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Modeling the Actin.myosin ATPase cross-bridge cycle for skeletal and cardiac muscle myosin isoforms

Mijailovich, S.M., Nedic, D., Svicevic, M., Stojanovic, B., Walklate, J., Ujfalusi, Z., Geeves, M.A. (2017) Modeling the Actin.myosin ATPase cross-bridge cycle for skeletal and cardiac muscle myosin isoforms. Biophysical Journal, 112 (5). pp. 984-996. ISSN 0006-3495. E-ISSN 1542-0086. (doi:10.1016/j.bpj.2017.01.021) (KAR id:60553)

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Modeling the complete actin.myosin ATPase cycle has always been limited by the lack of experimental data concerning key steps of the cycle, because these steps can only be defined at very low ionic strength. Here, using human ?-cardiac myosin-S1, we combine published data from transient and steady-state kinetics to model a minimal eight-state ATPase cycle. The model illustrates the occupancy of each intermediate around the cycle and how the occupancy is altered by changes in actin concentration for [actin] = 1–20Km. The cycle can be used to predict the maximal velocity of contraction (by motility assay or sarcomeric shortening) at different actin concentrations (which is consistent with experimental velocity data) and predict the effect of a 5 pN load on a single motor. The same exercise was repeated for human ?-cardiac myosin S1 and rabbit fast skeletal muscle S1. The data illustrates how the motor domain properties can alter the ATPase cycle and hence the occupancy of the key states in the cycle. These in turn alter the predicted mechanical response of the myosin independent of other factors present in a sarcomere, such as filament stiffness and regulatory proteins. We also explore the potential of this modeling approach for the study of mutations in human ?-cardiac myosin using the hypertrophic myopathy mutation R453C. Our modeling, using the transient kinetic data, predicts mechanical properties of the motor that are compatible with the single-molecule study. The modeling approach may therefore be of wide use for predicting the properties of myosin mutations.

Item Type: Article
DOI/Identification number: 10.1016/j.bpj.2017.01.021
Subjects: Q Science
Divisions: Divisions > Division of Natural Sciences > School of Biosciences
Depositing User: Susan Davies
Date Deposited: 27 Feb 2017 10:25 UTC
Last Modified: 23 Jan 2020 04:12 UTC
Resource URI: (The current URI for this page, for reference purposes)
Geeves, M.A.:
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