Knowledge-based potential for positioning membrane-associated structures and assessing residue-specific energetic contributions

Sequence-dependent scale for translocon-mediated insertion of interfacial helices in membranes

Biological membranes consist of a lipid bilayer studded with integral and peripheral membrane proteins. Most α-helical membrane proteins require protein-conducting insertases known as translocons to assist in their membrane insertion and folding. While the sequence-dependent propensities for a helix to either translocate through the translocon or insert into the membrane have been codified into numerical hydrophobicity scales, the corresponding propensity to partition into the membrane interface remains unrevealed. By engineering diagnostic glycosylation sites around test peptide sequences inserted into a host protein, we devised a system that can differentiate between water-soluble, surface-bound, and transmembrane (TM) states of the sequence based on its glycosylation pattern. Using this system, we determined the sequence-dependent propensities for transfer from the translocon to a TM, interfacial, or extramembrane space and compared these propensities with the corresponding probability distributions determined from the sequences and structures of experimentally determined proteins.

OPRLM: A Web Tool and a Database for Positioning and Simulations of Proteins in Realistic Lipid Membranes

Molecular dynamics (MD) simulations in explicit lipid bilayers enable modeling of protein-lipid interactions essential for membrane protein functions and regulation. The newly developed computational web tool, OPRLM (Orientations of Proteins in Realistic Lipid Membranes), automates the assembly of membrane protein structures with explicit lipids corresponding to 18 biological membrane types with symmetric or asymmetric lipid distributions, as well as 5 types of two-component lipid bilayers with varying cholesterol content. Built upon the CHARMM-GUI toolset and the PPM method, OPRLM simplifies the setup of complex simulation system involving integral and/or peripheral membrane proteins with explicit lipid mixtures and generates all necessary files for subsequent all-atom MD simulations. OPRLM has successfully generated protein-membrane systems for 286 tested protein structures in various biomembranes, including 138 structures containing ligands. The OPRLM database, an advanced successor of the OPM database, includes explicit protein-lipid systems for tested proteins in their native biomembranes. It provides coordinates of integral and peripheral membrane proteins from the Protein Data Bank embedded in planar or curved implicit lipid bilayers. Additionally, it includes the classification of proteins into types, superfamilies, and families, along with the information on intracellular localizations and membrane topology and visualization options. The OPRLM web tool and the database are publicly accessible at https://oprlm.org.

Implicit model to capture electrostatic features of membrane environment

Membrane protein structure prediction and design are challenging due to the complexity of capturing the interactions in the lipid layer, such as those arising from electrostatics. Accurately capturing electrostatic energies in the low-dielectric membrane often requires expensive Poisson-Boltzmann calculations that are not scalable for membrane protein structure prediction and design. In this work, we have developed a fast-to-compute implicit energy function that considers the realistic characteristics of different lipid bilayers, making design calculations tractable. This method captures the impact of the lipid head group using a mean-field-based approach and uses a depth-dependent dielectric constant to characterize the membrane environment. This energy function Franklin2023 (F23) is built upon Franklin2019 (F19), which is based on experimentally derived hydrophobicity scales in the membrane bilayer. We evaluated the performance of F23 on five different tests probing (1) protein orientation in the bilayer, (2) stability, and (3) sequence recovery. Relative to F19, F23 has improved the calculation of the tilt angle of membrane proteins for 90% of WALP peptides, 15% of TM-peptides, and 25% of the adsorbed peptides. The performances for stability and design tests were equivalent for F19 and F23. The speed and calibration of the implicit model will help F23 access biophysical phenomena at long time and length scales and accelerate the membrane protein design pipeline.

Implicit model to capture electrostatic features of membrane environment

Membrane protein structure prediction and design are challenging due to the complexity of capturing the interactions in the lipid layer, such as those arising from electrostatics. Accurately capturing electrostatic energies in the low-dielectric membrane often requires expensive Poisson-Boltzmann calculations that are not scalable for membrane protein structure prediction and design. In this work, we have developed a fast-to-compute implicit energy function that considers the realistic characteristics of different lipid bilayers, making design calculations tractable. This method captures the impact of the lipid head group using a mean-field-based approach and uses a depth-dependent dielectric constant to characterize the membrane environment. This energy function Franklin2023 (F23) is built upon Franklin2019 (F19), which is based on experimentally derived hydrophobicity scales in the membrane bilayer. We evaluated the performance of F23 on five different tests probing (1) protein orientation in the bilayer, (2) stability, and (3) sequence recovery. Relative to F19, F23 has improved the calculation of the tilt angle of membrane proteins for 90% of WALP peptides, 15% of TM-peptides, and 25% of the adsorbed peptides. The performances for stability and design tests were equivalent for F19 and F23. The speed and calibration of the implicit model will help F23 access biophysical phenomena at long time and length scales and accelerate the membrane protein design pipeline.

Comprehensive classification of proteins based on structures that engage lipids by COMPOSEL

Structures can now be predicted for any protein using programs like AlphaFold and Rosetta, which rely on a foundation of experimentally determined structures of architecturally diverse proteins. The accuracy of such artificial intelligence and machine learning (AI/ML) approaches benefits from the specification of restraints which assist in navigating the universe of folds to converge on models most representative of a given protein's physiological structure. This is especially pertinent for membrane proteins, with structures and functions that depend on their presence in lipid bilayers. Structures of proteins in their membrane environments could conceivably be predicted from AI/ML approaches with user-specificized parameters that describe each element of the architecture of a membrane protein accompanied by its lipid environment. We propose the Classification Of Membrane Proteins based On Structures Engaging Lipids (COMPOSEL), which builds on existing nomenclature types for monotopic, bitopic, polytopic and peripheral membrane proteins as well as lipids. Functional and regulatory elements are also defined in the scripts, as shown with membrane fusing synaptotagmins, multidomain PDZD8 and Protrudin proteins that recognize phosphoinositide (PI) lipids, the intrinsically disordered MARCKS protein, caveolins, the β barrel assembly machine (BAM), an adhesion G-protein coupled receptor (aGPCR) and two lipid modifying enzymes - diacylglycerol kinase DGKε and fatty aldehyde dehydrogenase FALDH. This demonstrates how COMPOSEL communicates lipid interactivity as well as signaling mechanisms and binding of metabolites, drug molecules, polypeptides or nucleic acids to describe the operations of any protein. Moreover COMPOSEL can be scaled to express how genomes encode membrane structures and how our organs are infiltrated by pathogens such as SARS-CoV-2.

