Francesco Pontiggia

Molecular mechanism of Aurora A kinase autophosphorylation and its allosteric activation by TPX2

We elucidate the molecular mechanisms of two distinct activation strategies (autophosphorylation and TPX2-mediated activation) in human Aurora A kinase. Classic allosteric activation is in play where either activation loop phosphorylation or TPX2 binding to a conserved hydrophobic groove shifts the equilibrium far towards the active conformation. We resolve the controversy about the mechanism of autophosphorylation by demonstrating intermolecular autophosphorylation in a long-lived dimer by combining X-ray crystallography with functional assays. We then address the allosteric activation by TPX2 through activity assays and the crystal structure of a domain-swapped dimer of dephosphorylated Aurora A and TPX21−25. While autophosphorylation is the key regulatory mechanism in the centrosomes in the early stages of mitosis, allosteric activation by TPX2 of dephosphorylated Aurora A could be at play in the spindle microtubules. The mechanistic insights into autophosphorylation and allosteric activation by TPX2 binding proposed here, may have implications for understanding regulation of other protein kinases. DOI: http://dx.doi.org/10.7554/eLife.02667.001

Small- and Large-Scale Conformational Changes of Adenylate Kinase: A Molecular Dynamics Study of the Subdomain Motion and Mechanics

Adenylate kinase, an enzyme that catalyzes the phosphoryl transfer between ATP and AMP, can interconvert between the open and catalytically potent (closed) forms even without binding ligands. Several aspects of the enzyme elasticity and internal dynamics are analyzed here by atomistic molecular dynamics simulations covering a total time span of 100 ns. This duration is sufficiently long to reveal a partial conversion of the enzyme that proceeds through jumps between structurally different substates. The intra- and intersubstates contributions to the enzymes structural fluctuations are analyzed and compared both in magnitude and directionality. It is found that, despite the structural heterogeneity of the visited conformers, the generalized directions accounting for conformational fluctuations within and across the substates are mutually consistent and can be described by a limited set of collective modes. The functional-oriented nature of the consensus modes is suggested by their good overlap with the deformation vector bridging the open and closed crystal structures. The consistency of adenylate kinases internal dynamics over timescales wide enough to capture intra- and intersubstates fluctuations adds elements in favor of the recent proposal that the free (apo) enzyme possesses an innate ability to sustain the open/close conformational changes.

Coarse-Grained Description of Protein Internal Dynamics: An Optimal Strategy for Decomposing Proteins in Rigid Subunits

The possibility of accurately describing the internal dynamics of proteins, in terms of movements of a few approximately-rigid subparts, is an appealing biophysical problem with important implications for the analysis and interpretation of data from experiments or numerical simulations. The problem is tackled here by means of a novel variational approach that exploits information about equilibrium fluctuations of interresidues distances, provided, e.g., by atomistic molecular dynamics simulations or coarse-grained models. No contiguity in primary sequence or in space is enforced a priori for amino acids grouped in the same rigid unit. The identification of the rigid protein moduli, or dynamical domains, provides valuable insight into functionally oriented aspects of protein internal dynamics. To illustrate this point, we first discuss the decomposition of adenylate kinase and HIV-1 protease and then extend the investigation to several representatives of the hydrolase enzymatic class. The known catalytic site of these enzymes is found to be preferentially located close to the boundary separating the two primary dynamical subdomains.

The energy landscape of adenylate kinase during catalysis

Kinases perform phosphoryl-transfer reactions in milliseconds; without enzymes, these reactions would take about 8,000 years under physiological conditions. Despite extensive studies, a comprehensive understanding of kinase energy landscapes, including both chemical and conformational steps, is lacking. Here we scrutinize the microscopic steps in the catalytic cycle of adenylate kinase, through a combination of NMR measurements during catalysis, pre-steady-state kinetics, molecular-dynamics simulations and crystallography of active complexes. We find that the Mg2+ cofactor activates two distinct molecular events: phosphoryl transfer (>105-fold) and lid opening (103-fold). In contrast, mutation of an essential active site arginine decelerates phosphoryl transfer 103-fold without substantially affecting lid opening. Our results highlight the importance of the entire energy landscape in catalysis and suggest that adenylate kinases have evolved to activate key processes simultaneously by precise placement of a single, charged and very abundant cofactor in a preorganized active site.

Anharmonicity and self-similarity of the free energy landscape of protein G

The near-native free-energy landscape of protein G is investigated through 0.4-micros-long atomistic molecular dynamics simulations in an explicit solvent. A theoretical and computational framework is used to assess the time dependence of salient thermodynamical features. While the quasiharmonic character of the free energy is found to degrade in a few ns, the slow modes display a very mild dependence on the trajectory duration. This property originates from a striking self-similarity of the free-energy landscape embodied by the consistency of the principal directions of the local minima, where the system dwells for several ns, and of the virtual jumps connecting them.

