Biology subjects

Hegedus, T.

Publications and source records attributed to Hegedus, T..

12 recordsLinked to original sources

bioRxiv2026

SERCA is a host target of the SARS-CoV-2 envelope protein linking calcium homeostasis to autophagy

The SARS-CoV-2 envelope (E) protein is a virulence factor that remodels host endomembranes, but mechanisms remain incompletely understood. We recently demonstrated that E protein interacts with and inhibits the sarco/endoplasmic reticulum Ca2-ATPase (SERCA), disrupting ER calcium homeostasis. Here, we investigated how this perturbation affects autophagy-associated membrane organization. E protein expression induced lipidated LC3 accumulation and enlarged p62-positive structures, consistent with dysregulated autophagic turnover. Although E protein partially colocalized with LC3 and p62, enlarged p62-positive structures were also observed in cells retaining the reticular ER distribution of E protein, indicating that their formation does not require association with E protein or ER reorganization. E protein also increased the association of p62-positive structures with lysosomes without altering lysosome abundance. Pharmacological SERCA activation attenuated E protein-induced remodeling of autophagy-associated structures, demonstrating that SERCA inhibition contributes to these alterations. Together, our findings establish SERCA-dependent ER calcium homeostasis as a host pathway linking E protein expression to remodeling of autophagy-associated membrane compartments, providing a mechanistic framework for how the SARS-CoV-2 E protein promotes ER membrane remodeling associated with coronavirus replication.

cell biology↗

bioRxiv2026

The FKBP42, TWISTED DWARF1, prioritizes auxin over brassinosteroidtransport by peptidyl-prolyl cis-trans isomerization of ABCB1

The ATP-binding cassette (ABC) transporter ABCB1 transports both auxins and the brassinosteroid brassinolide (BL). ABCB1-mediated auxin (IAA) transport depends on interaction with the FKBP42 protein TWISTED DWARF1 (TWD1), yet the mechanism underlying substrate selectivity remains unclear. Here, we confirm dual IAA and BL transport by ABCB1 and show that the two substrates compete for ABCB1-mediated transport. We demonstrate that a conserved proline residue (P1008) is required for IAA, but not BL, transport. Furthermore, we identify TWD1 as a calmodulin-activated peptidyl-prolyl cis-trans isomerase (PPIase) that selectively enhances IAA, but not BL, transport through isomerization of the E1007-P1008 peptide bond. Loss of TWD1 PPIase activity abolishes ABCB1-mediated IAA export without affecting BL transport, revealing a regulatory mechanism that prioritizes auxin over brassinosteroid transport. Cryo-EM, molecular docking, and molecular dynamics simulations of wild-type ABCB1 and the ABCB1P1008G variant suggest that the P1008 loop mediates long-range communication between the nucleotide-binding domain surface and the substrate-binding pocket, thereby providing a structural mechanism by which TWD1 modulates substrate specificity. In summary, our findings establish the structural basis of ABCB1 substrate selectivity and uncover a post-translational mechanism that selectively regulates auxin transport while preserving brassinosteroid transport. One Sentence SummaryTWD1 prioritizes ABCB1-mediated auxin over brassinosteroid transport

biochemistry↗

bioRxiv2025

pLM-SAV: A Δ-Embedding Approach for Predicting Pathogenic Single Amino Acid Variants

Predicting whether single amino acid variants (SAVs) in proteins lead to pathogenic outcomes is a critical challenge in molecular biology and precision medicine. Experimental determination of all possible mutation effects is infeasible, and while state-of-the-art tools such as AlphaMissense show promise, their diagnostic performance is insufficient and they are often difficult to run locally. We developed pLM-SAV, a simple yet effective predictor that leverages protein language models (pLMs). {Delta}-embeddings, computed as the difference between wild-type and mutant sequence embeddings, are used as input for a convolutional neural network. To prevent data leakage, we trained our model on a well-characterized, labeled set of Eff10k and evaluated it on a non-homologous subset of ClinVar data. Our results demonstrate that this approach performs exceptionally well on the Eff10k test folds and reasonably on ClinVar test sets. Notably, pLM-SAV excels in resolving ambiguous predictions by AlphaMissense. We also found that an ensemble method, REVEL, outperforms both AlphaMissense and pLM-SAV, thus, we integrated these REVEL- enhanced predictions into our widely used AlphaMissense web application. Our results demonstrate that an SAV predictor trained on labeled data can achieve high predictive performance. Unlike previous methods such as VESPA, pLM-SAV uses no handcrafted features or substitution matrices, relying solely on pLM-derived representations. We anticipate that incorporating delta-embeddings into other mutation effect predictors or mutant structure prediction methods will further enhance their accuracy and utility in diverse biological contexts. Availability and ImplementationFreely available at https://doi.org/10.5281/zenodo.15502498 and https://alphamissense.hegelab.org.