SARS-CoV-2 Omicron Subvariants Balance Host Cell Membrane, Receptor, and Antibody Docking via an Overlapping Target Site

Variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are emerging rapidly and offer surfaces that are optimized for recognition of host cell membranes while also evading antibodies arising from vaccinations and previous infections. Host cell infection is a multi-step process in which spike heads engage lipid bilayers and one or more angiotensin-converting enzyme 2 (ACE-2) receptors. Here, the membrane binding surfaces of Omicron subvariants are compared using cryo-electron microscopy (cEM) structures of spike trimers from BA.2, BA.2.12.1, BA.2.13, BA.2.75, BA.3, BA.4, and BA.5 viruses. Despite significant differences around mutated sites, they all maintain strong membrane binding propensities that first appeared in BA.1. Both their closed and open states retain elevated membrane docking capacities, although the presence of more closed than open states diminishes opportunities to bind receptors while enhancing membrane engagement. The electrostatic dipoles are generally conserved. However, the BA.2.75 spike dipole is compromised, and its ACE-2 affinity is increased, and BA.3 exhibits the opposite pattern. We propose that balancing the functional imperatives of a stable, readily cleavable spike that engages both lipid bilayers and receptors while avoiding host defenses underlies betacoronavirus evolution. This provides predictive criteria for rationalizing future pandemic waves and COVID-19 transmissibility while illuminating critical sites and strategies for simultaneously combating multiple variants.

Transmembrane Membrane Readers form a Novel Class of Proteins That Include Peripheral Phosphoinositide Recognition Domains and Viral Spikes

Membrane proteins are broadly classified as transmembrane (TM) or peripheral, with functions that pertain to only a single bilayer at a given time. Here, we explicate a class of proteins that contain both transmembrane and peripheral domains, which we dub transmembrane membrane readers (TMMRs). Their transmembrane and peripheral elements anchor them to one bilayer and reversibly attach them to another section of bilayer, respectively, positioning them to tether and fuse membranes while recognizing signals such as phosphoinositides (PIs) and modifying lipid chemistries in proximity to their transmembrane domains. Here, we analyze full-length models from AlphaFold2 and Rosetta, as well as structures from nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography, using the Membrane Optimal Docking Area (MODA) program to map their membrane-binding surfaces. Eukaryotic TMMRs include phospholipid-binding C1, C2, CRAL-TRIO, FYVE, GRAM, GTPase, MATH, PDZ, PH, PX, SMP, StART and WD domains within proteins including protrudin, sorting nexins and synaptotagmins. The spike proteins of SARS-CoV-2 as well as other viruses are also TMMRs, seeing as they are anchored into the viral membrane while mediating fusion with host cell membranes. As such, TMMRs have key roles in cell biology and membrane trafficking, and include drug targets for diseases such as COVID-19.

Progressive membrane-binding mechanism of SARS-CoV-2 variant spike proteins

Membrane recognition by viral spike proteins is critical for infection. Here we show the host cell membrane-binding surfaces of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike variants Alpha, Beta, Gamma, Delta, Epsilon, Kappa, and Omicron as well as SARS-CoV-1 and pangolin and bat relatives. They show increases in membrane binding propensities over time, with all spike head mutations in variants, and particularly BA.1, impacting the protein's affinity to cell membranes. Comparison of hundreds of structures yields a progressive model of membrane docking in which spike protein trimers shift from initial perpendicular stances to increasingly tilted positions that draw viral particles alongside host cell membranes before optionally engaging angiotensin-converting enzyme 2 (ACE2) receptors. This culminates in the assembly of the symmetric fusion apparatus, with enhanced membrane interactions of variants explaining their unique cell fusion capacities and COVID-19 disease transmission rates.

Multifaceted membrane binding head of the SARS-CoV-2 spike protein

The SARS-CoV-2 spike protein presents a surface with enormous membrane binding potential to host tissues and organelles of infected cells. Its exposed trimeric head binds not only the angiotensin-converting enzyme 2 (ACE2), but also host phospholipids which are missing from all existing structures. Hence, the membrane interaction surfaces that mediate viral fusion, entry, assembly and egress remain unclear. Here the spike:membrane docking sites are identified based on membrane optimal docking area (MODA) analysis of 3D structures of spike proteins in closed and open conformations at endocytic and neutral pH levels as well as ligand complexes. This reveals multiple membrane binding sites in the closed spike head that together prefer convex membranes and are modulated by pH, fatty acids and post-translational modifications including glycosylation. The exposure of the various membrane interaction sites adjusts upon domain repositioning within the trimer, allowing formation of intermediate bilayer complexes that lead to the prefusion state while also enabling ACE2 receptor recognition. In contrast, all antibodies that target the spike head would block the membrane docking process that precedes ACE2 recognition. Together this illuminates the engagements of the spike protein with plasma, endocytic, ER or exocytic vesicle membranes that help to drive the cycle of viral infection, and offers novel sites for intervention.

How physical forces drive the process of helical membrane protein folding

Protein folding is a fundamental process of life with important implications throughout biology. Indeed, tens of thousands of mutations have been associated with diseases, and most of these mutations are believed to affect protein folding rather than function. Correct folding is also a key element of design. These factors have motivated decades of research on protein folding. Unfortunately, knowledge of membrane protein folding lags that of soluble proteins. This gap is partly caused by the greater technical challenges associated with membrane protein studies, but also because of additional complexities. While soluble proteins fold in a homogenous water environment, membrane proteins fold in a setting that ranges from bulk water to highly charged to apolar. Thus, the forces that drive folding vary in different regions of the protein, and this complexity needs to be incorporated into our understanding of the folding process. Here, we review our understanding of membrane protein folding biophysics. Despite the greater challenge, better model systems and new experimental techniques are starting to unravel the forces and pathways in membrane protein folding.

Spatial arrangement of proteins in planar and curved membranes by PPM 3.0

Cellular protrusions, invaginations, and many intracellular organelles have strongly curved membrane regions. Transmembrane and peripheral membrane proteins that induce, sense, or stabilize such regions cannot be properly fitted into a single flat bilayer. To treat such proteins, we developed a new method and a web tool, PPM 3.0, for positioning proteins in curved or planar, single or multiple membranes. This method determines the energetically optimal spatial position, the hydrophobic thickness, and the radius of intrinsic curvature of a membrane-deforming protein structure by arranging it in a single or several sphere-shaped or planar membrane sections. In addition, it can define the lipid-embedded regions of a protein that simultaneously spans several membranes or determine the optimal position of a peptide in a spherical micelle. The PPM 3.0 web server operates with 17 types of biological membranes and 4 types of artificial bilayers. It is publicly available at https://opm.phar.umich.edu/ppm_server3. PPM 3.0 was applied to identify and characterize arrangements in membranes of 128 proteins with a significant intrinsic curvature, such as BAR domains, annexins, Piezo, and MscS mechanosensitive channels, cation-chloride cotransporters, as well as mitochondrial ATP synthases, calcium uniporters, and TOM complexes. These proteins form large complexes that are mainly localized in mitochondria, plasma membranes, and endosomes. Structures of bacterial drug efflux pumps, AcrAB-TolC, MexAB-OrpM, and MacAB-TolC, were positioned in both membranes of the bacterial cell envelop, while structures of multimeric gap-junction channels were arranged in two opposed cellular membranes.

