labels needed to determine the correct topology of a helical transmembrane protein. Tests on DsbB (four helices) using just one label lead to correct topology predictions in four of five cases, with the predicted structures <6 Å to the native structure. Benchmark results using simulated PRE data show that we can generally predict the correct topology for five and six to seven helices using two and three labels, respectively, with an average success rate of 76% and structures of similar precision. The results show promise in facilitating experimentally constrained structure prediction of membrane proteins.

RosettaEPR: an integrated tool for protein structure determination from sparse EPR data

Site-directed spin labeling electron paramagnetic resonance (SDSL-EPR) is often used for the structural characterization of proteins that elude other techniques, such as X-ray crystallography and nuclear magnetic resonance (NMR). However, high-resolution structures are difficult to obtain due to uncertainty in the spin label location and sparseness of experimental data. Here, we introduce RosettaEPR, which has been designed to improve de novo high-resolution protein structure prediction using sparse SDSL-EPR distance data. The "motion-on-a-cone" spin label model is converted into a knowledge-based potential, which was implemented as a scoring term in Rosetta. RosettaEPR increased the fractions of correctly folded models ( [Formula: see text] <7.5Å) and models accurate at medium resolution ( [Formula: see text] <3.5Å) by 25%. The correlation of score and model quality increased from 0.42 when using no restraints to 0.51 when using bounded restraints and again to 0.62 when using RosettaEPR. This allowed for the selection of accurate models by score. After full-atom refinement, RosettaEPR yielded a 1.7Å model of T4-lysozyme, thus indicating that atomic detail models can be achieved by combining sparse EPR data with Rosetta. While these results indicate RosettaEPR's potential utility in high-resolution protein structure prediction, they are based on a single example. In order to affirm the method's general performance, it must be tested on a larger and more versatile dataset of proteins.

Structural origins of nitroxide side chain dynamics on membrane protein α-helical sites

Understanding the structure and dynamics of membrane proteins in their native, hydrophobic environment is important to understanding how these proteins function. EPR spectroscopy in combination with site-directed spin labeling (SDSL) can measure dynamics and structure of membrane proteins in their native lipid environment; however, until now the dynamics measured have been qualitative due to limited knowledge of the nitroxide spin label's intramolecular motion in the hydrophobic environment. Although several studies have elucidated the structural origins of EPR line shapes of water-soluble proteins, EPR spectra of nitroxide spin-labeled proteins in detergents or lipids have characteristic differences from their water-soluble counterparts, suggesting significant differences in the underlying molecular motion of the spin label between the two environments. To elucidate these differences, membrane-exposed α-helical sites of the leucine transporter, LeuT, from Aquifex aeolicus, were investigated using X-ray crystallography, mutational analysis, nitroxide side chain derivatives, and spectral simulations in order to obtain a motional model of the nitroxide. For each crystal structure, the nitroxide ring of a disulfide-linked spin label side chain (R1) is resolved and makes contacts with hydrophobic residues on the protein surface. The spin label at site I204 on LeuT makes a nontraditional hydrogen bond with the ortho-hydrogen on its nearest neighbor F208, whereas the spin label at site F177 makes multiple van der Waals contacts with a hydrophobic pocket formed with an adjacent helix. These results coupled with the spectral effect of mutating the i ± 3, 4 residues suggest that the spin label has a greater affinity for its local protein environment in the low dielectric than on a water-soluble protein surface. The simulations of the EPR spectra presented here suggest the spin label oscillates about the terminal bond nearest the ring while maintaining weak contact with the protein surface. Combined, the results provide a starting point for determining a motional model for R1 on membrane proteins, allowing quantification of nitroxide dynamics in the aliphatic environment of detergent and lipids. In addition, initial contributions to a rotamer library of R1 on membrane proteins are provided, which will assist in reliably modeling the R1 conformational space for pulsed dipolar EPR and NMR paramagnetic relaxation enhancement distance determination.

Structural evidence for loose linkage between ligand binding and kinase activation in the epidermal growth factor receptor

The mechanisms by which signals are transmitted across the plasma membrane to regulate signaling are largely unknown for receptors with single-pass transmembrane domains such as the epidermal growth factor receptor (EGFR). A crystal structure of the extracellular domain of EGFR dimerized by epidermal growth factor (EGF) reveals the extended, rod-like domain IV and a small, hydrophobic domain IV interface compatible with flexibility. The crystal structure and disulfide cross-linking suggest that the 7-residue linker between the extracellular and transmembrane domains is flexible. Disulfide cross-linking of the transmembrane domain shows that EGF stimulates only moderate association in the first two α-helical turns, in contrast to association throughout the membrane over five α-helical turns in glycophorin A and integrin. Furthermore, systematic mutagenesis to leucine and phenylalanine suggests that no specific transmembrane interfaces are required for EGFR kinase activation. These results suggest that linkage between ligand-induced dimerization and tyrosine kinase activation is much looser than was previously envisioned.