bioinformatics↗

bioRxiv2024

A key residue of the extracellular gate provides quality control contributing to ABCG substrate specificity

For G-type ATP-binding cassette (ABC) transporters, a hydrophobic "di-leucine motif" as part of a hydrophobic extracellular gate has been described to separate a large substrate-binding cavity from a smaller upper cavity and proposed to act as a valve controlling drug extrusion. Here, we show that an L704F mutation in the hydrophobic extracellular gate of Arabidopsis ABCG36/PDR8/PEN3 uncouples the export of the auxin precursor indole-3-butyric acid (IBA) from that of the defense compound camalexin (CLX). Molecular dynamics simulations reveal an increase in free energy and pulling forces for CLX at both the entrance and exit sites of ABCG36L704F, respectively, providing a mechanistic rationale for the transport discrimination of CLX. Mutagenesis of L704 to tyrosine allows export of structurally related non-ABCG36 substrates, indole-3-acetic acid (IAA) and indole, suggesting an allosteric communication between the extracellular gate and the central substrate binding pocket. In summary, our work supports the conclusion that L704 is a key residue of the extracellular gate that provides a final quality control contributing to ABCG substrate specificity.

biochemistry↗

bioRxiv2023

Lightway access to AlphaMissense data that demonstrates a balanced performance of this missense mutation predictor

Single amino acid substitutions can profoundly affect protein folding, dynamics, and function, leading to potential pathological consequences. The ability to discern between benign and pathogenic substitutions is pivotal for therapeutic interventions and research directions. Given the limitations in experimental examination of these variants, AlphaMissense has emerged as a promising predictor of the pathogenicity of single nucleotide polymorphism variants. In our study, we assessed the efficacy of AlphaMissense across several protein groups, such as mitochondrial, housekeeping, transmembrane proteins, and specific proteins like CFTR, using ClinVar data for validation. Our comprehensive evaluation showed that AlphaMissense delivers outstanding performance, with MCC scores predominantly between 0.6 and 0.74. We observed low performance on the CFTR and disordered, membrane-interacting MemMoRF datasets. However, an enhanced performance with CFTR was shown when benchmarked against the CFTR2 database. Our results also emphasize that quality of AlphaFolds predictions can seriously influence AlphaMissense predictions. Most importantly, AlphaMissenses consistent capability in predicting pathogenicity across diverse protein groups, spanning both transmembrane and soluble domains was found. Moreover, the prediction of likely-pathogenic labels for IBS and CFTR coupling helix residues emphasizes AlphaMissenses potential as a tool for pinpointing functionally significant sites. Additionally, to make AlphaMissense predictions more accessible, we have introduced a user-friendly web resource (https://alphamissense.hegelab.org) to enhance the utility of this valuable tool. Our insights into AlphaMissenses capability, along with this online resource, underscore its potential to significantly aid both research and clinical applications.

bioinformatics↗

bioRxiv2023

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

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

biophysics↗

bioRxiv2023

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 confirmed that a direct interaction between E protein and SERCA2b results in a decrease in SERCA-mediated ER Ca2+ reload. Structural modeling and molecular dynamics 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.

cell biology↗

bioRxiv2022

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 modelling 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.

bioinformatics↗

bioRxiv2022

Comprehensive collection and prediction of ABC transmembrane protein structures in the AI era of structural biology

The number of unique transmembrane (TM) protein structures doubled in the last four years that can be attributed to the revolution of cryo-electron microscopy. In addition, AlphaFold2 (AF2) also provided a large number of predicted structures with high quality. However, if a specific protein family is the subject of a study, collecting the structures of the family members is highly challenging in spite of existing general and protein domain-specific databases. Here, we demonstrate this and assess the applicability and usability of automatic collection and presentation of protein structures via the ABC protein superfamily. Our pipeline identifies and classifies transmembrane ABC protein structures using PFAM search and also aims to determine their conformational states based on special geometric measures, conftors. Since the AlphaFold database contains structure predictions only for single polypeptide chains, we performed AF2-Multimer predictions for human ABC half transporters functioning as dimers. Our AF2 predictions warn of possibly ambiguous interpretation of some biochemical data regarding interaction partners and call for further experiments and experimental structure determination. We made our predicted ABC protein structures available through a web application, and we joined the 3D-Beacons Network to reach the broader scientific community through platforms such as PDBe-KB.

