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Phosphorylation ofEscherichia coliCheY protein transduces chemoreceptor stimulation to a highly cooperative flagellar motor response. CheY binds to the N-terminal peptide of the FliM motor protein (FliMN). Constitutively active D13K-Y106W CheY has been an important tool for motor physiology. The crystal structures of CheY and CheY.FliMNwith and without D13K-Y106W have shown FliMNbound CheY contains features of both active and inactive states. We used molecular dynamics (MD) simulations to characterize the CheY conformational landscape accessed by FliMNand D13K-Y106W. Mutual information measures identified the central features of the long-range CheY allosteric network between D13K at the D57 phosphorylation site and Y/W106 at the FliMNinterface; namely the closure of the α4-β4 hinge and inward rotation of Y/W106 with W58. We used hydroxy-radical foot-printing with mass spectroscopy (XFMS) to track the solvent accessibility of these and other sidechains. The solution XFMS oxidation rate correlated with the solvent-accessible area of the crystal structures. The protection of allosteric relay sidechains reported by XFMS confirmed the intermediate conformation of the native CheY.FliMNcomplex, the inactive state of free D13K-Y106W CheY and the MD-based network architecture. We extended the MD analysis to determine temporal coupling and energetics during activation. Coupled aromatic residue rotation was a graded rather than a binary switch with Y/W106 sidechain burial correlated with increased FliMNaffinity. Activation entrained CheY fold stabilization to FliMNaffinity. The CheY network could be partitioned into four dynamically coordinated community sectors. Residue substitutions mapped to sectors around D57 or the FliMNinterface according to phenotype. FliMNincreased sector size and interactions. These sectors fused between the substituted K13K-W106 residues to organize a tightly packed core and novel surfaces that may bind additional sites to explain the cooperative motor response. The community maps provide a more complete description of CheY priming than proposed thus far.Statement of SignificanceCheY affinity for FliMN, its binding target at the flagellar motor, is increased by phosphorylation to switch rotation sense. Atomistic simulations based on CheY and CheY.FliMNcrystal structures with and without the phospho-mimetic double substitution (D13K-Y106W) showed CheY compaction is entrained to increased FliMNaffinity. Burial of exposed aromatic sidechains drove compaction, as validated by tracking sidechain solvent accessibility with hydroxyl-radical foot-printing. The substitutions were localized at the phosphorylation pocket (D13K) and FliMNinterface (Y106W). Mutual information measures revealed these locations were allosterically coupled by a specialized conduit when the conformational landscape of FliMN-tethered CheY was modified by the substitutions. Novel surfaces stabilized by the conduit may bind additional motor sites, essential for the high cooperativity of the flagellar switch.

The proton-driven ATP synthase (FoF1) is comprised of two rotary, stepping motors (Fo and F1) coupled by an elastic power transmission. The elastic compliance resides in the rotor module that includes the membrane-embedded FO c-ring. Proton transport by FO is firmly coupled to the rotation of the c-ring relative to other FO subunits (ab2). It drives ATP synthesis. We used a computational method to investigate the contribution of the c-ring to the total elastic compliance. We performed principal component analysis of conformational ensembles built using distance constraints from the bovine mitochondrial c-ring X-ray structure. Angular rotary twist, the dominant ring motion, was estimated to show that the c-ring accounted in part for the measured compliance. Ring rotation was entrained to rotation of the external helix within each hairpin-shaped c-subunit in the ring. Ensembles of monomer and dimers extracted from complete c-rings showed that the coupling between collective ring and the individual subunit motions was independent of the size of the c-ring which varies between organisms. Molecular determinants were identified by covariance analysis of residue co-evolution and a structural alphabet based local dynamics correlations. The residue co-evolution gave a read-out of subunit architecture. The dynamic couplings revealed that the hinge for both ring and subunit helix rotations was constructed from the proton-binding site and the adjacent glycine motif (IB-GGGG) in the mid-membrane plane. IB-GGGG motifs were linked by long-range couplings across the ring, while intra-subunit couplings connected the motif to the conserved cytoplasmic loop and adjacent segments. The correlation with principal collective motions shows that the couplings underlie both ring rotary and bending motions. Non-contact couplings between IB-GGGG motifs matched the co-evolution signal as well as contact couplings. The residue co-evolution reflects the physiological importance of the dynamics that may link proton transfer to ring compliance.

IntroductionConformational changes associated with protein function often occur at timescales inaccessible to unbiased Molecular Dynamics (MD) simulations, consequently different approaches have been developed to accelerate their sampling. Here we investigate how the knowledge of backbone conformations preferentially adopted by protein fragments, as contained in pre-calculated libraries known as Structural Alphabets (SA)[1], can be used to explore the landscape of global protein conformations in MD simulations.MethodsSAs were successfully used to analyze protein dynamics after simulation[2,3]. Here we define a novel SA-based Collective Variable (CVSA) to bias the sampling of backbone conformations of protein fragments towards experimentally preferred local states[4].ResultsWe find that: a) Enhancing the sampling of native local states allows recovery of global folded states, both in Metadynamics and in Steered MD, when the local states are encoded by strings of SA letters derived from the native structures. b) Global folded states are still recovered when the information on the native local states is reduced by using a low-resolution SA, where the original letters are clustered into macrostates. The macrostates provide the approximate shape of the fragments, while sampling with the atomistic force field allows the structure to adopt the native conformation of the specific amino acid sequence. c) SA strings derived from collections of structural motifs can be effectively used to sample alternative conformations of pre-selected regions. These findings have potential impact on a wide range of applications, from protein model refinement to folding and design.References1. Pandini A., Fornili A., Kleinjung J., BMC Bioinformatics 11:97 (2010).2. Pandini A., Fornili A., Fraternali F., Kleinjung J., FASEB J. 26:868 (2012).3. Pandini A., Fornili A., Fraternali F., Kleinjung J., Bioinformatics 29:2053 (2013).4. Pandini A., Fornili A., submitted.

