The Structural Asymmetry of Mitochondrial Hsp90 ... - ACS Publications

Subscriber access provided by READING UNIV

Article

The Structural Asymmetry of Mitochondrial Hsp90 (Trap1) Determines Fine Tuning of Functional Dynamics Elisabetta Moroni, David A. Agard, and Giorgio Colombo J. Chem. Theory Comput., Just Accepted Manuscript • DOI: 10.1021/acs.jctc.7b00766 • Publication Date (Web): 10 Jan 2018 Downloaded from http://pubs.acs.org on January 16, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Journal of Chemical Theory and Computation is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Journal of Chemical Theory and Computation

The Structural Asymmetry of Mitochondrial Hsp90 (Trap1) Determines Fine Tuning of Functional Dynamics Elisabetta Moroni1, David A. Agard2, Giorgio Colombo3,4* 1)

IRCCS Multimedica, via Fantoli 16/15, 20138 Milano, Italy

2)

Howard Hughes Medical Institute and Dept. of Biochemistry & BiophysicsUniversity of California 600 16th Street, San Francisco, 94158 USA

3)

Istituto di Chimica del Riconoscimento Molecolare, CNR Via Mario Bianco 9, 20131 Milano, Italy.

4)

Dipartimento di Chimica, Università di Pavia, V.le Taramelli 12, 27100 Pavia, Italy

*Author to whom correspondence should be addressed: [email protected]

ACS Paragon Plus Environment

1

Journal of Chemical Theory and Computation 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 2 of 33

ABSTRACT The Hsp90 family of molecular chaperones oversees the folding of a wide range of client proteins. Hsp90 is a homodimer, whose conformational states and functions are regulated by ATP-binding and hydrolysis. The crystal structure of mitochondrial Hsp90 (Trap1) showed that one of the two protomers in the active state is buckled, resulting in an asymmetric conformation. The asymmetry between the two protomers corresponds to the broadly conserved region responsible for client binding. Moreover, asymmetry determines differential hydrolysis for each protomer, with the buckled conformation favoring ATP processing. Experimental results show that after the first hydrolysis, the dimer flips to a different asymmetric state while remaining in a closed conformation for the second hydrolysis. In this model, asymmetry plays a key role in the mechanism that drives chaperone function. Herein, we investigate the nucleotide-dependent internal dynamics of Trap1 with computational approaches. Our results shed light on the relationship between the nucleotide-state in the N-terminal domain and the asymmetric modulation of the dynamic and structural properties of the client-binding region in the Middle domain. According to our analysis, this is the region that undergoes the most intense dynamic modulation upon nucleotide exchange. This result provides molecular insights into the roles of structural asymmetry in the regulation of Trap1, and suggests that this substructure is a promising target to modulate the functionally oriented aspects of Trap1 dynamics, therefore opening fresh opportunities for the design of selective therapeutics for Trap1 dependent diseases.


2

Page 3 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Introduction Understanding the molecular interplay between protein functions, sequence, structure and dynamics represents a fundamental problem in biology

1-3

. Molecular chaperones vividly portray the

fact that a combination of ligand binding, dynamic modulation and recognition are required to guarantee proper cell functioning 4. Chaperone proteins facilitate the correct folding of other proteins, named ‘clients’, at different stages of their life cycle 4. Most molecular chaperones belong to the family of “heat shock proteins (Hsps)”, which are highly conserved in almost all species, from bacteria to eukaryotes and are generally induced upon stresses such as elevated temperatures or unfavourable environmental conditions. A notable example is Heat Shock Protein 90 (Hsp90) 5-6, which represents a nodal point in many different signaling pathways and is required to preserve the stability of a highly diverse ensemble of client proteins. Given its role in different aspects of cell survival and maintenance, it has been demonstrated that dis-regulation of Hsp90 is associated with several pathologies ranging from cancer to neurodegeneration and consequently, Hsp90 proteins have become the target of intense drug discovery efforts 7.

Hsp90 family members are ATPase regulated molecules that share common structural features: they are homodimers, with each protomer consisting of three structural domains: an N-terminal regulatory Domain (NTD), responsible for ATP binding, a Middle Domain (M-domain), which facilitates ATP hydrolysis and binds client proteins, and a C-terminal Domain (CTD) that is involved in dimerization 814

.

The available structural repertoire of full-length Hsp90 homologues, which includes the yeast Hsp90 12, the bacterial HtpG14 and the mammalian endoplasmatic reticulum (ER) Grp94 enriched by the crystallographic structure of the mitochondrial Hsp90, Trap1

13

9, 15

, has recently been

. It has been shown

that Trap1 assists protein folding and acts as an indicator of the health of proteins in the mitochondria. Recent data indicate that the roles and functions of Trap1 are complex: indeed, it has recently been reported that some cancers express less Trap1 than their normal tissue counterparts, while other express more. As a consequence, while Trap1 is generally considered to be an anticancer molecular target it would be highly desirable to develop molecules that can distinguish between Trap1 in the mitochondria and Hsp90 in other cell compartments to better probe Trap1 function 16.

Interestingly, the series of crystal structures of Trap1 bound to different ATP analogs

9, 15

revealed a

striking asymmetry between the two protomers (Figure 1), with the maximal differences occurring at ACS Paragon Plus Environment

3


the interface between the M-Domain and CTD, the region responsible for client binding

Page 4 of 33

8, 17

. The

Agard group showed that this asymmetry is also present in solution, providing the basis for a novel model of coupling between ATP hydrolysis and client remodeling 9, 15. A second peculiar characteristic of the new structure entails the presence of a long extension (strap) of the N-terminus of one protomer that wraps around the other protomer, possibly stabilizing the closed state. Structural and functional data indicate that the strap plays a regulatory role in determining the kinetics of ATPase hydrolysis and protein closure kinetics 9, 15.

In this paper, we investigate the nucleotide-dependent microscopic dynamics of Trap1 and show that the observed structural asymmetry reverberates in the fine modulation of the protein’s internal dynamics and response to the specific nucleotide bound at each protomer. We focus on how the closed state mechanically responds to nucleotide changes through MD simulations: indeed, experimental data from the Agard lab18 show that the consequence of asymmetry in the dimer is a different hydrolysis rate for each protomer, in which the buckled conformation favors ATPase. Interestingly, after the first hydrolysis, the asymmetry of the dimer flips, while the protein remains in a closed state for the subsequent, second hydrolysis. In this model, ATP hydrolysis on the two protomers is sequential and deterministic. Here, our goal is not to observe large-scale conformational changes. Our effort rather aims to investigate how changes on a short time-scale in the structural dynamics of Trap1, starting from the experimentally available asymmetric conformation that corresponds to the catalytically active state, may reverberate in the onset and modulation of the slow motions of regions that determine biological functions. Here, we analyze such closed conformations, to identify the determinants of microscopic dynamics that can directly be related to the onset of functionally oriented dynamic states of the chaperone, selected by nucleotide variation in each protomer. It is important to note that nanosecond timescale residue fluctuations and modulation of protein flexibility have been linked in other cases to the regulation of protein activities, including Hsp90 allosterically-regulated conformational rearrangements that lead to catalytically competent states

19

. In this view, breaking and reassembly of

interactions coupled to (even) small differences in the structural dynamics at distal functional sites can be sufficient to set the stage for a modulation of the populations of activated vs. inactive states (see also 3, 20-22

).

