Biology subjects

Dror, R.

Publications and source records attributed to Dror, R..

9 recordsLinked to original sources

bioRxiv2026

Structural basis for nutrient-activated channel opening in bacterial spore germination receptors

GerA-family germinant receptors were recently identified as ion channels that initiate germination of dormant bacterial spores in response to nutrients. Here we report 2.0-[A] cryo-electron microscopy structures of apo, agonist-bound, and antagonist-bound GerA, revealing a symmetric pentamer of heterotrimers. Signaling relies on two allosteric switches that radiate from the LeuT-type ligand-binding subunit in opposite directions, one away from the channel subunit and one directly toward it. A lipoprotein subunit reroutes the first switch and allosterically activates the second, promoting their convergence on the channel. Together, these rearrangements comprise a multipronged, cooperative signal transduction pathway that connects nutrient binding to pore opening in this new class of ligand-gated ion channels.

biophysics↗

bioRxiv2023

How accurately can one predict drug binding modes using AlphaFold models?

Computational prediction of protein structure has been pursued intensely for decades, motivated largely by the goal of using structural models for drug discovery. Recently developed machine learning methods such as AlphaFold 2 (AF2) have dramatically improved protein structure prediction, with reported accuracy approaching that of experimentally determined structures. To what extent do these advances translate to an ability to predict more accurately how drugs and drug candidates bind to their target proteins? Here we carefully examine the utility of AF2 protein structure models for predicting binding poses of drug-like molecules at the largest class of drug targets, the G protein-coupled receptors. We find that AF2 models capture binding pocket structures much more accurately than traditional homology models, with errors nearly as small as differences between structures of the same protein determined experimentally with different ligands bound. Strikingly, however, the accuracy of ligand binding poses predicted by computational docking to AF2 models is not significantly higher than when docking to traditional homology models and is much lower than when docking to structures determined experimentally without these ligands bound. These results have important implications for all those who might use predicted protein structures for drug discovery.

biophysics↗

bioRxiv2022

Modulation of cannabinoid receptor signaling by endocannabinoids

Endocannabinoids (eCBs) are endogenous lipid molecules that activate the cannabinoid receptor 1 (CB1), a G protein coupled receptor (GPCR) that signals primarily through the Gi/o family of G proteins to regulate neurotransmitter release. Consequently, CB1 is an important therapeutic target for several neurological disorders. How eCBs interact with CB1 is not known and the downstream signaling they activate is not well understood. In this study we show that eCBs do not activate Gi1 as much as synthetic cannabinoids. To characterize activation of CB1 by eCB, we formed an eCB analogue-bound (AMG315) CB1-Gi signaling complex for structural studies. The structure reveals differences in the orthosteric ligand binding pocket not seen in the previous CB1 structures, providing insights into the structural determinants of ligand efficacy. In combination with signaling and simulation data, this study provides mechanistic insights into CB1 activation by different classes of ligands, and sheds light on the G protein preferences between endogenous and exogenous ligands.

biochemistry↗

bioRxiv2022

Fragment-Based Ligand Generation Guided By Geometric Deep Learning On Protein-Ligand Structure

AO_SCPLOWBSTRACTC_SCPLOWComputationally-aided design of novel molecules has the potential to accelerate drug discovery. Several recent generative models aimed to create new molecules for specific protein targets. However, a rate limiting step in drug development is molecule optimization, which can take several years due to the challenge of optimizing multiple molecular properties at once. We developed a method to solve a specific molecular optimization problem in silico: expanding a small, fragment-like starting molecule bound to a protein pocket into a larger molecule that matches that physiochemical properties of known drugs. Using data-efficient E(3) equivariant based neural networks and a 3D atomic point cloud representation, our model learns how to attach new molecular fragments to a growing structure by recognizing realistic intermediates generated en route to a final ligand. This approach always generates chemically valid molecules and incorporates all relevant 3D spatial information from the protein pocket. This framework produces promising molecules as assessed by multiple properties that address binding affinity, ease of synthesis, and solubility. Overall, we demonstrate the feasibility of 3D molecular structure expansion conditioned on protein pockets while maintaining desirable drug-like physiochemical properties and developed a tool that could accelerate the work of medicinal chemists.

bioengineering↗

bioRxiv2021

A positively Tuned Voltage Indicator Reveals Electrical Correlates of Calcium Activity in the Brain

Neuronal spiking activity is routinely recorded using genetically encoded calcium indicators (GECIs), but calcium imaging is limited in temporal resolution and does not report subthreshold voltage changes. Genetically encoded voltage indicators (GEVIs) offer better temporal resolution and subthreshold sensitivity, but spike detection with fast GEVIs has required specialized imaging equipment. Here, we report the ASAP4 subfamily of genetically encoded voltage indicators (GEVIs) that brighten in response to membrane depolarization, inverting the fluorescence-voltage relationship of previous ASAP GEVIs. Two variants, ASAP4b and ASAP4e, feature 128% and 178% fluorescence increases over 100-mV of depolarization, respectively, facilitating spike detection in single trials in vivo with standard 1 and 2-photon imaging systems. Simultaneous voltage and calcium imaging confirms improved temporal resolution and spike discernment by ASAP4 GEVIs. Thus, positively tuned ASAP4 voltage indicators enable recording of neuronal spiking activity using similar equipment as calcium imaging, while providing higher temporal resolution. One Sentence SummaryUpward ASAPs increase detection capability of GEVIs in vivo.

