Biology subjects

Eckhard, U.

Publications and source records attributed to Eckhard, U..

5 recordsLinked to original sources

bioRxiv2025

Bile acids target an exposed cavity in the glucocorticoid receptor modulating receptor self-assembly, chromatin binding and transcriptional activity

The glucocorticoid receptor (GR) is an essential transcription factor that controls metabolism and homeostasis. Glucocorticoids (GCs) activate the GR upon occupying the internal ligand-binding pocket (LBP) of its ligand-binding domain (GR-LBD), which has been the focus of most previous structure-function studies. Synthetic GCs such as dexamethasone are widely used to treat inflammatory diseases, but their chronic use results in major side effects, whose molecular underpinnings remain unresolved. Here we present a thorough analysis of the topography of GR-LBD and its ability to bind small-molecule compounds, especially cholesterol derivatives. We show that one important class of steroids, bile acids, bind to previously unidentified and highly conserved, surface-exposed cavities on GR-LBD. We show that bile acids affect GR turnover and self-assembly in living cells, modulating receptor transcriptional activity. These findings reveal a previously unrecognized mechanism of GR regulation, with implications for the design of GCs with novel mechanisms of action. TeaserBile acids modulate the activity of the glucocorticoid receptor upon binding to an exposed allosteric pocket thereby influencing transcriptional regulation and receptor self-assembly in living cells.

molecular biology↗

bioRxiv2024

Comparative proteomics of biofilm development in Pseudoalteromonas tunicata discovers a distinct family of Ca2+-dependent adhesins

The marine bacterium, Pseudoalteromonas tunicata, is a useful model for studying mechanisms of biofilm development due to its ability to colonize and form biofilms on a variety of marine and eukaryotic host-associated surfaces. However, the pathways responsible for P. tunicata biofilm formation are still incompletely understood, in part due to a lack of functional information for a large proportion of its proteome. Here, we used comparative shotgun proteomics to examine P. tunicata biofilm development throughout the planktonic phase to three stages of biofilm development at 24, 48, and 72 h. Proteomic analysis identified 232 proteins that were up-regulated during different stages of biofilm development, including many hypothetical proteins as well as proteins known to be important for P. tunicata biofilm development such as the autocidal enzyme AlpP, violacein proteins, S-layer protein SLR4, and various pili proteins. We further investigated the top identified biofilm-associated protein (Bap), a previously uncharacterized 1600 amino acid protein (EAR30327), which we designated as "BapP". Based on AlphaFold modeling and genomic context analysis, we predicted BapP as a distinct Ca2+-dependent biofilm adhesin. Consistent with this prediction, a {Delta}bapP knockout mutant was defective in forming both pellicle and surface-associated biofilms, which was rescued by re-insertion of bapP into the genome. Similar to mechanisms of RTX adhesins, BapP-mediated biofilm formation was influenced by Ca2+ levels, and BapP is likely exported by a type 1 secretion system. Ultimately, our work not only provides a useful proteomic dataset for studying biofilm development in an ecologically relevant organism, but it also adds to our knowledge of bacterial adhesin diversity, emphasizing Bap-like proteins as widespread determinants of biofilm formation in bacteria.

microbiology↗

bioRxiv2024

Conditional language models enable the efficient design of proficient enzymes

The design of functional enzymes holds promise for transformative solutions across various domains but presents significant challenges. Inspired by the success of language models in generating nature-like proteins, we explored the potential of an enzyme-specific language model in designing catalytically active artificial enzymes. Here, we introduce ZymCTRL (enzyme control), a conditional language model trained on the enzyme sequence space, capable of generating enzymes based on user-defined specifications. Experimental validation at diverse data regimes and for different enzyme families demonstrated ZymCTRLs ability to generate active enzymes across various sequence identity ranges. Specifically, we describe the design of carbonic anhydrases and lactate dehydrogenases in zero-shot, without requiring further training of the model, and showcasing activity at sequence identities below 40% compared to natural proteins. Biophysical analysis confirmed the globularity and well-folded nature of the generated sequences. Furthermore, fine-tuning the model enabled the generation of lactate dehydrogenases outside of natural sequence space but with activity comparable to their natural counterparts. Two of the artificial lactate dehydrogenases were selected for scale production and successfully lyophilised, maintaining activity and demonstrating preliminary conversion in one-pot enzymatic cascades under extreme conditions. Our findings open a new door towards the rapid and cost-effective design of artificial proficient enzymes. The model and dataset are freely available to the community.

bioinformatics↗

bioRxiv2021

De Novo Design of Immunoglobulin-like Domains

Antibodies and antibody derivatives such as nanobodies contain immunoglobulin-like (Ig) {beta}-sandwich scaffolds which anchor the hypervariable antigen-binding loops and constitute the largest growing class of drugs. Current engineering strategies for this class of compounds rely on naturally existing Ig frameworks, which can be hard to modify and have limitations in manufacturability, designability and range of action. Here we develop design rules for the central feature of the Ig fold architecture - the non-local cross-{beta} structure connecting the two {beta}-sheets - and use these to de novo design highly stable seven-stranded Ig domains, confirm their structures through X-ray crystallography, and show they can correctly scaffold functional loops. Our approach opens the door to the design of a new class of antibody-like scaffolds with tailored structures and superior biophysical properties.

biochemistry↗

bioRxiv2020

Structure and mechanism of a phage-encoded SAM lyase revises catalytic function of enzyme family

The first SAM degrading enzyme (SAMase) was discovered in bacteriophage T3, as a counter-defense against the bacterial restriction-modification system, and annotated as an S-adenosyl-L-methionine (SAM) hydrolase forming 5-methyl-thioadenosine (MTA) and L-homoserine. From environmental phages, we recently discovered three SAMases with barely detectable sequence similarity to T3 SAMase and without homology to proteins of known structure. Here, we present the very first phage SAMase structures, in complex with a substrate analogue and the product MTA. The structure shows a trimer of alpha-beta sandwiches similar to the GlnB-like superfamily, with active sites formed at the trimer interfaces. Quantum-mechanical calculations, thin-layer chromatography and NMR spectroscopy demonstrate that this family of enzymes are not hydrolases but lyases forming MTA and L-homoserine lactone in a unimolecular reaction mechanism. Sequence analysis, in vitro and in vivo mutagenesis support that T3 SAMase belongs to the same structural family and utilizes the same reaction mechanism.

biochemistry↗