Structure and function of the metagenomic plastic-degrading polyester hydrolase PHL7 bound to its product

The recently discovered metagenomic-derived polyester hydrolase PHL7 is able to efficiently degrade amorphous polyethylene terephthalate (PET) in post-consumer plastic waste. We present the cocrystal structure of this hydrolase with its hydrolysis product terephthalic acid and elucidate the influence of 17 single mutations on the PET-hydrolytic activity and thermal stability of PHL7. The substrate-binding mode of terephthalic acid is similar to that of the thermophilic polyester hydrolase LCC and deviates from the mesophilic IsPETase. The subsite I modifications L93F and Q95Y, derived from LCC, increased the thermal stability, while exchange of H185S, derived from IsPETase, reduced the stability of PHL7. The subsite II residue H130 is suggested to represent an adaptation for high thermal stability, whereas L210 emerged as the main contributor to the observed high PET-hydrolytic activity. Variant L210T showed significantly higher activity, achieving a degradation rate of 20 µm h−1 with amorphous PET films

Untersuchungen zur Wechselwirkung von Interleukin-10 mit Glykosaminoglykanen mittels NMR-Spektroskopie

Das Zytokin Interleukin-10 (IL-10) ist ein Schlüsselspieler in der Regulation des Immunsystems mit pro- und anti-inflammatorischen Funktionen. Es spielt eine wichtige Rolle bei der Terminierung und Unterdrückung einer Entzündungsantwort, die ansonsten zu einer bleibenden Schädigung des Gewebes führen kann. Eine Dysregulation von IL-10 ist mit verschiedenen Krankheitsbildern wie chronischen Entzündungen, Autoimmunerkrankungen und Krebs assoziiert. IL-10 wird von einem breiten Spektrum von Zelltypen, darunter hauptsächlich hämatopoetische Zellen, aber auch epitheliale und mesenchymale Zellen, gebildet und in den extrazellulären Raum freigesetzt, wo es mit Komponenten der extrazellulären Matrix in Kontakt kommt. Es ist bekannt, dass IL-10 an Glykosaminoglykane (GAGs) binden kann und dass diese Interaktion seine biologische Aktivität beeinflusst. GAGs sind eine Klasse linearer Polysaccharide der extrazellulären Matrix. Sie bestehen aus wiederholenden Disaccharideinheiten und haben einen hoch negativ geladenen Charakter, welcher durch einen hohen Grad an Sulfatierung in der Zuckerkette zustandekommt. Sie binden eine Vielzahl an Signalproteinen und regulieren deren biologische Funktionen, etwa indem sie Einfluss auf die Rezeptorbindung oder die räumliche Verteilung des Proteins im Gewebe nehmen. Die molekularen Mechanismen, wodurch GAGs die biologische Aktivität von IL-10 beeinflussen, sind bisher unbekannt. Insbesondere ist nichts über die strukturellen Grundlagen der Interaktion bekannt, die Voraussetzung für ihr funktionelles Verständnis sind. In dieser Arbeit wurden daher die Bindungseigenschaften von IL-10 und GAGs sowie der strukturelle Aufbau ihres molekularen Komplexes unter Verwendung von NMR-Spektroskopie in Lösung charakterisiert. Es wurde eine definierte GAG-Bindungsstelle in IL-10 identifiziert und die Bindungsepitope und Bindungsaffinitäten von GAGs bestimmt. Die Ergebnisse dieser Arbeit weisen auf eine wichtige Rolle, die GAGs in der Biologie von IL-10 spielen können, hin – etwa für seine Speicherung im Gewebe oder für die IL-10-Rezeptorbindung

Recent Advances in NMR Protein Structure Prediction with ROSETTA

Nuclear magnetic resonance (NMR) spectroscopy is a powerful method for studying the structure and dynamics of proteins in their native state. For high-resolution NMR structure determination, the collection of a rich restraint dataset is necessary. This can be difficult to achieve for proteins with high molecular weight or a complex architecture. Computational modeling techniques can complement sparse NMR datasets (<1 restraint per residue) with additional structural information to elucidate protein structures in these difficult cases. The Rosetta software for protein structure modeling and design is used by structural biologists for structure determination tasks in which limited experimental data is available. This review gives an overview of the computational protocols available in the Rosetta framework for modeling protein structures from NMR data. We explain the computational algorithms used for the integration of different NMR data types in Rosetta. We also highlight new developments, including modeling tools for data from paramagnetic NMR and hydrogen–deuterium exchange, as well as chemical shifts in CS-Rosetta. Furthermore, strategies are discussed to complement and improve structure predictions made by the current state-of-the-art AlphaFold2 program using NMR-guided Rosetta modeling

Guiding protein design choices by per-residue energy breakdown analysis with an interactive web application

