Key result
A combination of diffusional encounter and internal buried channel descriptions provides superior descriptions of association rates for calcium binding in troponin C and SERCA, improving estimates by orders of magnitude.
A novel computational pipeline improves the estimation of protein-ligand association rates for calcium-binding proteins like Troponin C and SERCA by orders of magnitude.
Advances computational estimates of cardiac calcium kinetics; hypothesis-generating and requires experimental validation before clinical relevance.
We introduce a computational pipeline and suite of software tools for the approximation of diffusion-limited binding based on a recently developed theoretical framework. Our approach handles molecular geometries generated from high-resolution structural data and can account for active sites buried within the protein or behind gating mechanisms. Using tools from the FEniCS library and the APBS solver, we implement a numerical code for our method and study two Ca(2+)-binding proteins: Troponin C and the Sarcoplasmic Reticulum Ca(2+) ATPase (SERCA). We find that a combination of diffusional encounter and internal 'buried channel' descriptions provide superior descriptions of association rates, improving estimates by orders of magnitude.
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Kekenes–Huskey et al. (2012) studied Calcium binding in troponin C and SERCA. Finite-element estimation of protein-ligand association rates with post-encounter effects vs. Standard diffusional encounter models was evaluated on Association rates (kon). A combination of diffusional encounter and internal buried channel descriptions provides superior descriptions of association rates for calcium binding in troponin C and SERCA, improving estimates by orders of magnitude.
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