Spiers Memorial Lecture: Analysis and de novo design of membrane-interactive peptides

Membrane-peptide interactions play critical roles in many cellular and organismic functions, including protection from infection, remodeling of membranes, signaling, and ion transport. Peptides interact with membranes in a variety of ways: some associate with membrane surfaces in either intrinsically disordered conformations or well-defined secondary structures. Peptides with sufficient hydrophobicity can also insert vertically as transmembrane monomers, and many associate further into membrane-spanning helical bundles. Indeed, some peptides progress through each of these stages in the process of forming oligomeric bundles. In each case, the structure of the peptide and the membrane represent a delicate balance between peptide-membrane and peptide-peptide interactions. We will review this literature from the perspective of several biologically important systems, including antimicrobial peptides and their mimics, α-synuclein, receptor tyrosine kinases, and ion channels. We also discuss the use of de novo design to construct models to test our understanding of the underlying principles and to provide useful leads for pharmaceutical intervention of diseases.

BRANEart: Identify Stability Strength and Weakness Regions in Membrane Proteins

Understanding the role of stability strengths and weaknesses in proteins is a key objective for rationalizing their dynamical and functional properties such as conformational changes, catalytic activity, and protein-protein and protein-ligand interactions. We present BRANEart, a new, fast and accurate method to evaluate the per-residue contributions to the overall stability of membrane proteins. It is based on an extended set of recently introduced statistical potentials derived from membrane protein structures, which better describe the stability properties of this class of proteins than standard potentials derived from globular proteins. We defined a per-residue membrane propensity index from combinations of these potentials, which can be used to identify residues which strongly contribute to the stability of the transmembrane region or which would, on the contrary, be more stable in extramembrane regions, or vice versa. Large-scale application to membrane and globular proteins sets and application to tests cases show excellent agreement with experimental data. BRANEart thus appears as a useful instrument to analyze in detail the overall stability properties of a target membrane protein, to position it relative to the lipid bilayer, and to rationally modify its biophysical characteristics and function. BRANEart can be freely accessed from http://babylone.3bio.ulb.ac.be/BRANEart.

Principles and Methods in Computational Membrane Protein Design

After decades of progress in computational protein design, the design of proteins folding and functioning in lipid membranes appears today as the next frontier. Some notable successes in the de novo design of simplified model membrane protein systems have helped articulate fundamental principles of protein folding, architecture and interaction in the hydrophobic lipid environment. These principles are reviewed here, together with the computational methods and approaches that were used to identify them. We provide an overview of the methodological innovations in the generation of new protein structures and functions and in the development of membrane-specific energy functions. We highlight the opportunities offered by new machine learning approaches applied to protein design, and by new experimental characterization techniques applied to membrane proteins. Although membrane protein design is in its infancy, it appears more reachable than previously thought.

How bilayer properties influence membrane protein folding

The question of how proteins manage to organize into a unique three-dimensional structure has been a major field of study since the first protein structures were determined. For membrane proteins, the question is made more complex because, unlike water-soluble proteins, the solvent is not homogenous or even unique. Each cell and organelle has a distinct lipid composition that can change in response to environmental stimuli. Thus, the study of membrane protein folding requires not only understanding how the unfolded chain navigates its way to the folded state, but also how changes in bilayer properties can affect that search. Here we review what we know so far about the impact of lipid composition on bilayer physical properties and how those properties can affect folding. A better understanding of the lipid bilayer and its effects on membrane protein folding is not only important for a theoretical understanding of the folding process, but can also have a practical impact on our ability to work with and design membrane proteins.

Robust Sequence Determinants of α-Synuclein Toxicity in Yeast Implicate Membrane Binding

Protein conformations are shaped by cellular environments, but how environmental changes alter the conformational landscapes of specific proteins in vivo remains largely uncharacterized, in part due to the challenge of probing protein structures in living cells. Here, we use deep mutational scanning to investigate how a toxic conformation of α-synuclein, a dynamic protein linked to Parkinson's disease, responds to perturbations of cellular proteostasis. In the context of a course for graduate students in the UCSF Integrative Program in Quantitative Biology, we screened a comprehensive library of α-synuclein missense mutants in yeast cells treated with a variety of small molecules that perturb cellular processes linked to α-synuclein biology and pathobiology. We found that the conformation of α-synuclein previously shown to drive yeast toxicity-an extended, membrane-bound helix-is largely unaffected by these chemical perturbations, underscoring the importance of this conformational state as a driver of cellular toxicity. On the other hand, the chemical perturbations have a significant effect on the ability of mutations to suppress α-synuclein toxicity. Moreover, we find that sequence determinants of α-synuclein toxicity are well described by a simple structural model of the membrane-bound helix. This model predicts that α-synuclein penetrates the membrane to constant depth across its length but that membrane affinity decreases toward the C terminus, which is consistent with orthogonal biophysical measurements. Finally, we discuss how parallelized chemical genetics experiments can provide a robust framework for inquiry-based graduate coursework.

A paradigm of thermal adaptation in penguins and elephants by tuning cold activation in TRPM8

Sensing temperature is critical for the survival of all living beings. Here, we show that during cold-induced activation of the archetypical temperature-sensitive TRPM8 ion channel, there are hydrophobic residues in the pore domain stabilized in the exposed state. Tuning hydrophobicity of these residues specifically alters cold response in TRPM8. Furthermore, TRPM8 orthologs in vertebrates evolved to employ such a mechanism, which physiologically tunes cold tolerance for better thermal adaptation. Our findings not only advance the understanding of the cold-induced activation mechanism of TRPM8 but also bring insights to the molecular evolution strategy for ambient-temperature adaptation in vertebrates.