Specifically, the internal dynamics of Trap1 bound to different nucleotide combinations in the two protomers (Buckled protomer labeled Bu; and Straight protomer labeled St) are compared at different levels, ranging from local inter-residue fluctuations to global coordination/rigidity and macromolecular ACS Paragon Plus Environment

4

Page 5 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


motions. Using recently developed methods for the analysis of atomistic MD simulations

23-32

, we

demonstrate that the substructures at the interface between the Middle Domain (M-Domain) and the CTerminal Domain (CTD) of Trap1 are specifically modulated by the hydrolysis state of the nucleotides and the specific protomer to which they are bound. This defines a specific cross-talk between the nucleotide site and distal client binding sites, which allows the conformational dynamics of the clientrecognition region to be coupled to ATP hydrolysis9,

15

, within the closed states of Trap1. This

modulation of the communication between the two sites supports the observation that structural asymmetry plays a role in functional regulation and tuning of the chaperone properties. We also suggest that the dynamic information gathered here could represent a promising starting point for the discovery of small molecule inhibitors/modulators specifically targeting Trap1.

Materials and Methods Molecular dynamics simulations The Trap1 structure used for MD simulations is the full length dimer of the canine protein crystallized by Lavery et al. 9, PDB entry 4IPE.pdb. The apo and ADP simulations were carried out respectively by removing the ligand and by replacing ATP with ADP in the respective protomer as reported in Table1. Each complex was solvated in a tetrahedral box large enough to contain the protein and a 1nm layer of solvent on each side. The simulated systems eventually feature more than 220000 particles. All simulations and the analysis of the trajectories were performed using the 4.5 version of the GROMACS software package 33 using the GROMOS force field 34-35 and the SPC water model 36. Additionally, the four systems containing nucleotides, namely Bu.ATP:St.ATP, Bu.ADP:St.ATP, Bu.ATP:St.ADP, and Bu.ADP:St.ADP, which are known to be the most relevant and populated ones in experimental conditions were studied using 3 independent replicas for each system. This resulted in 600ns of sampling overall for each system. The three replicas for each state were then combined and analyses were carried out on the resulting meta-trajectories. We also repeated these calculations using the AMBER force field and suite of programs, obtaining another 600ns overall for each doublenucleotide system 37.

In the GROMOS simulations, following the same protocol used for the Hsp90 simulations, for which we refer to

27

, each system was first energy relaxed with 2000 steps of steepest descent energy

minimization followed by another 2000 steps of conjugate gradient energy minimization, in order to remove possible bad contacts from the initial structures. All systems were first equilibrated by 50 ps of ACS Paragon Plus Environment

5


Page 6 of 33

MD runs with position restraints on the protein and ligand to allow relaxation of the solvent molecules. These first equilibration runs were followed by other 50 ps runs without position restraints on the solute. The first 20 ns of each trajectory were not used in the subsequent analysis in order to minimize convergence artifacts. Equilibration of the trajectories was checked by monitoring the equilibration of the RMSD with respect to the initial structure, and of the internal protein energy. Production runs span 200ns for each of the studied complexes, for a total simulation time of 2.2 microseconds. The electrostatic term was described by using the particle mesh Ewald algorithm. The LINCS

38

algorithm

was used to constrain all bond lengths. For the water molecules the SETTLE algorithm 39 was used. A dielectric permittivity, є = 1, and a time step of 2 fs were used. All atoms were given an initial velocity obtained from a Maxwellian distribution at the desired initial temperature of 300K. The density of the system was adjusted performing the first equilibration runs at NPT condition by weak coupling to a bath of constant pressure (P0 = 1 bar, coupling time p = 0.5 ps) 40. In all simulations the temperature was maintained close to the intended values by weak coupling to an external temperature bath 40 with a coupling constant of 0.1 ps. The proteins and the rest of the system were coupled separately to the temperature bath.

Additionally, MD simulations were performed using Amber14 pmemd.CUDA with the all atom ff99SB force field, under periodic boundary conditions 37. In order to remove any bad contacts, every system was first minimized in vacuo by multiple minimizations (200 steps steepest descent plus 200 steps conjugate gradient). The triclinic simulative box, filled with TIP3P water molecules41 and rendered electroneutral by addition of sodium counterions, consists of a final number of atoms of ~190000 for each system. The systems were then subjected to a round of minimization of 10000 steps of steepest descend followed by 10000 steps of conjugate gradient. Relaxation of water molecules and thermalization in NPT environment were carried out for 1.2 ns at 1 fs time-step. In particular, 6 runs of 200 ps each were carried out increasing the temperature of 50 K at each step, starting from 50 K to 300 K. The systems were then simulated with a 2 fs time-step in periodic boundary conditions in the NVT ensemble, using a cut-off of 8 Å for the evaluation of short-range non-bonded interactions and the Particle Mesh Ewald method for the long-range electrostatic interactions 42. The temperature was kept constant at 300 K with Langevin Thermostat. Bonds involving hydrogen atoms were constrained with the SHAKE algorithm

43

. The atomic positions were saved every 10 ps for analysis. Analyses were

carried out with the tools in the Gromacs 4.6.2 package or with code written in-house.


6

Page 7 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


For Hsp90, the simulation protocol is analogous and is fully described in 27. The starting structure was downloaded from the Protein Data Bank, file 1CG9.pdb 12. Production runs for the ATP and ADP cases were extended to 200ns.

Protein internal dynamics. In order to analyze the differences of the impact of each nucleotide on the internal dynamics of Trap1, we made use of the previously introduced distance fluctuation analysis. For each MD trajectory in different bound states, we computed on the equilibrated part of the trajectory (time interval 25–200 ns), the matrix of distance fluctuations, in which each element of the matrix corresponds to the DF parameter: DFij = where dij is the (time-dependent) distance of the Cα atoms of amino acids i and j and the brackets indicate the time-average over the trajectory. This paramenter is invariant under translations and rotations of the molecules and, unlike the covariance matrix, does not depend on the choice of a particular protein reference structure. The DF matrix, can be used to assess the intrinsic flexibility of proteins, and how it changes upon ligand binding. The DF was calculated for any pair of residues during the trajectory. This parameter characterizes residues that move in a highly coordinated fashion, and it is actually able to reflect the presence of specific coordination patterns and quasi-rigid domains motion in the protein of interest. In particular, pairs of amino acids belonging to the same quasi-rigid domain are associated with small distance fluctuations and vice-versa.

Local Flexibility Parameter and long range analysis of coordinated motion Local flexibility (LF) was obtained by calculating the average fluctuation in the distance dij between every Cα atom and the Cα atoms of neighboring residues j comprised in the interval (i− 2, i -2) along the sequence. The average LF values for consecutive amino acids along the sequence calculated for all simulations, range from 2.4 to 2.8 Å. In order to identify residues distant from the nucleotides binding site which display high coordination whit it despite their physical separation, the threshold for every simulation for discriminating high dynamic coordination at long distance has been set to the corresponding average LF value. The result of this analysis is reported in Figure 3.Long-range-analysis. Each bin of the histogram refers to a residue and gives the fraction of residues that have high coordination with it (DF < average LF) at


7


Page 8 of 33

distances larger than 40 Å. Residues corresponding to histogram peaks define regions that are specifically involved in efficient long-range correlations.