neuroscience↗

bioRxiv2020

Structure of human ferroportin reveals molecular basis of iron homeostasis

The serum iron level in humans is tightly controlled by the action of the hormone hepcidin on the iron efflux transporter ferroportin. Hepcidin negatively regulates iron absorption and recycling by inducing ferroportin internalization and degradation. Aberrant ferroportin activity can lead to diseases of iron overload, like hemochromatosis, or iron limitation anemias. Here, we determined cryogenic electron microscopy (cryo-EM) structures of ferroportin in lipid nanodiscs, both in the apo state and in complex with cobalt, an iron mimetic, and hepcidin. These structures and accompanying molecular dynamics simulations identify two divalent metal binding sites within the N- and C-domains of ferroportin. Hepcidin binds ferroportin in an outward-open conformation and completely occludes the iron efflux pathway. The carboxy-terminus of hepcidin directly contacts the divalent metal in the FPN C-domain. We further show that hepcidin binding to ferroportin is coupled to iron binding, with an 80-fold increase in hepcidin affinity in the presence of iron. These results suggest a new model for hepcidin regulation of ferroportin, where only iron loaded ferroportin molecules are targeted for degradation. More broadly, our structural and functional insights are likely to enable more targeted manipulation of the hepcidin-ferroportin axis in disorders of iron homeostasis.

biochemistry↗

bioRxiv2019

Medical relevance of common protein-altering variants in GPCR genes across 337,205 individuals in the UK Biobank study

G protein-coupled receptors (GPCRs) drive an array of critical physiological functions and are an important class of drug targets, though a map of which GPCR genetic variants are associated with phenotypic variation is lacking. We performed a phenome-wide association analysis for 269 common protein-altering variants in 156 GPCRs and 275 phenotypes, including disease outcomes and diverse quantitative measurements, using 337,205 UK Biobank participants and identified 138 associations. We discovered novel associations between GPCR variants and migraine risk, hypothyroidism, and dietary consumption. We also demonstrated experimentally that variants in the {beta}2 adrenergic receptor (ADRB2) associated with immune cell counts and pulmonary function and variants in the gastric inhibitory polypeptide receptor (GIPR) associated with food intake and body size affect downstream signaling pathways. Overall, this study provides a map of genetic associations for GPCR coding variants across a wide variety of phenotypes, which can inform future drug discovery efforts targeting GPCRs.

genetics↗

bioRxiv2019

Uncovering patterns of atomic interactions in static and dynamic structures of proteins

The number of structures and molecular dynamics simulations of proteins is exploding owing to dramatic advances in cryo-electron microscopy, crystallography, and computing. One of the most powerful ways to analyze structural information involves comparisons of interatomic interactions across different structures or simulations of the same protein or related proteins from the same family (e.g. different GPCRs). Such comparative analyses are of interest to a wide range of researchers but currently prove challenging for all but a few. To facilitate comparative structural analyses, we have developed tools for (i) rapidly computing and comparing interatomic interactions and (ii) interactively visualizing interactions to enable structure-based interpretations. Using these tools, we have developed the Contact Comparison Atlas, a web-based resource for the comparative analysis of interactions in structures and simulations of proteins. Using the Contact Comparison Atlas and our tools, we have identified patterns of interactions with functional implications in structures of G-protein-coupled receptors, G proteins and kinases and in the dynamics of muscarinic receptors. The Contact Comparison Atlas can be used to enable structure modeling, drug discovery, protein engineering, and the prediction of disease-associated mutations. Contact Comparison Atlas website: https://getcontacts.github.io/atlas/

biophysics↗

bioRxiv2018

Stable networks of water-mediated interactions are conserved in activation of diverse GPCRs

G protein-coupled receptors (GPCRs) have evolved to recognize incredibly diverse extracellular ligands while sharing a common architecture and structurally conserved intracellular signaling partners. It remains unclear how binding of diverse ligands brings about GPCR activation, the common structural change that enables intracellular signaling. Here, we identify highly conserved networks of water-mediated interactions that play a central role in activation. Using atomic-level simulations of diverse GPCRs, we show that most of the water molecules in GPCR crystal structures are highly mobile. Several water molecules near the G protein-coupling interface, however, are stable. These water molecules form two kinds of polar networks that are conserved across diverse GPCRs: (i) a network that is maintained across the inactive and the active states and (ii) a network that rearranges upon activation. Comparative analysis of GPCR crystal structures independently confirms the striking conservation of water-mediated interaction networks. These conserved water-mediated interactions near the G protein-coupling region, along with diverse water-mediated interactions with extracellular ligands, have direct implications for structure-based drug design and GPCR engineering.

biophysics↗