Biology subjects

Clayton, J.

Publications and source records attributed to Clayton, J..

10 recordsLinked to original sources

bioRxiv2026

Ryanodine receptor 1 ( RYR1 ) patient-derived muscle cells recapitulate disease phenotypes in 2D and 3D culture models

The Ryanodine Receptor 1 (RyR1) is the major Ca2+ release channel in skeletal muscle and plays a crucial role in excitation-contraction coupling. Pathogenic variants in RYR1 are the most common cause of congenital myopathy, for which there are no approved treatments. Patient-centric disease models may help to facilitate the design and screening of novel therapeutics in a human genomic context. In this report, we describe the differentiation of five dominant RYR1-related myopathy patient-derived induced pluripotent stem cell (iPSC) lines into muscle progenitor cells (MPCs), and subsequently into multinucleated myotubes in 2- and 3- Dimensional (D) culture models. In 2D, we show significantly reduced Ca2+ release in a patient line compared to a healthy control following stimulation with caffeine. In 3D engineered muscle tissues (EMTs), patient-relevant phenotypes including reduced twitch amplitude, delayed relaxation and altered force-frequency relationships were observed in a patient line compared to two healthy controls. We also show that the 2D cultures are a suitable platform for screening the efficacy and cellular toxicity of antisense oligonucleotide therapeutics. Together, these results suggest that iPSC-derived skeletal muscle cultures are useful models for understanding the pathobiology of RYR1-related myopathies and as a testbed for emerging treatments.

Cell Biology↗

bioRxiv2026

Slow Dissociation of Nitazenes from the μ-Opioid Receptor Underlies the Challenge of Overdose Reversal

Nitazenes are driving a wave of overdose deaths in the United States and Europe and often require additional doses of naloxone to reverse. To understand the molecular basis, we conducted a joint experimental and simulation study of three common nitazenes, eto-, etodes-, and protonitazene. Radioligand experiments demonstrated that all three nitazenes display higher receptor affinity and longer dissociation half-lives than fentanyl. Notably, protonitazene dissociates slower than carfentanil and its displacement requires fourfold higher antagonist concentrations. The observed trend in nitazene half-lives is recapitulated by molecular dynamics simulations, which suggest that kinetics is controlled by specific interactions with two receptor subpockets. A newly published cryo-EM structure of fluetonitazene-OR complex confirms the predicted interactions, including a{pi} -hole bond between the nitro group and Tyr1.39, a residue recently shown to modulate OR signaling bias. Our findings suggest slow receptor dissociation as a key factor challenging overdose reversal. The mechanistic insights have implications for understanding opioid toxicity and designing more effective countermeasures.

pharmacology and toxicology↗

bioRxiv2025

The Plasma Membrane may Serve as a Drug Depot to Drive the Extreme Potency of Fentanyl

Fentanyl is a leading cause of drug overdose deaths in the United States, yet the mechanisms underlying its extreme in vivo potency remain poorly understood. Recently, new synthetic opioids nitazene derivatives have emerged, among which isotonitazene is 50 times more potent than fentanyl. Here we used state-of-the-art molecular dynamics (MD) simulations and experiments to investigate the membrane-dependent pharmacology of fentanyl, isotonitazene, morphine, and naloxone. Using the weighted-ensemble continuous constant pH MD, we estimated the effective permeability of fentanyl at pH 7.5 to be on the order of 10-7 cm/s, which is about two orders of magnitude faster than the simulation estimate for morphine. In contrast, isotonitazene and naloxone effectively do not partition into the membrane under the same conditions. The simulations captured the protoncoupled permeation processes, challenging as well as refining the long-standing pH-partition hypothesis. Subsequent BRET reporter cell experiments demonstrated that cells exposed to fentanyl, but not morphine, reactivated the receptor after washout and in competition with naloxone. Immobilized affinity membrane chromatography confirmed fentanyls high affinity for phospholipids. Our findings strongly support the hypothesis that fentanyls extreme in vivo potency may be driven by its accumulation within the plasma membrane or intracellularly, enabling it to repartition into the extracellular space to rebind the receptor, or potentially access it via a lipid-mediated route. This highlights the importance of membrane-dependent pharmacology for understanding opioid toxicity and guiding the design of more effective antagonists. Our simulation methodology enables accurate prediction and analysis of membrane permeation of ionizable molecules, providing a valuable tool for ADME optimization in drug development.

