No abstract

Compartmentalized cAMP/PKA signalling is now recognized as important for physiology and pathophysiology, yet a detailed understanding of the properties, regulation and function of local cAMP/PKA signals is lacking. Here we present a fluorescence resonance energy transfer (FRET)-based sensor, CUTie, which detects compartmentalized cAMP with unprecedented accuracy. CUTie, targeted to specific multiprotein complexes at discrete plasmalemmal, sarcoplasmic reticular and myofilament sites, reveals differential kinetics and amplitudes of localized cAMP signals. This nanoscopic heterogeneity of cAMP signals is necessary to optimize cardiac contractility upon adrenergic activation. At low adrenergic levels, and those mimicking heart failure, differential local cAMP responses are exacerbated, with near abolition of cAMP signalling at certain locations. This work provides tools and fundamental mechanistic insights into subcellular adrenergic signalling in normal and pathological cardiac function.

Coarse-grain (CG) techniques allow considerable extension of the accessible size and time scales in simulations of biological systems. Although many CG representations are available for the most common biomacromolecules, very few have been reported for nucleic acids. Here, we present a CG model for molecular dynamics simulations of DNA on the multi-microsecond time scale. Our model maps the complexity of each nucleotide onto six effective superatoms keeping the "chemical sense" of specific Watson-Crick recognition. Molecular interactions are evaluated using a classical Hamiltonian with explicit electrostatics calculated under the framework of the generalized Born approach. This CG representation is able to accurately reproduce experimental structures, breathing dynamics, and conformational transitions from the A to the B form in double helical fragments. The model achieves a good qualitative reproduction of temperature-driven melting and its dependence on size, ionic strength, and sequence specificity. Reconstruction of atomistic models from CG trajectories give remarkable agreement with structural, dynamic, and energetic features obtained from fully atomistic simulation, opening the possibility to acquire nearly atomic detail data from CG trajectories.

Modeling of macromolecular structures and interactions represents an important challenge for computational biology, involving different time and length scales. However, this task can be facilitated through the use of coarse-grained (CG) models, which reduce the number of degrees of freedom and allow efficient exploration of complex conformational spaces. This article presents a new CG protein model named SIRAH, developed to work with explicit solvent and to capture sequence, temperature, and ionic strength effects in a topologically unbiased manner. SIRAH is implemented in GROMACS, and interactions are calculated using a standard pairwise Hamiltonian for classical molecular dynamics simulations. We present a set of simulations that test the capability of SIRAH to produce a qualitatively correct solvation on different amino acids, hydrophilic/hydrophobic interactions, and long-range electrostatic recognition leading to spontaneous association of unstructured peptides and stable structures of single polypeptides and protein-protein complexes.

Biological processes occur on space and time scales that are often unreachable for fully atomistic simulations. Therefore, simplified or coarse grain (CG) models for the theoretical study of these systems are frequently used. In this context, the accurate description of solvation properties remains an important and challenging field. In the present work, we report a new CG model based on the transient tetrahedral structures observed in pure water. Our representation lumps approximately 11 WATer molecules into FOUR tetrahedrally interconnected beads, hence the name WAT FOUR (WT4). Each bead carries a partial charge allowing the model to explicitly consider long-range electrostatics, generating its own dielectric permittivity and obviating the shortcomings of a uniform dielectric constant. We obtained a good representation of the aqueous environment for most biologically relevant temperature conditions in the range from 278 to 328 K. The model is applied to solvate simple CG electrolytes developed in this work (Na + , K + , and Cl -) and a recently published simplified representation of nucleic acids. In both cases, we obtained a good resemblance of experimental data and atomistic simulations. In particular, the solvation structure around DNA, partial charge neutralization by counterions, preference for sodium over potassium, and ion mediated minor groove narrowing as reported from X-ray crystallography are well reproduced by the present scheme. The set of parameters presented here opens the possibility of reaching the multimicroseconds time scale, including explicit solvation, ionic specificity, and long-range electrostatics, keeping nearly atomistic resolution with significantly reduced computational cost.