Reverse engineering of mechano-kinetic parameters from stochastic force profiles in heterogeneous ensembles of molecular motors and tracks

Abstract

Heterogeneity in contractile systems of molecular motors interacting with their tracks plays a key role in numerous cellular physiological and pathological processes. However, its effects cannot be captured by theoretical models assuming identical mechano-kinetic properties for all motors. We developed a stochastic framework to describe heterogeneous ensembles of myosin motors comprising two populations with distinct mechano-kinetic properties. Assuming that motors interact with the actin filament (their track) as independent force generators, we derived the probability distribution of the isometric force and characterised the statistics of finite-size force fluctuations. The proposed framework includes an estimation procedure that simultaneously infers the mechano-kinetic parameters and the size of the motor ensemble, eliminating the need to prescribe it a priori. Validation against synthetic and experimental data shows the model accurately captures force fluctuations and provides realistic estimates of the ensemble size. Furthermore, the framework enables a quantitative assessment of ensemble heterogeneity and the inference of an unknown motor species properties. This approach provides a quantitative tool for characterising heterogeneous actin-myosin systems, such as those arising from the co-presence of different protein isoforms in cardiac and skeletal muscle, or from the partial replacement of native proteins with mutation-derived or engineered variants.