ALADYN: a web server for aligning proteins by matching their large-scale motion

The ALADYN web server aligns pairs of protein structures by comparing their internal dynamics and detecting regions that sustain similar large-scale movements. The latter often accompany functional conformational changes in proteins and enzymes. The ALADYN dynamics-based alignment can therefore highlight functionally-oriented correspondences that could be more elusive to sequence- or structure-based comparisons. The ALADYN server takes the structure files of the two proteins as input. The optimal relative positioning of the molecules is found by maximizing the similarity of the pattern of structural fluctuations which are calculated via an elastic network model. The resulting alignment is presented via an interactive graphical Java applet and is accompanied by a number of quantitative indicators and downloadable data files. The ALADYN web server is freely accessible at the http://aladyn.escience-lab.org address.

Structural and dynamical alignment of enzymes with partial structural similarity

Proteins and enzymes, in order to carry our their biological tasks, often need to sustain concerted displacements of a large number of amino acids. In recent years many theoretical and computational studies have pointed out how these large-scale movements, also termed slow modes or essential dynamical spaces, are mostly dictated by the overall structural organization of the protein. Several fundamental questions arise when this fact is complemented by the observation that enzymes within the same enzymatic superfamily can have remarkable conformational differences. Could their large-scale movements be similar despite the difference in structure? In this study we address this issue and present a quantitative scheme for comparing the slow modes in proteins that, though differing in sequence, length and tertiary structure, still admit a partial structural superposition. We illustrate the application of the method to two representatives of the protease enzymatic superfamily, carboxypeptidase A and pyroglutamyl peptidase.

Conformational Selection in a Protein-Protein Interaction Revealed by Dynamic Pathway Analysis

Molecular recognition plays a central role in biology, and protein dynamics has been acknowledged to be important in this process. However, it is highly debated whether conformational changes happen before ligand binding to produce a binding-competent state (conformational selection) or are caused in response to ligand binding (induced fit). Proposals for both mechanisms in protein/protein recognition have been primarily based on structural arguments. However, the distinction between them is a question of the probabilities of going via these two opposing pathways. Here, we present a direct demonstration of exclusive conformational selection in protein/protein recognition by measuring the flux for rhodopsin kinase binding to its regulator recoverin, an important molecular recognition in the vision system. Using nuclear magnetic resonance (NMR) spectroscopy, stopped-flow kinetics, and isothermal titration calorimetry, we show that recoverin populates a minor conformation in solution that exposes a hydrophobic binding pocket responsible for binding rhodopsin kinase. Protein dynamics in free recoverin limits the overall rate of binding.

Bridging the Atomic and Coarse-Grained Descriptions of Collective Motions in Proteins

In proteins and enzymes the necessity that the native state is thermodynamically stable must be appropriately balanced by the capability of the structure to sustain conformational changes and efficiently interconvert among different functionally relevant conformers. This subtle equilibrium reverberates in the complexity of the free-energy landscape which is endowed by a variety of local minima of varying depth and breadth corresponding to the salient structural states of the molecules. In this chapter we will present some concepts and computational algorithms that can be used to characterize the internal dynamics of proteins and relate it to their “functional mechanics.” We will apply these concepts to the analysis of a molecular dynamics simulation of adenylate kinase, a protein for which the structural rearrangement is known to be crucial for the accomplishment of its biological function. We will show that, despite the structural heterogeneity of the explored conformational ensemble, the generalized directions accounting for conformational fluctuations within and across the visited conformational substates are robust and can be described by a limited set of collective coordinates. Finally, as a term of comparison, we will show that in the case of HIV-1 Trans-Activator of Transcription (TAT), a naturally unstructured protein, the lack of any hierarchical organization of the free-energy minima results in a poor consistency of the essential dynamical spaces sampled during the dynamical evolution of the system.

Pisqrd: A Novel Variational Scheme to Identify Dinamical Domains in Proteins

A key biophysical problem is how to describe accurately the internal dynamics of proteins in terms of movements of few approximately-rigid subparts. This issue has important implications ranging from the analysis and interpretation of data from experiments or numerical simulations to the design of optimal coarse-graining schemes for multiscale description of the kinetics of interacting biomolecules.We report on a novel variational clustering scheme that can be used to decompose proteins into rigid moduli (dynamical domains) by using internal dynamics data from atomistic molecular dynamics simulations or coarse-grained elastic network models. The method not only has a physically appealing and transparent formulation, but is also apt for efficient computational implementation.By applying the decomposition scheme to several biomolecules of high biological interest, such as Adenylate Kinase or HIV-1 protease and other members of the hydrolase superfamily, we demonstrate that the identification of dynamical domains can provide valuable insight into the functionality of proteins and especially enzymes.The decomposition algorithm is made freely available to the academic community in the form of a web server at the address http://pisqrd.escience-lab.org/.