Biology subjects

Bekker, S.

Publications and source records attributed to Bekker, S..

3 recordsLinked to original sources

bioRxiv2025

Diet induced insulin resistance is due to induction of PTEN expression

Insulin resistance is a condition associated with obesity, type 2 diabetes(T2D), hyperinsulinemia, hyperglycemia and defined by reduced sensitivity to insulin signaling. Molecular causes and early signaling events underlying insulin resistance are not well understood. Here we show that insulin activation of PI3K/AKT/mTOR signaling in insulin target tissues, causes mTORC1 induction of PTEN translation, a negative regulator of PI3K signaling. We hypothesized that insulin resistance is due to insulin dependent induction of PTEN that prevents further increases in PI3K signaling. In a diet induced animal model of obesity and insulin resistance, we show that PTEN levels are increased in fat, muscle, and liver. Hyperinsulinemia and PTEN induction are followed by hyperglycemia, severe glucose intolerance, and hepatic steatosis. In response to chronic hyperinsulinemia, PTEN remains increased, while AKT activity is induced transiently before settling down to a PTEN-high and AKT-low state in the tissues, predicted by computational modeling of the PTEN-AKT feedback loop. Treatment with PTEN and mTORC1 inhibitors prevent and reverse the effect of PTEN induction, rescue insulin resistance and increase PI3K/AKT signaling. Thus, we show that PTEN induction by increased insulin levels elevates feedback inhibition of the pathway causing insulin resistance, its associated phenotypes, and is a potential therapeutic target.

cell biology↗

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↗