To adapt to habitat temperature, vertebrates have developed sophisticated physiological and ecological mechanisms through evolution. Transient receptor potential melastatin 8 (TRPM8) serves as the primary sensor for cold. However, how cold activates TRPM8 and how this sensor is tuned for thermal adaptation remain largely unknown. Here we established a molecular framework of how cold is sensed in TRPM8 with a combination of patch-clamp recording, unnatural amino acid imaging, and structural modeling. We first observed that the maximum cold activation of TRPM8 in eight different vertebrates (i.e., African elephant and emperor penguin) with distinct side-chain hydrophobicity (SCH) in the pore domain (PD) is tuned to match their habitat temperature. We further showed that altering SCH for residues in the PD with solvent-accessibility changes leads to specific tuning of the cold response in TRPM8. We also observed that knockin mice expressing the penguin’s TRPM8 exhibited remarkable tolerance to cold. Together, our findings suggest a paradigm of thermal adaptation in vertebrates, where the evolutionary tuning of the cold activation in the TRPM8 ion channel through altering SCH and solvent accessibility in its PD largely contributes to the setting of the cold-sensitive/tolerant phenotype.

Protein Structure Prediction and Design in a Biologically Realistic Implicit Membrane

Protein design is a powerful tool for elucidating mechanisms of function and engineering new therapeutics and nanotechnologies. Although soluble protein design has advanced, membrane protein design remains challenging because of difficulties in modeling the lipid bilayer. In this work, we developed an implicit approach that captures the anisotropic structure, shape of water-filled pores, and nanoscale dimensions of membranes with different lipid compositions. The model improves performance in computational benchmarks against experimental targets, including prediction of protein orientations in the bilayer, ΔΔG calculations, native structure discrimination, and native sequence recovery. When applied to de novo protein design, this approach designs sequences with an amino acid distribution near the native amino acid distribution in membrane proteins, overcoming a critical flaw in previous membrane models that were prone to generating leucine-rich designs. Furthermore, the proteins designed in the new membrane model exhibit native-like features including interfacial aromatic side chains, hydrophobic lengths compatible with bilayer thickness, and polar pores. Our method advances high-resolution membrane protein structure prediction and design toward tackling key biological questions and engineering challenges.

De novo protein design, a retrospective

Proteins are molecular machines whose function depends on their ability to achieve complex folds with precisely defined structural and dynamic properties. The rational design of proteins from first-principles, or de novo, was once considered to be impossible, but today proteins with a variety of folds and functions have been realized. We review the evolution of the field from its earliest days, placing particular emphasis on how this endeavor has illuminated our understanding of the principles underlying the folding and function of natural proteins, and is informing the design of macromolecules with unprecedented structures and properties. An initial set of milestones in de novo protein design focused on the construction of sequences that folded in water and membranes to adopt folded conformations. The first proteins were designed from first-principles using very simple physical models. As computers became more powerful, the use of the rotamer approximation allowed one to discover amino acid sequences that stabilize the desired fold. As the crystallographic database of protein structures expanded in subsequent years, it became possible to construct proteins by assembling short backbone fragments that frequently recur in Nature. The second set of milestones in de novo design involves the discovery of complex functions. Proteins have been designed to bind a variety of metals, porphyrins, and other cofactors. The design of proteins that catalyze hydrolysis and oxygen-dependent reactions has progressed significantly. However, de novo design of catalysts for energetically demanding reactions, or even proteins that bind with high affinity and specificity to highly functionalized complex polar molecules remains an importnant challenge that is now being achieved. Finally, the protein design contributed significantly to our understanding of membrane protein folding and transport of ions across membranes. The area of membrane protein design, or more generally of biomimetic polymers that function in mixed or non-aqueous environments, is now becoming increasingly possible.

Role of the N-Terminal Transmembrane Helix Contacts in the Activation of FGFR3

Fibroblast growth factor receptor 3 (FGFR3) is a member of receptor tyrosine kinases, which is involved in skeletal cell growth, differentiation, and migration. FGFR3 transduces biochemical signals from the extracellular ligand-binding domain to the intracellular kinase domain through the conformational changes of the transmembrane (TM) helix dimer. Here, we apply generalized replica exchange with solute tempering method to wild type (WT) and G380R mutant (G380R) of FGFR3. The dimer interface in G380R is different from WT and the simulation results are in good agreement with the solid-state nuclear magnetic resonance (NMR) spectroscopy. TM helices in G380R are extended more than WT, and thereby, G375 in G380R contacts near the N-termini of the TM helix dimer. Considering that both G380R and G375C show the constitutive activation, the formation of the N-terminal contacts of the TM helices can be generally important for the activation mechanism. © 2019 Wiley Periodicals, Inc.

A Membrane Burial Potential with H-Bonds and Applications to Curved Membranes and Fast Simulations

We use the statistics of a large and curated training set of transmembrane helical proteins to develop a knowledge-based potential that accounts for the dependence on both the depth of burial of the protein in the membrane and the degree of side-chain exposure. Additionally, the statistical potential includes depth-dependent energies for unsatisfied backbone hydrogen bond donors and acceptors, which are found to be relatively small, ∼2 RT. Our potential accurately places known proteins within the bilayer. The potential is applied to the mechanosensing MscL channel in membranes of varying thickness and curvature, as well as to the prediction of protein structure. The potential is incorporated into our new Upside molecular dynamics algorithm. Notably, we account for the exchange of protein-lipid interactions for protein-protein interactions as helices contact each other, thereby avoiding overestimating the energetics of helix association within the membrane. Simulations of most multimeric complexes find that isolated monomers and the oligomers retain the same orientation in the membrane, suggesting that the assembly of prepositioned monomers presents a viable mechanism of oligomerization.

Design of self-assembling transmembrane helical bundles to elucidate principles required for membrane protein folding and ion transport

Ion transporters and channels are able to identify and act on specific substrates among myriads of ions and molecules critical to cellular processes, such as homeostasis, cell signalling, nutrient influx and drug efflux. Recently, we designed Rocker, a minimalist model for Zn²⁺/H⁺ co-transport. The success of this effort suggests that de novo membrane protein design has now come of age so as to serve a key approach towards probing the determinants of membrane protein folding, assembly and function. Here, we review general principles that can be used to design membrane proteins, with particular reference to helical assemblies with transport function. We also provide new functional and NMR data that probe the dynamic mechanism of conduction through Rocker.This article is part of the themed issue 'Membrane pores: from structure and assembly, to medicine and technology'.

