From residue coevolution to protein conformational ensembles and functional dynamics

The analysis of evolutionary amino acid correlations has recently attracted a surge of renewed interest, also due to their successful use in de novo protein native structure prediction. However, many aspects of protein function, such as substrate binding and product release in enzymatic activity, can be fully understood only in terms of an equilibrium ensemble of alternative structures, rather than a single static structure. In this paper we combine coevolutionary data and molecular dynamics simulations to study protein conformational heterogeneity. To that end, we adapt the Boltzmann-learning algorithm to the analysis of homologous protein sequences and develop a coarse-grained protein model specifically tailored to convert the resulting contact predictions to a protein structural ensemble. By means of exhaustive sampling simulations, we analyze the set of conformations that are consistent with the observed residue correlations for a set of representative protein domains, showing that (i) the most representative structure is consistent with the experimental fold and (ii) the various regions of the sequence display different stability, related to multiple biologically relevant conformations and to the cooperativity of the coevolving pairs. Moreover, we show that the proposed protocol is able to reproduce the essential features of a protein folding mechanism as well as to account for regions involved in conformational transitions through the correct sampling of the involved conformers

Changes in the free-energy landscape of p38α MAP kinase through its canonical activation and binding events as studied by enhanced molecular dynamics simulations

p38α is a Ser/Thr protein kinase involved in a variety of cellular processes and pathological conditions, which makes it a promising pharmacological target. Although the activity of the enzyme is highly regulated, its molecular mechanism of activation remains largely unexplained, even after decades of research. By using state-of-the-art molecular dynamics simulations, we decipher the key elements of the complex molecular mechanism refined by evolution to allow for a fine tuning of p38α kinase activity. Our study describes for the first time the molecular effects of different regulators of the enzymatic activity, and provides an integrative picture of the activation mechanism that explains the seemingly contradictory X-ray and NMR data

Equilibrium properties of realistic random heteropolymers and their relevance for globular and naturally unfolded proteins

Random heteropolymers do not display the typical equilibrium properties of globular proteins, but are the starting point to understand the physics of proteins and, in particular, to describe their non-native states. So far, they have been studied only with mean-field models in the thermodynamic limit, or with computer simulations of very small chains on lattice. After describing a self-adjusting parallel-tempering technique to sample efficiently the low-energy states of frustrated systems without the need of tuning the system-dependent parameters of the algorithm, we apply it to random heteropolymers moving in continuous space. We show that if the mean interaction between monomers is negative, the usual description through the random energy model is nearly correct, provided that it is extended to account for non-compact conformations. If the mean interaction is positive, such a simple description breaks out and the system behaves in a way more similar to Ising spin glasses. The former case is a model for the denatured state of glob- ular proteins, the latter of naturally-unfolded proteins, whose equilibrium properties thus result qualitatively different

Use of the Metropolis algorithm to simulate the dynamics of protein chains

The Metropolis implementation of the Monte Carlo algorithm has been developed to study the equilibrium thermodynamics of many-body systems. Choosing small trial moves, the trajectories obtained applying this algorithm agree with those obtained by Langevin's dynamics. Applying this procedure to a simplified protein model, it is possible to show that setting a threshold of 1 degree on the movement of the dihedrals of the protein backbone in a single Monte Carlo step, the mean quantities associated with the off-equilibrium dynamics (e.g., energy, RMSD, etc.) are well reproduced, while the good description of higher moments requires smaller moves. An important result is that the time duration of a Monte Carlo step depends linearly on the temperature, something which should be accounted for when doing simulations at different temperatures.Comment: corrections to the text and to the figure

Design of amino acid sequences to fold into C_alpha-model proteins

In order to extend the results obtained with minimal lattice models to more realistic systems, we study a model where proteins are described as a chain of 20 kinds of structureless amino acids moving in a continuum space and interacting through a contact potential controlled by a 20x20 quenched random matrix. The goal of the present work is to design and characterize amino acid sequences folding to the SH3 conformation, a 60-residues recognition domain common to many regulatory proteins. We show that a number of sequences can fold, starting from a random conformation, to within a distance root mean square deviation (dRMSD) of 2.6A from the native state. Good folders are those sequences displaying in the native conformation an energy lower than a sequence--independent threshold energy

