Using Structural Bioinformatics to Model and Design Membrane Proteins

Cells require membrane proteins for a wide spectrum of critical functions. Transmembrane proteins enable cells to communicate with its environment, catalysis, ion transport and scaffolding. The functional roles of membrane proteins are specified by their sequence composition and precise three dimensional folding. The exact mechanisms driving folding of membrane proteins is still not fully understood. Further, the association between membrane proteins occurs with pinpoint specificity. For example, there exists common sequence features within families of transmembrane receptors, yet there is little cross talk between families. Therefore, we ask how membrane proteins dial in their specificity and what factors are responsible for adoption of native structure. Advancements in membrane protein structure determination methods has been followed by a sharp increase in three dimensional structures. Structural bioinfomatics has been utilized effectively to study water soluble proteins. The field is now entering an era where structural bioinformatics can be applied to modeling membrane proteins without structure and engineering novel membrane proteins. The transmembrane domains of membrane proteins were first categorized structurally. From this analysis, we are able to describe the ways in which membrane proteins fold and associate. We further derived sequence profiles for the commonly occurring structural motifs, enabling us to investigate the role of amino acids within the bilayer. Utilizing these tools, a transmembrane structural model was constructed of principle cell surface receptors (integrins). The structural model enabled understanding of possible mechanisms used to signal and to propose a novel membrane protein packing motif. In addition, novel scoring functions for membrane proteins were developed and applied to modeling membrane proteins. We derived the first all-atom membrane statistical potential and introduced the usage of exposed volume. These potentials allowed modeling of complex interactions in membrane proteins, such as salt bridges. To understand the geometric preferences of salt bridges, we surveyed a structural database. We learned about large biases in salt bridge orientations that will be useful in modeling and design. Lastly, we combine these structural bioinformatic efforts, enabling us to model membrane proteins in ways which were previously inaccessible

Toward biologically realistic computational membrane protein structure prediction and design

Membrane proteins function as gates and checkpoints that control the transit of molecules and information across the lipid bilayer. Understanding their structures will provide mechanistic insights in how to keep cells healthy and defend against disease. However, experimental difficulties have slowed the progress of structure determination. Previous work has demonstrated the promise of computational modeling for elucidating membrane protein structures. A remaining challenge is to model proteins coupled with the heterogeneous cell membrane environment. In the first half of this dissertation, I detail the development, testing and integration of a biologically realistic implicit lipid bilayer model in Rosetta. First, I describe the initial iteration of the implicit model that captures the anisotropic structure, shape of water-filled pores, and nanoscale dimensions of membranes with different lipid compositions. Second, I explain my approach to energy function benchmarking and optimization given the challenge of sparse and low-quality experimental data. Third, I outline the second generation that incorporates a new electrostatics and pH model. All of these developments have advanced the accuracy of Rosetta membrane protein structure prediction and design. In the second half of this dissertation, I investigate three challenging biological and engineering applications involving membrane proteins. In the first application, I examine mutation-induced stability changes in the integral membrane zinc metalloprotease ZMPSTE24: a protein with a large voluminous chamber that is not captured by current implicit models. In the second application, I model interactions between the SERCA2a calcium pump and the regulatory transmembrane protein phospholamban: a key membrane protein-protein interaction implicated in the heart’s response to adrenaline. Finally, I explore the challenge of membrane protein design to engineer a self-assembling transmembrane protein pore for nanotechnology applications. These applications highlight the next steps required to improve computational membrane protein modeling tools. Taken together, my work in both methods development and applications has advanced our understanding and ability to model and design membrane protein structures

Membrane bending is critical for assessing the thermodynamic stability of proteins in the membrane

The ability of biological membranes to bend is critical to understanding the interaction between proteins and the lipid bilayer. Experimental and computational studies have shown that the membrane can bend to expose charged and polar residues to the lipid headgroups and water, greatly reducing the cost of protein insertion. However, current computational approaches are poorly equipped to accurately model such deformation; atomistic simulations often do not reach the time-scale necessary to observe large-scale rearrangement, and continuum approaches assume a flat, rigid bilayer. In this thesis we present an efficient computational model of a deformable membrane for probing these interactions with elasticity theory and continuum electrostatics. To validate the model, we first investigate the insertion of three membrane proteins and three aqueous proteins. The model finds the membrane proteins and aqueous proteins stable and unstable in the membrane, respectively. We also investigate the sensitivity of these predictions to changes in several key parameters. The model is then applied to interactions between the membrane and the voltage sensor segments of voltage-gated potassium channels. Despite their high numbers of basic residues, experiments have shown that voltage sensors can be stably accommodated in the membrane. For simple continuum electrostatics approaches that assume a flat membrane, the penalty of inserting these charged residues would seem to prohibit voltage sensor insertion. However, in our method the membrane deforms to enable interaction between solvent and the charged residues. Our calculations predict that the highly charged S4 helices of several potassium channels are in fact stable in the membrane, in accord with experimental observations. Experimental and computational evidence has shown that the cost for inserting multiple charged amino acids into the membrane is not additive; it is not as costly to insert a second charge once a first has already been inserted. Our model reflects this phenomenon and provides a simple mechanical explanation linked to membrane deformation. We additionally consider the energetics of passive ion penetration into the membrane from bulk solvent. We use coarse-grained molecular dynamics to guide our input parameters and show that ion permeation energy profiles agree with atomistic simulations when membrane bending is included