Statistically derived asymmetric membrane potentials from α-helical and β-barrel membrane proteins

Modeling membrane protein (MP) folding, insertion, association and their interactions with other proteins, lipids, and drugs requires accurate transfer free energies (TFEs). Various TFE scales have been derived to quantify the energy required or released to insert an amino acid or protein into the membrane. Experimental measurement of TFEs is challenging, and only few scales were extended to depth-dependent energetic profiles. Statistical approaches can be used to derive such potentials; however, this requires a sufficient number of MP structures. Furthermore, MPs are tightly coupled to bilayers that are heterogeneous in terms of lipid composition, asymmetry, and protein content between organisms and organelles. Here we derived asymmetric implicit membrane potentials from β-barrel and α-helical MPs and use them to predict topology, depth and orientation of proteins in the membrane. Our data confirm the ‘charge-outside’ and ‘positive-inside’ rules for β-barrels and α-helical proteins, respectively. We find that the β-barrel profiles have greater asymmetry than the ones from α-helical proteins, as a result of the different membrane architecture of gram-negative bacterial outer membranes and the existence of lipopolysaccharide in the outer leaflet. Our data further suggest that pore-facing residues in β-barrels have a larger contribution to membrane insertion and stability than previously suggested.

Efficient computation of transfer free energies of amino acids in beta-barrel membrane proteins

Motivation

Transmembrane beta-barrel proteins (TMBs) serve a multitude of essential cellular functions in Gram-negative bacteria, mitochondria and chloroplasts. Transfer free energies (TFEs) of residues in the transmembrane (TM) region provides fundamental quantifications of thermodynamic stabilities of TMBs, which are important for the folding and the membrane insertion processes, and may help in understanding the structure-function relationship. However, experimental measurement of TFEs of TMBs is challenging. Although a recent computational method can be used to calculate TFEs, the results of which are in excellent agreement with experimentally measured values, this method does not scale up, and is limited to small TMBs.

Results

We have developed an approximation method that calculates TFEs of TM residues in TMBs accurately, with which depth-dependent transfer free energy profiles can be derived. Our results are in excellent agreement with experimental measurements. This method is efficient and applicable to all bacterial TMBs regardless of the size of the protein.

Availability and Implementation

An online webserver is available at http://tanto.bioe.uic.edu/tmb-tfe .

Contact

: jliang@uic.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Towards an experimental classification system for membrane active peptides

Mature proteins can act as potential sources of encrypted bioactive peptides that, once released from their parent proteins, might interact with diverse biomolecular targets. In recent work we introduced a systematic methodology to uncover encrypted intragenic antimicrobial peptides (IAPs) within large protein sequence libraries. Given that such peptides may interact with membranes in different ways, resulting in distinct observable outcomes, it is desirable to develop a predictive methodology to categorize membrane active peptides and establish a link to their physicochemical properties. Building upon previous work, we explored the interaction of a range of IAPs with model membranes probed by differential scanning calorimetry (DSC) and circular dichroism (CD) techniques. The biophysical data were submitted to multivariate statistical methods and resulting peptide clusters were correlated to peptide structure and to their antimicrobial activity. A re-evaluation of the physicochemical properties of the peptides was conducted based on peptide cluster memberships. Our data indicate that membranolytic peptides produce characteristic thermal transition (DSC) profiles in model vesicles and that this can be used to categorize novel molecules with unknown biological activity. Incremental expansion of the model presented here might result in a unified experimental framework for the prediction of novel classes of membrane active peptides.

Electrostatic Interactions in Protein Structure, Folding, Binding, and Condensation

Charged and polar groups, through forming ion pairs, hydrogen bonds, and other less specific electrostatic interactions, impart important properties to proteins. Modulation of the charges on the amino acids, e.g., by pH and by phosphorylation and dephosphorylation, have significant effects such as protein denaturation and switch-like response of signal transduction networks. This review aims to present a unifying theme among the various effects of protein charges and polar groups. Simple models will be used to illustrate basic ideas about electrostatic interactions in proteins, and these ideas in turn will be used to elucidate the roles of electrostatic interactions in protein structure, folding, binding, condensation, and related biological functions. In particular, we will examine how charged side chains are spatially distributed in various types of proteins and how electrostatic interactions affect thermodynamic and kinetic properties of proteins. Our hope is to capture both important historical developments and recent experimental and theoretical advances in quantifying electrostatic contributions of proteins.

A single residue controls electron transfer gating in photosynthetic reaction centers

Interquinone Q_A⁻ → Q_B electron-transfer (ET) in isolated photosystem II reaction centers (PSII-RC) is protein-gated. The temperature-dependent gating frequency “k” is described by the Eyring equation till levelling off at T ≥ 240 °K. Although central to photosynthesis, the gating mechanism has not been resolved and due to experimental limitations, could not be explored in vivo. Here we mimic the temperature dependency of “k” by enlarging V_D1-208, the volume of a single residue at the crossing point of the D1 and D2 PSII-RC subunits in Synechocystis 6803 whole cells. By controlling the interactions of the D1/D2 subunits, V_D1-208 (or 1/T) determines the frequency of attaining an ET-active conformation. Decelerated ET, impaired photosynthesis, D1 repair rate and overall cell physiology upon increasing V_D1-208 to above 130 ų, rationalize the >99% conservation of small residues at D1-208 and its homologous motif in non-oxygenic bacteria. The experimental means and resolved mechanism are relevant for numerous transmembrane protein-gated reactions.

Vesicular acetylcholine transporter defect underlies devastating congenital myasthenia syndrome

OBJECTIVE

To identify the genetic basis of a recessive congenital neurologic syndrome characterized by severe hypotonia, arthrogryposis, and respiratory failure.

METHODS

Identification of the responsible gene by exome sequencing and assessment of the effect of the mutation on protein stability in transfected rat neuronal-like PC12^A123.7 cells.

RESULTS

Two brothers from a nonconsanguineous Yemeni Jewish family manifested at birth with severe hypotonia and arthrogryposis. The older brother died of respiratory failure at 5 days of age. The proband, now 4.5 years old, has been mechanically ventilated since birth with virtually no milestones achievement. Whole exome sequencing revealed homozygosity of SLC18A3 c.1078G>C, p.Gly360Arg in the affected brothers but not in other family members. SLC18A3 p.Gly360Arg is not reported in world populations but is present at a carrier frequency of 1:30 in healthy Yemeni Jews. SLC18A3 encodes the vesicular acetylcholine transporter (VAChT), which loads newly synthesized acetylcholine from the neuronal cytoplasm into synaptic vesicles. Mice that are VAChT-null have been shown to die at birth of respiratory failure. In human VAChT, residue 360 is located in a conserved region and substitution of arginine for glycine is predicted to disrupt proper protein folding and membrane embedding. Stable transfection of wild-type and mutant human VAChT into neuronal-like PC12^A123.7 cells revealed similar mRNA levels, but undetectable levels of the mutant protein, suggesting post-translational degradation of mutant VAChT.

