Controlling protein function by fine-tuning conformational flexibility
Protein function is essential for life as we know it . It is largely encoded in a protein’s amino-acid chain that dictates not only the specific 3D structure , but also the conformational flexibility and dynamics of a protein in a given environment . Precise regulation of protein function is vital for every living cell to cope with an ever-changing environment , and occurs on many levels pre- and post-translationally ( Vogel and Marcotte , 2012; Hirano et al . , 2016 ) . After translation by the ribosome , protein function depends strongly on post-translational modifications ( PTMs ) ( Deribe et al . , 2010 ) , but also on binding of nucleotides ( Hodge and Ridley , 2016 ) , cofactors ( Weikum et al . , 2017 ) , various protein-protein interactions ( PPIs ) ( Scott et al . , 2016 ) , and global effects , such as temperature ( Danielsson et al . , 2015 ) , macro-molecular crowding and phase separation ( Uversky , 2017 ) , redox conditions ( Levin et al . , 2017 ) , osmolarity ( de Nadal and Posas , 2015 ) etc . Importantly , this regulation occurs on very diverse levels of localization . Global effects affect the whole protein non-specifically , PPIs act at a given interface and site-specific modifications are very localized . Nevertheless , all of them influence the molecular properties that determine the 3D conformation , the conformational dynamics , and thereby also the function of a protein ( Schwenkert et al . , 2014; Lewandowski et al . , 2015; Schummel et al . , 2016; Wei et al . , 2016; Csizmok and Forman-Kay , 2018 ) . The chaperone protein Hsp90 ( Schopf et al . , 2017 ) is an excellent test system to investigate diverse regulation mechanisms ( Stetz et al . , 2018 ) . It was recently discussed that a single PTM can functionally mimic a specific co-chaperone interaction in human Hsp90 ( Zuehlke et al . , 2017 ) . Here we take a next step and disentangle how a PTM-related point mutation , a co-chaperone interaction , and macro-molecular crowding affect the function , kinetics , and thermodynamics of this multi-domain protein . Hsp90 is an important metabolic hub . Assisted by about twenty known cochaperones , yeast Hsp90 is involved in the maturation of 20% of the entire proteome ( Taipale et al . , 2010 ) . Among its substrates ( referred to as ‘clients’ ) are many kinases involved in signal transduction , hormone receptors , the 'guardian of the genome p53' ( Lane , 1992 ) , and also cytoskeletal proteins such as actin , tubulin , and many more ( Pearl and Prodromou , 2006; Khandelwal et al . , 2016 ) . Cancer cells were found to be ‘addicted’ to Hsp90 ( Trepel et al . , 2010 ) , which is therefor also a prominent drug target in cancer research . Hsp90 is a homo-dimer where each monomer consists of three domains ( Ali et al . , 2006 ) : the N-terminal domain ( N ) with a slow ATPase function , the middle domain ( M ) believed to be the primary client interaction site ( Verba et al . , 2016 ) , and the C-terminal domain providing the main dimerization contacts . Apart from closed conformations , where the three domains align in parallel , Hsp90 exists primarily in V-shaped , open conformations with dissociated N-terminal and middle domains ( Krukenberg et al . , 2008; Hellenkamp et al . , 2017 ) . Both global arrangements are semi-stable at room temperature . As a consequence , Hsp90 alternates constantly between open and closed conformations - even in the absence of the chemical energy source , ATP ( Mickler et al . , 2009; Schmid et al . , 2016; Lee et al . , 2019 ) . Surprisingly , the characteristic conformational changes of Hsp90 are only little affected by e . g . anti-cancer drug candidates ( Schmid et al . , 2018 ) or natural nucleotides ( Schmid et al . , 2016 ) . In addition , to the stress-induced isoform discussed herein ( Hsp82 ) , there is also a cognate isoform ( Hsc82 ) in yeast , which differs in unfolding stability , client range and more , despite 97% sequence identity ( Girstmair et al . , 2019 ) . Here , we present three orthogonal ways to modulate Hsp90's conformational state space , illustrated in Figure 1 . The investigated point mutation A577I is located in the C-terminal hinge region of Hsp90 . Residue A577 is the equivalent of the post-translational S-nitrosylation site C598 in human Hsp90 ( Martínez-Ruiz et al . , 2005 ) . While nitrosylation of that residue has a two-fold inhibitory effect – on the ATPase