Comprehensive Collection and Prediction of ABC Transmembrane Protein Structures in the AI Era of Structural Biology

TMVisDB: Annotation and 3D-visualization of Transmembrane Proteins

Since the rise of cellular life, transmembrane proteins (TMPs) have been crucial to various cellular processes through their central role as gates and gatekeepers. Despite their importance, experimental high-resolution structures for TMPs remain underrepresented due to experimental challenges. Given its performance leap, structure predictions have begun to close the gap. However, identifying the membrane regions and topology in three-dimensional structure files on a large scale still requires additional in silico predictions. Here, we introduce TMVisDB to sieve through millions of predicted structures for TMPs. This resource enables both browsing through 46 million predicted TMPs and visualizing them along with their topological annotations without having to tap into costly predictions of the AlphaFold3-style. TMVisDB joins AlphaFoldDB structure predictions and transmembrane topology predictions from the protein language model (pLM) based method TMbed. We showcase the utility of TMVisDB for the analysis of proteins through two use cases, namely the B-lymphocyte antigen CD20 (Homo sapiens) and the cellulose synthase (Novosphingobium sp. P6W). We demonstrate the value of TMVisDB for large-scale analyses through findings pertaining to all TMPs predicted for the human proteome. TMVisDB is freely available at https://tmvisdb.rostlab.org.

Challenges in bridging the gap between protein structure prediction and functional interpretation

The rapid evolution of protein structure prediction tools has significantly broadened access to protein structural data. Although predicted structure models have the potential to accelerate and impact fundamental and translational research significantly, it is essential to note that they are not validated and cannot be considered the ground truth. Thus, challenges persist, particularly in capturing protein dynamics, predicting multi-chain structures, interpreting protein function, and assessing model quality. Interdisciplinary collaborations are crucial to overcoming these obstacles. Databases like the AlphaFold Protein Structure Database, the ESM Metagenomic Atlas, and initiatives like the 3D-Beacons Network provide FAIR access to these data, enabling their interpretation and application across a broader scientific community. Whilst substantial advancements have been made in protein structure prediction, further progress is required to address the remaining challenges. Developing training materials, nurturing collaborations, and ensuring open data sharing will be paramount in this pursuit. The continued evolution of these tools and methodologies will deepen our understanding of protein function and accelerate disease pathogenesis and drug development discoveries.

Genome wide structural prediction of ABC transporter systems in Bacillus subtilis

ABC transporters are a diverse superfamily of membrane protein complexes that utilize the binding/hydrolysis of ATP to power substrate movement across biological membranes or perform mechanical work. In bacteria, these transporters play essential roles in biochemical processes ranging from nutrient uptake and protein secretion to antibiotic resistance and cell-wall remodeling. Analysis of the complete genome sequence of the Gram-positive organism Bacillus subtilis has previously revealed that ABC transporters comprise the largest family of proteins across the entire genome. Despite the widespread presence of these transporters in B. subtilis, relatively few experimental structures of ABC transporters from this organism have been determined. Here we leverage the power of AlphaFold-Multimer to predict the 3-dimensional structure of all potential ABC transporter complexes that have been identified from bioinformatic analysis of the B. subtilis genome. We further classify the ABC transporters into discrete classes based on their predicted architecture and the presence or absence of distinct protein domains. The 3-dimensional structure predictions presented here serve as a template to understand the structural and functional diversity of ABC transporter systems in B. subtilis and illuminate areas in which further experimental structural validation is warranted.

SARS-CoV-2 envelope protein alters calcium signaling via SERCA interactions

The clinical management of severe COVID-19 cases is not yet well resolved. Therefore, it is important to identify and characterize cell signaling pathways involved in virus pathogenesis that can be targeted therapeutically. Envelope (E) protein is a structural protein of the virus, which is known to be highly expressed in the infected host cell and is a key virulence factor; however, its role is poorly characterized. The E protein is a single-pass transmembrane protein that can assemble into a pentamer forming a viroporin, perturbing Ca2+ homeostasis. Because it is structurally similar to regulins such as, for example, phospholamban, that regulate the sarco/endoplasmic reticulum calcium ATPases (SERCA), we investigated whether the SARS-CoV-2 E protein affects the SERCA system as an exoregulin. Using FRET experiments we demonstrate that E protein can form oligomers with regulins, and thus can alter the monomer/multimer regulin ratio and consequently influence their interactions with SERCAs. We also confirm that a direct interaction between E protein and SERCA2b results in a decrease in SERCA-mediated ER Ca2+ reload. Structural modeling of the complexes indicates an overlapping interaction site for E protein and endogenous regulins. Our results reveal novel links in the host-virus interaction network that play an important role in viral pathogenesis and may provide a new therapeutic target for managing severe inflammatory responses induced by SARS-CoV-2.

