cMyBPC phosphorylation modulates the effect of omecamtiv mecarbil on myocardial force generation

DeepMPSF: A Deep Learning Network for Predicting General Protein Phosphorylation Sites Based on Multiple Protein Sequence Features

Phosphorylation, as one of the most important post-translational modifications, plays a key role in various cellular physiological processes and disease occurrences. In recent years, computer technology has been gradually applied to the prediction of protein phosphorylation sites. However, most existing methods rely on simple protein sequence features that provide limited contextual information. To overcome this limitation, we propose DeepMPSF, a phosphorylation site prediction model based on multiple protein sequence features. There are two types of features: sequence semantic features, which comprise protein residue type information and relative position information within protein sequence, and protein background biophysical features, which include global semantic information containing more comprehensive protein background information obtained from pretrained models. To extract these features, DeepMPSF employs two separate subnetworks: the S71SFE module and the BBFE module, which automatically extract high-level semantic features. Our model incorporates a learning strategy for handling imbalanced datasets through ensemble learning during training and prediction. DeepMPSF is trained and evaluated on a well-established dataset of human proteins. Comparing the analysis with other benchmark methods reveals that DeepMPSF outperforms in predicting both S/T residues and Y residues. In particular, DeepMPSF showed excellent generalization performance in cross-species blind test performance, with an average improvement of 5.63%/5.72%, 22.28%/25.94%, 20.11%/17.49%, and 26.40%/28.33% for Mus musculus/Rattus norvegicus test sets in area under curves (AUCs) of ROC curve, AUC of the PR curve, F1-score, and MCC metrics, respectively. Furthermore, it also shows excellent performance in the latest updated case of natural proteins with functional phosphorylation sites. Through an ablation study and visual analysis, we uncover that the design of different feature modules significantly contributes to the accurate classification of DeepMPSF, which provides valuable insights for predicting phosphorylation sites and offers effective support for future downstream research.

Effect of the Novel Myotrope Danicamtiv on Cross-Bridge Behavior in Human Myocardium

Background Omecamtiv mecarbil (OM) and danicamtiv both increase myocardial force output by selectively activating myosin within the cardiac sarcomere. Enhanced force generation is presumably due to an increase in the total number of myosin heads bound to the actin filament; however, detailed comparisons of the molecular mechanisms of OM and danicamtiv are lacking. Methods and Results The effect of OM and danicamtiv on Ca2+ sensitivity of force generation was analyzed by exposing chemically skinned myocardial samples to a series of increasing Ca2+ solutions. The results showed that OM significantly increased Ca2+ sensitivity of force generation, whereas danicamtiv showed similar Ca2+ sensitivity of force generation to untreated preparations. A direct comparison of OM and danicamtiv on dynamic cross-bridge behavior was performed at a concentration that produced a similar force increase when normalized to predrug levels at submaximal force (pCa 6.1). Both OM and danicamtiv-treated groups slowed the rates of cross-bridge detachment from the strongly bound state and cross-bridge recruitment into the force-producing state. Notably, the significant OM-induced prolongation in the time to reach force relaxation and subsequent commencement of force generation following rapid stretch was dramatically reduced in danicamtiv-treated myocardium. Conclusions This is the first study to directly compare the effects of OM and danicamtiv on cross-bridge kinetics. At a similar level of force enhancement, danicamtiv had a less pronounced effect on the slowing of cross-bridge kinetics and, therefore, may provide a similar improvement in systolic function as OM without excessively prolonging systolic ejection time and slowing cardiac relaxation facilitating diastolic filling at the whole-organ level.

Phosphorylation Mimetic of Myosin Regulatory Light Chain Mitigates Cardiomyopathy-Induced Myofilament Impairment in Mouse Models of RCM and DCM

This study focuses on mimicking constitutive phosphorylation in the N-terminus of the myosin regulatory light chain (S15D-RLC) as a rescue strategy for mutation-induced cardiac dysfunction in transgenic (Tg) models of restrictive (RCM) and dilated (DCM) cardiomyopathy caused by mutations in essential (ELC, MYL3 gene) or regulatory (RLC, MYL2 gene) light chains of myosin. Phosphomimetic S15D-RLC was reconstituted in left ventricular papillary muscle (LVPM) fibers from two mouse models of cardiomyopathy, RCM-E143K ELC and DCM-D94A RLC, along with their corresponding Tg-ELC and Tg-RLC wild-type (WT) mice. The beneficial effects of S15D-RLC in rescuing cardiac function were manifested by the S15D-RLC-induced destabilization of the super-relaxed (SRX) state that was observed in both models of cardiomyopathy. S15D-RLC promoted a shift from the SRX state to the disordered relaxed (DRX) state, increasing the number of heads readily available to interact with actin and produce force. Additionally, S15D-RLC reconstituted with fibers demonstrated significantly higher maximal isometric force per cross-section of muscle compared with reconstitution with WT-RLC protein. The effects of the phosphomimetic S15D-RLC were compared with those observed for Omecamtiv Mecarbil (OM), a myosin activator shown to bind to the catalytic site of cardiac myosin and increase myocardial contractility. A similar SRX↔DRX equilibrium shift was observed in OM-treated fibers as in S15D-RLC-reconstituted preparations. Additionally, treatment with OM resulted in significantly higher maximal pCa 4 force per cross-section of muscle fibers in both cardiomyopathy models. Our results suggest that both treatments with S15D-RLC and OM may improve the function of myosin motors and cardiac muscle contraction in RCM-ELC and DCM-RLC mice.