Principal component analysis The Bio3D R package (version 2.2–3) was used for PCA analysis 44. Principal component analysis was used to characterize the relationships between the structures obtained from molecular dynamics trajectory in different nucleotide bound states. In this analysis we used the representative structures of the most populated clusters of each simulation of the full-length protein, selecting a number of structures that cover at least 96% of the population of each simulated bound state. PCA is based on the diagonalization of the covariance matrix, C, with elements Cij calculated from the aligned and superimposed Cartesian coordinates, r, of equivalent Cα atoms: C(ij) = where i and j represent all possible pairs of 3N Cartesian coordinates (N is the number of atoms) and denotes the ensemble average. The eigenvectors of the covariance matrix (referred to as principal components (PCs)) are a linear basis set describing the distribution of structures in term of atomic displacement. The corresponding eigenvalues provide the variance of the distribution along the specific eigenvector. Projecting structures into the sub-space defined by the largest principal components provides a low-dimensional representation of the structures. The resulting low-dimensional conformer plots display the major differences between structures, enabling the inter-conformer analysis of the relationships among them.

Results and Discussion Molecular Dynamics (MD) simulations were carried out in explicit water starting from the crystal structure of the full-length Trap1 in the closed state. In the following paragraphs, the different conformations of the two protomers will be labeled as Buckled (Bu) and Straight (St). The most relevant closed states are ATP-ATP, ATP-ADP, ADP-ATP, and ADP-ADP (see

18

). Other mixed or

APO states are used as internal controls. Consistent with experimental findings 18, we decided to run multiple independent simulations for the double nucleotide systems, as detailed in Table 1 and in Materials and Methods.


8

Page 9 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Nucleotide state

Label for simulation

Simulated time

No nucleotide in both protomers

Bu.APO:St.APO

200ns

ATP in Buckled chain, ATP in Straight chain

Bu.ATP:St.ATP

600ns (Gromos) + 600ns (AMBER)

ADP in Buckled chain, ADP in Straight chain

Bu.ADP:St.ADP


ATP in Buckled chain

Bu.ATP:St.APO

200ns

ATP in Straight chain

Bu.APO:St.ATP

200ns

ATP in Buckled chain, ADP in Straight chain

Bu.ATP:St.ADP


ADP in Buckled chain, ATP in Straight chain

Bu.ADP:St.ATP


ATP in Buckled chain, ATP in Straight chain of the nostrap-Bu.ATP:St.ATP

200ns

truncated form of Trap1 ADP in Buckled chain, ADP in Straight chain of the nostrap-Bu.ADP:St.ADP

200ns

truncated form of Trap1

Table 1 Summarizing, based on the novel model of chaperone cycle proposed by Lavery et al. 9, which implies two closed states that sequentially perform differential ATP hydrolysis in the two protomers, we have simulated mixed ATP/ADP states, with either nucleotide form bound to the Buckled or Straight protomer, respectively. We have also simulated the full-length chaperone in different nucleotide-bound states, representing the partially or completely unliganded forms of the protein (Table 1).

In order to investigate the role of the straps on protein dynamics we also simulated Trap1 truncating this extension in the ATP-bound and ADP-bound forms (Table 1). Table 1 summarizes all the ligand states of the simulations and their respective labels used throughout the text, covering a total time span of 5.8 microseconds, for a system of about 200000 particles.

The Global Internal Dynamics of Trap1 is regulated by the nucleotide in an asymmetric manner. The analysis of nucleotide-modulated internal dynamics can help identify regions that manifest a dynamic response to ATP binding and its sequential hydrolysis, thus playing a critical role in the selection of microscopic states related to the onset and regulation of functionally oriented conformational changes

23-25, 27, 29-30, 45-48

. We have previously addressed this problem computationally

through a novel method of analysis of all-atom molecular dynamics simulations, which consists in


9


Page 10 of 33

calculating the mean square fluctuation of the inter-residue distances for every residue-pair to highlight specific patterns of ligand-dependent mechanical coordination throughout the whole structure 23-25, 27, 2930, 45-47

. This analysis, validated by a number of experimentally tested predictions

19

, was shown to

pinpoint amino acids that move in a coordinated manner, detecting groups of residues that most strongly contribute to modulating functionally relevant motions, even in the absence of major conformational changes.

Analysis of Trap1 dynamics in the simulated bound states shows that differential ATP and/or ADP binding significantly modulates the internal coordination, especially within single protomers (Figure 2). Upon moving from the Bu.ATP:St.ATP state to the Bu.ADP:St.ADP state, a qualitatively similar modification of the internal coordination patterns is observed in the Gromos and Amber simulations: in both simulation setups, the presence of two ATP molecules appears to determine a more defined blockcharacter within each protomer, indicative of the accumulation of internal protomer strain which may be needed to trigger ATP hydrolysis. In this context, it is worth underlining that the catalytic activity of the chaperone was experimentally shown to be facilitated by the accumulation and consequent release of strain from the structure 9. The presence of two ADP molecules induces a different internal dynamics in particular at the interfaces of the Small M-Domain and CTD, supporting the hypothesis that the M-Domain\CTD substructure is the one most prone to structural rearrangements.

The mixed ATP/ADP simulations, Bu.ATP:St.ADP and Bu.ADP:St.ATP, confirm the modulation of the flexibility of the M-Domain\CTD, in particular of the buckled protomer where ADP changes the connection between the CTD, the buckling region and the NTD. This observation supports the concept that the particular structural organization of this substructure in the buckled protomer (and consequent different degree of compactness compared to the straight one) indeed makes this region highly responsive to the type of nucleotide in the NTD binding site. In general, even though the matrices for the two mixed states are still qualitatively similar, fluctuations in the residue pair-distances of the protein in the specific protomers (see the Bu.ATP:St.ATP state as a reference) indicate that they have different internal dynamics. It is worth noting that when comparing the data from the two meta-trajectories using the two different force fields and simulation engines, differences emerge in the fine patterns. This is to be expected given the differences in their development. However, the overall results consistently capture the different protomer dynamics and the peculiar modulation of the M-Domain\CTD substructure in the buckled protomer. ACS Paragon Plus Environment

10

Page 11 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


In the nostrap-Bu.ATP:St.ATP simulation, both protomers display a higher flexibility than in the Bu.ATP:St.ATP state, leading to the loss of the coordinated motion between the two Large M-Domains and to the absence of the flexibility signature previously observed at the interface of the Small MDomain and the CTD. Consistent with previous observations on the role of the N-terminal extensions as regulators of the kinetic stabilization of the closed state ensemble, this result suggests that besides stabilizing the asymmetric closed state via additional contacts, the strap impacts Trap1 internal dynamic properties combining with ATP to determine high strain (rigidity) coupled to the large deviation from symmetry at the M-Domain\CTD interface. The absence of the strap results in a preferential intra-protomer coordination (see the APO state as a reference) and favors interprotomer flexibility compared to the Bu.ATP:St.ATP case. These two factors can expectedly combine to increase ATPase activity as observed for the strap deletion mutant: intraprotomer coordination can preorganize the single protomers for nucleotide binding, while larger interprotomer flexibility may allow for a faster conformational search of the ATPase competent state. A similar mechanism has been observed previously in the case of yHsp90 stimulation by allosteric modulators

29-30

and designed point mutations

19

. In general, these data suggest a complex molecular

mechanism for Trap1 reactivity. These results are reported in Supplementary Material.