CONCLUSION

Loss of function of VAChT underlies severe arthrogryposis and respiratory failure. While most congenital myasthenic syndromes are caused by defects in postsynaptic proteins, VAChT deficiency is a presynaptic myasthenic syndrome.

Membranome: a database for proteome-wide analysis of single-pass membrane proteins

The Membranome database was developed to assist analysis and computational modeling of single-pass (bitopic) transmembrane (TM) proteins and their complexes by providing structural information about these proteins on a genomic scale. The database currently collects data on >6000 bitopic proteins from Homo sapiens, Arabidopsis thaliana, Dictyostelium discoideum, Saccharomyces cerevisiae, Escherichia coli and Methanocaldococcus jannaschii It presents the following data: (i) hierarchical classification of bitopic proteins into 15 functional classes, 689 structural superfamilies and 1404 families; (ii) 446 complexes of bitopic proteins with known three-dimensional (3D) structures classified into 129 families; (iii) computationally generated three-dimensional models of TM α-helices positioned in membranes; (iv) amino acid sequences, domain architecture, functional annotation and available experimental structures of bitopic proteins; (v) TM topology and intracellular localization, (vi) physical interactions between proteins from the database along with links to other resources. The database is freely accessible at http://membranome.org There is a variety of options for browsing, sorting, searching and retrieval of the content, including downloadable coordinate files of TM domains with calculated membrane boundaries.

TMPL: a database of experimental and theoretical transmembrane protein models positioned in the lipid bilayer

Knowing the position of protein structures within the membrane is crucial for fundamental and applied research in the field of molecular biology. Only few web resources propose coordinate files of oriented transmembrane proteins, and these exclude predicted structures, although they represent the largest part of the available models. In this article, we present TMPL (http://www.dsimb.inserm.fr/TMPL/), a database of transmembrane protein structures (α-helical and β-sheet) positioned in the lipid bilayer. It is the first database to include theoretical models of transmembrane protein structures, making it a large repository with more than 11 000 entries. The TMPL database also contains experimentally solved protein structures, which are available as either atomistic or coarse-grained models. A unique feature of TMPL is the possibility for users to update the database by uploading, through an intuitive web interface, the membrane assignments they can obtain with our recent OREMPRO web server.

Achievements and Challenges in Computational Protein Design

Computational protein design (CPD), a yet evolving field, includes computer-aided engineering for partial or full de novo designs of proteins of interest. Designs are defined by a requested structure, function, or working environment. This chapter describes the birth and maturation of the field by presenting 101 CPD examples in a chronological order emphasizing achievements and pending challenges. Integrating these aspects presents the plethora of CPD approaches with the hope of providing a "CPD 101". These reflect on the broader structural bioinformatics and computational biophysics field and include: (1) integration of knowledge-based and energy-based methods, (2) hierarchical designated approach towards local, regional, and global motifs and the integration of high- and low-resolution design schemes that fit each such region, (3) systematic differential approaches towards different protein regions, (4) identification of key hot-spot residues and the relative effect of remote regions, (5) assessment of shape-complementarity, electrostatics and solvation effects, (6) integration of thermal plasticity and functional dynamics, (7) negative design, (8) systematic integration of experimental approaches, (9) objective cross-assessment of methods, and (10) successful ranking of potential designs. Future challenges also include dissemination of CPD software to the general use of life-sciences researchers and the emphasis of success within an in vivo milieu. CPD increases our understanding of protein structure and function and the relationships between the two along with the application of such know-how for the benefit of mankind. Applied aspects range from biological drugs, via healthier and tastier food products to nanotechnology and environmentally friendly enzymes replacing toxic chemicals utilized in the industry.

The Framework of Computational Protein Design

Computational protein design (CPD) has established itself as a leading field in basic and applied science with a strong coupling between the two. Proteins are computationally designed from the level of amino acids to the level of a functional protein complex. Design targets range from increased thermo- (or other) stability to specific requested reactions such as protein-protein binding, enzymatic reactions, or nanotechnology applications. The design scheme may encompass small regions of the proteins or the entire protein. In either case, the design may aim at the side-chains or at the full backbone conformation. Herein, the main framework for the process is outlined highlighting key elements in the CPD iterative cycle. These include the very definition of CPD, the diverse goals of CPD, components of the CPD protocol, methods for searching sequence and structure space, scoring functions, and augmenting the CPD with other optimization tools. Taken together, this chapter aims to introduce the framework of CPD.

Coarse-Grained Simulations of Membrane Insertion and Folding of Small Helical Proteins Using the CABS Model

The CABS coarse-grained model is a well-established tool for modeling globular proteins (predicting their structure, dynamics, and interactions). Here we introduce an extension of the CABS representation and force field (CABS-membrane) to the modeling of the effect of the biological membrane environment on the structure of membrane proteins. We validate the CABS-membrane model in folding simulations of 10 short helical membrane proteins not using any knowledge about their structure. The simulations start from random protein conformations placed outside the membrane environment and allow for full flexibility of the modeled proteins during their spontaneous insertion into the membrane. In the resulting trajectories, we have found models close to the experimental membrane structures. We also attempted to select the correctly folded models using simple filtering followed by structural clustering combined with reconstruction to the all-atom representation and all-atom scoring. The CABS-membrane model is a promising approach for further development toward modeling of large protein-membrane systems.

Predictive energy landscapes for folding membrane protein assemblies

We study the energy landscapes for membrane protein oligomerization using the Associative memory, Water mediated, Structure and Energy Model with an implicit membrane potential (AWSEM-membrane), a coarse-grained molecular dynamics model previously optimized under the assumption that the energy landscapes for folding α-helical membrane protein monomers are funneled once their native topology within the membrane is established. In this study we show that the AWSEM-membrane force field is able to sample near native binding interfaces of several oligomeric systems. By predicting candidate structures using simulated annealing, we further show that degeneracies in predicting structures of membrane protein monomers are generally resolved in the folding of the higher order assemblies as is the case in the assemblies of both nicotinic acetylcholine receptor and V-type Na(+)-ATPase dimers. The physics of the phenomenon resembles domain swapping, which is consistent with the landscape following the principle of minimal frustration. We revisit also the classic Khorana study of the reconstitution of bacteriorhodopsin from its fragments, which is the close analogue of the early Anfinsen experiment on globular proteins. Here, we show the retinal cofactor likely plays a major role in selecting the final functional assembly.

