Multiscale modeling shows how 2'-deoxy-ATP rescues ventricular function in heart failure

Abstract

2'-deoxy-ATP (dATP) improves cardiac function by increasing the rate of crossbridge cycling and Ca[Formula: see text] transient decay. However, the mechanisms of these effects and how therapeutic responses to dATP are achieved when dATP is only a small fraction of the total ATP pool remain poorly understood. Here, we used a multiscale computational modeling approach to analyze the mechanisms by which dATP improves ventricular function. We integrated atomistic simulations of prepowerstroke myosin and actomyosin association, filament-scale Markov state modeling of sarcomere mechanics, cell-scale analysis of myocyte Ca[Formula: see text] dynamics and contraction, organ-scale modeling of biventricular mechanoenergetics, and systems level modeling of circulatory dynamics. Molecular and Brownian dynamics simulations showed that dATP increases the actomyosin association rate by 1.9 fold. Markov state models predicted that dATP increases the pool of myosin heads available for crossbridge cycling, increasing steady-state force development at low dATP fractions by 1.3 fold due to mechanosensing and nearest-neighbor cooperativity. This was found to be the dominant mechanism by which small amounts of dATP can improve contractile function at myofilament to organ scales. Together with faster myocyte Ca[Formula: see text] handling, this led to improved ventricular contractility, especially in a failing heart model in which dATP increased ejection fraction by 16% and the energy efficiency of cardiac contraction by 1%. This work represents a complete multiscale model analysis of a small molecule myosin modulator from single molecule to organ system biophysics and elucidates how the molecular mechanisms of dATP may improve cardiovascular function in heart failure with reduced ejection fraction.

Keywords: cardiac function; dATP; multiscale modeling; myosin; sarcomere.

Fig. 1.

Multiscale modeling overview. Gray arrows indicate coupling between models. MD simulations of ATP–myosin and dATP–myosin binding to actin (A) in combination with BD simulations (B) were utilized to determine myosin.actin association rate, which was used to constrain a spatially explicit model of cooperative sarcomere mechanics (C). The effects of dATP on myosin predicted by this model were extended to a myocyte model containing an implicit sarcomere mechanics model (D), which is driven by experimental Ca²⁺ data, and is coupled to a mitochondrial energetics model (E). The myocyte model [(D and E), and experimental Ca²⁺ data] is embedded within a biventricular mechanics and hemodynamics model of the failing heart (F).

Fig. 2.

MD simulations and MSM demonstrate that binding of dATP may stabilize the prepowerstroke myosin head compared with binding of ATP, increasing its affinity for actin. (A) Correlation analysis between input features from MD simulations (distances between key structural features on myosin) and first (0) and second (1) tICA components. Clustered with “City-Block” metric. Full region feature descriptions can be found in SI Appendix, Fig. S2. Center of mass is abbreviated as COM, and alpha carbons are abbreviated as CA. (B and C) tICA space visualization of MD simulations, with three metastable states shown for each MSM based on first and second tICA components. Arrows represent flux between states. (D) RMSF shown for ATP and dATP, averaged across three MD trajectories for each. Regions of interest on myosin are highlighted. (E) Mean first passage times between metastable states shown in (B) of ATP-bound myosin simulations (ns). (F) Mean first passage times between metastable states shown in (C) of dATP-bound myosin simulations (ns). (G) Representative conformations from three metastable states for ATP-bound myosin. (H) Representative conformations from three metastable states for dATP-bound myosin. Loop 2 is colored in green in (G and H). (I) Binding rate constant estimates of myosin binding to actin using BD simulations.