Development of a rotamer library for use in beta-peptide foldamer computational design

Foldamers present a particularly difficult challenge for accurate computational design compared to the case for conventional peptide and protein design due to the lack of a large body of structural data to allow parametrization of rotamer libraries and energies. We therefore explored the use of molecular mechanics for constructing rotamer libraries for non-natural foldamer backbones. We first evaluated the accuracy of molecular mechanics (MM) for the prediction of rotamer probability distributions in the crystal structures of proteins is explored. The van der Waals radius, dielectric constant and effective Boltzmann temperature were systematically varied to maximize agreement with experimental data. Boltzmann-weighted probabilities from these molecular mechanics energies compare well with database-derived probabilities for both an idealized alpha-helix (R = 0.95) as well as beta-strand conformations (R = 0.92). Based on these parameters, de novo rotamer probabilities for secondary structures of peptides built from beta-amino acids were determined. To limit computational complexity, it is useful to establish a residue-specific criterion for excluding rare, high-energy rotamers from the library. This is accomplished by including only those rotamers with probability greater than a given threshold (e.g., 10%) of the random value, defined as 1/n where n is the number of potential rotamers for each residue type.

Practically useful: what the Rosetta protein modeling suite can do for you

The objective of this review is to enable researchers to use the software package Rosetta for biochemical and biomedicinal studies. We provide a brief review of the six most frequent research problems tackled with Rosetta. For each of these six tasks, we provide a tutorial that illustrates a basic Rosetta protocol. The Rosetta method was originally developed for de novo protein structure prediction and is regularly one of the best performers in the community-wide biennial Critical Assessment of Structure Prediction. Predictions for protein domains with fewer than 125 amino acids regularly have a backbone root-mean-square deviation of better than 5.0 Å. More impressively, there are several cases in which Rosetta has been used to predict structures with atomic level accuracy better than 2.5 Å. In addition to de novo structure prediction, Rosetta also has methods for molecular docking, homology modeling, determining protein structures from sparse experimental NMR or EPR data, and protein design. Rosetta has been used to accurately design a novel protein structure, predict the structure of protein−protein complexes, design altered specificity protein−protein and protein−DNA interactions, and stabilize proteins and protein complexes. Most recently, Rosetta has been used to solve the X-ray crystallographic phase problem.

Predicting transmembrane helix packing arrangements using residue contacts and a force-directed algorithm

Alpha-helical transmembrane proteins constitute roughly 30% of a typical genome and are involved in a wide variety of important biological processes including cell signalling, transport of membrane-impermeable molecules and cell recognition. Despite significant efforts to predict transmembrane protein topology, comparatively little attention has been directed toward developing a method to pack the helices together. Here, we present a novel approach to predict lipid exposure, residue contacts, helix-helix interactions and finally the optimal helical packing arrangement of transmembrane proteins. Using molecular dynamics data, we have trained and cross-validated a support vector machine (SVM) classifier to predict per residue lipid exposure with 69% accuracy. This information is combined with additional features to train a second SVM to predict residue contacts which are then used to determine helix-helix interaction with up to 65% accuracy under stringent cross-validation on a non-redundant test set. Our method is also able to discriminate native from decoy helical packing arrangements with up to 70% accuracy. Finally, we employ a force-directed algorithm to construct the optimal helical packing arrangement which demonstrates success for proteins containing up to 13 transmembrane helices. This software is freely available as source code from http://bioinf.cs.ucl.ac.uk/memsat/mempack/.