Interplay of Specific Trans- and Juxtamembrane Interfaces in Plexin A3 Dimerization and Signal Transduction

Plexins are transmembrane proteins that serve as guidance receptors during angiogenesis, lymphangiogenesis, neuronal development, and zebrafish fin regeneration, with a putative role in cancer metastasis. Receptor dimerization or clustering, induced by extracellular ligand binding but modulated in part by the plexin transmembrane (TM) and juxtamembrane (JM) domains, is thought to drive plexin activity. Previous studies indicate that isolated plexin TM domains interact through a conserved, small-x3-small packing motif, and the cytosolic JM region interacts through a hydrophobic heptad repeat; however, the roles and interplay of these regions in plexin signal transduction remain unclear. Using an integrated experimental and simulation approach, we find disruption of the small-x3-small motifs in the Danio rerio Plexin A3 TM domain enhances dimerization of the TM-JM domain by enhancing JM-mediated dimerization. Furthermore, mutations of the cytosolic JM heptad repeat that disrupt dimerization do so even in the presence of TM domain mutations. However, mutations to the small-x3-small TM interfaces also disrupt Plexin A3 signaling in a zebrafish axonal guidance assay, indicating the importance of this TM interface in signal transduction. Collectively, our experimental and simulation results demonstrate that multiple TM and JM interfaces exist in the Plexin A3 homodimer, and these interfaces independently regulate dimerization that is important in Plexin A3 signal transduction.

Interplay between hydrophobicity and the positive-inside rule in determining membrane-protein topology

The energetics of membrane-protein interactions determine protein topology and structure: hydrophobicity drives the insertion of helical segments into the membrane, and positive charges orient the protein with respect to the membrane plane according to the positive-inside rule. Until recently, however, quantifying these contributions met with difficulty, precluding systematic analysis of the energetic basis for membrane-protein topology. We recently developed the dsTβL method, which uses deep sequencing and in vitro selection of segments inserted into the bacterial plasma membrane to infer insertion-energy profiles for each amino acid residue across the membrane, and quantified the insertion contribution from hydrophobicity and the positive-inside rule. Here, we present a topology-prediction algorithm called TopGraph, which is based on a sequence search for minimum dsTβL insertion energy. Whereas the average insertion energy assigned by previous experimental scales was positive (unfavorable), the average assigned by TopGraph in a nonredundant set is -6.9 kcal/mol. By quantifying contributions from both hydrophobicity and the positive-inside rule we further find that in about half of large membrane proteins polar segments are inserted into the membrane to position more positive charges in the cytoplasm, suggesting an interplay between these two energy contributions. Because membrane-embedded polar residues are crucial for substrate binding and conformational change, the results implicate the positive-inside rule in determining the architectures of membrane-protein functional sites. This insight may aid structure prediction, engineering, and design of membrane proteins. TopGraph is available online (topgraph.weizmann.ac.il).

Identifying possible sites for antibody neutralization escape: Implications for unique functional properties of the C-terminal tail of Human Immunodeficiency Virus Type 1 gp41

A previous amino acid sequence analyses from our laboratory reported nine potential sites in gp41 glycoprotein of HIV-1 that may contribute to virus escape from antibody neutralization. Besides four sites found outside the membrane of HIV-1 virus, five located in the C-terminal tail of gp41 specifically in the lentivirus lytic peptides motifs (LLPs). To further study the bioinformatical results, the virus infectivity assay and the standard neutralization assay were conducted on conservatively mutated virus. Two sites in the LLP3 domain stood out with the ability to alter the resistance of HIV-1 virus to certain broadly neutralizing antibodies (bNAbs). While the glycoprotein incorporation on the viral membrane and the interaction of the LLP3 domain with the lipid membrane remained unaltered, the increase in neutralization resistance of the mutant virus was associated with the changes on Env conformation. Our findings demonstrate different sensibility of bNAbs to mutations in the C-terminal tail and indicate an unrecognized potential role for even minor sequence variation in the C-terminal tail in modulating the antigenicity of the ectodomain of HIV-1 envelope glycoprotein complex.

Juxta-terminal Helix Unwinding as a Stabilizing Factor to Modulate the Dynamics of Transmembrane Helices

Transmembrane helices of integral membrane proteins often are flanked by interfacial aromatic residues that can serve as anchors to aid the stabilization of a tilted transmembrane orientation. Yet, physical factors that govern the orientation or dynamic averaging of individual transmembrane helices are not well understood and have not been adequately explained. Using solid-state (2) H NMR spectroscopy to examine lipid bilayer-incorporated model peptides of the GWALP23 (acetyl-GGALW(LA)6 LWLAGA-amide) family, we observed substantial unwinding at the terminals of several tilted helices spanning the membranes of DLPC, DMPC, or DOPC lipid bilayers. The fraying of helix ends might be vital for defining the dynamics and orientations of transmembrane helices in lipid bilayer membranes.

Outer Membrane Protein Folding and Topology from a Computational Transfer Free Energy Scale

Knowledge of the transfer free energy of amino acids from aqueous solution to a lipid bilayer is essential for understanding membrane protein folding and for predicting membrane protein structure. Here we report a computational approach that can calculate the folding free energy of the transmembrane region of outer membrane β-barrel proteins (OMPs) by combining an empirical energy function with a reduced discrete state space model. We quantitatively analyzed the transfer free energies of 20 amino acid residues at the center of the lipid bilayer of OmpLA. Our results are in excellent agreement with the experimentally derived hydrophobicity scales. We further exhaustively calculated the transfer free energies of 20 amino acids at all positions in the TM region of OmpLA. We found that the asymmetry of the Gram-negative bacterial outer membrane as well as the TM residues of an OMP determine its functional fold in vivo. Our results suggest that the folding process of an OMP is driven by the lipid-facing residues in its hydrophobic core, and its NC-IN topology is determined by the differential stabilities of OMPs in the asymmetrical outer membrane. The folding free energy is further reduced by lipid A and assisted by general depth-dependent cooperativities that exist between polar and ionizable residues. Moreover, context-dependency of transfer free energies at specific positions in OmpLA predict regions important for protein function as well as structural anomalies. Our computational approach is fast, efficient and applicable to any OMP.