Overall, these results combine to extend the concept of asymmetric functioning of Trap1 from the level of structure to that of conformational dynamics. The analysis of internal dynamics, in particular for the most populated states in solution, the double nucleotide ones, shows that nucleotide exchange modulates the degree of coordination throughout the protein with a distinction between the two protomers, consistent with their observed differential reactivity.

These observations also show that the presence of ATP is coupled to and modulates the conformational dynamics of the M-Domain\CTD interface, indicating that the structural properties of this important region of the chaperone, the client-binding site, are directly responsive to the presence and identity of the nucleotide. These data are consistent with previous X-ray and SAXS results that implied coupling between ATP hydrolysis, client binding site and structural remodeling of the client

9, 15

. From the

mechanistic point of view, the differential dynamic response to the nucleotides expands the available dynamic states of the chaperone, which can be exploited to modulate the recognition of structurally different client proteins as well as to provide additional levels of functional regulation.


11


Page 12 of 33

Identification of residues that respond to the nucleotide (Long range analysis) These preliminary analyses have shown that the dynamics of the closed state of Trap1 are particularly dependent on the nucleotide state and on the structural properties of the two protomers. The latter result in the mechanical modulation of regions that are distal from the ATP site, in particular the Middle Domains. Previously, analysis of MD simulations of yHsp90, Grp94 and HtpG using this approach showed that the effect of ATP and ADP binding at the NTD binding site can propagate to the region located at the M-Domain\CTD border, largely overlapping with the client binding site. The identification of distal residues that are most responsive to the presence of a specific nucleotide led to the design of small molecule ligands targeting such residues and able to affect Hsp90 functions 25, 29-30, 47

. In this work we use a similar approach to identify regions in Trap1 that communicate at long

distance. In particular, we combine the results of the analyses of global and local flexibility (see Methods) to identify Trap1 regions and secondary structure elements that may be allosterically coordinated with the N-terminal nucleotide-binding site.

For all the simulated states we generated a set of histograms to analyze the coordinated motion at increasing distances (Figure 3). To emphasize long-range coordination, for each residue, we only show the fraction of all other protein residues more than 40Å distant that move coherently with it (i.e. with fluctuations lower than the threshold defined in Materials and Methods; the same calculation has been carried out for 10, 20, 30, 60 and 80Å cutoffs, consistently with previous papers. The latter 2 distances giving no appreciable signal

23-25, 27, 29-30, 45-47

(data not shown)). Note that the number of

amino acid pairs at distance larger than 40A is approximately constant across the various types of conformers. Each bin in the histograms refers to a residue and shows the fraction of residues of the whole protein that are most prone to be coordinated with it. Ensembles of residues corresponding to histogram peaks define regions that are dynamically coordinated at a distance with a particular residue. Residues whose coordination with distal parts of the protein is conserved at increasing distances may aptly represent pathways that play a relevant role in the modulation of functional dynamics and in the response to nucleotides. Dynamic coordination was evaluated by examining the variance of the distance calculated for every pair of residues during the trajectory: low values identify pairs that move coherently. We thus set a threshold for efficient coordination. The threshold was defined as the average value of the variances of the distance of consecutive amino acids in the interval (i-2 to i+2), calculated for all pairs along the whole protein sequence. Since residues that belong to the same short sequence stretch are expected to ACS Paragon Plus Environment

12

Page 13 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


move in a highly coherent way because of their proximity, the defined threshold represents a convenient way to highlight those pairs of residues that move in a highly coordinated way, despite being distantly separated

Our analysis shows that all the simulated bound states have very different patterns of distal coordination, and these highlight the sensitivity of the M-Domain dynamics to the particular nucleotide state. Again, we focus in particular on the double nucleotide states as the ones most representative of the actual situation in solution. In the Bu.ATP:St.ATP state, ATP turns on the long-range connection between residues in the N-terminal and Middle Domains of both protomers, with the straight protomer showing a higher fraction of connected residues. Upon binding of two ADP molecules (Bu.ADP:St.ADP), coordination patterns consistently change in particular in the straight protomer. In the mixed states, which are the ones more likely to be populated in solution and responsible for regulating the chaperone cycle of Trap1, the Straight monomer consistently shows a higher degree of coordination compared to the Buckled one. This result supports the view that differential ATP hydrolysis modulates structural dynamics and induces the deformations in specific regions of the protein that are needed for function. In this picture, interactions in the two M-domains can differentially break and reassemble. Such dynamic differences between the two protomers may thus help switching among different nucleotide states. This scenario is reminiscent of the cracking model proposed by Wolynes and coworkers, which implied that local interaction reassembly events underlie allosteric enzyme function 49. Once more, notwithstanding finely detailed differences that are to be expected when looking at two different force fields and two different simulation engines, the overall results show that the differential dynamic rearrangements at the M-Domain\CTD interface in the two protomers in the mixed states, highlights once more how the different structural organization of Trap1 protomers combined to nucleotide processing determine the fine-tuning of dynamics in functionally relevant regions.

The remaining simulations from Table 1 are commented in the Supporting Information Material.

Analysis of specific coordination with ATP in the activated state: signal transduction pathways To further investigate the mechanisms linking the dynamics of the chaperone to the nucleotide state, we hypothesize that the conformational signal that depends on the presence of ATP in the NTDs arises from the residues in direct contact with the nucleotide and then that the signal is relayed by local structural and dynamic changes propagating along different pathways throughout the protein. In this ACS Paragon Plus Environment

13


Page 14 of 33

framework, we aim to identify key residues that underlie such pathways by detecting those amino acids that are highly dynamically connected specifically with residues of the nucleotide-binding site (the latter are: 130-141, 173,176-178,182,186,187, 192-196, 213-221, 234, 266, 268, 417, according to the 4IVG.pdb structure), and that are distal to this site. Since the ATP-state represents the activated one that may be targeted by clients and competed for by chemical intervention, we focused on this latter state (Figure 4). We then set out to evaluate the coupling between residues in the nucleotide binding site and all the residues of the protein at distances larger than 40Å. Then we selected only those residues whose variance of the distance is lower than the threshold defined in the previous paragraphs. In this way we filter out only those residues that move coherently with the residue of the nucleotidebinding site at long distance.