bioinformatics↗

bioRxiv2021

AlphaFold2 transmembrane protein structure prediction shines

Transmembrane (TM) proteins are major drug targets, indicated by the high percentage of prescription drugs acting on them. For a rational drug design and an understanding of mutational effects on protein function, structural data at atomic resolution are required. However, hydrophobic TM proteins often resist experimental structure determination and in spite of the increasing number of cryo-EM structures, the available TM folds are still limited in the Protein Data Bank. Recently, the DeepMinds AlphaFold2 machine learning method greatly expanded the structural coverage of sequences, with high accuracy. Since the employed algorithm did not take specific properties of TM proteins into account, the validity of the generated TM structures should be assessed. Therefore, we investigated the quality of structures at genome scales, at the level of ABC protein superfamily folds, and also in specific individual cases. We tested template-free structure prediction also with a new TM fold, dimer modeling, and stability in molecular dynamics simulations. Our results strongly suggest that AlphaFold2 performs astoundingly well in the case of TM proteins and that its neural network is not overfitted. We conclude that a careful application of its structural models will advance TM protein associated studies at an unexpected level.

bioinformatics↗

bioRxiv2021

Nanomechanics combined with HDX reveal allosteric drug binding sites of CFTR NBD1

Cystic fibrosis is most frequently caused by the deletion of F508 ({Delta}F508) in CFTRs nucleotide binding domain 1 (NBD1), compromising CFTR folding, stability and domain assembly. The limitation of developing a successful therapy is due to the lack of molecules that synergistically facilitate folding by targeting distinct structural defects of {Delta}F508-CFTR. To improve drug efficacy by targeting the {Delta}F508-NBD1 folding and stability, and to study potential {Delta}F508-NBD1 allosteric corrector binding sites at the atomic level, we combined molecular dynamics (MD) simulations, atomic force spectroscopy (AFM) and hydrogen-deuterium exchange (HDX) experiments. These methods allowed us to describe unfolding intermediates and forces acting during NBD1 mechanical unfolding and to elucidate the stabilization mechanism of {Delta}F508-NBD1 by 5-bromoindole-3-acetic acid (BIA). An NBD1 region, including the -subdomain, was identified as a potentially important participant of the first folding steps, characterized by non-native interactions of F508, thus destabilized in the deletion mutant. The instability was counteracted by the low-potency corrector BIA, increasing the mechanical resistance of the {Delta}F508-NBD1 -subdomain, which was confirmed as a binding site by computational modeling and HDX experiments. Our results underline the complementarity of computational and experimental methods and provide a possible strategy to improve folding correctors.

biophysics↗

bioRxiv2020

Mechanism of non-blocking inhibition of sodium channels revealed by conformation-selective photolabeling

Sodium channel inhibitor drugs can exert their effect by either blocking, or modulating the channel. The extent of modulation versus channel block is crucial regarding the therapeutic potential of drug candidates. Modulation can be selective for pathological hyperactivity, while channel block affects vital physiological function as much as pathological activity. Previous results indicated that riluzole, a drug with neuroprotective and antiepileptic effects, may have a unique mechanism of action, where modulation is predominant, and channel block is negligible. We studied the effects of riluzole on rNaV1.4 channels expressed in HEK cells. We observed that inhibition by riluzole disappeared and reappeared at a rate that could not be explained by association/dissociation dynamics. In order to verify the mechanism of non-blocking modulation, we synchronized photolabeling with the voltage clamp protocol of patch-clamp experiments. Using this method, we could bind a photoreactive riluzole analog covalently to specific conformations of the channel. Photolabeling was ineffective at resting conformation, but effective at inactivated conformation, as judged from persisting modulated gating after removal of unbound photoactive drug from the solution. Mutation of the key residue of the local anesthetic binding site (F1579A) did not fully prevent ligand binding and inhibition, however, it eliminated most of the modulation caused by ligand binding. Our results indicate that riluzole binds with highest affinity to the local anesthetic binding site, which transmits inhibition by the unique non-blocking modulation mechanism. Our results also suggest the existence of one or more additional binding sites, with lower affinity, and different inhibition mechanism.

pharmacology and toxicology↗