MemSTATS: A Benchmark Set of Membrane Protein Symmetries and Pseudosymmetries

Tumoral P2Y2 receptor modulates tumor growth and host anti-tumor immune responses in a syngeneic murine model of oral cancer

Head and neck squamous cell carcinomas (HNSCCs) are a heterogenous group of tumors and among the top 10 most common cancers and they arise from the epithelial tissues of the mucosal surfaces of the oral cavity, oropharynx, and larynx. Aberrant purinergic signaling has been associated with various cancer types. Here, we studied the role of the P2Y2 purinergic receptor (P2Y2R) in the context of oral cancer. We utilized bioinformatics analysis of deposited datasets to examine purinome gene expression in HNSCC tumors and cells lines and functionally characterized nucleotide-induced P2 receptor signaling in human FaDu and Cal27 and murine MOC2 oral cancer cell lines. Utilizing tumorigenesis assays with wild-type or P2ry2 knockout MOC2 cells we evaluated the role of P2Y2Rs in tumor growth and the host anti-tumor immune responses. Our data demonstrate that human and murine oral cancer cell lines express numerous P2 receptors, with the P2Y2R being highly expressed. Using syngeneic tumor grafts in wild-type mice, we observed that MOC2 tumors expressing P2Y2R were larger than P2Y2R-/- tumors. Wild-type MOC2 tumors contained a lower population of tumor-infiltrating CD11b+F4/80+ macrophages and CD3+ cells, which were revealed to be CD3+CD4+IFNγ+ T cells, compared to P2Y2R-/- tumors. These results were mirrored when utilizing P2Y2R-/- mice, indicating that the changes in MOC2 tumor growth and to the host anti-tumor immune response were independent of host derived P2Y2Rs. Results suggest that targeted suppression of the P2Y2R in HNSCC cells in vivo, rather than systemic P2Y2R antagonism, may be a more effective treatment strategy for HNSCCs.

Peripheral positions encode transport specificity in the small multidrug resistance exporters

In secondary active transporters, a relatively limited set of protein folds have evolved diverse solute transport functions. Because of the conformational changes inherent to transport, altering substrate specificity typically involves remodeling the entire structural landscape, limiting our understanding of how novel substrate specificities evolve. In the current work, we examine a structurally minimalist family of model transport proteins, the small multidrug resistance (SMR) transporters, to understand the molecular basis for the emergence of a novel substrate specificity. We engineer a selective SMR protein to promiscuously export quaternary ammonium antiseptics, similar to the activity of a clade of multidrug exporters in this family. Using combinatorial mutagenesis and deep sequencing, we identify the necessary and sufficient molecular determinants of this engineered activity. Using X-ray crystallography, solid-supported membrane electrophysiology, binding assays, and a proteoliposome-based quaternary ammonium antiseptic transport assay that we developed, we dissect the mechanistic contributions of these residues to substrate polyspecificity. We find that substrate preference changes not through modification of the residues that directly interact with the substrate but through mutations peripheral to the binding pocket. Our work provides molecular insight into substrate promiscuity among the SMRs and can be applied to understand multidrug export and the evolution of novel transport functions more generally.

EncoMPASS: An encyclopedia of membrane proteins analyzed by structure and symmetry

Protein structure determination and prediction, active site detection, and protein sequence alignment techniques all exploit information about protein structure and structural relationships. For membrane proteins, however, there is limited agreement among available online tools for highlighting and mapping such structural similarities. Moreover, no available resource provides a systematic overview of quaternary and internal symmetries, and their orientation relative to the membrane, despite the fact that these properties can provide key insights into membrane protein function and evolution. Here, we describe the Encyclopedia of Membrane Proteins Analyzed by Structure and Symmetry (EncoMPASS), a database for relating integral membrane proteins of known structure from the points of view of sequence, structure, and symmetry. EncoMPASS is accessible through a web interface, and its contents can be easily downloaded. This allows the user not only to focus on specific proteins, but also to study general properties of the structure and evolution of membrane proteins.

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.

Diverse Scientific Benchmarks for Implicit Membrane Energy Functions

Energy functions are fundamental to biomolecular modeling. Their success depends on robust physical formalisms, efficient optimization, and high-resolution data for training and validation. Over the past 20 years, progress in each area has advanced soluble protein energy functions. Yet, energy functions for membrane proteins lag behind due to sparse and low-quality data, leading to overfit tools. To overcome this challenge, we assembled a suite of 12 tests on independent data sets varying in size, diversity, and resolution. The tests probe an energy function's ability to capture membrane protein orientation, stability, sequence, and structure. Here, we present the tests and use the franklin2019 energy function to demonstrate them. We then identify areas for energy function improvement and discuss potential future integration with machine-learning-based optimization methods. The tests are available through the Rosetta Benchmark Server (https://benchmark.graylab.jhu.edu/) and GitHub (https://github.com/rfalford12/Implicit-Membrane-Energy-Function-Benchmark).

