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.

A new version of the coarse-grained (CG) SIRAH force field for proteins has been developed. Modifications to bonded and non-bonded interactions on the existing molecular topologies significantly ameliorate the structural description and flexibility of a non-redundant set of proteins. The SIRAH 2.0 force field has also been ported to the popular simulation package AMBER, which along with the former implementation in GROMACS expands significantly the potential range of users and performance of this CG force field on CPU/GPU codes. As a non-trivial example of application, we undertook the structural and dynamical analysis of the most abundant and conserved calcium-binding protein, namely, Calmodulin (CaM). CaM is constituted by two calcium-binding motifs called EF-hands, which in presence of Calcium specifically recognize a cognate peptide by embracing it. CG simulations of CaM bound to four Calcium ions in the presence or absence of a binding peptide (holo and apo forms, respectively), resulted in good and stable ion coordination. The simulation of the holo form starting from an experimental structure sampled nearnative conformations, retrieving quasi-atomistic precision. Removing the binding peptide enabled the EF-hands to perform large reciprocal movements, comparable to those observed in NMR structures. On the other hand, the isolated peptide starting from the helical conformation experienced spontaneous unfolding, in agreement with previous experimental data. However, repositioning the peptide in the neighborhood of one EF-hand not only prevented the peptide unfolding but also drove CaM to a fully bound conformation with both EF-hands embracing the cognate peptide, resembling the experimental holo structure. Therefore, SIRAH 2.0 showed the capacity to handle a number of structurally and dynamically challenging situations including metal ion coordination, unbiased conformational sampling, and specific protein-peptide recognition.

Two-component systems (TCS) are protein machineries that enable cells to respond to input signals. Histidine kinases (HK) are the sensory component, transferring information toward downstream response regulators (RR). HKs transfer phosphoryl groups to their specific RRs, but also dephosphorylate them, overall ensuring proper signaling. The mechanisms by which HKs discriminate between such disparate directions, are yet unknown. We now disclose crystal structures of the HK:RR complex DesK:DesR from Bacillus subtilis, comprising snapshots of the phosphotransfer and the dephosphorylation reactions. The HK dictates the reactional outcome through conformational rearrangements that include the reactive histidine. The phosphotransfer center is asymmetric, poised for dissociative nucleophilic substitution. The structural bases of HK phosphatase/phosphotransferase control are uncovered, and the unexpected discovery of a dissociative reactional center, sheds light on the evolution of TCS phosphotransfer reversibility. Our findings should be applicable to a broad range of signaling systems and instrumental in synthetic TCS rewiring.DOI: http://dx.doi.org/10.7554/eLife.21422.001

: mmachado@pasteur.edu.uy or spantano@pasteur.edu.uy.

Hybrid simulations of molecular systems, which combine all-atom (AA) with simplified (or coarse grain, CG) representations, propose an advantageous alternative to gain atomistic details on relevant regions while getting profit from the speedup of treating a bigger part of the system at the CG level. Here we present a reduced set of parameters derived to treat a hybrid interface in DNA simulations. Our method allows us to forthrightly link a state-of-the-art force field for AA simulations of DNA with a CG representation developed by our group. We show that no modification is needed for any of the existing residues (neither AA nor CG). Only the bonding parameters at the hybrid interface are enough to produce a smooth transition of electrostatic, mechanic and dynamic features in different AA/CG systems, which are studied by molecular dynamics simulations using an implicit solvent. The simplicity of the approach potentially permits us to study the effect of mutations/modifications as well as DNA binding molecules at the atomistic level within a significantly larger DNA scaffold considered at the CG level. Since all the interactions are computed within the same classical Hamiltonian, the extension to a quantum/classical/coarse-grain multilayer approach using QM/MM modules implemented in widely used simulation packages is straightforward.