Biology subjects

van der Velden, W. J. C.

Publications and source records attributed to van der Velden, W. J. C..

5 recordsLinked to original sources

bioRxiv2026

Allosteric pathways govern Gα protein coupling selectivity at promiscuous GPCRs

G protein-coupled receptors (GPCRs) regulate diverse physiological responses by engaging distinct heterotrimeric G proteins, yet the basis of G selectivity in promiscuous receptors remains unclear. Although ligand bias holds therapeutic promise, selectivity has been assumed to reside mainly in the ligand-binding site (LBS) or G protein interface (GPI). Here, we combine whole-receptor mutagenesis, functional G protein assays, molecular dynamics simulations, interpretable machine learning method, and Bayesian network modeling to identify residue networks governing Gq/11 and G12/13 coupling and to define the molecular basis of G protein preference and promiscuity at two vasopressor GPCRs, the angiotensin II type 1 and prostaglandin F2 receptors. While residues within the LBS and GPI domains contribute to coupling efficiency and subtype discrimination, we find that long-range allosteric communication across the receptor, including from structurally unresolved domains, is the principal determinant of G protein preference and promiscuity. These allosteric pathways integrate multiple receptor domains, confer signaling robustness to mutation, and hierarchically govern coupling preferences. Our findings suggest that G protein selectivity is an allosterically encoded property of GPCRs and provide a conceptual framework for designing ligands and receptors with tailored G protein-biased signaling.

pharmacology and toxicology↗

bioRxiv2026

Interpretable Machine Learning Model of Receptor Dynamics Reveals AT1R Allostery and a Negative Allosteric Modulator

Allosteric modulation of G protein-coupled receptors (GPCRs) offers major advantages in receptor selectivity and signaling control; yet systematic approaches to identify allosteric modulators, define their binding sites, and map the underlying allosteric networks remain limited. Current molecular dynamics (MD) and machine learning (ML)-based methods often rely on correlation-driven or black-box models that provide limited mechanistic insight. We developed an interpretable probabilistic framework that extracts residue-level dependencies from MD ensembles using Bayesian network modeling (BNM). By representing each residue through its local interaction energy, BNM identifies both local and long-range energetic couplings and maps the allosteric communication pathways linking the AngII binding site to the G-protein interface in the angiotensin II type 1 receptor (AT1R). To functionally prioritize these pathways, we integrated BNM with comprehensive mutational analysis, combining whole-receptor alanine mutagenesis data with exhaustive in silico deep mutational scanning to validate BNM-predicted hotspots. This approach recovered state-dependent allosteric communities, revealed residues in noncanonical regions that regulate Gq coupling and identified positions whose functional importance emerged only with specific, predicted substitutions, as well as highlighted a cryptic intracellular pocket enriched in communication hubs. Guided by these network-derived residues and pocket geometries, structure-based virtual screening identified a small, fragment-like molecule negative allosteric modulator (NAM) named Q2 that attenuates AngII-mediated Gq signaling. Mutational mapping supports Q2 binding adjacent to the G-protein interface, consistent with its mechanism of action. Together, these results establish a generalizable and interpretable framework for uncovering GPCR allosteric communication networks and discovering modulators that exploit these networks.

molecular biology↗

bioRxiv2026

Mapping the Ligand-dependent Remodeling of the Conformational Entropy Landscape in Neurotensin Receptor 1 by NMR-guided Molecular Simulations

This study presents a comprehensive analysis of the dynamic properties and allosteric regulation mechanisms of Class A G protein-coupled receptors (GPCRs) by integrating molecular dynamics (MD) simulations with nuclear magnetic resonance (NMR) relaxation measurements. Utilizing generalized order parameters derived from NMR data and MD trajectories, we quantitatively assess conformational entropy changes that occur during receptor activation and ligand binding events. This approach enables a detailed characterization of protein flexibility at multiple timescales, revealing how dynamic fluctuations contribute to allosteric signal transmission within the receptor. Our results demonstrate that conformational entropy plays a pivotal role in modulating the functional states of Class A GPCRs, influencing the equilibrium between inactive and active conformations. By elucidating the interplay between structural dynamics and allostery, this work advances the molecular-level understanding of GPCR function and highlights the importance of entropy-driven effects in receptor signaling. The integrative methodology and findings provide a valuable framework for future investigations aimed at targeting receptor dynamics in drug discovery and rational design of allosteric modulators.

molecular biology↗

bioRxiv2025

Stabilization versus flexibility: detergent-dependent trade-offs in neurotensin receptor 1 GPCR ensembles

Detergents provide essential membrane-mimetic environments for studying G protein-coupled receptors (GPCRs), but their molecular impact on receptor energetics remains incompletely understood. We combined ligand binding, thermostability measurements and atomistic molecular dynamics to dissect detergent- versus ligand-driven stabilization in a thermostabilized neurotensin receptor 1 (enNTS1). Circular dichroism and ligand binding assays revealed that apo enNTS1 becomes progressively more stable in decyl maltoside (DM), dodecyl maltoside (DDM), and lauryl maltose neopentyl glycol (LMNG). Yet this gain in baseline stability was accompanied by a paradox: LMNG, the most stabilizing detergent, supported the weakest neurotensin agonist binding affinity. Thermodynamic analysis resolved this contradiction by partitioning stability into detergent-driven conformational rigidity ({Delta}Gconf) and ligand-induced stabilization ({Delta}Gligand). In DM, {Delta}Gligand contributions were large, consistent with the receptors engineered background. In contrast, LMNG maximized {Delta}Gconf, constraining conformational flexibility and reducing {Delta}Gligand. Molecular dynamics simulations corroborated these results, showing that LMNG formed denser, less mobile detergent shells around the receptor, enhancing protein-detergent interaction energies while limiting conformational flexibility. Redistribution of ligand contacts, particularly at neurotensin residue Y11, further underscored detergent-dependent modulation of the binding pocket. These results highlight a fundamental trade-off: LMNG provides exceptional receptor stabilization, supporting structural studies, but may mask conformational states relevant to signaling. In contrast, less rigid detergents preserve ligand-induced transitions at the expense of stability. These findings emphasize that detergent choice should be guided by whether the goal is structural resolution or dynamic characterization.

biophysics↗

bioRxiv2022

Structural basis of odorant recognition by a human odorant receptor

Our sense of smell enables us to navigate a vast space of chemically diverse odor molecules. This task is accomplished by the combinatorial activation of approximately 400 olfactory G protein-coupled receptors (GPCRs) encoded in the human genome1-3. How odorants are recognized by olfactory receptors (ORs) remains mysterious. Here we provide mechanistic insight into how an odorant binds a human olfactory receptor. Using cryogenic electron microscopy (cryo-EM), we determined the structure of active human OR51E2 bound to the fatty acid propionate. Propionate is bound within an occluded pocket in OR51E2 and makes specific contacts critical to receptor activation. Mutation of the odorant binding pocket in OR51E2 alters the recognition spectrum for fatty acids of varying chain length, suggesting that odorant selectivity is controlled by tight packing interactions between an odorant and an olfactory receptor. Molecular dynamics simulations demonstrate propionate-induced conformational changes in extracellular loop 3 to activate OR51E2. Together, our studies provide a high-resolution view of chemical recognition of an odorant by a vertebrate OR, providing insight into how this large family of GPCRs enables our olfactory sense.

biochemistry↗