Biology subjects

DeMarco, K. R.

Publications and source records attributed to DeMarco, K. R..

4 recordsLinked to original sources

bioRxiv2023

Modeling stereospecific drug interactions with beta-adrenergic receptors

Beta adrenergic receptors ({beta}ARs) are G protein-coupled receptors that control processes as varied as heart rhythm and vascular tone by binding agonists such as norepinephrine to induce downstream signaling pathways. Beta blockers antagonize {beta}ARs to downregulate their activity, thus reducing heart rate and lowering vascular tone. We developed new Rosetta structural modeling protocol to develop state-specific models of {beta}1AR, expressed in cardiac myocytes, as well as {beta}2AR, expressed in the smooth muscle cells of vasculature and other tissues, and their atomistic-scale interactions with beta-blockers using RosettaLigand. We identified structural features of drug - receptor interactions, which may account for their receptor conformational state and drug stereospecific preferences. Furthermore, we estimated structural stabilities of our models using atomistic molecular dynamics (MD) simulations. In our recent study we validated our structural models of norepinephrine-bound {beta}2AR and its complex with stimulatory G protein via multi-microsecond MD simulations. Thus, here we mostly focused on state-dependent and stereospecific {beta}1AR interactions with beta-blocking drugs sotalol and propranolol. We observed expected inactive receptor state preferences and structural stabilities of our models in MD simulations, but neither those simulations nor RosettaLigand docking could clearly distinguish stereospecific preferences of those drugs. This warrants consideration of alternative hypotheses and enhanced sampling MD simulations, which we discussed as well. Nevertheless, our study provides basis for understanding conformational state selectivity and stereospecificity of beta-blockers for {beta}ARs, important pharmacological targets, and may be extended to other drug classes and receptor types. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=157 SRC="FIGDIR/small/560334v1_fig0.gif" ALT="Figure 0"> View larger version (82K): org.highwire.dtl.DTLVardef@e8a838org.highwire.dtl.DTLVardef@7c2743org.highwire.dtl.DTLVardef@f5ac43org.highwire.dtl.DTLVardef@100a3d3_HPS_FORMAT_FIGEXP M_FIG Norepinephrine (NE) bound active-state beta-1 adrenergic receptor (1AR) in complex with the stimulatory G protein (Gs) heterotrimer embedded in a lipid bilayer. When expressed at the plasma membrane, the 1AR is oriented such that the ligand binding pocket (*) is accessible to ligands from the extracellular side (Ex.) of the membrane. The Gs (red), G (blue), and G{gamma} (yellow) subunits comprise the Gs heterotrimer. Nucleotides GDP or GTP bind G at the P-loop (**). Inset: Representative image of NE bound within the orthosteric ligand binding pocket. C_FIG

molecular biology↗

bioRxiv2019

Atomistic modeling towards predictive cardiotoxicity

Current methods for assessing safety pharmacology in the context of cardiac arrhythmia risk are unable to distinguish between drugs that cause cardiac rhythm disturbances and benign drugs. Drugs deemed likely to be unsafe share the common property of blocking the human Ether-a-go-go-Related Gene (hERG) encoded cardiac potassium channel and consequent prolongation of QT interval on the ECG. However, hERG block and QT prolongation alone are not selective indicators for cardiac arrhythmia. Here we present a prototype computational framework to distinguish between safe and unsafe hERG blockers. We used recent cryo-EM hERG structure to build and validate an atomistic structural model of the channel open conducting state. We also developed structural atomistic models of dofetilide, a hERG blocking drug with high pro-arrhythmia risk, in both charged and neutral ionization states. Next, we employed unbiased and enhanced sampling all-atom molecular dynamics (MD) simulations to probe atomic-scale mechanisms of dofetilide interaction with open-state hERG. Multi-microsecond drug \"flooding\" simulations revealed spontaneous dofetilide binding to the channel pore through the intracellular gate. Umbrella sampling MD was used to compute dofetilide affinity to hERG, in good agreement with experiment, as well as ingress and egress rates, which in a novel linkage between the atomistic and functional scale are utilized in our companion paper (Yang P-C et al. 2019 bioRxiv:635433) to parameterize functional kinetic models of dofetilide - hERG interactions used to predict emergent drug effects on the cardiac rhythm. This study represents the first necessary components of a computational framework for virtual cardiac safety pharmacology screening from the atom to the rhythm.