The contribution of N-terminal truncated cMyBPC to in vivo cardiac function

Cardiac myosin binding protein C (cMyBPC) is an 11-domain sarcomeric protein (C0-C10) integral to cardiac muscle regulation. In vitro studies have demonstrated potential functional roles for regions beyond the N-terminus. However, the in vivo contributions of these domains are mostly unknown. Therefore, we examined the in vivo consequences of expression of N-terminal truncated cMyBPC (C3C10). Neonatal cMyBPC-/- mice were injected with AAV9-full length (FL), C3C10 cMyBPC, or saline, and echocardiography was performed 6 wk after injection. We then isolated skinned myocardium from virus-treated hearts and performed mechanical experiments. Our results show that expression of C3C10 cMyBPC in cMyBPC-/- mice resulted in a 28% increase in systolic ejection fraction compared to saline-injected cMyBPC-/- mice and a 25% decrease in left ventricle mass-to-body weight ratio. However, unlike expression of FL cMyBPC, there was no prolongation of ejection time compared to saline-injected mice. In vitro mechanical experiments demonstrated that functional improvements in cMyBPC-/- mice expressing C3C10 were primarily due to a 35% reduction in the rate of cross-bridge recruitment at submaximal Ca2+ concentrations when compared to hearts from saline-injected cMyBPC-/- mice. However, unlike the expression of FL cMyBPC, there was no change in the rate of cross-bridge detachment when compared to saline-injected mice. Our data demonstrate that regions of cMyBPC beyond the N-terminus are important for in vivo cardiac function, and have divergent effects on cross-bridge behavior. Elucidating the molecular mechanisms of cMyBPC region-specific function could allow for development of targeted approaches to manipulate specific aspects of cardiac contractile function.

Effects of omecamtiv mecarbil and mavacamten in isolated human atrium

Heart failure is a syndrome that can result from impaired heart muscle contractions like in dilative cardiomyopathy but also from hypertrophic obstructive cardiomyopathy (HOCOM). A pharmacological therapy might lie in Ca²⁺-sensitizing or Ca²⁺-desensitizing drugs, respectively. Such drugs are thought to be omecamtiv mecarbil (OME) and mavacamten (MYK-461), respectively. Their function in contracting human muscle is not fully understood and was the focus of the present study. OME from 1 nM to 10 µM cumulatively applied failed to raise force of contraction in human right atrial preparations strips (HAP) or mouse left atrial preparations (LA). However, OME prolonged time to peak tension and time of relaxation in HAP and LA but did not alter the beating rate in right atrial preparations from mice (RA). In contrast, MYK-461 (10 nM to 10 µM) reduced concentration- and time-dependently force of contraction in HAP and LA. MYK-461 (10 µM) did not affect the beating rate in RA. In summary, the present data failed to detect an increase in force of contraction for OME, in human and mouse atrium. In contrast, a Ca²⁺ desensitizer studied for comparison was able to reduce force of contraction in HAP and LA. We conclude that putative beneficial effects of OME in dilated cardiomyopathy cannot be explained by positive inotropic effects in the HAP, whereas beneficial functional effects of MYK-461 in HOCOM can be explained by negative inotropic effects in HAP.

Generative adversarial networks for construction of virtual populations of mechanistic models: simulations to study Omecamtiv Mecarbil action

Biophysical models are increasingly used to gain mechanistic insights by fitting and reproducing experimental and clinical data. The inherent variability in the recorded datasets, however, presents a key challenge. In this study, we present a novel approach, which integrates mechanistic modeling and machine learning to analyze in vitro cardiac mechanics data and solve the inverse problem of model parameter inference. We designed a novel generative adversarial network (GAN) and employed it to construct virtual populations of cardiac ventricular myocyte models in order to study the action of Omecamtiv Mecarbil (OM), a positive cardiac inotrope. Populations of models were calibrated from mechanically unloaded myocyte shortening recordings obtained in experiments on rat myocytes in the presence and absence of OM. The GAN was able to infer model parameters while incorporating prior information about which model parameters OM targets. The generated populations of models reproduced variations in myocyte contraction recorded during in vitro experiments and provided improved understanding of OM’s mechanism of action. Inverse mapping of the experimental data using our approach suggests a novel action of OM, whereby it modifies interactions between myosin and tropomyosin proteins. To validate our approach, the inferred model parameters were used to replicate other in vitro experimental protocols, such as skinned preparations demonstrating an increase in calcium sensitivity and a decrease in the Hill coefficient of the force–calcium (F–Ca) curve under OM action. Our approach thereby facilitated the identification of the mechanistic underpinnings of experimental observations and the exploration of different hypotheses regarding variability in this complex biological system.

cMyBPC phosphorylation alters response to heart failure drug

JGP study shows that the phosphorylation state of cMyBPC modulates the ability of omecamtiv mecarbil to enhance myocardial force generation.