Sequence based methods for the prediction and analysis of the structural topology of transmembrane beta barrel proteins

Transmembrane proteins play a major role in the normal functioning of the cell. Many transmembrane proteins act as a drug target and hence are of utmost importance to the pharmaceutical industry. In spite of the significance of transmembrane proteins, relatively few transmembrane 3D structures are available due to experimental bottlenecks. Due to this, it is imperative to develop novel computational methods to elucidate the structure and function of these proteins. The two major classes of transmembrane proteins are helical membrane proteins and transmembrane beta barrel proteins. Relatively more 3D structures of helical membrane proteins have been experimentally determined and in general, the majority of computational methods in the realm of transmembrane proteins deal with helical membrane proteins. However, in the recent years there has been an increased interest in the development of computational methods for the transmembrane beta barrel proteins. In this study, I focus on the transmembrane beta barrel proteins. More specifically, I present here computational methods for the prediction of the exposure status of the residues in the membrane spanning region of the transmembrane beta barrel proteins. To the best of our knowledge, the exposure status prediction is a novel problem in the realm of transmembrane beta barrel proteins. The knowledge about the exposure status of the membrane spanning residues is then used to analyse the structural properties of transmembrane beta strands. The exposure status information is also employed to identify relevant physico-chemical properties that are statistically significantly different in the transmembrane beta strands at the oligomeric interfaces and the rest of the protein surface. A method for the prediction of the beta strands in the membrane spanning regions of putative transmembrane beta barrel proteins from protein sequence has also been developed. The computational method for strand prediction is novel in the respect that it also gives the exposure status information of the residues predicted to be in the predicted transmembrane beta strands. The two computational methods developed in this study have been made available as web services. In the future, the information about the exposure status of the residues in the transmembrane beta strands can be used to identify putative transmembrane beta barrels from proteomic data. The exposure status prediction can also be extended to predict the pore region of transmembrane beta barrel proteins from sequence, which could in turn be used in the function prediction of putative transmembrane beta barrels.Die Klasse der Transmembranproteine übernimmt eine Reihe wesentlicher Funktionen innerhalb der Zelle. Daher eignen sich viele dieser Proteine als Ziele für medizinische Wirkstoffe und sind daher von außerordentlichem Interesse für die Pharmaindustrie. Trotz ihrer Wichtigkeit wurden bislang nur wenige drei-dimensionale Strukturen von Membranproteinen erfasst, denn deren experimentelle Bestimmung hat sich als ausgesprochen schwierig herausgestellt. Aus diesem Grund erweist sich die Entwicklung von in silico Methoden zur de novo Vorhersage von Struktur und Funktion dieser Proteine von als notwendige Strategie. Die beiden wesentlichen Klassen von Transmembranproteinen unterteilt man, basierend auf ihren charakteristischen Sekundärstrukturen, in alpha-helikale Proteine und beta-Barrels. Erstere machen den größeren Anteil an experimentell bestimmten Strukturen aus, und auch die meisten bislang vorgestellten in silico Methoden konzentrieren sich auf die Modellierung solch alpha-helikaler Strukturen. In den vergangenen Jahren stieg daher das Interesse an Methoden zur Modellierung von transmembranen beta-Barrels. Die vorliegende Disseration beschäftigt sich vorrangig mit dieser Klasse von Transmembranproteinen, insbesondere präsentieren wir ein Verfahren zur Vorhersage der Exposition ("Exposure\u27;) zur Lipidschicht einzelner Residuen innerhalb der Transmembranregion von beta-Barrels. Diese Vorhersage der Exposition stellt bislang ein neuartiges Problem im Feld der beta-Barrels dar. Die daraus gewonnenen Informationen wurden zur Analyse der strukturellen Eigenschaften von Transmembranketten verwendet. Darüber hinaus können die Exposure-Daten zur Identifikation bedeutender physikochemischer Eigenschaften verwendet werden. Unsere Untersuchungen ergaben, dass zwischen transmembranen beta-strands an Oligomer-Interfaces und dem Rest der Proteinoberfläche statistisch signifikante Unterschiede bezüglich dieser Eigenschaften auftreten. Darüber hinaus stellen wir ein Verfahren zur sequenzbasierten Vorhersage von Transmembran-Residuen mutmaßlicher beta-Barrels vor, welches in Kombination mit der Vorhersage des Exposure-Status in dieser Form neuartig ist. Die beiden in dieser Studie vorgestellten Methoden sind online als Webdienste verfügbar. Basierend auf den Exposure-Vorhersagen von beta-Faltblättern ist es möglich, in künftigen Studien mutmaßliche transmembrane beta-Barrels aus Proteomdatenzu identifizieren