Dynamical properties of proteins may have a significant role in regulating protein-protein interactions. In particular, intrinsic disorder and disorder-order transitions have been claimed to be especially involved in the binding of proteins known as “hubs” [1], which are characterized by a high level of connectivity in protein-protein interaction (PPI) networks. We therefore started to investigate the dynamical properties of hubs through molecular simulations, to assess the role of conformational flexibility in promoting “promiscuity” of interactions.For this study, a dataset of proteins with known structure and interaction partners was first prepared. To cope with the incompleteness of the interaction data contained in the Protein Data Bank (PDB), we mapped the PPI database IntAct [2], which collects interactions from a wide range of experimental techniques, onto the structure-based database PiSite [3]. The proteins were then partitioned into ‘classes’ with increasing number of interactions.A preliminary survey of the dynamical properties of each class was done using two independent approaches, namely tCONCOORD [4] and the Gaussian Network Model [5]. For each complex, the interfaces were extracted using the POPSComp method [6,7]. The availability of information on both the dynamics and the interaction properties will allow to determine possible correlations between flexibility and binding diversity.[1] Dosztnyi et al., J. Proteome Res., 5, 2985-2995 (2006).[2] Kerrien et al., Nucleic Acids Res., 35, D561-D565 (2006).[3] Higurashi et al., Nucleic Acids Res., 37, D360-D364 (2009).[4] Seeliger et al., Structure, 15, 1482-1492 (2007).[5] Bahar et al., Folding & Design, 2, 173-181 (1997).[6] Fraternali et al., Nucleic Acids Res., 30, 2950-2960 (2002).[7] Kleinjung et al., Nucleic Acids Res., 33, W342-W346 (2005).

IntroductionAllosteric inhibitors were shown to be effective in targeting multiple conformational states and more selective than competitive inhibitors [1]. However, allosteric signal transmission is difficult to model because often mediated by small local changes propagating along multiple pathways in the protein structure [2]. Therefore, we developed a method to identify these pathways by an information-theoretic analysis of Molecular Dynamics (MD) simulations.MethodsFirst, MD ensembles are mapped onto a canonical set of representative fragments, i.e. a set of discrete 4-residue states [3]. By this mapping, the contribution of rigid fragment roto-translations is removed and relevant changes are detected, even if subtle. Second, local motions are modelled as transitions between the fragment states. This removes background noise from harmonic high-frequency fluctuations. Third, the communication between parts of the molecule is modelled by the coupling of fragment transitions. These are resolved spatially and temporally. The time-averaged spatial couplings are analyzed with a network model of fragment correlations. Then communication pathways are characterised by time-resolved analysis of fragment couplings.ResultsThe method was applied to the NtrC, CheY, and FixJ receiver domains. The results are consistent with the emerging picture of allosteric regulation [2]: a pre-organized network of fragment couplings connects the allosteric and functional sites already in the inactive state, and fragments with high network centrality (hubs) are part of functionally relevant regions. Critical nodes on the signalling pathways correspond to residues experimentally known to affect the kinetics and thermodynamics of the allosteric mechanism.References1. Kar, G., Keskin, O., Gursoy, A. & Nussinov, R. Curr Opin Pharmacol 10, 715–22 (2010).2. del Sol, A., Tsai, C.J., Ma, B. & Nussinov, R. Structure 17, 1042–1050 (2009).3. Pandini, A., Fornili, A., Kleinjung, J. BMC Bioinformatics 11, 97 (2010).

BackgroundBiomolecular motions play a key role in several biological functions: enzymatic activity, protein-protein interactions, ligand binding and allosteric regulation. Computational approaches, such as Molecular Dynamics (MD), are now routinely used to reproduce the intrinsic dynamics of proteins, but effective tools are still required to gain functional insight from the simulated data.Methods and ResultsWe previously suggested a method aimed at recovering the role of local conformational changes in functional motions. To this purpose we developed a Structural Alphabet (SA): a set of 25 canonical states of 4-residue protein fragments (Cα atoms only) describing the most probable local conformations in high-resolution protein structures [1]. The SA provides a mean for the coarse-grained annotation and processing of local conformations in a string format, which lends itself to a range of efficient sequence analysis algorithms. The SA has been successfully used in analysing local changes and allosteric signal transmission [2].Here we present GSATools [3], a set of SA-related tools interfacing with GROMACS for the analysis of conformational ensembles. GSATools is designed for the investigation of the conformational dynamics of local structures, the functional correlations between local and global motions, and the mechanisms of allosteric communication.ConclusionsGSATools is a free, easy-to-use and fully documented software for the analysis of conformational ensembles of proteins. The GSATools complement the GROMACS toolkit with a powerful set of analyses to detect, annotate and interpret local motions of functional relevance.1. Pandini A., Fornili A. & Kleinjung J. BMC Bioinformatics 11, 97 (2010).2. Pandini A., Fornili A., Fraternali F. & Kleinjung J., FASEB J., 26, 868 (2012).3. Pandini A., Fornili A., Fraternali F. & Kleinjung J., Bioinformatics, 29, 2053 (2013).