Membrane transporter dimerization driven by differential lipid solvation energetics of dissociated and associated states

Over two-thirds of integral membrane proteins of known structure assemble into oligomers. Yet, the forces that drive the association of these proteins remain to be delineated, as the lipid bilayer is a solvent environment that is both structurally and chemically complex. In this study, we reveal how the lipid solvent defines the dimerization equilibrium of the CLC-ec1 Cl^-/H⁺ antiporter. Integrating experimental and computational approaches, we show that monomers associate to avoid a thinned-membrane defect formed by hydrophobic mismatch at their exposed dimerization interfaces. In this defect, lipids are strongly tilted and less densely packed than in the bulk, with a larger degree of entanglement between opposing leaflets and greater water penetration into the bilayer interior. Dimerization restores the membrane to a near-native state and therefore, appears to be driven by the larger free-energy cost of lipid solvation of the dissociated protomers. Supporting this theory, we demonstrate that addition of short-chain lipids strongly shifts the dimerization equilibrium toward the monomeric state, and show that the cause of this effect is that these lipids preferentially solvate the defect. Importantly, we show that this shift requires only minimal quantities of short-chain lipids, with no measurable impact on either the macroscopic physical state of the membrane or the protein's biological function. Based on these observations, we posit that free-energy differentials for local lipid solvation define membrane-protein association equilibria. With this, we argue that preferential lipid solvation is a plausible cellular mechanism for lipid regulation of oligomerization processes, as it can occur at low concentrations and does not require global changes in membrane properties.

A cell’s outer membrane is made of molecules called lipids, which band together to form a flexible thin film, just two molecules thick. This membrane is dotted with proteins that transport materials in to and out of cells. Most of these membrane proteins join with other proteins to form structures known as oligomers. Except, how membrane-bound proteins assemble into oligomers – the physical forces driving these molecules to take shape – remains unclear.

This is partly because the structural, physical and chemical properties of fat-like lipid membranes are radically different to the cell’s watery interior. Consequently, the conditions under which membrane oligomers form are distinct from those surrounding proteins inside cells. Membrane proteins are also more difficult to study and characterize than water-soluble proteins inside the cell, and yet many therapeutic drugs such as antibiotics specifically target membrane proteins. Overall, our understanding of how the unique properties of lipid membranes affect the formation of protein structures embedded within, is lacking and warrants further investigation.

Now, Chadda, Bernhardt et al. focused on one membrane protein, known as CLC, which tends to exist in pairs – or dimers. To understand why these proteins form dimers (a process called dimerization) Chadda, Bernhardt et al. first used computer simulations, and then validated the findings in experimental tests.

These complementary approaches demonstrated that the main reason CLC proteins ‘dimerize’ lies in their interaction with the lipid membrane, and not the attraction of one protein to its partner. When CLC proteins are on their own, they deform the surrounding membrane and create structural defects that put the membrane under strain. But when two CLC proteins join as a dimer, this membrane strain disappears – making dimerization the more stable and energetically favorable option.

Chadda, Bernhardt et al. also showed that with the addition of a few certain lipids, specifically smaller lipids, cell membranes become more tolerant of protein-induced structural changes. This might explain how cells could use various lipids to fine-tune the activity of membrane proteins by controlling how oligomers form. However, the theory needs to be examined further. Altogether, this work has provided fundamental insights into the physical forces shaping membrane-bound proteins, relevant to researchers studying cell biology and pharmacology alike.

Altering CLC stoichiometry by reducing non-polar side-chains at the dimerization interface

CLC-ec1 is a Cl^-/H⁺ antiporter that forms stable homodimers in lipid bilayers, with a free energy of -10.9 kcal/mol in 2:1 POPE/POPG lipid bilayers. The dimerization interface is formed by four transmembrane helices: H, I, P and Q, that are lined by non-polar side-chains that come in close contact, yet it is unclear as to whether their interactions drive dimerization. To investigate whether non-polar side-chains are required for dimer assembly, we designed a series of constructs where side-chain packing in the dimer state is significantly reduced by making 4-5 alanine substitutions along each helix (H-ala, I-ala, P-ala, Q-ala). All constructs are functional and three purify as stable dimers in detergent micelles despite the removal of significant side-chain interactions. On the other hand, H-ala shows the unique behavior of purifying as a mixture of monomers and dimers, followed by a rapid and complete conversion to monomers. In lipid bilayers, all four constructs are monomeric as examined by single-molecule photobleaching analysis. Further study of the H-helix shows that the single mutation L194A is sufficient to yield monomeric CLC-ec1 in detergent micelles and lipid bilayers. X-ray crystal structures of L194A reveal the protein re-assembles to form dimers, with a structure that is identical to wild-type. Altogether, these results demonstrate that non-polar membrane embedded side-chains play an important role in defining dimer stability, but the stoichiometry is highly contextual to the solvent environment. Furthermore, we discovered that L194 is a molecular hot-spot for defining dimerization of CLC-ec1.

RepeatsDB in 2021: improved data and extended classification for protein tandem repeat structures

The RepeatsDB database (URL: https://repeatsdb.org/) provides annotations and classification for protein tandem repeat structures from the Protein Data Bank (PDB). Protein tandem repeats are ubiquitous in all branches of the tree of life. The accumulation of solved repeat structures provides new possibilities for classification and detection, but also increasing the need for annotation. Here we present RepeatsDB 3.0, which addresses these challenges and presents an extended classification scheme. The major conceptual change compared to the previous version is the hierarchical classification combining top levels based solely on structural similarity (Class > Topology > Fold) with two new levels (Clan > Family) requiring sequence similarity and describing repeat motifs in collaboration with Pfam. Data growth has been addressed with improved mechanisms for browsing the classification hierarchy. A new UniProt-centric view unifies the increasingly frequent annotation of structures from identical or similar sequences. This update of RepeatsDB aligns with our commitment to develop a resource that extracts, organizes and distributes specialized information on tandem repeat protein structures.