biophysics↗

bioRxiv2024

Computational Analysis of the Binding Poses of Nitazene Derivatives at the mu-Opioid Receptor

Nitazenes are a class of novel synthetic opioids with exceptionally high potency. Currently, an experimental structure of {micro}OR-opioid receptor ({micro}OR) in complex with a nitazene is lacking. Here we used a suite of computational tools, including consensus docking, conventional molecular dynamics (MD) and metadynamics simulations, to investigate the {micro}OR binding modes of nitro-containing meto-, eto-, proto-, buto-, and isotonitazenes and nitro-less analogs, metodes-, etodes-, and protodesnitazenes. Docking generated three binding modes, whereby the nitro-substituted or unsubstituted benzimidazole group extends into SP1 (subpocket 1 between transmembrane helix or TM 2 and 3), SP2 (subpocket 2 between TM1, TM2, and TM7) or SP3 (subpocket 3 between TM5 and TM6). Simulations suggest that etonitazene and likely also other nitazenes favor the SP2-binding mode. Comparison to the experimental structures of {micro}OR in complex with BU72, fentanyl, and mitragynine pseudoindoxyl (MP) allows us to propose a putative model for {micro}OR-ligand recognition in which ligand can access hydrophobic SP1 or hydrophilic SP2, mediated by the conformational change of Gln1242.60. Interestingly, in addition to water-mediated hydrogen bonds, the nitro group in nitazenes forms a{pi} -hole interaction with the conserved Tyr751.39. Our computational analysis provides new insights into the mechanism of {micro}OR-opioid recognition, paving the way for investigations of the structure-activity relationships of nitazenes. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/616560v2_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@f3a933org.highwire.dtl.DTLVardef@e98f41org.highwire.dtl.DTLVardef@1bc0962org.highwire.dtl.DTLVardef@c416b_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2024

Why is the Omicron main protease of SARS-CoV-2 less stable than its wild-type counterpart? A crystallographic, biophysical, and theoretical study of the free enzyme and its complex with inhibitor 13b-K

During the continuing evolution of SARS-CoV-2, the Omicron variant of concern emerged in the second half of 2021 and has been dominant since November that year. Along with its sublineages, it has maintained a prominent role ever since. The Nsp5 main protease (Mpro) of the Omicron virus is characterized by a single dominant mutation, P132H. Here we determined the X-ray crystal structures of the P132H mutant (or O-Mpro) as free enzyme and in complex with the Mpro inhibitor, the alpha-ketoamide 13b-K, and we conducted enzymology, biophysical as well as theoretical studies to characterize the O-Mpro. We found that O-Mpro has a similar overall structure and binding with 13b-K; however, it displays lower enzymatic activity and lower thermal stability compared to the WT-Mpro (with "WT" referring to the original Wuhan-1 strain). Intriguingly, the imidazole ring of His132 and the carboxylate plane of Glu240 are in a stacked configuration in the X-ray structures determined here. The empirical folding free energy calculations suggest that the O-Mpro dimer is destabilized relative to the WT-Mpro due to the less favorable van der Waals interactions and backbone conformation in the individual protomers. The all-atom continuous constant pH molecular dynamics (MD) simulations reveal that His132 and Glu240 display coupled titration. At pH 7, His132 is predominantly neutral and in a stacked configuration with respect to Glu240 which is charged. In order to examine whether the Omicron mutation eases the emergence of further Mpro mutations, we also determined crystal structures of the relatively frequent P132H+T169S double mutant but found little evidence for a correlation between the two sites.

