Ludovico Sutto

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.

Self-assembling vesicles made of copolymer mimics biological systems.

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. Significance Evolutionary-related protein sequences have been selected to preserve a common function and fold. Residues in contact in this conserved structure are coupled by evolution and show correlated mutational patterns. The exponential growth of sequenced genomes makes it possible to detect these coevolutionary coupled pairs and to infer three-dimensional folds from predicted contacts. But how far can we push the prediction of native folds? Can we predict the conformational heterogeneity of a protein directly from sequences? We address these questions developing an accurate contact prediction algorithm and a protein coarse-grained model, and exploring conformational landscapes congruent with coevolution. We find that both structural and dynamical properties can be already recovered using evolutionary information only.

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. The Abl kinase is a key player in many crucial cellular processes. It is also an important anti-cancer drug target, because a mutation leading to the fusion protein Bcr-Abl is the main cause for chronic myeloid leukemia (CML). Abl inhibitors are currently the only pharmaceutical treatment for CML. There are two main difficulties associated with the development of kinase inhibitors: the high similarity between active sites of different kinases, which makes selectivity a challenge, and mutations leading to resistance, which make it mandatory to search for alternative drugs. One important factor controlling Abl is the interplay between the catalytic domain and an SH2 domain. We used computer simulations to understand how the interactions between the domains modify the dynamic of the kinase and detected both local and global effects. Based on our computer model, we suggested mutations that should alter the domain-domain interplay. Consequently, we tested the mutants experimentally and found that they support our hypothesis. We propose that our findings can be of help for the development of new classes of Abl inhibitors, which would modify the domain-domain interplay instead of interfering directly with the active site.

Proteins are dynamic molecules and their ability to adopt alternative conformations is central to their biological function. The structural and biophysical properties of transiently and sparsely populated states are, however, difficult to study and an atomic-level description of those states is challenging. We have used enhanced-sampling all-atom, explicit-solvent molecular simulations, guided by structural information from X-ray crystallography and NMR, to describe quantitatively the transition between the major and a minor state of Cyclophilin A, thus providing new insight into how dynamics can affect enzyme function. We calculate the conformational free energy between the two states, and comparison with experiments demonstrates a surprisingly high accuracy for both the wild type protein and a mutant that traps the protein in its alternative conformation. Our results demonstrate how the combination of state-of-the-art force fields and enhanced sampling methods can provide a detailed and quantitative description of the conformational changes in proteins such as those observed in Cyclophilin A.

Activating mutations in the epidermal growth factor receptor (EGFR) tyrosine kinase are frequently found in many cancers. It has been suggested that changes in the equilibrium between its active and inactive conformations are linked to its oncogenic potential. Here, we quantify the effects of some of the most common single (L858R and T790M) and double (T790M-L858R) oncogenic mutations on the conformational free-energy landscape of the EGFR kinase domain by using massive molecular dynamics simulations together with parallel tempering, metadynamics, and one of the best force-fields available. Whereas the wild-type EGFR catalytic domain monomer is mostly found in an inactive conformation, our results show a clear shift toward the active conformation for all of the mutants. The L858R mutation stabilizes the active conformation at the expense of the inactive conformation and rigidifies the αC-helix. The T790M gatekeeper mutant favors activation by stabilizing a hydrophobic cluster. Finally, T790M with L858R shows a significant positive epistasis effect. This combination not only stabilizes the active conformation, but in nontrivial ways changes the free-energy landscape lowering the transition barriers.

Metamorphic proteins are an extremely intriguing case of protein evolution and a golden opportunity to challenge the current simplified models. In a recent work, we showed that a coarse-grained Gō model can be used to study the thermodynamics of lymphotactin, a naturally occurring metamorphic protein. Here, we extend such model by including the necessary atomic detail to study the effects of the single mutations that artificially bring the GA domain of protein G to fold into the GB domain of the same protein. The results of this all-atom Gō model show how the residual structure of the denatured state is an early indicator of a forthcoming fold and function switch. These findings reconcile the results of previous studies on similar systems highlighting the different role played by secondary and tertiary interactions and suggesting a possible way for new folds to arise.

Metadynamics is an algorithm for accelerating rare events and reconstructing the associated free energy surface. It works by biasing the evolution of the system by a history‐dependent potential that is adaptively constructed in the space of a suitably chosen set of collective variables. Since its first appearance, the method has been successfully applied in several domains of science. Its widespread adoption is not only due to its efficiency, flexibility, and availability but also to its continuous evolution and its combination with complementary enhanced sampling algorithms. Here, we focus on the progress made in the development of more general and powerful collective variables and on the very recent and exciting evolutions of the method. © 2012 John Wiley & Sons, Ltd.This article is categorized under: Molecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods

C-Src and c-Abl are two closely related protein kinases that constitute important anticancer targets. Despite their high sequence identity, they show different sensitivities to the anticancer drug imatinib, which binds specifically to a particular inactive conformation in which the Asp of the conserved DFG motif points outward (DFG-out). We have analyzed the DFG conformational transition of the two kinases using massive molecular dynamics simulations, free energy calculations, and isothermal titration calorimetry. On the basis of the reconstruction of the free energy surfaces for the DFG-in to DFG-out conformational changes of c-Src and c-Abl, we propose that the different flexibility of the two kinases results in a different stability of the DFG-out conformation and might be the main determinant of imatinib selectivity.

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 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 noncompact 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 globular proteins, the latter of naturally unfolded proteins, whose equilibrium properties thus result as qualitatively different.