Fig. 3.

dATP increases the pool of myosin available for crossbridge cycling, which leads to disproportionate increases in force with 1% dATP. (A) Model-predicted force-pCa curves are shown for ATP (purple) and 1% dATP (teal). ATP curve was fit to experimental steady-state force-pCa data from ref. . dATP simulation includes increases in actomyosin association rate ($k_f^{+}$), powerstroke rate ($k_p^{+}$), and detachment rate ($k_g^{+}$), as well as increased force-dependent recruitment of myosin ($k_{\text{recruit}}$). Effects of setting cooperative parameters ${\gamma }_B$ and ${\mu }_M$ to one, thus removing their effects from the model, are also shown. (B) Relative contributions of increased crossbridge binding and cycling and increased myosin recruitment to increases in maximum steady-state force (at pCa 4.0) relative to ATP. Differences are expressed as percentages relative to ATP. Full simulation results are shown in SI Appendix, Fig. S8.

Fig. 4.

Increased myosin recruitment and Ca²⁺ sequestering dynamics are needed to explain improvements in myocyte contractility and lusitropy with elevated dATP. (A) Model-simulated Ca²⁺ transients for ATP (purple) and dATP (teal), based on average experimental data from refs. and . (B) Cell shortening simulations for ATP (purple) and 1% dATP (teal), including increased crossbridge binding (increasing $k_f^{+}$) and cycling (increasing $k_f^{-}$ and $k_w^{+}$), faster Ca²⁺ dynamics [shown in (A)], and increased myosin recruitment (increasing $k_{\text{recruit}}$). (C) Relative contributions of increased crossbridge binding and cycling, faster Ca²⁺ dynamics, and increased myosin recruitment to changes in FS, RT50, and RT90 compared with average experimental data from refs. and . Baseline experimental ATP values are shown as purple dashed lines, and experimental dATP values are shown as teal dashed lines. Differences are expressed as percentages relative to ATP. Full simulation results are shown in SI Appendix, Fig. S15.

Fig. 5.

Increased myosin recruitment leads to improvements in ventricular contractility with elevated dATP. (A) Model-simulated average calcium transients for ATP (purple) and dATP (teal), based on experimental data from refs. and . (B) Pressure volume loops for ATP (purple) and 1% dATP (teal), including increased crossbridge binding (increasing $k_f^{+}$) and cycling (increasing $k_f^{-}$ and $k_w^{+}$), faster Ca²⁺ dynamics [shown in (A)], and increased myosin recruitment (increasing $k_{\text{recruit}}$). (C) Relative contributions of increased crossbridge binding and cycling, faster Ca²⁺ dynamics, and increased myosin recruitment to changes in EF compared with experimental data from ref. . Baseline experimental ATP values are shown as purple dashed lines, and experimental dATP values are shown as teal dashed lines. Differences are expressed as percentages relative to ATP. Full simulation results are shown in SI Appendix, Fig. S19.

Fig. 6.

Elevated dATP leads to improved ventricular function in failing hearts with 1% dATP, and improves energetic efficiency. (A) Pressure–volume loops for varying ratios of dATP, including increased myosin recruitment (increasing $k_{\text{recruit}}$), crossbridge binding (increasing $k_f^{+}$) and cycling (increasing $k_f^{-}$ and $k_w^{+}$), and Ca²⁺ sequestering dynamics with elevated dATP. Baseline ATP healthy heart simulation (fit to data from ref. 4) is shown as a purple dashed line. For HFrEF simulations, the pink dashed line is baseline HFrEF simulation, the yellow line is 20% dATP, and color gradient represents increasing ratios of dATP (1%, 2%, and 20%). Varying dATP percentages were simulated as described in Materials and Methods. (B–M) Metrics of LV mechanical function and energetics vs. dATP ratio, for the same dATP percentages as in (A).

Fig. 7.

Elevated dATP improves ventricular function, especially in the failing heart. (A–H) Effects of parameter changes on percent change in metrics of LV function and energetics with 1% dATP in healthy and failing heart simulations, shown as percent change compared to ATP. Parameter changes include increased myosin recruitment (increasing $k_{\text{recruit}}$), crossbridge binding (increasing $k_f^{+}$) and cycling (increasing $k_f^{-}$ and $k_w^{+}$), and Ca²⁺ sequestering dynamics with elevated dATP.