MUSICO: An in silico platform for evaluating the effects of disease and drug effectiveness in HCM and DCM cardiomyopathies

SUMMARY ABSTRACT Cardiovascular diseases, including hypertrophic and dilated cardiomyopathies (HCM and DCM), are leading global causes of death, imposing significant societal and economic burdens. Current therapies focus primarily on symptom management rather than addressing root causes. Mutations within sarcomeric proteins, which account for approximately 30-60% of cardiomyopathies, emphasize the critical role of acto-myosin interactions and sarcomere regulation in these conditions. Despite this understanding, developing effective treatments remains costly, prone to late-stage failures, and limited in predicting outcomes in humans. There is an urgent need to identify and eliminate ineffective drug candidates earlier in the development process. To address these challenges, we present MUSICO (MUscle SImulation COde), a state-of-the-art in silico platform designed to integrate diverse experimental data and predict muscle behavior across multiple scales and species, from molecular interactions to whole heart function. The platform incorporates “translational matrix” (TM) method, effectively converting in vitro animal model data into relevant human in vivo insights, enabling comprehensive data utilization and robust cross-species correlations. This project (Phase 1) aims to demonstrate the MUSICO platform’s predictive capabilities for four novel drugs currently in various stages of development, preparing it for commercial drug discovery applications. Specifically, we will conduct rodent studies using demembranated trabeculae measurements, force-pCa, and intact twitch measurements, as well as twitch experiments with human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) and engineered heart tissue (EHT). Additionally, we will collect crucial data from porcine heart muscles through X-ray diffraction experiments (Aim 1). These experimental data will be integrated with MUSICO simulations to validate the platform’s accuracy in predicting the effects of myosin activators Danicamtiv (Dani) and 2’-deoxy-ATP (dATP) for treating DCM, and Aficamten (Afi) and a novel myosin inhibitor (RLC-1) for treating HCM (Aim 2). Finally, we will develop a commercialization strategy, including establishing connections with potential clients such as pharmaceutical companies, CROs, and academic labs (Aim 3). This will strongly enhance our capabilities for Phase 2 of the SBIR program. The extensive simulations conducted in Phases 1 and 2 will enable the creation of a standardized database, automating predictions and providing valuable insights into the effects of genetic mutations and drugs, ultimately guiding more effective treatment strategies for cardiomyopathies. MUSICO has already shown promise in accurately predicting muscle behavior affected by mutations and drugs before experimental confirmation. We successfully demonstrated the mechanism of mavacamten action even before it was experimentally confirmed. By reducing reliance on animal and human trials and translating data across species, this project will further establish MUSICO’s potential as a powerful tool in drug discovery and personalized medicine.