In the Bu.ATP:St.ATP simulation both protomers show a high number of residues mechanically connected with the ATP binding sites, in both the Gromacs and Amber settings (Figure 4). Remarkably, in this state, it is possible to find coordinated residue pairs even if the threshold on the relative distance is greater than 60Å. Interestingly, this analysis shows that the long-range dynamics connection of both ATP binding sites is directed towards the same protein region in the Middle domain of the Straight protomer. In particular residues of the ATP binding site of Buckled chain are connected with residues 365-375 (residue numbering from 4IYN.pdb) of the M-Domain of the other chain, while residues of the ATP binding sites of the Straight protomer are connected with residues 373-383 of the M-Domain of the same chain. The crystal structure of the full-length protein shows that some of these residues (365-375) correspond to a solvent-exposed notably hydrophobic loop, while residues 373-383 form one of the strands of the beta sheet in the Middle segment. It is important to stress that we were able to observe the dynamic connection between the ATP binding sites and residues in the Middle domain of the Straight protomer only in the simulation of the double ATP-bound state, which expectedly corresponds to the fully activated state of the chaperone. The presence of ATP stabilizes the NTD interfaces, and the stable contacts formed by the catalytic Arg at the top of the long helix in the Middle domain with the ATP molecules in both protomers favor long-range coordination with the distal three-helix bundle regions at the end of the M-Domains. In this background, the different degrees of compactness of the two MD:CTD interfaces, with the buckled protomer significantly less packed than the straight one, structurally supports the observed tendency of the M-domain of the Straight protomer to be the one most connected to the ATP site. The larger number of contacts among residues in this chain reverberates in a more efficient relay of the chemical information represented by the nucleotide. ACS Paragon Plus Environment

14

Page 15 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Interestingly, the observed dynamic communication implies that changes at the ATP-binding sites are connected with one single protein region, close to the client binding site, implying that the two protomers are not equivalent from a dynamic point of view. Altogether these dynamics-based data suggest that MD:CTD interface communicates directly with Trap1 catalytic domains, defining a direct link between the client binding site and the chaperone’s hydrolysis state. Thus, the asymmetric organization of the M-Domain emerges as a hot spot for structural and functional regulation.

A simple model of nucleotide regulated Trap1 conformational dynamics Experimental evidence demonstrates that ATP binding and hydrolysis are essential to client maturation 50

. However it is still unclear how the energy available from ATP hydrolysis would determine the client

remodeling and release process. The experimental results obtained in 9 allowed the Agard group to propose a model for the chaperone cycle in which ATP binding by both protomers shifts the protein population to a closed, strained, highenergy asymmetric state. More recent experimental data show that ATP hydrolysis is sequential and deterministic 18: hydrolysis happens first in one protomer and then in the other, without Trap1 leaving the closed state. In this framework, asymmetry sets up differential hydrolysis rates for each protomer with the buckled conformation favoring ATP processing: after the first hydrolysis in the buckled protomer, the asymmetry flips to the second one, while the whole dimer remains in the closed state, required for enzymatic activity. This model is also relevant to explain the general client remodeling mechanism: in fact, conformational flipping is centered on the client-binding site, and its connection to ATP hydrolysis provides direct coupling between the reactions happening in the N-terminal nucleotide binding site and the mechanical action that the chaperone performs on the client. Instead of focusing on the large conformational changes of the protein from the open V-shape state to the dimerized closed state, this model suggests that the utilization of the energy from ATP hydrolysis for client remodeling occurs through fine structural rearrangements in the closed state which depend on the bound nucleotide, exploiting the structural asymmetry in the homodimer. In this context we expect that the generated MD trajectories of the closed conformation, representing dynamic ensembles in different ligand conditions, may indicate which directions of conformational change are determined by the presence of a particular ligand. By analyzing the structural/dynamic similarity among the ensembles of different nucleotide complexes, we aim to shed light on the ACS Paragon Plus Environment

15


Page 16 of 33

progression through different states during the functional cycle of Trap1. To this end, we combined all the explored conformations obtained for each double nucleotide state for both force-fields and applied PCA analysis to the representative structures of the most populated clusters of each state, selecting a number of structures that covers at least 96% of the population of each state (see Methods). The principal components are a set of orthogonal vectors that represent the axes of maximal mean square displacement or variance of atom positional fluctuations. We used the first two principal components to analyze the structural similarity among different states (Figure 5). This graph reports on the eigenvalue associated to each dimension, which corresponds to the percentage of variance of atom positional fluctuations captured by these two components. It is important to point out that this analysis is able to discriminate the dynamic differences/similarities among the representative structures of the simulated states. From the energetic standpoint, in contrast, we are unable to evaluate the correct (free) energy differences between the different states, so that we cannot rigorously define transition pathways connecting them. The dynamic differences among the states highlighted by this analysis, and their relations in the PCA space, can thus be interpreted on the basis of experimental data on the transitions in the conformational cycle of Trap1. In this regard, we aim to push structural and dynamic detail into the updated model for the conformational cycle of Trap1 9, 15, 18. Our analysis suggests that the Bu.ATP:St:ATP state is distinct from the Bu.ADP:St:ATP and Bu.ATP:St:ADP states in the PCA space, suggesting that the differential hydrolysis shifts the population towards states which are well separated from the starting point of the cycle. While some overlap among states can be observed, it is interesting to note that the most different states in terms of structural displacements along the first two principal components are the Bu.ATP:St.ATP and the Bu.ADP:St.ATP states. They belong to two distinct clusters in the PCA space, suggesting that ATP hydrolysis of the buckled protomer would cause the protein in the Bu.ATP:St.ATP to shift into a dynamic state having different accessible conformations. As for the Bu.ATP:St.ADP state, it appears to be the conformational state that is closer to the Bu.ATP:St.ATP one, suggesting that more limited dynamic variations are necessary to shift between the two. In other words, if the ATP in the straight protomer is hydrolyzed first, limited structural rearrangements are required to progress through the cycle and, as a consequence, structural changes of the client-binding site residues that would be coupled to remodeling of the client are limited. By contrast, if ATP in the buckled protomer is hydrolyzed first, the conformational rearrangements required to progress through the cycle would


16

Page 17 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


expectedly be larger, determining considerable remodeling of the bound client. Interestingly, the two mixed nucleotide states (Bu.ADP:St.ATP and Bu.ATP:St.ADP) are close to each other supporting the hypothesis that the protein may flip between these two dynamic states without necessarily undergoing major conformational changes. It worth noting here, that the ‘flipping’ transition may still be high energy, so that the states can be distinct. In the light of the recent experimental model 18, PCA then leads to specific clusters, with the “biggest” change being Bu.ATP:St.ATP to Bu.ADP:St.ATP; flipping from this state would then lead to a partial relaxation to Bu.ATP:St.ADP, then to Bu.ADP:ST.ADP and finally back to the double ATP state. PCA analysis also allows us also to highlight what protein regions are responsible for the major differences between structures of the different states. A picture of these differences mapped onto the protein structure is shown in Figure 6. This Figure displays an interpolation between the most dissimilar structures in the distribution along the first principal component showing that the most dissimilar structures mainly differ at the small MD and in the CTD while NTDs marginally contribute to these differences, despite the fact these domains accommodate the different nucleotides that define the states. This data suggest that the presence/absence of the different nucleotides in the NTDs govern the rearrangement of the MDs and CTDs to progress through the functional cycle, while overall they maintain a similar conformation in all bound-states.

To provide an additional control on the structural differences, we compared the representative structures of the different states with two nucleotides bound, which correspond to the separated regions in the PCA plot above (Figure 7). Once more, it is interesting to observe that the largest structural variations center on the small MD:CTD interface. Taking the Bu.ATP:St.ATP structure as a reference, the RMSD for Bu.ADP:St.ATP and Bu.ADP:St.ADP reaches 8Å while the RMSD for the Bu.ATP:St.ADP structure is around 5Å, indicating that changing nucleotide in the buckled protomer may immediately translate into a structural perturbation. Finally, to quantify the degree of dynamical variation, we used these structures as input for the analysis implemented in the Aladyn webserver

51

.