biophysics↗

bioRxiv2019

A computational pipeline to predict cardiotoxicity:From the atom to the rhythm

We simulate and predict cardiotoxicity over multiple temporal and spatial scales from the drug chemistry to the cardiac rhythm.\n\nABSTRACTDrug-induced proarrhythmia is so tightly associated with prolongation of the QT interval that QT prolongation has become widely accepted as a surrogate marker for arrhythmia. The problem is that QT interval as an arrhythmia indicator is too sensitive and not selective, resulting in many potentially useful drugs eliminated early in the drug discovery process. We first set out to predict the fundamental mode of binding for the proarrhythmic drug dofetilide with the promiscuous cardiac drug target, the hERG potassium channel. In a novel linkage between the atomistic and functional scales, computed binding affinities and rates from atomistic simulation are utilized here to parameterize function scale kinetic models of dofetilide interactions with the hERG channel. The kinetic model components are then integrated into predictive models at the cell and tissue scales to expose fundamental arrhythmia vulnerability mechanisms and complex interactions underlying emergent behaviors. Human clinical data from published studies were used to validate model framework and showed excellent agreement, demonstrating feasibility of the approach. The model predictions show that a clinically relevant dose of dofetilide increased arrhythmia vulnerability in all emergent TRIaD-linked parameters including Triangulation, Reverse use-dependence, beat-to-beat Instability and temporal and spatial action potential duration Dispersion. Application of machine learning demonstrated redundancy in the TRIaD linked parameters and suggested that changes in beat-to-beat instability were highly predictive of arrhythmia vulnerability in this setting. Here, we demonstrate the development and validation of a prototype multiscale model framework to predict electro-toxicity in the heart for the proarrhythmic drug dofetilide from the atom to the rhythm.\n\nSIGNIFICANCE STATEMENTCardiotoxicity in the form of deadly abnormal rhythms is one of the most common and dangerous risks for drugs in development and clinical use. There is an urgent need for new approaches to screen and predict the effects of chemically similar drugs on the cardiac rhythm and to move beyond the QT interval as a diagnostic indicator for arrhythmia. To this end, we present a computational pipeline to predict cardiotoxicity over multiple temporal and spatial scales from the drug chemistry to the cardiac rhythm. We utilize predicted quantitative estimates of ion channel-drug interactions from our companion paper to simulate cardiotoxicity over multiple temporal and spatial scales from the drug chemistry to the cardiac rhythm.

systems biology↗

bioRxiv2018

Structural Basis for Antiarrhythmic Drug Interactions with the Human Cardiac Sodium Channel

The human voltage-gated sodium channel, hNav1.5, is responsible for the rapid upstroke of the cardiac action potential and is target for antiarrhythmic therapy. Despite the clinical relevance of hNav1.5 targeting drugs, structure-based molecular mechanisms of promising or problematic drugs have not been investigated at atomic scale to inform drug design. Here, we used Rosetta structural modeling and docking as well as molecular dynamics simulations to study the interactions of antiarrhythmic and local anesthetic drugs with hNav1.5. These calculations revealed several key drug binding sites formed within the pore lumen that can simultaneously accommodate up to two drug molecules. Molecular dynamics simulations identified a hydrophilic access pathway through the intracellular gate and a hydrophobic access pathway through a fenestration between domains III and IV. Our results advance the understanding of molecular mechanisms of antiarrhythmic and local anesthetic drug interactions with hNav1.5 and will be useful for rational design of novel therapeutics.

biophysics↗