A unified hydrophobicity scale for multispan membrane proteins

The concept of hydrophobicity is critical to our understanding of the principles of membrane protein (MP) folding, structure, and function. In the last decades, several groups have derived hydrophobicity scales using both experimental and statistical methods that are optimized to mimic certain natural phenomena as closely as possible. The present work adds to this toolset the first knowledge-based scale that unifies the characteristics of both alpha-helical and beta-barrel multispan MPs. This unified hydrophobicity scale (UHS) distinguishes between amino acid preference for solution, transition, and trans-membrane states. The scale represents average hydrophobicity values of amino acids in folded proteins, irrespective of their secondary structure type. We furthermore present the first knowledge-based hydrophobicity scale for mammalian alpha-helical MPs (mammalian hydrophobicity scale--MHS). Both scales are particularly useful for computational protein structure elucidation, for example as input for machine learning techniques, such as secondary structure or trans-membrane span prediction, or as reference energies for protein structure prediction or protein design. The knowledge-based UHS shows a striking similarity to a recent experimental hydrophobicity scale introduced by Hessa and coworkers (Hessa T et al., Nature 2007;450:U1026-U1032). Convergence of two very different approaches onto similar hydrophobicity values consolidates the major differences between experimental and knowledge-based scales observed in earlier studies. Moreover, the UHS scale represents an accurate absolute free energy measure for folded, multispan MPs--a feature that is absent from many existing scales. The utility of the UHS was demonstrated by analyzing a series of diverse MPs. It is further shown that the UHS outperforms nine established hydrophobicity scales in predicting trans-membrane spans along the protein sequence. The accuracy of the present hydrophobicity scale profits from the doubling of the number of integral MPs in the PDB over the past four years. The UHS paves the way for an increased accuracy in the prediction of trans-membrane spans.

Community-wide assessment of GPCR structure modelling and ligand docking: GPCR Dock 2008

Recent breakthroughs in the determination of the crystal structures of G protein-coupled receptors (GPCRs) have provided new opportunities for structure-based drug design strategies targeting this protein family. With the aim of evaluating the current status of GPCR structure prediction and ligand docking, a community-wide, blind prediction assessment - GPCR Dock 2008 - was conducted in coordination with the publication of the crystal structure of the human adenosine A(2A) receptor bound to the ligand ZM241385. Twenty-nine groups submitted 206 structural models before the release of the experimental structure, which were evaluated for the accuracy of the ligand binding mode and the overall receptor model compared with the crystal structure. This analysis highlights important aspects for success and future development, such as accurate modelling of structurally divergent regions and use of additional biochemical insight such as disulphide bridges in the extracellular loops.

RHYTHM--a server to predict the orientation of transmembrane helices in channels and membrane-coils

RHYTHM is a web server that predicts buried versus exposed residues of helical membrane proteins. Starting from a given protein sequence, secondary and tertiary structure information is calculated by RHYTHM within only a few seconds. The prediction applies structural information from a growing data base of precalculated packing files and evolutionary information from sequence patterns conserved in a representative dataset of membrane proteins ('Pfam-domains'). The program uses two types of position specific matrices to account for the different geometries of packing in channels and transporters ('channels') or other membrane proteins ('membrane-coils'). The output provides information on the secondary structure and topology of the protein and specifically on the contact type of each residue and its conservation. This information can be downloaded as a graphical file for illustration, a text file for analysis and statistics and a PyMOL file for modeling purposes. The server can be freely accessed at: URL: http://proteinformatics.de/rhythm.

SuperLooper--a prediction server for the modeling of loops in globular and membrane proteins

SuperLooper provides the first online interface for the automatic, quick and interactive search and placement of loops in proteins (LIP). A database containing half a billion segments of water-soluble proteins with lengths up to 35 residues can be screened for candidate loops. A specified database containing 180 000 membrane loops in proteins (LIMP) can be searched, alternatively. Loop candidates are scored based on sequence criteria and the root mean square deviation (RMSD) of the stem atoms. Searching LIP, the average global RMSD of the respective top-ranked loops to the original loops is benchmarked to be <2 Å, for loops up to six residues or <3 Å for loops shorter than 10 residues. Other suitable conformations may be selected and directly visualized on the web server from a top-50 list. For user guidance, the sequence homology between the template and the original sequence, proline or glycine exchanges or close contacts between a loop candidate and the remainder of the protein are denoted. For membrane proteins, the expansions of the lipid bilayer are automatically modeled using the TMDET algorithm. This allows the user to select the optimal membrane protein loop concerning its relative orientation to the lipid bilayer. The server is online since October 2007 and can be freely accessed at URL: http://bioinformatics.charite.de/superlooper/

The structure of a receptor with two associating transmembrane domains on the cell surface: integrin alphaIIbbeta3

Structures of intact receptors with single-pass transmembrane domains are essential to understand how extracellular and cytoplasmic domains regulate association and signaling through transmembrane domains. A chemical and computational method to determine structures of the membrane regions of such receptors on the cell surface is developed here and validated with glycophorin A. An integrin heterodimer structure reveals association over most of the lengths of the alpha and beta transmembrane domains and shows that the principles governing association of hetero and homo transmembrane dimers differ. A turn at the Gly of the juxtamembrane GFFKR motif caps the alpha TM helix and brings the two Phe of GFFKR into the alpha/beta interface. A juxtamembrane Lys residue in beta also has an important role in the interface. The structure shows how transmembrane association/dissociation regulates integrin signaling. A joint ectodomain and membrane structure shows that substantial flexibility between the extracellular and TM domains is compatible with TM signaling.