This tool aligns pairs of structures by comparing their internal dynamics, calculated via an elastic network model, and detecting regions that can sustain similar movements 51. This approach may further support the distinction of the dynamic differences between specific protomeric states. The input structures are the two protometers from the representative conformation of the first most populate cluster obtained from the simulations of the Bu.ATP:St.ATP, Bu.ADP:St.ADP,


17


Page 18 of 33

Bu.ADP:St.ATP and Bu.ATP:St.ADP states. The results reported in Figure 8 show the alignments of the buckled protomer (cyan/blue) and the straight protomer (pink/red) in the various nucleotide bound states studied. The aligned regions are shown in red and blue. Interestingly, this analysis once more confirms that the bound nucleotides influence the internal dynamics of the two protomers in a specific way. Indeed, every bound state is characterized by dynamics alignments that involve different protein regions. In all cases the dynamics alignments superpose the corresponding protein regions of the two protomers, which is a non-trivial result as no information about the primary structure is used, suggesting that the analogue protein zones moves together to carry on the protein function. In the ATP-ase competent state, the dynamic alignment involves the interface between the large and the small middle domains and and the C-terminal domains, suggesting that these regions are more prone to large scale motions which can be involved in protein function. A similar path is shown in the Bu.ATP:St.ADP state. After hydrolysis of the buckled protomer (Bu.ADP:St.ATP state), the dynamic alignment highlights a large rotation around the region centered on the MTD:CTD interface in this protomer, where helix swapping determines structural asymmetry. In this state, the dynamical alignment mainly involves the NTDs and the large MDs, suggesting that conformational change of the straight protomer, which would be necessary to reach the ATP-ase competent state, is mainly due to the the movements of these two domains. In the Bu.ADP:St.ADP state, the dynamic alignment mainly involves the NTDs, which also move coherently, as shown in the distance fluctuations matrix.

Overall, the differences among these states are in agreement with the model that suggests that the differential ATP hydrolysis is coupled to rearrangement of the client binding site residues and would then be coupled to structural changes in the client.

CONCLUSIONS In this paper, we have used novel computational analyses to establish a mechanistic link at atomic resolution between the peculiar asymmetry reported for the X-ray structure of Trap1 in the closed state and the salient traits of its nucleotide-dependent dynamics. The presence of ATP in both monomers determines a significant inter-residue coordination that diffuses throughout the protein, inducing a degree of strain that is relaxed upon exchanging either one or both ATP molecules for ADP. In the former case, the resulting local and global coordination and strain patterns depend on the specific ACS Paragon Plus Environment

18

Page 19 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


protomer to which the ADP is bound. Furthermore, we observe that the region undergoing the most intense conformational and dynamic modulation upon nucleotide exchange corresponds to the substructure at the boundary between the small M-Domain and CTD, which in the X-ray structure is significantly reconfigured in one of the two protomers compared to the fully symmetric structure of yHsp90. Our data, consistent with new experimental findings on the differential role of the two protomers in the sequential ATP hydrolysis, bridge the nucleotide processing events in the NTD with the modulation of the dynamic and conformational properties of the client-binding region in the Middle domain, and shed light on the molecular mechanisms at the basis of Trap1 client-recognition. Targeting such asymmetrically modulated regions with small molecules might provide new opportunities to affect the mechanisms of conformational transition that are crucial for Trap1 activity. This pharmacological design strategy may aptly be translated into the discovery of Trap1 selective drugs and chemical tools.


19


Page 20 of 33

Captions for Figures Figure 1. Alignment of the full length protomers from Trap1, showing the maximal differences at the interface between the middle domains and the C-temrinal domains.

Figure 2. Distance fluctuation matrices for all the simulated bound states calculated considering the motions of Cα atoms around the average position. The color map is discretized to provide a clearer view of the value of the variance of the interatomic distances measured for any pair of residues during the trajectory. Residue pairs wit fluctuations between 0 and 2Å are white; between 2 and 4Å blue; larger than 4Å black. A) Results with Gromos simulations; B) Results with Amber simulations.

Figure 3. Analysis of the coordinated motion at distance higher than 40Å. Each bar refers to a residue and shows the fraction of residues of the whole protein that moves coherently with it, based on a threshold calculated on consecutive amminoacids (see main text). The percentage on each graph corresponds to the number of total residues which move in a coordinated way. A) Results with Gromos simulations; B) Results with Amber simulations.

Figure 4. Full-length structures of Trap1. Red color highlights those residues that move coherently with the residue of the ATP-binding site at long distance. A) Results with Gromos simulations; B) Results with Amber simulations.

Figure 5. Plot of PCA results for the representative structures of the most populated clusters of the simulated states of the full-length protein Trap1, selecting a number of structures that cover at least 96% of the population of each state.

Figure 6. Interpolation of the most dissimilar structures along the first Principal Component. The superposition of the interpolated structures shows that they mainly differ at the small Middle domain and in the C-terminal domain.

Figure 7. Structural comparison of the representative structures for the buckled protomer for the four double nucleotide states. The yellow shading indicates the point of maximal structural distortion.

Figure 8. Graphical representation of the Aladyn-server dynamic alignment.


20

Page 21 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


ASSOCIATED CONTENT Supporting Information. This material is available free of charge via the Internet at http://pubs.acs.org Supporting text: detailed description of APO states and comparison with yeast Hsp90 dynamics. Supporting figures: detailed figures describing the comparison of Trap1 and yHsp90 dynamics.

AUTHOR INFORMATION *Corresponding author: Giorgio Colombo, Istituto di Chimica del Riconoscimento Molecolare, CNR; via Mario Bianco 9, 20131 Milano, Italy. E-mail: [email protected]. Tel: +39-0228500031, Fax: +39-02-28901239.

Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript Funding Sources

This work was supported through funding to GC from Associazione Italiana Ricerca sul Cancro (AIRC) grants IG 15420 and IG 20019.

ABBREVIATIONS HSP90, Heat Shock Protein 90; Trap1, TNF receptor associated protein 1 a member of the Hsp90 family of proteins; PDB, Protein Data Bank (PDB); MD, Molecular Dynamics; DF, Distance fluctuations; LF, Local Flexibility.