Molecular Dynamics Investigations of Structural Conversions in Transformer Proteins

Multifunctional proteins that undergo major structural changes to perform different functions are known as “Transformer Proteins”, which is a recently identified class of proteins. One such protein that shows a remarkable structural plasticity and has two distinct functions is the transcription antiterminator, RfaH. Depending on the interactions between its N-terminal domain and its C-terminal domain, the RfaH CTD exists as either an all-α-helix bundle or all-β-barrel structure. Another example of a transformer protein is the Ebola virus protein VP40 (eVP40), which exists in different conformations and oligomeric states (dimer, hexamer, and octamer), depending on the required function.I performed Molecular Dynamics (MD) computations to investigate the structural conversion of RfaH-CTD from its all-a to all-b form. I used various structural and statistical mechanics tools to identify important residues involved in controlling the conformational changes. In the full-length RfaH, the interdomain interactions were found to present the major barrier in the structural conversion of RfaH-CTD from all-a to all-b form. I mapped the energy landscape for the conformational changes by calculating the potential of mean force using the Adaptive Biasing Force and Jarzynski Equality methods. Similarly, the interdomain salt-bridges in the eVP40 protomer were found to play a critical role in domain association and plasma membrane (PM) assembly. This molecular dynamic simulation study is supported by virus like particle budding assays investigated by using live cell imaging that highlighted the important role of these saltbridges. I also investigated the plasma membrane association of the eVP40 dimer in various PM compositions and found that the eVP40 dimer readily associates with the PM containing POPS and PIP2 lipids. Also, the CTD helices were observed to be important in stabilizing the dimer-membrane complex. Coarse-grained MD simulations of the eVP40 hexamer and PM system revealed that the hexamer enhances the PIP2 lipid clustering at the lower leaflet of the PM. These results provide insight on the critical steps in the Ebola virus life cycle

Computational Investigation of the Pore Formation Mechanism of Beta-Hairpin Antimicrobial Peptides

β-hairpin antimicrobial peptides (AMPs) are small, usually cationic peptides that provide innate biological defenses against multiple agents. They have been proposed as the basis for novel antibiotics, but their pore formation has not been directly observed on a molecular level. We review previous computational studies of peptide-induced membrane pore formation and report several new molecular dynamics simulations of β-hairpin AMPs to elucidate their pore formation mechanism. We simulated β-barrels of various AMPs in anionic implicit membranes, finding that most of the AMPs’ β-barrels were not as stable as those of protegrin. We also performed an optimization study of protegrin β-barrels in implicit membranes, finding that nonamers were the most stable, but that multiplicities 7–13 were almost equally favorable. This indicated the possibility of a diversity of pore states consisting of various numbers of protegrin peptides. Finally, we used the Anton 2 supercomputer to perform multimicrosecond, all-atom molecular dynamics simulations of various protegrin-1 oligomers on the membrane surface and in transmembrane topologies. We also considered an octamer of the β-hairpin AMP tachyplesin. The simulations on the membrane surface indicated that protegrin dimers are stable, while trimers and tetramers break down because they assume a bent, twisted β-sheet shape. Tetrameric arcs remained stably inserted, but the pore water was displaced by lipid molecules. Unsheared protegrin β-barrels opened into long, twisted β-sheets that surrounded stable aqueous pores, whereas tilted barrels with sheared hydrogen bonding patterns were stable in most topologies. A third type of observed pore consisted of multiple small oligomers surrounding a small, partially lipidic pore. The octameric tachyplesin bundle resulted in small pores surrounded by 6 peptides as monomers and dimers. The results imply that multiple protegrin configurations may produce aqueous pores and illustrate the relationship between topology and pore formation steps. However, these structures’ long-term stability requires further investigation