biochemistry↗

bioRxiv2023

Mechanism of Dimer Selectivity and Binding Cooperativity of BRAF inhibitors

Aberrant signaling of BRAFV600E is a major cancer driver. Current FDA-approved RAF inhibitors selectively inhibit the monomeric BRAFV600E and suffer from tumor resistance. Recently, dimer-selective and equipotent RAF inhibitors have been developed; however, the mechanism of dimer selectivity is poorly understood. Here, we report extensive molecular dynamics (MD) simulations of the monomeric and dimeric BRAFV600E in the apo form or in complex with one or two dimer-selective (PHI1) or equipotent (LY3009120) inhibitor(s). The simulations uncovered the unprecedented details of the remarkable allostery in BRAFV600E dimerization and inhibitor binding. Specifically, dimerization retrains and shifts the C helix inward and increases the flexibility of the DFG motif; dimer compatibility is due to the promotion of the C-in conformation, which is stabilized by a hydrogen bond formation between the inhibitor and the C Glu501. A more stable hydrogen bond further restrains and shifts the C helix inward, which incurs a larger entropic penalty that disfavors monomer binding. This mechanism led us to propose an empirical way based on the co-crystal structure to assess the dimer selectivity of a BRAFV600E inhibitor. Simulations also revealed that the positive cooperativity of PHI1 is due to its ability to preorganize the C and DFG conformation in the opposite protomer, priming it for binding the second inhibitor. The atomically detailed view of the interplay between BRAF dimerization and inhibitor allostery as well as cooperativity has implications for understanding kinase signaling and contributes to the design of protomer selective RAF inhibitors.

biophysics↗

bioRxiv2023

Interrogating Proteome-wide Cysteine Ligandabilities: Crystallography Meets Chemoproteomics Through Machine Learning

Machine learning (ML) identification of covalently ligandable sites may accelerate targeted covalent inhibitor design and help expand the druggable proteome space. Here we report the rigorous development and validation of the tree-based models and convolutional neural networks (CNNs) trained on a newly curated database (LigCys3D) of over 1,000 liganded cysteines in nearly 800 proteins represented by over 10,000 three-dimensional structures in the protein data bank. The unseen tests yielded 94% and 93% AUCs (area under the receiver operating characteristic curve) for the tree models and CNNs, respectively. Based on the AlphaFold2 predicted structures, the ML models recapitulated the newly liganded cysteines in the PDB with over 90% recall values. To assist the community of covalent drug discoveries, we report the predicted ligandable cysteines in 392 human kinases and their locations in the sequence-aligned kinase structure including the PH and SH2 domains. Furthermore, we disseminate a searchable online database LigCys3D (https://ligcys.computchem.org/) and a web prediction server DeepCys (https://deepcys.computchem.org/), both of which will be continuously updated and improved by including newly published experimental data. The present work represents a first step towards the ML-led integration of big genome data and structure models to annotate the human proteome space for the next-generation covalent drug discoveries.

bioinformatics↗

bioRxiv2021

Directed inter-domain motions enable the IsdH Staphylococcus aureus receptor to rapidly extract heme from human hemoglobin

Pathogenic Staphylococcus aureus actively acquires iron from human hemoglobin (Hb) using the IsdH surface receptor. Heme extraction is mediated by a tridomain unit within the receptor that contains its second (N2) and third (N3) NEAT domains joined by a helical linker domain. Extraction occurs within a dynamic complex, in which receptors engage each globin chain; the N2 domain tightly binds to Hb, while substantial inter-domain motions within the receptor enable its N3 domain to transiently distort the globins heme pocket. Using molecular simulations, Markov modeling, and quantitative measurements of heme transfer kinetics, we show that directed inter-domain motions within the receptor play a critical role in the extraction process. The directionality of N3 domain motion and the rate of heme extraction is controlled by amino acids within a short, flexible inter-domain tether that connects the N2 and linker domains. In the wild-type receptor directed motions originating from the tether enable the N3 domain to populate configurations capable of distorting Hbs pocket, whereas mutant receptors containing altered tethers are less able to adopt these conformers and capture heme slowly via indirect processes in which Hb first releases heme into the solvent. Thus, our results show inter-domain motions within the IsdH receptor play a critical role in its ability to extract heme from Hb and highlight the importance of directed motions by the short, unstructured, amino acid sequence connecting the domains in controlling the directionality and magnitude of these functionally important motions.