21


Page 22 of 33

References 1. Smock, R. G.; Gierasch, L. M., Sending signals dynamically. Science 2009, 324, 198-203. 2. Swain, J. F.; Gierasch, L. M., The changing landscape of protein allostery. Curr. Opin. Struct. Biol. 2006, 16 (1), 102-108. 3. Nussinov, R.; Tsai, C.-J.; Li, J., Principles of Allosteric Interactions in Cell Signaling. J. Am. Chem. Soc. 2014, 136 (51), 17692-17701. 4. Hartl, F. U.; Bracher, A.; Hayer-Hartl, M., Molecular chaperones in protein folding and proteostasis. Nature 2011, 475, 324-332. 5. Johnson, J. L., Evolution and function of diverse Hsp90 homologs and cochaperone proteins. . Biochim. Biophys. Acta 2012, 1823, 607–613. 6. Li, J.; Buchner, J., Structure, function and regulation of the Hsp90 machinery. Biomed. J. 2013, 36 (3), 106-117. 7. Neckers, L.; Workman, P., Hsp90 Molecular Chaperone inhibitors: are we there yet? Clin Cancer Res 2013, 18 (64-76). 8. Street, T. O.; Zeng, X.; Pellarin, R.; Bonomi, M.; Sali, A.; Kelly, M. J. S.; Chu, F.; Agard, D. A., Elucidating the mechanism of substrate recognition by the bacterial Hsp90 molecular chaperone. J. Mol. Biol. 2014, 426, 2393–2404. 9. Lavery, L. A.; Partridge, J. R.; Ramelot, T. A.; Elnatan, D.; Kennedy, M. A.; Agard, D. A., Structural asimmetry in the closed state of mitochondrial Hsp90 (TRAP1) supports a two-step ATP hydrolysis mechanism. Mol. Cell. 2014, 53 (2), 330-343. 10. Krukenberg, K. A.; Street, T. O.; Lavery, L. A.; Agard, D. A., Conformational dynamics of the molecular chaperone Hsp90. Q. Rev. Biophys. 2011, 44 (2), 229-255. 11. Southworth, D. R.; Agard, D. A., Species-Dependent ensembles of conserved conformational states define the Hsp90 chaperone ATPase cycle. Mol. Cell. 2008, 32, 631-640. 12. Ali, M. M. U.; Roe, S. M.; Vaughan, C. K.; Meyer, P.; Panaretou, B.; Piper, P. W.; Prodromou, C.; Pearl, L. H., Crystal structure of an Hsp90-nucleotide-p23/Sba1 closed chaperone complex. . Nature 2006, 440 (7087), 1013-1017 13. Dollins, D. E.; Warren, J. J.; Immormino, R. M.; Gewirth, D. T., Structures of GRP94Nucleotide complexes reveal mechanistic differences between the hsp90 chaperones. Mol. Cell. 2007, 28 (1), 41-56. 14. Shiau, A. K.; Harris, S. F.; Southworth, D. R.; Agard, D. A., Structural analysis of E-coli hsp90 reveals dramatic nucleotide-dependent conformational rearrangements. Cell 2006, 127 (2), 329-340. 15. Partridge, J. R.; Lavery, L. A.; Elnatan, D.; Naber, N.; Cooke, R.; Agard, D. A., A novel Nterminal extension in mitochondrial TRAP1 serves as a thermal regulator of chaperone activity. eLife 2014, 10.7554/eLife.03487. 16. Rasola, A.; Neckers, L.; Picard, D., Mitochondrial oxidative phosphorylation TRAP(1)ped in tumor cells. Trends Cell Biol 2014, 24 (8), 455-463. 17. Genest, O.; Reidy, M.; Street, T. O.; Hoskins, J. R.; Camberg, J. L.; Agard, D. A.; Masison, D. C.; Wickner, S., Uncovering a region of heat shock protein 90 important for client binding in E. coli and chaperone function in yeast. Mol Cell 2013, 49 (3), 464-473. 18. Elnatan, D.; Betegon, M.; Liu, Y.; Ramelot, T.; Kennedy, M. A.; Agard, D. A., Symmetry broken and rebroken during the ATP hydrolysis cycle of the mitochondrial Hsp90 TRAP1. eLife 2017, 6, e25235. 19. Rehn, A.; Moroni, E.; Zierer, B. K.; Tippel, F.; Morra, G.; John, C.; Richter, K.; Colombo, G.; Buchner, J., Allosteric Regulation Points Control the Conformational Dynamics of the Molecular Chaperone Hsp90. J. Mol. Biol. 2016, 428 (22), 4559-4571. 20. Nussinov, R.; Tsai, C.-J., Allostery in Disease and in Drug Discovery. Cell 2013, 153 (2), 293ACS Paragon Plus Environment

22

Page 23 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


305. 21. Tsai, C.-J.; Nussinov, R., A Unified View of “How Allostery Works”. PLoS computational biology 2014, 10 (2), e1003394. 22. Cooper, A.; Dryden, D. T., Allostery without conformational change. A plausible model. Eur. Biophys. J. 1984, 11, 103-109. 23. Morra, G.; Genoni, A.; Colombo, G., Mechanisms of Differential Allosteric Modulation in Homologous Proteins: Insights from the Analysis of Internal Dynamics and Energetics of PDZ Domains. J Chem Theory Comput. 2014, 10 (12), 5677-5689 24. Morra, G.; Potestio, R.; Micheletti, C.; Colombo, G., Corresponding Functional Dynamics across the Hsp90 Chaperone Family: Insights from a Multiscale Analysis of MD Simulations. Plos Comput. Biol. 2012, 8 (3), e1002433. 25. Morra, G.; Neves, M. A. C.; Plescia, C. J.; Tsutsumi, S.; Neckers, L.; Verkhivker, G.; Altieri, D. C.; Colombo, G., Dynamics-Based Discovery of Allosteric Inhibitors: Selection of New Ligands for the C-terminal Domain of Hsp90. J. Chem. Theory Comput. 2010, 6 (9), 2978-2989. 26. Bracci, A.; Colombo, G.; Ronchetti, F.; Compostella, F., 2 '-O-Alkyl Derivatives and 5 'Analogues of 5-Aminoimidazole-4-carboxamide-1-beta-D-ribofuranoside (AICAR) as Potential Hsp90 Inhibitors. European Journal of Organic Chemistry 2009, (34), 5913-5919. 27. Morra, G.; Verkhivker, G. M.; Colombo, G., Modeling signal propagation mechanisms and ligand-based conformational dynamics of the Hsp90 molecular chaperone full length dimer. PLOS Comp. Biol. 2009, 5 (3), e1000323. 28. Meli, M.; Gasset, M.; Colombo, G., Dynamic Diagnosis of Familial Prion Diseases Supports the beta 2-alpha 2 Loop as a Universal Interference Target. Plos One 2011, 6 (4), e19093. 29. Vettoretti, G.; Moroni, E.; Sattin, S.; Tao, J.; Agard, D.; Bernardi, A.; Colombo, G., Molecular Dynamics Simulations Reveal the Mechanisms of Allosteric Activation of Hsp90 by Designed Ligands. Sci. Rep. 2016, 6, 23830. 30. Sattin, S.; Tao, J.; Vettoretti, G.; Moroni, E.; Pennati, M.; Lopergolo, A.; Morelli, L.; Bugatti, A.; Zuehlke, A.; Moses, M.; Prince, T.; Kijima, T.; Beebe, K.; Rusnati, M.; Neckers, L.; Zaffaroni, N.; Agard, D.; Bernardi, A.; Colombo, G., Activation of Hsp90 Enzymatic Activity and Conformational Dynamics through Rationally Designed Allosteric Ligands. Chemistry 2015, 21 (39), 13598-13608. 31. Pontiggia, F.; Colombo, G.; Micheletti, C.; Orland, H., Anharmonicity and self-similarity of the free energy landscape of protein G. Phys. Rev. Lett. 2007, 98 (4), 048102. 32. Pontiggia, F.; Zen, A.; Micheletti, C., Small and large scale conformational changes of adenylate kinase: a molecular dynamics study of the subdomain motion and mechanics. Biophys J. 2008, 95 5901-5912. 33. Hess, B.; Kutzner, C.; van der Spoel, D.; Lindahl, E., GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation. J. Chem. Theory and Computation 2008, 4 (3), 435-447. 34. van Gunsteren, W. F.; Daura, X.; Mark, A. E., GROMOS Force Field. Encyclopedia of Computational Chemistry 1998, 2, 1211-1216. 35. Scott, W. R. P.; Hunenberger, P. H.; Tironi, I. G.; Mark, A. E.; Billeter, S. R.; Fennen, J.; Torda, A. E.; Huber, T.; Kruger, P.; Gunsteren, W. F. V., TheGROMOS biomolecular simulation program package. J.Phys.Chem.A 1999, 103, 3596-3607. 36. Berendsen, H. J. C.; Grigera, J. R.; Straatsma, P. R., The missing term in effective pair potentials. J. Phys. Chem. 1987, 91, 6269-6271. 37. Case, D. A.; Cerutti, D. S.; Cheatham, T. E. I.; Darden, T. A.; Duke, R. E.; Giese, T. J.; Gohlke, H.; Goetz, A. W.; Greene, D.; Homeyer, N.; Izadi, S.; Kovalenko, A.; Lee, T. S.; LeGrand, S.; Li, P. L., C. ; Liu, J.; Luchko, T.; Luo, R.; Mermelstein, D.; Merz, K. M.; Monard, G.; Nguyen, H.; Omelyan, I.; Onufriev, A.; Pan, F.; Qi, R.; Roe, D. R.; Roitberg, A.; Sagui, C.; Simmerling, C. L.; Botello-Smith, W. M.; Swails, J.; Walker, R. C.; Wang, J.; Wolf, R. M.; Wu, X.; Xiao, L.; York, D. M.; Kollman, P. A., ACS Paragon Plus Environment