An Allosteric Cross-Talk Between the Activation Loop and the ATP Binding Site Regulates the Activation of Src Kinase

Phosphorylation of the activation loop is a fundamental step in the activation of most protein kinases. In the case of the Src tyrosine kinase, a prototypical kinase due to its role in cancer and its historic importance, phosphorylation of tyrosine 416 in the activation loop is known to rigidify the structure and contribute to the switch from the inactive to a fully active form. However, whether or not phosphorylation is able per-se to induce a fully active conformation, that efficiently binds ATP and phosphorylates the substrate, is less clear. Here we employ a combination of solution NMR and enhanced-sampling molecular dynamics simulations to fully map the effects of phosphorylation and ATP/ADP cofactor loading on the conformational landscape of Src tyrosine kinase. We find that both phosphorylation and cofactor binding are needed to induce a fully active conformation. What is more, we find a complex interplay between the A-loop and the hinge motion where the phosphorylation of the activation-loop has a significant allosteric effect on the dynamics of the C-lobe

The SH2 Domain Regulates c-Abl Kinase Activation by a Cyclin-Like Mechanism and Remodulation of the Hinge Motion

Regulation of the c-Abl (ABL1) tyrosine kinase is important because of its role in cellular signaling, and its relevance in the leukemiogenic counterpart (BCR-ABL). Both auto-inhibition and full activation of c-Abl are regulated by the interaction of the catalytic domain with the Src Homology 2 (SH2) domain. The mechanism by which this interaction enhances catalysis is not known. We combined computational simulations with mutagenesis and functional analysis to find that the SH2 domain conveys both local and global effects on the dynamics of the catalytic domain. Locally, it regulates the flexibility of the αC helix in a fashion reminiscent of cyclins in cyclin-dependent kinases, reorienting catalytically important motifs. At a more global level, SH2 binding redirects the hinge motion of the N and C lobes and changes the conformational equilibrium of the activation loop. The complex network of subtle structural shifts that link the SH2 domain with the activation loop and the active site may be partially conserved with other SH2-domain containing kinases and therefore offer additional parameters for the design of conformation-specific inhibitors

Clinical Trials in Pregnant Women with Preeclampsia

Preeclampsia (PE) is the leading cause of preterm birth by medical indication when associated with premature detachment of placenta normoinserta, and Intrauterine growth restriction (IUGR) is associated with high perinatal morbidity and mortality and long-term sequelae. The main problem of PE is threefold: the diagnostic difficulty, the complicated interrelationship of the pathophysiological processes, and the vulnerability of the maternal-fetal binomial to the therapeutic interventions. The approach for management with PE is preventing its late occurrence in pregnancy. The key to preventing PE is knowledge of the factors that trigger the pathophysiological processes that culminate in the presentation of PE. Understanding the developmental characteristics of the placenta in pregnancy at high risk for PE is essential for understanding the pathophysiology and developing strategies for prevention. When deciding that the population of study is a group of pregnant women, the first ethical criteria that need to be reviewed are those aimed at the protection of the fetus. There are no specific guidelines on how to assess fetal well-being during pregnancy routinely in the clinic, and this deficiency is shifted to clinical research with pregnant women

The Effect of Mutations on Drug Sensitivity and Kinase Activity of Fibroblast Growth Factor Receptors: A Combined Experimental and Theoretical Study

Fibroblast growth factor receptors (FGFRs) are recognized therapeutic targets in cancer. We here describe insights underpinning the impact of mutations on FGFR1 and FGFR3 kinase activity and drug efficacy, using a combination of computational calculations and experimental approaches including cellular studies, X-ray crystallography and biophysical and biochemical measurements. Our findings reveal that some of the tested compounds, in particular TKI258, could provide therapeutic opportunity not only for patients with primary alterations in FGFR but also for acquired resistance due to the gatekeeper mutation. The accuracy of the computational methodologies applied here shows a potential for their wider application in studies of drug binding and in assessments of functional and mechanistic impacts of mutations, thus assisting efforts in precision medicine