Insight into factors directing high production of eukaryotic membrane proteins; production of 13 human AQPs in Pichia pastoris

Membrane proteins are key players in all living cells. To achieve a better understanding of membrane protein function, significant amounts of purified protein are required for functional and structural analyses. Overproduction of eukaryotic membrane proteins, in particular, is thus an essential yet non-trivial task. Hence, improved understanding of factors which direct a high production of eukaryotic membrane proteins is desirable. In this study we have compared the overproduction of all human aquaporins in the eukaryotic host Pichia pastoris. We report quantitated production levels of each homologue and the extent of their membrane localization. Our results show that the protein production levels vary substantially, even between highly homologous aquaporins. A correlation between the extents of membrane insertion with protein function also emerged, with a higher extent of membrane insertion for pure water transporters compared to aquaporin family members with other substrate specificity. Nevertheless, the nucleic acid sequence of the second codon appears to play an important role in overproduction. Constructs containing guanine at the first position of this codon (being part of the mammalian Kozak sequence) are generally produced at a higher level, which is confirmed for hAQP8. In addition, mimicking the yeast consensus sequence (ATGTCT) apparently has a negative influence on the production level, as shown for hAQP1. Moreover, by mutational analysis we show that the yield of hAQP4 can be heavily improved by directing the protein folding pathway as well as stabilizing the aquaporin tetramer.

Prediction of membrane protein structures with complex topologies using limited constraints

Reliable structure-prediction methods for membrane proteins are important because the experimental determination of high-resolution membrane protein structures remains very difficult, especially for eukaryotic proteins. However, membrane proteins are typically longer than 200 aa and represent a formidable challenge for structure prediction. We have developed a method for predicting the structures of large membrane proteins by constraining helix-helix packing arrangements at particular positions predicted from sequence or identified by experiments. We tested the method on 12 membrane proteins of diverse topologies and functions with lengths ranging between 190 and 300 residues. Enforcing a single constraint during the folding simulations enriched the population of near-native models for 9 proteins. In 4 of the cases in which the constraint was predicted from the sequence, 1 of the 5 lowest energy models was superimposable within 4 A on the native structure. Near-native structures could also be selected for heme-binding and pore-forming domains from simulations in which pairs of conserved histidine-chelating hemes and one experimentally determined salt bridge were constrained, respectively. These results suggest that models within 4 A of the native structure can be achieved for complex membrane proteins if even limited information on residue-residue interactions can be obtained from protein structure databases or experiments.

Comparing four different approaches for the determination of inter-residue interactions provides insight for the structure prediction of helical membrane proteins

Studying inter-residue interactions provides insight into the folding and stability of both soluble and membrane proteins and is essential for developing computational tools for protein structure prediction. As the first step, various approaches for elucidating such interactions within protein structures have been proposed and proven useful. Since different approaches may grasp different aspects of protein structural folds, it is of interest to systematically compare them. In this work, we applied four approaches for determining inter-residue interactions to the analysis of three distinct structure datasets of helical membrane proteins and compared their correlation to the three individual quality measures of structures in these datasets. These datasets included one of 35 structures of rhodopsin receptors and bacterial rhodopsins determined at various resolutions, one derived from the HOMEP benchmark dataset previously reported, and one comprising of 139 homology models. It was found that the correlation between the average number of inter-residue interactions obtained by applying the four approaches and the available structure quality measures varied quite significantly among them. The best correlation was achieved by the approach focusing exclusively on favorable inter-residue interactions. These results provide interesting insight for the development of objective quality measure for the structure prediction of helical membrane proteins.

Protein structure prediction using basin-hopping

Associative memory Hamiltonian structure prediction potentials are not overly rugged, thereby suggesting their landscapes are like those of actual proteins. In the present contribution we show how basin-hopping global optimization can identify low-lying minima for the corresponding mildly frustrated energy landscapes. For small systems the basin-hopping algorithm succeeds in locating both lower minima and conformations closer to the experimental structure than does molecular dynamics with simulated annealing. For large systems the efficiency of basin-hopping decreases for our initial implementation, where the steps consist of random perturbations to the Cartesian coordinates. We implemented umbrella sampling using basin-hopping to further confirm when the global minima are reached. We have also improved the energy surface by employing bioinformatic techniques for reducing the roughness or variance of the energy surface. Finally, the basin-hopping calculations have guided improvements in the excluded volume of the Hamiltonian, producing better structures. These results suggest a novel and transferable optimization scheme for future energy function development.