23


Page 24 of 33

AMBER 2017. University of California, San Francisco 2017. 38. Hess, B.; Bekker, H.; Fraaije, J. G. E. M.; Berendsen, H. J. C., A linear constraint solver for molecular simulations. J.Comp.Chem. 1997, 18, 1463-1472. 39. Miyamoto, S.; Kollman, P. A., SETTLE: An analytical version of the SHAKE and RATTLE algorithms for rigid water models. J. Comp. Chem. 1992, 13, 952-962. 40. Berendsen, H. J. C.; Postma, J. P. M.; van Gunsteren, W. F.; Di Nola, A.; Haak, J. R., Molecular dynamics with coupling to an external bath. J. Chem. Phys. 1984, 81, 3684-3690. 41. Jorgensen, W. L.; Chandrasekhar, J.; Madura, J.; Impey, R. W.; Klein, M. L., Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 1983, 79, 926-935. 42. Darden, T.; York, D.; Pedersen, L., Particle mesh Ewald: An N-log(N) method for Ewald sums in large systems. J. Chem. Phys. 1993, 98 (10089-10092). 43. Ryckaert, J. P.; Ciccotti, G.; Berendsen, H. J. C., Numerical Integration of the Cartesian Equations of Motion of a System with Constraints: Molecular Dynamics of n-Alkanes. Journal of Computational Physics. 1977, 23 (3), 327–341. 44. Grant, B. J.; Rodrigues, A. P.; ElSawy, K. M.; McCammon, J. A.; Caves, L. S., Bio3d: an R package for the comparative analysis of protein structures. Bioinformatics 2006, 22 (21), 2695-2696. 45. Colombo, G.; Morra, G.; Meli, M.; Verkhivker, G. M., Understanding ligand-based modulation of the Hsp90 molecular chaperone dynamics at atomic resolution. Proc. Natl. Acad. Sci. USA 2008, 105 (23), 7676-7681. 46. Morra, G.; Baragli, C.; Colombo, G., Selecting sequences that fold into a defined 3D structure: A new approach for protein design based on molecular dynamics and energetics. Biophys. Chem. 2010, 146 (Issue 2-3), 76-84. 47. Moroni, E.; Zhao, H.; Blagg, B. S.; Colombo, G., Exploiting Conformational Dynamics in Drug Discovery: Design of C-Terminal Inhibitors of Hsp90 with Improved Activities. J Chem Inf Model 2014, 54 (1), 195-208. 48. D'Annessa, I.; Sattin, S.; Tao, J.; Pennati, M.; Sànchez-Martìn, C.; Moroni, E.; Rasola, A.; Zaffaroni, N.; Agard, D. A.; Bernardi, A.; Colombo, G., Design of allosteric stimulators of the HSP90 ATPase as novel anticancer leads. Chemistry 2017, doi: 10.1002/chem.201700169. 49. Miyashita, O.; Onuchic, J. N.; Wolynes, P. G., Nonlinear elasticity, proteinquakes, and the energy landscapes of functional transitions in proteins. Proceedings of the National Academy of Sciences 2003, 100 (22), 12570-12575. 50. Panaretou, B.; Prodromou, C.; Roe, S. M.; O'Brien, R.; Ladbury, J. E.; Piper, P. W.; Pearl, L. H., ATP binding and hydrolysis are essential to the function of the Hsp90 molecular chaperone in vivo. EMBO J 1998, 17, 4829–4836. 51. Potestio, R.; Aleksiev, T.; Pontiggia, F.; Cozzini, S.; Micheletti, C., ALADYN: a web server for aligning proteins by matching their large-scale motion. Nucleic Acids Research 2010, 38 (Web Server issue), W41-W45.


24

Page 25 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


82x36mm (300 x 300 DPI)



Figure 1. Alignment of the full length protomers from Trap1, showing the maximal differences at the interface between the middle domains and the C-terminal domains. 16x24mm (600 x 600 DPI)


Page 26 of 33

Page 27 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 2. Distance fluctuation matrices for all the simulated bound states calculated considering the motions of Cα atoms around the average position. The color map is discretized to provide a clearer view of the value of the variance of the interatomic distances measured for any pair of residues during the trajectory. Residue pairs wit fluctuations between 0 and 2Å are white; between 2 and 4Å blue; larger than 4Å black. A) Results with Gromos simulations; B) Results with Amber simulations. 916x1222mm (72 x 72 DPI)



Figure 3. Analysis of the coordinated motion at distance higher than 40Å. Each bar refers to a residue and shows the fraction of residues of the whole protein that moves coherently with it, based on a threshold calculated on consecutive amminoacids (see main text). The percentage on each graph corresponds to the number of total residues which move in a coordinated way. A) Results with Gromos simulations; B) Results with Amber simulations. 917x687mm (72 x 72 DPI)


Page 28 of 33

Page 29 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 4. Full-length structures of Trap1. Red color highlights those residues that move coherently with the residue of the ATP-binding site at long distance. A) Results with Gromos simulations; B) Results with Amber simulations. 917x687mm (72 x 72 DPI)



Figure 5. Plot of PCA results for the representative structures of the most populated clusters of the simulated states of the full-length protein Trap1, selecting a number of structures that cover at least 96% of the population of each state. 87x42mm (300 x 300 DPI)


Page 30 of 33

Page 31 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 6. Interpolation of the most dissimilar structures along the first Principal Component. The superposition of the interpolated structures shows that they mainly differ at the small Middle domain and in the C-terminal domain. 145x237mm (300 x 300 DPI)



Figure 7. Structural comparison of the representative structures of buckled protomer for the four double nucleotide states. The yellow shading indicates the point of maximal structural distortion. 389x669mm (72 x 72 DPI)


Page 32 of 33

Page 33 of 33 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 8. Graphical representation of the Aladyn-server dynamic alignment. 352x526mm (72 x 72 DPI)


The Structural Asymmetry of Mitochondrial Hsp90 ... - ACS Publications

Recommend Documents