function and the client stimulation by human Hsp90 – the A577I mutation caused a nearly 4-fold amplification of the ATPase rate ( Retzlaff et al . , 2009 ) . The fact that the point mutation is located in the C-terminal domain and the ATP binding site in the N-domain indicates a long-range communication , offering valuable mechanistic insight in Hsp90’s intra-molecular plasticity . Second , we consider the protein-protein interactions between Hsp90 and the activating co-chaperone Aha1 , which is a well-known stimulator of Hsp90's inherently slow ATPase activity . It makes contacts to the middle and N-terminal domain , which rearranges the ATP lid ( Schulze et al . , 2016 ) , and the catalytic loop ( including R380 ) ( Pearl , 2016 ) in a favorable way for ATP hydrolysis . The affinity of Aha1 for Hsp90 itself is also markedly enhanced by PTMs ( Xu et al . , 2019 ) . The third way of modulation mimics the crowding encountered in the cell , which is full of proteins , nucleic acids , vesicles and organelles . We mimic cellular macro-molecular crowding using the common crowding agent Ficoll400 , that is branched polymeric sucrose . In contrast to the previous two modulations , crowding represents a completely non-specific , physical interference . At first sight , all three modulations provoke a similar steady-state behavior in Hsp90 . But our single-molecule experiments allow us to disentangle the different underlying causes thereof .
First we follow yeast Hsp90's conformational kinetics in real-time using single-molecule Förster resonance energy transfer ( smFRET ) measured on a total-internal reflection fluorescence ( TIRF ) microscope ( Figure 2a ) . The FRET pair configuration displayed in Figure 2a ( top ) results in low FRET efficiency ( little acceptor fluorescence ) for V-shaped , open conformations of Hsp90 , and high FRET efficiency ( intense acceptor fluorescence ) for more compact , closed conformations . This allows us to obtain steady-state information , like the population of closed conformations , and also the kinetics of conformational changes ( Schmid et al . , 2016; Roy et al . , 2008; Lerner et al . , 2018; Mazal and Haran , 2019 ) . Example traces obtained from three Hsp90 molecules under different conditions are displayed in Figure 2b: First for the point mutant A577I , then in the presence of the cochaperone Aha1 , and lastly under macro-molecular crowding by Ficoll400 . The observed transitions between the low- and high-FRET states reflect global opening or closing . Figure 2c shows the steady-state ( equilibrium ) population of open and closed conformations . In all three cases , a shift toward closed conformations is observed with respect to the corresponding reference distribution obtained under equivalent experimental conditions ( see caption of Figure 2 and Materials and methods for details ) . The optimal buffer conditions for each of the three cases differ slightly , which explains the differences between the three reference datasets displayed in Figure 2c ( black lines ) . Relative populations and their uncertainties were obtained by bootstrapping ( see Materials and methods and Supplementary file 1 ) . The A577I mutation increased the closed population from ( 13 ± 3 . 5 ) % to ( 51 ± 5 . 5 ) % . This is a large effect considering that no big change in hydrophobic nor charged interactions is expected to result from this hydrophobic-to-hydrophobic point mutation . In particular , as the slightly bulkier isoleucine side chain points outward in the crystal structure of Hsp90’s closed conformation ( Ali et al . , 2006 ) . In addition to the A577I homodimer , already the A577I/wild type ( wt ) hetero-dimer shows a considerably larger population of closed conformations , especially in the presence of ATP ( Figure 2—figure supplement 3 ( left ) ) . Under ADP conditions the additive effect is also observed , but weaker ( Figure 2—figure supplement 3 ( right ) ) . Under both conditions , the second A577I in the homodimer leads to a further shift toward closed conformations . The slight but consistent shift of the corresponding low-FRET peak in Figure 2c ( left ) could be explained by a sterical hindrance of the farthest opening in the A577I homodimer . Furthermore , very fast transitions at the temporal resolution limit ( 200 ms ) occurred more frequently , which can be seen by the increased overlap between the two populations . Both , sterical hindrance and faster transitions , can be interpreted as a global stiffening of Hsp90’s structural core formed by the C- and middle domain . The interaction with Aha1 ( Figure 2c , center ) forms inter-domain ( N–M ) and inter-monomer contacts . The latter increase the affinity for N-N binding , and thus cause Hsp90 to shift from ( 24 ± 4 . 