biophysics↗

bioRxiv2021

Molecular adaptation to folivory and the conservation implications for Madagascar's lemurs

Folivory evolved independently at least three times over the last 40 million years among Madagascars lemurs. Many extant lemuriform folivores exist in sympatry in Madagascars remaining forests. These species avoid feeding competition by adopting different dietary strategies within folivory, reflected in behavioral, morphological, and microbiota diversity across species. These conditions make lemurs an ideal study system for understanding adaptation to leaf-eating. Most folivorous lemurs are also highly endangered. The significance of folivory for conservation outlook is complex. Though generalist folivores may be relatively well equipped to survive habitat disturbance, specialist folivores occupying narrow dietary niches may be less resilient. Characterizing the genetic bases of adaptation to folivory across species and lineages can provide insights into their differential physiology and potential to resist habitat change. We recently reported accelerated genetic change in RNASE1, a gene encoding an enzyme (RNase 1) involved in molecular adaptation in mammalian folivores, including various monkeys and sifakas (genus Propithecus; family Indriidae). Here, we sought to assess whether other lemurs, including phylogenetically and ecologically diverse folivores, might show parallel adaptive change in RNASE1 that could underlie a capacity for efficient folivory. We characterized RNASE1 in 21 lemur species representing all five families and members of the three extant folivorous lineages: 1) bamboo lemurs (family Lemuridae), 2) sportive lemurs (family Lepilemuridae), and 3) indriids (family Indriidae). We found pervasive sequence change in RNASE1 across all indriids, a dN/dS value > 3 in this clade, and evidence for shared change in isoelectric point, indicating altered enzymatic function. Sportive and bamboo lemurs, in contrast, showed more modest sequence change. The greater change in indriids may reflect a shared strategy emphasizing complex gut morphology and microbiota to facilitate folivory. This case study illustrates how genetic analysis may reveal differences in functional traits that could influence species ecology and, in turn, their resilience to habitat change. Moreover, our results support the contention that not all primate folivores are built the same and highlight the need to avoid generalizations about dietary guild in considering conservation outlook, particularly in lemurs where such diversity in folivory has probably led to extensive specialization via niche partitioning.

ecology↗

bioRxiv2018

BEES: Bayesian Ensemble Estimation from SAS, a SASSIE-web Module

1Many biomolecular complexes exist in a flexible ensemble of states in solution which are necessary to perform their biological function. Small angle scattering (SAS) measurements are a popular method for characterizing these flexible molecules due to their relative ease of use and ability to simultaneously probe the full ensemble of states. However, SAS data is typically low-dimensional and difficult to interpret without the assistance of additional structural models. In theory, experimental SAS curves can be reconstituted from a linear combination of theoretical models, although this procedure carries significant risk of overfitting the inherently low-dimensional SAS data. Previously, we developed a Bayesian-based method for fitting ensembles of model structures to experimental SAS data that rigorously avoids overfitting. However, we have found that these methods can be difficult to incorporate into typical SAS modeling workflows, especially for users that are not experts in computational modeling. To this end, we present the "Bayesian Ensemble Estimation from SAS" (BEES) program. Two forks of BEES are available, the primary one existing as module for the SASSIE webserver and a developmental version that is a standalone python program. BEES allows users to exhaustively sample ensemble models constructed from a library of theoretical states and to interactively analyze and compare each models performance. The fitting routine also allows for secondary data sets to be supplied, thereby simultaneously fitting models to both SAS data as well as orthogonal information. The flexible ensemble of K63-linked ubiquitin trimers is presented as an example of BEES capabilities.

biophysics↗