A dimeric holin/antiholin complex controls lysis by phage T4

Lytic phages control the timepoint of host cell lysis by timing the holin-mediated release of cell wall-degrading endolysins. In phage T4, the antiholin RI inhibits the holin T, thereby preventing the early release of the T4 endolysin and lysis. The antiholin achieves lysis inhibition (LIN) in response to phage superinfections, thereby increasing the chance for lysis in an environment with a lower phage concentration. The holin T consists of a small N-terminal cytoplasmic domain, a transmembrane helix, and a periplasmic C-terminal domain. The antiholin is targeted to the periplasm by a cleavable signal peptide. Recently, the periplasmic soluble domains of the holin and the antiholin were found to form T2/RI2 tetramers in crystals. To investigate the functional relevance of this complex, we reconstituted LIN in a phage-free system, using only RI, T, and endolysin, and combined targeted mutagenesis with functional analyses. Inactivation of the RI signal peptide cleavage site did not abolish LIN, indicating that RI can function in a membrane-bound state, which argued against the tetramer. This led to analyses showing that only one of the two T/RI interfaces in the tetramer is physiologically relevant, which is also the only interaction site predicted by AlphaFold2. Some holin mutations at this interaction site prevented lysis, suggesting that the RI interaction likely acts by blocking the holin oligomerization required for hole formation. We conclude that LIN is mediated by a dimeric T/RI complex that, unlike the tetramer, can be easily formed when both partners are membrane-anchored.

Explaining Conformational Diversity in Protein Families through Molecular Motions

Proteins play a central role in biological processes, and understanding their conformational variability is crucial for unraveling their functional mechanisms. Recent advancements in high-throughput technologies have enhanced our knowledge of protein structures, yet predicting their multiple conformational states and motions remains challenging. This study introduces Dimensionality Analysis for protein Conformational Exploration (DANCE) for a systematic and comprehensive description of protein families conformational variability. DANCE accommodates both experimental and predicted structures. It is suitable for analysing anything from single proteins to superfamilies. Employing it, we clustered all experimentally resolved protein structures available in the Protein Data Bank into conformational collections and characterized them as sets of linear motions. The resource facilitates access and exploitation of the multiple states adopted by a protein and its homologs. Beyond descriptive analysis, we assessed classical dimensionality reduction techniques for sampling unseen states on a representative benchmark. This work improves our understanding of how proteins deform to perform their functions and opens ways to a standardised evaluation of methods designed to sample and generate protein conformations.

Folding correctors can restore CFTR posttranslational folding landscape by allosteric domain-domain coupling

The folding/misfolding and pharmacological rescue of multidomain ATP-binding cassette (ABC) C-subfamily transporters, essential for organismal health, remain incompletely understood. The ABCC transporters core consists of two nucleotide binding domains (NBD1,2) and transmembrane domains (TMD1,2). Using molecular dynamic simulations, biochemical and hydrogen deuterium exchange approaches, we show that the mutational uncoupling or stabilization of NBD1-TMD1/2 interfaces can compromise or facilitate the CFTR(ABCC7)-, MRP1(ABCC1)-, and ABCC6-transporters posttranslational coupled domain-folding in the endoplasmic reticulum. Allosteric or orthosteric binding of VX-809 and/or VX-445 folding correctors to TMD1/2 can rescue kinetically trapped CFTR posttranslational folding intermediates of cystic fibrosis (CF) mutants of NBD1 or TMD1 by global rewiring inter-domain allosteric-networks. We propose that dynamic allosteric domain-domain communications not only regulate ABCC-transporters function but are indispensable to tune the folding landscape of their posttranslational intermediates. These allosteric networks can be compromised by CF-mutations, and reinstated by correctors, offering a framework for mechanistic understanding of ABCC-transporters (mis)folding.

Folding correctors can restore CFTR posttranslational folding landscape by allosteric domain-domain coupling

The folding/misfolding and pharmacological rescue of multidomain ATP-binding cassette (ABC) C-subfamily transporters, essential for organismal health, remain incompletely understood. The ABCC transporters core consists of two nucleotide binding domains (NBD1,2) and transmembrane domains (TMD1,2). Using molecular dynamic simulations, biochemical and hydrogen deuterium exchange approaches, we show that the mutational uncoupling or stabilization of NBD1-TMD1/2 interfaces can compromise or facilitate the CFTR(ABCC7)-, MRP1(ABCC1)-, and ABCC6-transporters posttranslational coupled domain-folding in the endoplasmic reticulum. Allosteric or orthosteric binding of VX-809 and/or VX-445 folding correctors to TMD1/2 can rescue kinetically trapped CFTR post-translational folding intermediates of cystic fibrosis (CF) mutants of NBD1 or TMD1 by global rewiring inter-domain allosteric-networks. We propose that dynamic allosteric domain-domain communications not only regulate ABCC-transporters function but are indispensable to tune the folding landscape of their post-translational intermediates. These allosteric networks can be compromised by CF-mutations, and reinstated by correctors, offering a framework for mechanistic understanding of ABCC-transporters (mis)folding.