Mutational scanning reveals the determinants of protein insertion and association energetics in the plasma membrane

Insertion of helix-forming segments into the membrane and their association determines the structure, function, and expression levels of all plasma membrane proteins. However, systematic and reliable quantification of membrane-protein energetics has been challenging. We developed a deep mutational scanning method to monitor the effects of hundreds of point mutations on helix insertion and self-association within the bacterial inner membrane. The assay quantifies insertion energetics for all natural amino acids at 27 positions across the membrane, revealing that the hydrophobicity of biological membranes is significantly higher than appreciated. We further quantitate the contributions to membrane-protein insertion from positively charged residues at the cytoplasm-membrane interface and reveal large and unanticipated differences among these residues. Finally, we derive comprehensive mutational landscapes in the membrane domains of Glycophorin A and the ErbB2 oncogene, and find that insertion and self-association are strongly coupled in receptor homodimers.

Membrane positioning for high- and low-resolution protein structures through a binary classification approach

The critical importance of algorithms for orienting proteins in the lipid bilayer stems from the extreme difficulty in obtaining experimental data about the membrane boundaries. Here, we present a computational method for positioning protein structures in the membrane, based on the sole alpha carbon coordinates and, therefore, compatible with both high and low structural resolutions. Our algorithm follows a new and simple approach, by treating the membrane assignment problem as a binary classification. Compared with the state-of-the-art algorithms, our method achieves similar accuracy, while being faster. Finally, our open-source software is also capable of processing coarse-grained models of protein structures.

Membrane Protein Properties Revealed through Data-Rich Electrostatics Calculations

The electrostatic properties of membrane proteins often reveal many of their key biophysical characteristics, such as ion channel selectivity and the stability of charged membrane-spanning segments. The Poisson-Boltzmann (PB) equation is the gold standard for calculating protein electrostatics, and the software APBSmem enables the solution of the PB equation in the presence of a membrane. Here, we describe significant advances to APBSmem, including full automation of system setup, per-residue energy decomposition, incorporation of PDB2PQR, calculation of membrane-induced pKa shifts, calculation of non-polar energies, and command-line scripting for large-scale calculations. We highlight these new features with calculations carried out on a number of membrane proteins, including the recently solved structure of the ion channel TRPV1 and a large survey of 1,614 membrane proteins of known structure. This survey provides a comprehensive list of residues with large electrostatic penalties for being embedded in the membrane, potentially revealing interesting functional information.

De novo design of a transmembrane Zn²⁺-transporting four-helix bundle

The design of functional membrane proteins from first principles represents a grand challenge in chemistry and structural biology. Here, we report the design of a membrane-spanning, four-helical bundle that transports first-row transition metal ions Zn(2+) and Co(2+), but not Ca(2+), across membranes. The conduction path was designed to contain two di-metal binding sites that bind with negative cooperativity. X-ray crystallography and solid-state and solution nuclear magnetic resonance indicate that the overall helical bundle is formed from two tightly interacting pairs of helices, which form individual domains that interact weakly along a more dynamic interface. Vesicle flux experiments show that as Zn(2+) ions diffuse down their concentration gradients, protons are antiported. These experiments illustrate the feasibility of designing membrane proteins with predefined structural and dynamic properties.

Evaluating membrane affinity by integrating protein orientations

Energetic interactions of a protein with lipid bilayers determine its propensity to reside in the membrane. Here we seek to evaluate the membrane interactions for EMAPII, a protein found to be released from the cell by unknown mechanisms, as well as several other proteins. Using a knowledge-based coarse-grained membrane potential, we calculate the free energy profiles for these proteins by integrating out the orientation degrees of freedom. Due to the invariance of energy under in-plane rotations about the membrane normal, the orientation space can be reduced to two dimensions and mapped onto the surface of a unit sphere, thus making visualization, sampling and integration more convenient. The integrated free energy profiles determine the relative probabilities along the membrane normal for the proteins regardless of their orientations, and display distinctive characteristics for membrane proteins and water-soluble proteins. The membrane interactions for EMAPII exhibit typical features of a water-soluble protein, with a high energetic barrier to enter or cross the membrane. Our results thus suggest that similar to the non-classical export of FGF1, the release of EMAPII would involve more complicated mechanisms than simple passive diffusion across the membrane.

Expediting topology data gathering for the TOPDB database

The Topology Data Bank of Transmembrane Proteins (TOPDB, http://topdb.enzim.ttk.mta.hu) contains experimentally determined topology data of transmembrane proteins. Recently, we have updated TOPDB from several sources and utilized a newly developed topology prediction algorithm to determine the most reliable topology using the results of experiments as constraints. In addition to collecting the experimentally determined topology data published in the last couple of years, we gathered topographies defined by the TMDET algorithm using 3D structures from the PDBTM. Results of global topology analysis of various organisms as well as topology data generated by high throughput techniques, like the sequential positions of N- or O-glycosylations were incorporated into the TOPDB database. Moreover, a new algorithm was developed to integrate scattered topology data from various publicly available databases and a new method was introduced to measure the reliability of predicted topologies. We show that reliability values highly correlate with the per protein topology accuracy of the utilized prediction method. Altogether, more than 52 000 new topology data and more than 2600 new transmembrane proteins have been collected since the last public release of the TOPDB database.

Interfacial partitioning of a loop hinge residue contributes to diacylglycerol affinity of conserved region 1 domains

Conventional and novel isoenzymes of PKC are activated by the membrane-embedded second messenger diacylglycerol (DAG) through its interactions with the C1 regulatory domain. The affinity of C1 domains to DAG varies considerably among PKCs. To gain insight into the origin of differential DAG affinities, we conducted high-resolution NMR studies of C1B domain from PKCδ (C1Bδ) and its W252Y variant. The W252Y mutation was previously shown to render C1Bδ less responsive to DAG (Dries, D. R., Gallegos, L. L., and Newton, A. C. (2007) A single residue in the C1 domain sensitizes novel protein kinase C isoforms to cellular diacylglycerol production. J. Biol. Chem. 282, 826-830) and thereby emulate the behavior of C1B domains from conventional PKCs that have a conserved Tyr at the equivalent position. Our data revealed that W252Y mutation did not perturb the conformation of C1Bδ in solution but significantly reduced its propensity to partition into a membrane-mimicking environment in the absence of DAG. Using detergent micelles doped with a paramagnetic lipid, we determined that both the residue identity at position 252 and complexation with diacylglycerol influence the geometry of C1Bδ-micelle interactions. In addition, we identified the C-terminal helix α1 of C1Bδ as an interaction site with the head groups of phosphatidylserine, a known activator of PKCδ. Taken together, our studies (i) reveal the identities of C1Bδ residues involved in interactions with membrane-mimicking environment, DAG, and phosphatidylserine, as well as the affinities associated with each event and (ii) suggest that the initial ligand-independent membrane recruitment of C1B domains, which is greatly facilitated by the interfacial partitioning of Trp-252, is responsible, at least in part, for the differential DAG affinities.