0 ) % closed to ( 48 ± 5 . 0 ) % closed population , which is in line with previous qualitative reports ( Hessling et al . , 2009; Wortmann et al . , 2017 ) . Lastly , macro-molecular crowding increased the closed population from ( 11 ± 4 . 5 ) % to ( 50 ± 10 . 5 ) % , in agreement with previous ensemble findings ( Halpin et al . , 2016 ) . In contrast , to the A577I mutant , crowding slowed down fast fluctuation at the resolution limit , which creates well-separated populations in Figure 2c ) . The induced shift toward closed conformations appears in a concentration-dependent manner , as can be seen in Figure 2—figure supplement 4 . In contrast to polymeric , branched sucrose ( Ficoll400 ) , monomeric sucrose had only negligible effect on the steady-state populations . This proves that macro-molecular crowding is the cause of the observed population shift , and a biochemical glucose-associated reason can be dismissed . In all three cases , a clear shift toward closed conformations is observed , although to slightly different extents . Importantly , based on these distributions alone , the energetic origin of the population shift remains unclear . That is whether the observations arise from a stabilization of closed conformations , or a destabilization of the open conformations , or even a combination of both . To answer these questions , we solved the full kinetic rate model , presented below . Figure 3a shows the kinetic rate models describing Hsp90's global opening and closing dynamics . The significant changes caused by each type of modulation are highlighted in red and green as indicated . The corresponding quantitative rate changes and confidence intervals are displayed in Figure 3b . We used the Single-Molecule Analysis of Complex Kinetic Sequences ( SMACKS [Schmid et al . , 2016] ) to quantify rate constants and uncertainties directly from the smFRET raw data . For Hsp90’s global conformational changes , we consistently infer 4-state models ( Schmid et al . , 2016; Schmid et al . , 2018; Schmid and Hugel , 2018 ) : two low-FRET states ( open conformations ) and two high-FRET states ( closed conformations ) . Although only two different FRET efficiencies can be resolved , at least four kinetic states are needed to describe the observed kinetic heterogeneity . Based on recent results ( Hellenkamp et al . , 2017 ) , we expect an entire ensemble of open sub-conformations that - on the timescale of the experiment - are sufficiently well described by two kinetically different low-FRET states . The two closed states , one short-lived ( state 2 ) and one longer-lived ( state 3 ) , likely differ in local conformational elements ( Giannoulis et al . , 2020; Huang et al . , 2019 ) . The well-known N-terminal beta-sheet with or without its cross-monomer contacts ( as observed in the closed crystal structure [Ali et al . , 2006] ) could explain the additional stabilization of state 3 with respect to state 2 . All states 0 , 1 , 2 , 3 of this highly dynamic Hsp90 system represent conformational ensembles that are defined by their FRET efficiency and their kinetics ( rather than discrete or ‘frozen’ conformations ) . In the case of the cochaperone Aha1 , the shift in the FRET efficiency histogram originates from opposing changes of the fast rates between states 1 and 2 ( Figure 3—figure supplement 1 ) . This is in contrast to the effect of the C-terminal point mutation A577I , which collectively accelerates the pathway from state 0 via state 1 and state 2 to state 3 . Note that a kinetic model with only three links - similar to the model for crowding in Figure 3a , right - is statistically sufficient ( according to likelihood ratio testing detailed in Schmid et al . , 2016 SI point 1 . 