One-Sentence Summary

Allosteric interdomain communication and its modulation are critical determinants of ABCC-transporters post-translational conformational biogenesis, misfolding, and pharmacological rescue.

An agnostic analysis of the human AlphaFold2 proteome using local protein conformations

Knowledge of the 3D structure of proteins is a valuable asset for understanding their precise biological mechanisms. However, the cost of production of 3D structures and experimental difficulties limit their obtaining. The proposal of 3D structural models is consequently an appealing alternative. The release of the AlphaFold Deep Learning approach has revolutionized the field. The recent near-complete human proteome proposal makes it possible to analyse large amounts of data and evaluate the results of the approach in greater depth. The 3D human proteome was thus analysed in light of the classic secondary structures, and many less-used protein local conformations (PolyProline II helices, type of γ-turns, of β-turns and of β-bulges, curvature of the helices, and a structural alphabet). Without questioning the global quality of the approach, this analysis highlights certain local conformations, which maybe poorly predicted and they could therefore be better addressed.

3D-Beacons: decreasing the gap between protein sequences and structures through a federated network of protein structure data resources

While scientists can often infer the biological function of proteins from their 3-dimensional quaternary structures, the gap between the number of known protein sequences and their experimentally determined structures keeps increasing. A potential solution to this problem is presented by ever more sophisticated computational protein modeling approaches. While often powerful on their own, most methods have strengths and weaknesses. Therefore, it benefits researchers to examine models from various model providers and perform comparative analysis to identify what models can best address their specific use cases. To make data from a large array of model providers more easily accessible to the broader scientific community, we established 3D-Beacons, a collaborative initiative to create a federated network with unified data access mechanisms. The 3D-Beacons Network allows researchers to collate coordinate files and metadata for experimentally determined and theoretical protein models from state-of-the-art and specialist model providers and also from the Protein Data Bank.

The Reentry Helix Is Potentially Involved in Cholesterol Sensing of the ABCG1 Transporter Protein

ABCG1 has been proposed to play a role in HDL-dependent cellular sterol regulation; however, details of the interaction between the transporter and its potential sterol substrates have not been revealed. In the present work, we explored the effect of numerous sterol compounds on the two isoforms of ABCG1 and ABCG4 and made efforts to identify the molecular motifs in ABCG1 that are involved in the interaction with cholesterol. The functional readouts used include ABCG1-mediated ATPase activity and ABCG1-induced apoptosis. We found that both ABCG1 isoforms and ABCG4 interact with several sterol compounds; however, they have selective sensitivities to sterols. Mutational analysis of potential cholesterol-interacting motifs in ABCG1 revealed altered ABCG1 functions when F571, L626, or Y586 were mutated. L430A and Y660A substitutions had no functional consequence, whereas Y655A completely abolished the ABCG1-mediated functions. Detailed structural analysis of ABCG1 demonstrated that the mutations modulating ABCG1 functions are positioned either in the so-called reentry helix (G-loop/TM5b,c) (Y586) or in its close proximity (F571 and L626). Cholesterol molecules resolved in the structure of ABCG1 are also located close to Y586. Based on the experimental observations and structural considerations, we propose an essential role for the reentry helix in cholesterol sensing in ABCG1.

AI-Based Protein Interaction Screening and Identification (AISID)

In this study, we presented an AISID method extending AlphaFold-Multimer's success in structure prediction towards identifying specific protein interactions with an optimized AISIDscore. The method was tested to identify the binding proteins in 18 human TNFSF (Tumor Necrosis Factor superfamily) members for each of 27 human TNFRSF (TNF receptor superfamily) members. For each TNFRSF member, we ranked the AISIDscore among the 18 TNFSF members. The correct pairing resulted in the highest AISIDscore for 13 out of 24 TNFRSF members which have known interactions with TNFSF members. Out of the 33 correct pairing between TNFSF and TNFRSF members, 28 pairs could be found in the top five (including 25 pairs in the top three) seats in the AISIDscore ranking. Surprisingly, the specific interactions between TNFSF10 (TNF-related apoptosis-inducing ligand, TRAIL) and its decoy receptors DcR1 and DcR2 gave the highest AISIDscore in the list, while the structures of DcR1 and DcR2 are unknown. The data strongly suggests that AlphaFold-Multimer might be a useful computational screening tool to find novel specific protein bindings. This AISID method may have broad applications in protein biochemistry, extending the application of AlphaFold far beyond structure predictions.