Recent developments in machine learning have greatly facilitated the design of proteins with improved properties. However, accurately assessing the contributions of an individual or multiple amino acid mutations to overall protein stability to select the most promising mutants remains a challenge. Knowing the specific types of amino acid interactions that improve energetic stability is crucial for finding favorable combinations of mutations and deciding which mutants to test experimentally. In this work, we present an interactive workflow for assessing the energetic contributions of single and multi-mutant designs of proteins. The energy breakdown guided protein design (ENDURE) workflow includes several key algorithms, including per-residue energy analysis and the sum of interaction energies calculations, which are performed using the Rosetta energy function, as well as a residue depth analysis, which enables tracking the energetic contributions of mutations occurring in different spatial layers of the protein structure. ENDURE is available as a web application that integrates easy-to-read summary reports and interactive visualizations of the automated energy calculations and helps users selecting protein mutants for further experimental characterization. We demonstrate the effectiveness of the tool in identifying the mutations in a designed polyethylene terephthalate (PET)-degrading enzyme that add up to an improved thermodynamic stability. We expect that ENDURE can be a valuable resource for researchers and practitioners working in the field of protein design and optimization. ENDURE is freely available for academic use at: http://endure.kuenzelab.org

Improving the Modeling of Extracellular Ligand Binding Pockets in RosettaGPCR for Conformational Selection

G protein-coupled receptors (GPCRs) are the largest class of drug targets and undergo substantial conformational changes in response to ligand binding. Despite recent progress in GPCR structure determination, static snapshots fail to reflect the conformational space of putative binding pocket geometries to which small molecule ligands can bind. In comparative modeling of GPCRs in the absence of a ligand, often a shrinking of the orthosteric binding pocket is observed. However, the exact prediction of the flexible orthosteric binding site is crucial for adequate structure-based drug discovery. In order to improve ligand docking and guide virtual screening experiments in computer-aided drug discovery, we developed RosettaGPCRPocketSize. The algorithm creates a conformational ensemble of biophysically realistic conformations of the GPCR binding pocket between the TM bundle, which is consistent with a knowledge base of expected pocket geometries. Specifically, tetrahedral volume restraints are defined based on information about critical residues in the orthosteric binding site and their experimentally observed range of Cα-Cα-distances. The output of RosettaGPCRPocketSize is an ensemble of binding pocket geometries that are filtered by energy to ensure biophysically probable arrangements, which can be used for docking simulations. In a benchmark set, pocket shrinkage observed in the default RosettaGPCR was reduced by up to 80% and the binding pocket volume range and geometric diversity were increased. Compared to models from four different GPCR homology model databases (RosettaGPCR, GPCR-Tasser, GPCR-SSFE, and GPCRdb), the here-created models showed more accurate volumes of the orthosteric pocket when evaluated with respect to the crystallographic reference structure. Furthermore, RosettaGPCRPocketSize was able to generate an improved realistic pocket distribution. However, while being superior to other homology models, the accuracy of generated model pockets was comparable to AlphaFold2 models. Furthermore, in a docking benchmark using small-molecule ligands with a higher molecular weight between 400 and 700 Da, a higher success rate in creating native-like binding poses was observed. In summary, RosettaGPCRPocketSize can generate GPCR models with realistic orthosteric pocket volumes, which are useful for structure-based drug discovery applications

Structural basis of the activation of PPARγ by the plasticizer metabolites MEHP and MINCH

Di-2-ethylhexyl phthalate (DEHP) and its substitute 1,2-cyclohexane dicarboxylic acid diisononyl ester (DINCH) are widely used as plasticizers but may have adverse health effects. Via hydrolysis of one of the two ester bonds in the human body, DEHP and DINCH form the monoesters MEHP and MINCH, respectively. Previous studies demonstrated binding of these metabolites to PPARγ and the induction of adipogenesis via this pathway. Detailed structural understanding of how these metabolites interact with PPARγ and thereby affect human health is lacking until now. We therefore characterized the binding modes of MINCH and MEHP to the ligand binding domain of PPARγ by X-ray crystallography and molecular dynamics (MD) simulations. Both compounds bind to the activating function-2 (AF-2) binding site via an interaction of the free carboxylates with the histidines 323 and 449, tyrosine 473 and serine 289. The alkyl chains form hydrophobic interactions with the tunnel next to cysteine 285. These binding modes are generally stable as demonstrated by the MD simulations and they resemble the complexation of fatty acids and their metabolites to the AF-2 site of PPARγ. Similar to the situation for these natural PPARγ agonists, the interaction of the free carboxylate groups of MEHP and MINCH with tyrosine 473 and surrounding residues stabilizes the AF-2 helix in the upward conformation. This state promotes binding of coactivator proteins and thus formation of the active complex for transcription of the specific target genes. Moreover, a comparison of the residues involved in binding of the plasticizer metabolites in vertebrate PPARγ orthologs shows that these compounds likely have similar effects in other species