2 ) to describe the observed kinetics of the A577I homodimer , implying less kinetically heterogeneous fluctuations ( Figure 3—figure supplement 2 ) . Under macro-molecular crowding , changes of the conformational dynamics are visible already from the stationary distributions: as shown in Figure 2a , the low and high FRET populations are most separated in this case . This is indicative of fast fluctuations , at or below the timescale of the sampling rate ( 5 Hz ) that are slowed down at higher viscosity . Still , transitions between open and closed conformations are regularly observed in the experiment ( Figure 3—figure supplement 3 ) . For the fully resolved kinetics , the main difference is observed for the rates between the closed states 2 and 3 . This agrees with the increase of the closed population under macro-molecular – but not small molecular – crowding . Altogether , Figure 3 shows three completely different kinetic effects that underlie seemingly analogous ensemble behavior . Based on the complete kinetic rate models , we can now deduce the impact on free energies along a specific spatial reaction coordinate , here the N-terminal extension ( Figure 4 ) . The point mutation A577I causes an asymmetric destabilization of open conformations . Aha1 leads to simultaneous destabilization of open conformations and stabilization of closed conformations , whereas macro-molecular crowding only stabilizes closed conformations . Importantly , this information is not accessible from the steady-state distributions in Figure 2c . The collective shift toward closed conformations is accompanied by an overall increase in ATPase activity under all three conditions ( Figure 5 ) : 7-fold for A577I , 17-fold for Aha1 , 4-fold for crowding , respectively . Thus , the increase in ATP hydrolysis rate does not reflect the increase in the closed population observed in Figure 2c . This is a first indication of causalities that involve more than just the occurrence of closed conformations . In the following , we dissect the molecular origins of the increased ATPase activity . The effect of macro-molecular crowding can serve as an estimate of the ATPase stimulation caused exclusively by the relative stabilization of closed conformations , because a biochemical interaction of sucrose was excluded in control experiments ( see above ) . Remarkably , the entirely non-specific interaction leads already to a considerable ATPase acceleration of a factor 4 . This supports the wide-spread notion that the closed conformation represents Hsp90's active state ( Prodromou , 2012 ) . But , in comparison to the biochemical effect of the cochaperone Aha1 , the stimulation by crowding is still modest , despite the much larger closed population . Specifically , the 4 . 5-fold increased closed population , comes with a 4-fold increased ATPase activity , whereas in the presence of Aha1 already a 2-fold increased closed population is accompanied by a 17-fold ATPase stimulation . The fact that Aha1 induces the smallest increase in closed population , but under the same conditions the largest ATPase stimulation , highlights the functional importance of specific contacts between Aha1 and Hsp90 , which are responsible for 88% of the ATPase stimulation by Aha1 . In the case of the A577I mutant a 3 . 9-fold increased closed population comes with a 7-fold ATPase amplification . This could result from the mentioned hindrance of extremely open states indicating a conformational stiffening , restricting Hsp90's native flexibility . In other words , not only changes in the equilibrium , but also changes in the kinetics affect the ATPase activity as discussed below . A comparison of the observed changes on the conformational steady-state and the ATPase rate allows us to estimate the contribution of conformational confinement in each case ( Supplementary file 1B ) . We find that conformational confinement accounts for 100% of the ATPase stimulation induced by macro-molecular crowding , for 60% of the stimulation by the point mutation A577I , and for only 10% of the stimulation by cochaperone Aha1 . The contribution of conformational confinement is thus largest for purely non-specific interactions , while additional allosteric effects may increase the stimulation by A577I , and specific rearrangements of the active site dominate the stimulating action of cochaperone Aha1 . Our data do not indicate additional combinatorial effects of these three stimulations , which can be investigated in a future study .
