Atomistic simulations of cardiac troponin with phosphorylation andmutation effects

Abstract

Cardiac troponin, the regulator of the striated muscle contraction process in sarcomere, plays an important role in the heart's circulation function. Phosphorylation of the cardiac troponin I by protein kinase A decreases troponin's calcium sensitivity and reduces the muscle relaxation time constant under beta-adrenergic signalling. This phosphorylation-induced lusitropic effect is disrupted by single amino-acid mutations in the thin filament which are the main causes of many genetic cardiomyopathies that can lead to unexpected heart failures or sudden death.

Experimentally, epigallocatechin-3 gallate (EGCG) and its analogues were shown to be able to restore the coupled relationship between calcium sensitivity and troponin's phosphorylation states in the diseased mutants. It is therefore of great interest to elucidate how phosphorylation at serines 22 and 23 of troponin I modulates muscle contractility and discover potential treatments for cardiomyopathies caused by mutations. However, this has been difficult because the key regulatory segments of cTn, especially cTnI 1-33, are disordered and absent from the crystal structures. A complete molecular mechanism of phosphorylation-dependent troponin dynamics is still unknown owing to the current limitations of experiments where only a partial structure or a static structure can be obtained.

Molecular dynamics (MD) simulation has gained popularity in recent years. The rapid increase in available computational resources has allowed the simulations of a more complete structure of troponin over a longer timescale. This study aims to discover the molecular mechanisms of phosphorylation effects in the wild-type and disease-causing mutations with MD simulation. Here I present the key results discovered from our all-atom MD simulations of the core of the troponin complex including the major changes in troponin's molecular interactions caused by phosphorylation and the TNNC1 G159D mutation. Additional work was conducted to include small molecules in the simulations to study the structural and dynamic changes in troponin due to ligand interactions. Finally, I propose a new method for analysing residue interaction networks based on the concept of Granger causality.