Biology subjects

Hildebrand, P. W.

Publications and source records attributed to Hildebrand, P. W..

5 recordsLinked to original sources

bioRxiv2023

Time-resolved cryo-EM of G protein activation by a GPCR

G protein-coupled receptors (GPCRs) activate heterotrimeric G proteins by stimulating the exchange of guanine nucleotide in the G subunit. To visualize this mechanism, we developed a time-resolved cryo-EM approach that examines the progression of ensembles of pre-steady-state intermediates of a GPCR-G protein complex. Using variability analysis to monitor the transitions of the stimulatory Gs protein in complex with the {beta}2-adrenergic receptor ({beta}2AR) at short sequential time points after GTP addition, we identified the conformational trajectory underlying G protein activation and functional dissociation from the receptor. Twenty transition structures generated from sequential overlapping particle subsets along this trajectory, compared to control structures, provide a high-resolution description of the order of events driving G protein activation upon GTP binding. Structural changes propagate from the nucleotide-binding pocket and extend through the GTPase domain, enacting alterations to G Switch regions and the 5 helix that weaken the G protein-receptor interface. Molecular dynamics (MD) simulations with late structures in the cryo-EM trajectory support that enhanced ordering of GTP upon closure of the alpha-helical domain (AHD) against the nucleotide-bound Ras-homology domain (RHD) correlates with irreversible 5 helix destabilization and eventual dissociation of the G protein from the GPCR. These findings also highlight the potential of time-resolved cryo-EM as a tool for mechanistic dissection of GPCR signaling events.

physiology↗

bioRxiv2023

Structural basis of GAIN domain autoproteolysis and cleavage-resistance in the adhesion G-protein coupled receptors

The GAIN domain is a hallmark of adhesion G-protein coupled receptors (aGPCRs) as this extracellular domain contains an integral agonistic sequence (Stachel) for activation via binding to the 7-transmembrane helical (7TM) domain of the receptor. Many aGPCRs are autoproteolytically cleaved at the GPCR proteolysis site (GPS) site within the GAIN domain formed HXS/T sequence motif. However, other aGPCR can be activated without GPS cleavage. We determined the crystal structure of the human ADGRB2/BAI2 hormone receptor (HormR) and GPCR autoproteolysis-inducing (GAIN) domains and found that this aGPCR is resistant to autoproteolysis despite the presence of a canonical HLS sequence motif at the GPS. We used structural comparisons and molecular dynamics (MD) simulations to identify structural determinants that are important for autocleavage beyond the canonical HXS/T motif. These studies characterized a conserved glycine residue and an edge-{pi} interaction of the histidine base of the GPS sequence with a phenylalanine residue that is highly conserved in cleavage-competent aGPCRs. The MD simulations showed that this interaction is important to position the imidazole group of the histidine for deprotonation of the serine or threonine nucleophile. Removal of this interaction reduced autoprote-olytic activity in the ADGRL1 receptor and restored cleavage competence of the ADGRB3 receptor in a R866H/L821F double mutant. Conservation analysis indicates that wild-type ADGRB2 and ADGRB3 are auto-cleavage-incompetent receptors.

biochemistry↗

bioRxiv2021

ProteinPrompt: a webserver for predictingprotein-protein interactions

MotivationProtein-protein interactions play an essential role in a great variety of cellular processes and are therefore of significant interest for the design of new therapeutic compounds as well as the identification of side-effects due to unexpected binding. Here, we present ProteinPrompt, a webserver that uses machine-learning algorithms to calculate specific, currently unknown protein-protein interactions. Our tool is designed to quickly and reliably predict contacts based on an input sequence in order to scan large sequence libraries for potential binding partners, with the goal to accelerate and assure the quality of the laborious process of drug target identification. MethodsWe collected and thoroughly filtered a comprehensive database of known contacts from several sources, which is available as download. ProteinPrompt provides two complementary search methods of similar accuracy for comparison and consensus building. The default method is a random forest algorithm that uses the auto-correlations of seven amino acid scales. Alternatively, a graph neural network implementation can be selected. Additionally, a consensus prediction is available. For each query sequence, potential binding partners are identified from a protein sequence database. The proteom of several organisms are available and can be searched for contacts. ResultsTo evaluate the predictive power of the algorithms, we prepared a test dataset that was rigorously filtered for redundancy. No sequence pairs similar to the ones used for training were included in this dataset. With this challenging dataset, the random forest method achieved an accuracy rate of 0.88 and an area under curve of 0.95. The graph neural network achieved an accuracy rate of 0.86 using the same dataset. Since the underlying learning approaches are unrelated, comparing the results of random forest and graph neural networks reduces the likelihood of errors. The consensus reached an accuracy of 0.89. ProteinPrompt is available online at: http://proteinformatics.org/ProteinPrompt The server makes it possible to scan the human proteome for potential binding partners of an input sequence within minutes. For local offline usage, we furthermore created a ProteinPrompt Docker image which allows for batch submission: https://gitlab.hzdr.de/Proteinprompt/ProteinPrompt. In conclusion, we offer a fast, accurate, easy-to-use online service for predicting binding partners from an input sequence.

bioinformatics↗

bioRxiv2021

Structures of active melanocortin-4 receptor--Gs-protein complexes with NDP-α-MSH and setmelanotide

The melanocortin-4 receptor (MC4R), a hypothalamic master regulator of energy homeostasis and appetite, is a G-protein coupled receptor and a prime target for the treatment of obesity. Here, we present cryo-electron microscopy structures of MC4R- Gs-protein complexes with two recently FDA-approved drugs, the peptide agonists NDP--MSH and setmelanotide, with 2.9 [A] and 2.6 [A] resolution. Together with signaling data, the complex structures reveal the agonist-induced origin of transmembrane helix (TM) 6 regulated receptor activation. In both structures, different ligand binding modes of NDP--MSH, a high-affinity variant of the endogenous agonist, and setmelanotide, an anti-obesity drug with biased signaling, underline the key role of TM3 for ligand-specific interactions and of calcium ion as a ligand-adaptable cofactor. The agonist-TM3 interplay subsequently impacts the receptor- Gs-protein interfaces, mainly at intracellular loop 2. These structures reveal mechanistic details of MC4R activation or inhibition and provide important insights into receptor selectivity that will facilitate the development of tailored anti-obesity drugs.

biochemistry↗

bioRxiv2019

GPCRmd uncovers the dynamics of the 3D-GPCRome

G protein-coupled receptors (GPCRs) are involved in numerous physiological processes and are the most frequent targets of approved drugs. The explosion in the number of new 3D molecular structures of GPCRs (3D-GPCRome) during the last decade has greatly advanced the mechanistic understanding and drug design opportunities for this protein family. While experimentally-resolved structures undoubtedly provide valuable snapshots of specific GPCR conformational states, they give only limited information on their flexibility and dynamics associated with function. Molecular dynamics (MD) simulations have become a widely established technique to explore the conformational landscape of proteins at an atomic level. However, the analysis and visualization of MD simulations requires efficient storage resources and specialized software, hence limiting the dissemination of these data to specialists in the field. Here we present the GPCRmd (http://gpcrmd.org/), an online platform that incorporates web-based visualization capabilities as well as a comprehensive and user-friendly analysis toolbox that allows scientists from different disciplines to visualize, analyse and share GPCR MD data. GPCRmd originates from a community-driven effort to create the first open, interactive, and standardized database of GPCR MD simulations. We demonstrate the power of this resource by performing comparative analyses of multiple GPCR simulations on two mechanisms critical to receptor function: internal water networks and sodium ion interaction.

biophysics↗