Paradoxical SERCA dysregulation contributes to atrial fibrillation in a model of diet-induced obesity.

Obesity is a major risk factor for atrial fibrillation (AF) the most common serious cardiac arrhythmia, but the molecular mechanisms underlying diet-induced AF remain unclear. In this study, we subjected mice to a chronic high-fat diet and acute sympathetic activation ('two-hit' model) to study the mechanisms by which diet-induced obesity promotes AF. Surface electrocardiography revealed that diet-induced obesity and sympathetic activation synergize during intracardiac tachypacing to induce AF. At the cellular level, diet-induced obesity and acute adrenergic stimulation facilitate the formation of delayed afterdepolarizations in atrial myocytes, implicating altered Ca2+ dynamics as the underlying cause of AF. We found that diet-induced obesity does not alter the expression of major Ca2+-handling proteins in atria, including the sarcoplasmic reticulum Ca2+-ATPase (SERCA), a major component of beat-to-beat Ca2+ cycling in the heart. Paradoxically, obesity reduces phospholamban phosphorylation, suggesting decreased SERCA activity, yet atrial myocytes from obese mice showed a significantly increased Ca2+ transient amplitude and SERCA-mediated Ca2+ uptake. Adrenergic stimulation further increases the Ca2+ transient amplitude but does not affect Ca2+ reuptake in atrial myocytes from obese mice. Transcriptomics analysis showed that a high-fat diet prompts upregulation of neuronatin, a protein that has been implicated in obesity and is known to stimulate SERCA activity. We propose a mechanism in which obesity primes SERCA for paradoxical activation, and adrenergic stimulation facilitates AF conversion through a Ca2+-induced Ca2+ release gain in atrial myocytes. Overall, this study links obesity, altered Ca2+ signaling, and AF, and targeting this mechanism may prove effective for treating obesity-induced AF.

Mechanisms for cardiac calcium pump activation by its substrate and a synthetic allosteric modulator using fluorescence lifetime imaging.

The discovery of allosteric modulators is an emerging paradigm in drug discovery, and signal transduction is a subtle and dynamic process that is challenging to characterize. We developed a time-correlated single photon-counting imaging approach to investigate the structural mechanisms for small-molecule activation of the cardiac sarcoplasmic reticulum Ca2+-ATPase, a pharmacologically important pump that transports Ca2+ at the expense of adenosine triphosphate (ATP) hydrolysis. We first tested whether the dissociation of sarcoplasmic reticulum Ca2+-ATPase from its regulatory protein phospholamban is required for small-molecule activation. We found that CDN1163, a validated sarcoplasmic reticulum Ca2+-ATPase activator, does not have significant effects on the stability of the sarcoplasmic reticulum Ca2+-ATPase-phospholamban complex. Time-correlated single photon-counting imaging experiments using the nonhydrolyzable ATP analog ß,γ-Methyleneadenosine 5'-triphosphate (AMP-PCP) showed ATP is an allosteric modulator of sarcoplasmic reticulum Ca2+-ATPase, increasing the fraction of catalytically competent structures at physiologically relevant Ca2+ concentrations. Unlike ATP, CDN1163 alone has no significant effects on the Ca2+-dependent shifts in the structural populations of sarcoplasmic reticulum Ca2+-ATPase, and it does not increase the pump's affinity for Ca2+ ions. However, we found that CDN1163 enhances the ATP-mediated modulatory effects to increase the population of catalytically competent sarcoplasmic reticulum Ca2+-ATPase structures. Importantly, this structural shift occurs within the physiological window of Ca2+ concentrations at which sarcoplasmic reticulum Ca2+-ATPase operates. We demonstrated that ATP is both a substrate and modulator of sarcoplasmic reticulum Ca2+-ATPase and showed that CDN1163 and ATP act synergistically to populate sarcoplasmic reticulum Ca2+-ATPase structures that are primed for phosphorylation. This study provides novel insights into the structural mechanisms for sarcoplasmic reticulum Ca2+-ATPase activation by its substrate and a synthetic allosteric modulator.

A novel machine learning-based screening identifies statins as inhibitors of the calcium pump SERCA.

We report a novel small-molecule screening approach that combines data augmentation and machine learning to identify Food and Drug Administration (FDA)-approved drugs interacting with the calcium pump (Sarcoplasmic reticulum Ca2+-ATPase, SERCA) from skeletal (SERCA1a) and cardiac (SERCA2a) muscle. This approach uses information about small-molecule effectors to map and probe the chemical space of pharmacological targets, thus allowing to screen with high precision large databases of small molecules, including approved and investigational drugs. We chose SERCA because it plays a major role in the excitation-contraction-relaxation cycle in muscle and it represents a major target in both skeletal and cardiac muscle. The machine learning model predicted that SERCA1a and SERCA2a are pharmacological targets for seven statins, a group of FDA-approved 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors used in the clinic as lipid-lowering medications. We validated the machine learning predictions by using in vitro ATPase assays to show that several FDA-approved statins are partial inhibitors of SERCA1a and SERCA2a. Complementary atomistic simulations predict that these drugs bind to two different allosteric sites of the pump. Our findings suggest that SERCA-mediated Ca2+ transport may be targeted by some statins (e.g., atorvastatin), thus providing a molecular pathway to explain statin-associated toxicity reported in the literature. These studies show the applicability of data augmentation and machine learning-based screening as a general platform for the identification of off-target interactions and the applicability of this approach extends to drug discovery.