Macromolecular modeling with rosetta

Advances over the past few years have begun to enable prediction and design of macromolecular structures at near-atomic accuracy. Progress has stemmed from the development of reasonably accurate and efficiently computed all-atom potential functions as well as effective conformational sampling strategies appropriate for searching a highly rugged energy landscape, both driven by feedback from structure prediction and design tests. A unified energetic and kinematic framework in the Rosetta program allows a wide range of molecular modeling problems, from fibril structure prediction to RNA folding to the design of new protein interfaces, to be readily investigated and highlights areas for improvement. The methodology enables the creation of novel molecules with useful functions and holds promise for accelerating experimental structural inference. Emerging connections to crystallographic phasing, NMR modeling, and lower-resolution approaches are described and critically assessed.

Peptide probes for protein transmembrane domains

Much current interest in chemical biology focuses on the transmembrane domains of proteins, which have emerged as targets for the development of novel diagnostics and therapeutics. Integral membrane proteins are a group of important biomolecules that play pivotal roles in many cellular activities. Previous studies primarily focused on the extra- and/or intracellular domains of membrane proteins. However, the importance of transmembrane regions in the regulation of protein complexes is beginning to emerge. As such, a number of methods for designing and testing novel exogenous peptides that recognize transmembrane targets and modulate cellular functions have been developed. This Review outlines current methodologies for developing these transmembrane probes that may provide useful tools to study a variety of biological phenomena in the membrane.

Generation, comparison, and merging of pathways between protein conformations: gating in K-channels

We present a general framework for the generation, alignment, comparison, and hybridization of motion pathways between two known protein conformations. The framework, which is rooted in probabilistic motion-planning techniques in robotics, allows for the efficient generation of collision-free motion pathways, while considering a wide range of degrees of freedom involved in the motion. Within the framework, we provide the means to hybridize pathways, thus producing, the motion pathway of the lowest energy barrier out of the many pathways proposed by our algorithm. This method for comparing and hybridizing pathways is modular, and may be used within the context of molecular dynamics and Monte Carlo simulations. The framework was implemented within the Rosetta software suite, where the protein is represented in atomic detail. The K-channels switch between open and closed conformations, and we used the overall framework to investigate this transition. Our analysis suggests that channel-opening may follow a three-phase pathway. First, the channel unlocks itself from the closed state; second, it opens; and third, it locks itself in the open conformation. A movie that depicts the proposed pathway is available in the Supplementary Material (Movie S1) and at http://www.cs.tau.ac.il/~angela/SuppKcsA.html.

Structural answers and persistent questions about how nicotinic receptors work

The electron diffraction structure of nicotinic acetylcholine receptor (nAChR) from Torpedo marmorata and the X-ray crystallographic structure of acetylcholine binding protein (AChBP) are providing new answers to persistent questions about how nAChRs function as biophysical machines and as participants in cellular and systems physiology. New high-resolution information about nAChR structures might come from advances in crystallography and NMR, from extracellular domain nAChRs as high fidelity models, and from prokaryotic nicotinoid proteins. At the level of biophysics, structures of different nAChRs with different pharmacological profiles and kinetics will help describe how agonists and antagonists bind to orthosteric binding sites, how allosteric modulators affect function by binding outside these sites, how nAChRs control ion flow, and how large cytoplasmic domains affect function. At the level of cellular and systems physiology, structures of nAChRs will help characterize interactions with other cellular components, including lipids and trafficking and signaling proteins, and contribute to understanding the roles of nAChRs in addiction, neurodegeneration, and mental illness. Understanding nAChRs at an atomic level will be important for designing interventions for these pathologies.

Exogenous agents that target transmembrane domains of proteins

Although membrane proteins account for approximately one third of all proteins encoded in the human genome, the functions and structures of their transmembrane domains are much less understood than the water-soluble regions. A major hurdle in studying these transmembrane domains is the lack of appropriate exogenous agents that can be used as specific probes. Despite the daunting challenges, major strides have recently been made in targeting the transmembrane domains of a variety of membrane proteins. High affinity and selectivity have been achieved in model biophysical systems, membranes of bacteria, and mammalian cells.