Whole length myosin binding protein C stabilizes myosin S2 as measured by gravitational force spectroscopy

Mutations in myosin S2 alter cardiac myosin-binding protein-C interaction in hypertrophic cardiomyopathy in a phosphorylation-dependent manner

Hypertrophic cardiomyopathy (HCM) is an inherited cardiovascular disorder primarily caused by mutations in the β-myosin heavy-chain gene. The proximal subfragment 2 region (S2), 126 amino acids of myosin, binds with the C0-C2 region of cardiac myosin-binding protein-C to regulate cardiac muscle contractility in a manner dependent on PKA-mediated phosphorylation. However, it is unknown if HCM-associated mutations within S2 dysregulate actomyosin dynamics by disrupting its interaction with C0-C2, ultimately leading to HCM. Herein, we study three S2 mutations known to cause HCM: R870H, E924K, and E930Δ. First, experiments using recombinant proteins, solid-phase binding, and isothermal titrating calorimetry assays independently revealed that mutant S2 proteins displayed significantly reduced binding with C0-C2. In addition, CD revealed greater instability of the coiled-coil structure in mutant S2 proteins compared with S2^Wt proteins. Second, mutant S2 exhibited 5-fold greater affinity for PKA-treated C0-C2 proteins. Third, skinned papillary muscle fibers treated with mutant S2 proteins showed no change in the rate of force redevelopment as a measure of actin–myosin cross-bridge kinetics, whereas S2^Wt showed increased the rate of force redevelopment. In summary, S2 and C0-C2 interaction mediated by phosphorylation is altered by mutations in S2, which augment the speed and force of contraction observed in HCM. Modulating this interaction could be a potential strategy to treat HCM in the future.

Demographic model for inheritable cardiac disease

The cardiac muscle proteins, generating and regulating energy transduction during a heartbeat, assemble in the sarcomere into a cyclical machine repetitively translating actin relative to myosin filaments. Myosin is the motor transducing ATP free energy into actin movement against resisting force. Cardiac myosin binding protein C (mybpc3) regulates shortening velocity probably by transient N-terminus binding to actin while its C-terminus strongly binds the myosin filament. Inheritable heart disease associated mutants frequently modify these proteins involving them in disease mechanisms. Nonsynonymous single nucleotide polymorphisms (SNPs) cause single residue substitutions with independent characteristics (sequence location, residue substitution, human demographic, and allele frequency) hypothesized to decide dependent phenotype and pathogenicity characteristics in a feed-forward neural network model. Trial models train and validate on a dynamic worldwide SNP database for cardiac muscle proteins then predict phenotype and pathogenicity for any single residue substitution in myosin, mybpc3, or actin. A separate Bayesian model formulates conditional probabilities for phenotype or pathogenicity given independent SNP characteristics. Neural/Bayes forecasting tests SNP pathogenicity vs (in)dependent SNP characteristics to assess individualized disease risk and in particular to elucidate gender and human subpopulation bias in disease. Evident subpopulation bias in myosin SNP pathogenicities imply myosin normally engages multiple sarcomere proteins functionally. Consistent with this observation, mybpc3 forms a third actomyosin interaction competing with myosin essential light chain N-terminus suggesting a novel strain-dependent mechanism adapting myosin force-velocity to load dynamics. The working models, and the integral myosin/mybpc3 motor concept, portends the wider considerations involved in understanding heart disease as a systemic maladaptation.

Skeletal myosin binding protein-C: An increasingly important regulator of striated muscle physiology

The Myosin Binding Protein-C (MyBP-C) family is a group of sarcomeric proteins important for striated muscle structure and function. Comprising approximately 2% of the myofilament mass, MyBP-C has important roles in both contraction and relaxation. Three paralogs of MyBP-C are encoded by separate genes with distinct expression profiles in striated muscle. In mammals, cardiac MyBP-C is limited to the heart, and it is the most extensively studied owing to its involvement in cardiomyopathies. However, the roles of two skeletal paralogs, slow and fast, in muscle biology remain poorly characterized. Nonetheless, both have been recently implicated in the development of skeletal myopathies. This calls for a better understanding of their function in the pathophysiology of distal arthrogryposis. This review characterizes MyBP-C as a whole and points out knowledge gaps that still remain with respect to skeletal MyBP-C.

Neural/Bayes network predictor for inheritable cardiac disease pathogenicity and phenotype

The cardiac muscle sarcomere contains multiple proteins contributing to contraction energy transduction and its regulation during a heartbeat. Inheritable heart disease mutants affect most of them but none more frequently than the ventricular myosin motor and cardiac myosin binding protein c (mybpc3). These co-localizing proteins have mybpc3 playing a regulatory role to the energy transducing motor. Residue substitution and functional domain assignment of each mutation in the protein sequence decides, under the direction of a sensible disease model, phenotype and pathogenicity. The unknown model mechanism is decided here using a method combing neural and Bayes networks. Missense single nucleotide polymorphisms (SNPs) are clues for the disease mechanism summarized in an extensive database collecting mutant sequence location and residue substitution as independent variables that imply the dependent disease phenotype and pathogenicity characteristics in 4 dimensional data points (4ddps). The SNP database contains entries with the majority having one or both dependent data entries unfulfilled. A neural network relating causes (mutant residue location and substitution) and effects (phenotype and pathogenicity) is trained, validated, and optimized using fulfilled 4ddps. It then predicts unfulfilled 4ddps providing the implicit disease model. A discrete Bayes network interprets fulfilled and predicted 4ddps with conditional probabilities for phenotype and pathogenicity given mutation location and residue substitution thus relating the neural network implicit model to explicit features of the motor and mybpc3 sequence and structural domains. Neural/Bayes network forecasting automates disease mechanism modeling by leveraging the world wide human missense SNP database that is in place and expanding.

Data on whole length myosin binding protein C stabilizes myosin S2 as measured by gravitational force spectroscopy

Data presented in this article relates to the research article entitled “Whole length myosin binding protein C stabilizes myosin subfragment-2 (S2) flexibility as measured by gravitational force spectroscopy.” (Singh et al., 2018) [1]. The data exhibits the purified skeletal myosin binding protein C (MyBPC) from rabbit back muscle was of slow skeletal type confirmed by chromatography and in unphosphorylated state based on its isoelectric point (pI) by chromatofocussing. The competitive enzyme linked immunosorbent assay (cELISA) data displayed the site specificity of polyclonal anti-S2 antibody to myosin S2. This polyclonal antibody binding site corresponds to a familial hypertrophic cardiomyopathy (FHC) point mutation hotspot on myosin S2 illustrated in a figure of compiled data.