Structural basis of the activation of PPARγ\gamma by the plasticizer metabolites MEHP and MINCH

Di-2-ethylhexyl phthalate (DEHP) and its substitute 1,2-cyclohexane dicarboxylic acid diisononyl ester (DINCH) are widely used as plasticizers but may have adverse health effects. Via hydrolysis of one of the two ester bonds in the human body, DEHP and DINCH form the monoesters MEHP and MINCH, respectively. Previous studies demonstrated binding of these metabolites to PPAR$\gamma$ and the induction of adipogenesis via this pathway. Detailed structural understanding of how these metabolites interact with PPAR$\gamma$ and thereby affect human health is lacking until now. We therefore characterized the binding modes of MINCH and MEHP to the ligand binding domain of PPAR$\gamma$ by X-ray crystallography and molecular dynamics (MD) simulations. Both compounds bind to the activating function-2 (AF-2) binding site via an interaction of the free carboxylates with the histidines 323 and 449, tyrosine 473 and serine 289. The alkyl chains form hydrophobic interactions with the tunnel next to cysteine 285. These binding modes are generally stable as demonstrated by the MD simulations and they resemble the complexation of fatty acids and their metabolites to the AF-2 site of PPAR$\gamma$. Similar to the situation for these natural PPAR$\gamma$ agonists, the interaction of the free carboxylate groups of MEHP and MINCH with tyrosine 473 and surrounding residues stabilizes the AF-2 helix in the upward conformation. This state promotes binding of coactivator proteins and thus formation of the active complex for transcription of the specific target genes. Moreover, a comparison of the residues involved in binding of the plasticizer metabolites in vertebrate PPAR$\gamma$ orthologs shows that these compounds likely have similar effects in other species

Paramagnetic spin labeling of a bacterial DnaB helicase for solid-state NMR

Labeling of biomolecules with a paramagnetic probe for nuclear magnetic resonance (NMR) spectroscopy enables determining long-range distance restraints, which are otherwise not accessible by classically used dipolar coupling-based NMR approaches. Distance restraints derived from paramagnetic relaxation enhancements (PREs) can facilitate the structure determination of large proteins and protein complexes. We herein present the site-directed labeling of the large oligomeric bacterial DnaB helicase from Helicobacter pylori with cysteine-reactive maleimide tags carrying either a nitroxide radical or a lanthanide ion. The success of the labeling reaction was followed by quantitative continuous-wave electron paramagnetic resonance (EPR) experiments performed on the nitroxide-labeled protein. PREs were extracted site-specifically from 2D and 3D solid-state NMR spectra. A good agreement with predicted PRE values, derived by computational modeling of nitroxide and Gd3+ tags in the low-resolution DnaB crystal structure, was found. Comparison of experimental PREs and model-predicted spin label-nucleus distances indicated that the size of the “blind sphere” around the paramagnetic center, in which NMR resonances are not detected, is slightly larger for Gd3+ (∼14 Å) than for nitroxide (∼11 Å) in 13C-detected 2D spectra of DnaB. We also present Gd3+-Gd3+ dipolar electron–electron resonance EPR experiments on DnaB supporting the conclusion that DnaB was present as a hexameric assembly.ISSN:1090-780

Binding of the three-repeat domain of tau to phospholipid membranes induces an aggregated-like state of the protein

AbstractIn patients with Alzheimer's disease, the microtubule-associated protein tau is found aggregated into paired helical filaments (PHFs) in neurofibrillary deposits. In solution, tau is intrinsically unstructured. However, the tubulin binding domain consisting of three or four 31–32 amino acid repeat regions exhibits both helical and β-structure propensity and makes up the proteolysis resistant core of PHFs. Here, we studied the structure and dynamics of the three-repeat domain of tau (i.e. K19) when bound to membranes consisting of a phosphatidylcholine and phosphatidylserine mixture or phosphatidylserine alone. Tau K19 binds to phospholipid vesicles with submicromolar affinity as measured by fluorescence spectroscopy. The interaction is driven by electrostatic forces between the positively charged protein and the phospholipid head groups. The structure of the membrane-bound state of K19 was studied using CD spectroscopy and solid-state magic-angle spinning NMR spectroscopy. To this end, the protein was selectively 13C-labeled at all valine and leucine residues. Isotropic chemical shift values of tau K19 were consistent with a β-structure. In addition, motionally averaged 1H–13C dipolar couplings indicated a high rigidity of the protein backbone. The structure formation of K19 was also shown to depend on the charge density of the membrane. Phosphatidylserine membranes induced a gain in the α-helix structure along with an immersion of K19 into the phospholipid bilayer as indicated by a reduction of the lipid chain 2H NMR order parameter. Our results provide structural insights into the membrane-bound state of tau K19 and support a potential role of phospholipid membranes in mediating the physiological and pathological functions of tau