Herein we compare three types of Hsp90 modulations , spanning a wide range from a site-specific point mutation , via cochaperone binding , to completely non-specific macro-molecular crowding . All three modulations provoke a similar steady-state ( equilibrium ) behavior , namely an increase in Hsp90's closed conformation and in Hsp90's ATPase rate . In contrast , they show significant differences in their kinetics , which could be revealed by single-molecule FRET . This can be rationalized by the emerging picture of yeast Hsp90 , as a very flexible dimer that relies critically on external assistance ( e . g . by cochaperones ) to control its non-productive flexibility . For example , Hsp90’s ATPase function requires the concerted action of the N-terminal nucleotide binding pocket with the ATP lid and distant elements such as the catalytic loop of the middle domain and parts of the opposite N-domain ( the N-terminal β1-α1 segment ) . These elements – also called the catalytic unit ( Prodromou , 2012 ) - however , are very flexible , such as the entire multi-domain dimer . Consequently , anything that constrains this flexibility and confines Hsp90 in a more compact conformation , has a high potential to increase the combined probability for such a concerted action - be it by specific or even non-specific interaction . Figure 6 shows that the functional impact of conformational confinement can be understood as a direct result of combinatorics: in a flexible protein such as Hsp90 , the catalytically active elements have many translational and rotational degrees of freedom . Thus , the probability for a certain hydrolysis-competent conformation is very small . It is however increased dramatically by conditions that constrain these degrees of freedom – even non-specifically – and localize the catalytically active elements . This notion can be further extended to cochaperone binding , and it also explains mutual effects upon client interaction . We conclude , while Hsp90’s flexibility may facilitate its numerous interactions with diverse clients and cochaperones , the flexibility itself has substantial off-state character regarding the ATPase function of Hsp90 . In turn , by directly affecting the lifetime of the nucleotide/active site contacts and the resulting structural stabilization , ATP hydrolysis controls also longer-range allosteric effects linked to these residues . A closer look at the regulation of Hsp90's conformational energy landscape by single-molecule FRET shows the many ways to reach similar ensemble results . The point mutation A557I destabilizes the open conformation , most probably by preventing access to a subset of the conformational ensemble of open states . This leads to an overall stiffened structure ( more confined ) of the A577I homodimer and therefore less extensive random walks , that is a more streamlined conformational transition toward the closed conformations . Macro-molecular crowding stabilizes the closed conformation by simple , sterical confinement . The cochaperone Aha1 combines both mechanisms with additional specific rearrangements . In theory , all three modulations can lead to the exactly same thermodynamic observation , and in fact we observe very similar steady-state distributions . Nevertheless , the kinetics may still vary significantly – as experimentally demonstrated herein . This is an important mathematical fact that holds true for all protein systems . Moreover , our findings indicate that regulation by cochaperones - and protein-protein interactions in general - can have far-reaching thermodynamic , kinetic , and functional consequences . Some of them can possibly be mimicked by individual point mutations , but other consequences might be missed . Lastly , as shown in this work , already non-specific , purely physical macro-molecular crowding has strong effects on thermodynamics , kinetics and function , therefore caution is advised when relating in vitro findings to in vivo function . Certain mutations that show little or no ATPase activity in vitro , may be ‘rescued’ by the conformational confinement in the crowded cellular environment , and still be ATPase active in vivo . As demonstrated herein , in many in vitro experiments macro-molecular crowding could easily be included . In conclusion , we demonstrated herein three ways of protein regulation , ranging from site-specific localized to global modulations . All three ways show very similar thermodynamic observations , which are , however , caused by clearly different conformational kinetics . This is direct evidence for the importance of kinetics , and of the dynamic structure–function relationship in proteins . The reduction of non-productive structural flexibility stimulates Hsp90’s ATPase function even by entirely non-specific means . Our findings demonstrate that functional stimulation as a result of conformational combinatorics plays an important role in protein regulation . We anticipate that such conformational confinement - by localized or global modulations - is an important mechanistic concept with wide-spread implications for protein function in diverse systems .
