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    Mathematical models are useful tools in the study of physiological phenomena. However, due to differences in assumptions and formulations, discrepancy in simulations may occur. Among the models for cardiomyocyte contraction based on Huxley's cross-bridge cycling, those proposed by Negroni and Lascano (NL) and Rice et al. (RWH) are the most frequently used. This study was aimed at developing a computational tool, ForceLAB, which allows implementing different contraction models and modifying several functional parameters. As an application, electrically-stimulated twitches triggered by an equal Ca2+ input and steady-state force x pCa relationship (pCa = -log of the molar free Ca2+ concentration) simulated with the NL and RWH models were compared. The equilibrium Ca2+-troponin C (TnC) dissociation constant (Kd) was modified by changing either the association (kon) or the dissociation (koff) rate constant. With the NL model, raising Kd by either maneuver decreased monotonically twitch amplitude and duration, as expected. With the RWH model, in contrast, the same Kd variation caused increase or decrease of peak force depending on which rate constant was modified. Additionally, force x pCa curves simulated using Ca2+ binding constants estimated in cardiomyocytes bearing wild-type and mutated TnC were compared to curves previously determined in permeabilized fibers. Mutations increased kon and koff, and decreased Kd. Both models produced curves fairly comparable to the experimental ones, although sensitivity to Ca2+ was greater, especially with RWH model. The NL model reproduced slightly better the qualitative changes associated with the mutations. It is expected that this tool can be useful for teaching and investigation. Copyright © 2021 Elsevier Ltd. All rights reserved.

    Citation

    Robson Rodrigues da Silva, Osias Baptista de Souza Filho, José Wilson Magalhães Bassani, Rosana Almada Bassani. The ForceLAB simulator: Application to the comparison of current models of cardiomyocyte contraction. Computers in biology and medicine. 2021 Apr;131:104240

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    PMID: 33556894

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