Structure and Dynamics of the Membrane Protein Bacteriorhodopsin Studied by Mass Spectrometry

Membrane proteins continue to represent a major challenge for most analytical techniques. Using bacteriorhodopsin (BR) as model system, this work aims to develop mass spectrometry (MS)-based approaches for exploring the structure, dynamics and folding of membrane proteins. As the first step, BR in its native lipid environment was exposed to hydroxyl radicals, which were produced by laser photolysis of hydrogen peroxide. It was found that the resulting methionine (Met) labeling pattern was consistent with the known BR structure. This finding demonstrates that laser-induced oxidative Met labeling can provide structural information on membrane proteins. In subsequent experiments, the effects of different denaturing agents (heat, acid, and SDS) on the BR conformation were investigated. It was demonstrated that each of these non-native conditions results in unique structural features that give rise to characteristic Met labeling patterns. These results highlight the ability of laser-induced oxidative labeling to detect conformational changes of membrane proteins. Obtaining better insights into the structural properties of SDS-denatured BR is particularly important because this form of protein is widely used as starting point for folding studies. Combining oxidative labeling with site-directed mutagenesis and fluorescence measurements, this work yielded a detailed structural model of SDS-denatured BR. Subsequently, pulsed oxidative labeling coupled with rapid mixing and MS was used to characterize short-lived intermediates that become populated during BR refolding. The combination of pulsed oxidative labeling and stopped-flow spectroscopy provided key structural insights into the kinetic mechanism by which the SDS-denatured protein inserts and folds into the lipid bilayer. Complementary to oxidative labeling, hydrogen/deuterium exchange (HDX) MS was employed to examine the structure and dynamics of BR under various physiochemical conditions. Structural features of different detergent/lipid-bound BR samples were characterized by their HDX kinetics. Comparative HDX experiments of BR were carried out in the dark (resting state) and under illumination where the induced retinal isomerization mediates proton transport (functioning state). Isotope exchange was found to be much faster during light exposure than in the dark. This observation reveals that structural dynamics of the protein scaffold are accelerated by motions of the retinal, reflecting a direct coupling between protein dynamics and function

Molecular Modeling of Bacterial Nanomachineries

Proteins have the ability to assemble in multimeric states to perform their specific biological function. Unfortunately, characterizing experimentally these structures at atomistic resolution is usually difficult. For this reason, in silico methodologies aiming at predicting how multiple protein copies arrange to forma multimeric complex would be desirable. We present Parallel OptimizationWorkbench (POW), a swarm intelligence based optimization framework able to deal, in principle, with any optimization problem. We show that POW can be applied to biologically relevant problems such as prediction of protein assemblies and the parameterization of a Coarse-Grained force field for proteins. By combining POW optimizations, Molecular Dynamics simulations, Poisson-Boltzmann calculations and a variety of experiments, we subsequently study two bacterial nanomachieries: Aeromonas hydrophila's pore-forming toxin aerolysin, and Yersinia enterocolitica injectisome. These structures are challenging both for their size, and for the timescales involved in their functioning. Aerolysin is a pore-forming toxin secreted as an hydrophilic monomer. By means of large conformational changes, the protein heptamerizes on the target cell's surface, and finally inserts β-barrel into its lipid bilayer, causing cell death. The main hurdle in the study of this structure is the complexity of the mode of action, which spans timescales currently unreachable by classical molecular dynamics. We show that aerolysin C-terminal region has the dual role of preventing premature oligomerization and helping the folding of tertiary structure, qualifying therefore as an intramolecular chaperone. We study the transmembrane β-barrel properties and compare them with those of the homologous protein α-hemolysin. We show that aerolysin's barrel is more rigid than α-hemolysin's, and should be anion selective. We present models for aerolysin heptamer both in prepore and, for the first time, in membrane-inserted conformation. Our results are validated experimentally, and are consistent with known biochemical and structural data. The injectisome is an example of a type III secretion system. Its most striking feature is probably its size: hundreds of proteins assemble in a unique structure spanning the Gram-negative bacterial double membrane, and protruding outside the cell as a needle for tenth of nanometers. Obtaining an atomistic representation of this massive structure, and therefore some insights about its mode of action, is one of the greatest challenges. We show that the final length of injectisome's needle is determined by the secondary structure content of a ruler protein located inside its cavity during assembly. Using POW, we also produce the first model for Yersinia injectisome's basal body, highlighting the flexibility of this region in adapting between the inner and outer membranes. As a whole, this work demonstrates that a synergy of dry and wet experiments can provide precious insights into macromolecular structure and function