Yeast Hsp90 dimers ( UniProtKB: P02829 ) with a C-terminal coiled-coil motif ( kinesin neck region of D . melanogaster ) were used to avoid dissociation at low concentrations ( Mickler et al . , 2009 ) . Previously published cysteine positions ( Hessling et al . , 2009 ) allowed for specific labeling with donor ( 61C ) or acceptor ( 385C ) fluorophores ( see below ) . Point mutation A577I was introduced using QuikChange Lightning Site-Directed Mutagenesis Kit ( Agilent Technologies ) . The constructs were cloned into a pET28b vector ( Novagen , Merck Biosciences , Billerica , MA ) . They include an N-terminal His-tag followed by a SUMO-domain for later tag cleavage . The QuickChange Lightning kit ( Agilent Technologies , Santa Clara , CA ) was used to insert an Avitag for specific in vivo biotinylation at the C-terminus of the acceptor construct . Escherichia coli BL21star cells ( Invitrogen , Carlsbad , CA ) were cotransformed with pET28b and pBirAcm ( Avidity Nanomedicines , La Jolla , CA ) by electroporation ( Peqlab , Erlangen , Germany ) and expressed according to Avidity’s in vivo biotinylation protocol . The donor construct was expressed in E . coli BL21 ( DE3 ) cod+ ( Stratagene , San Diego , CA ) for 3 hr at 37°C after induction with 1 mM isopropyl β-D-1-thiogalactopyranoside ( IPTG ) at OD600 = 0 . 7 in LBKana . A cell disruptor ( Constant Systems , Daventry , United Kingdom ) was used for lysis in both cases . Proteins were purified as published ( Jahn et al . , 2014 ) ( Ni-NTA , tag cleavage , anion exchange , size exclusion chromatography ) . 95% purity was confirmed by SDS-PAGE . Fluorescent labels ( Atto550- and Atto647N-maleimide ) were purchased from Atto-tec ( Siegen , Germany ) and coupled to cysteins according to the supplied protocol . If not stated differently , all chemicals were purchased from Sigma Aldrich , St . Louis , MO . Single-molecule FRET ( smFRET ) was measured as previously detailed using a home built TIRF setup ( Schmid et al . , 2016 ) . Hetero-dimers ( acceptor + donor ) were obtained by 20 min incubation of 1 µM donor and 0 . 1 µM biotinylated acceptor homodimers in measurement buffer ( 40 mM Hepes , 150 mM KCl , and 10 mM MgCl2 , pH7 . 5 ) at 47°C . This favors biotinylated heterodimers to bind to the polyethylene glycol ( PEG , Rapp Polymere , Tuebingen , Germany ) passivated and neutravidin ( Thermo Fisher Scientific , Waltham , MA ) coated fluid chamber . Residual homodimers are recognized using alternating laser excitation ( ALEX ) of donor and acceptor dyes ( Lee et al . , 2005; Hellenkamp et al . , 2018 ) and excluded from analysis . For optimal interaction affinity with Aha1 , measurements were performed in low salt buffer ( 40 mM Hepes , 20 mM KCl , 5 mM MgCl2 , pH 7 . 5 with 3 . 5 µM Aha1 and 2 mM ATP ) . For comparison , data without Aha1 were measured accordingly . Notably , significant binding was previously found for Aha1 with labeled Hsp90-385C at much lower concentration of 0 . 3 µM ( Li et al . , 2013 ) , which is exactly the dissociation constant reported for unlabeled Hsp90 ( Panaretou et al . , 2002 ) . This implies that , although not directly detectable in the experiment , Hsp90 exists predominantly in complex with Aha1 under the used conditions . A577I/wt constructs were created through monomer exchange ( see above ) . They are distinguished from both kinds of homodimers through the fluorescence signal ( donor+acceptor ) . Measurements were performed in measurement buffer plus 2 mM ATP if not stated differently . Macro-molecular crowding was mimicked by 20wt% polymeric sucrose , known as Ficoll400 ( Sigma Aldrich ) in measurement buffer if not stated differently . Single-molecule FRET trajectories were selected , and corrected for background , donor leakage , acceptor direct excitation , as well as different fluorescence quantum yields , detection efficiencies , excitation efficiencies , and laser powers , as described before ( Hellenkamp et al . , 2018 ) . The uncertainties of steady-state populations were estimated by bootstrapping: out of each dataset , random subsets ( or samples ) containing two thirds of the total number of traces were drawn with replacement . A histogram was compiled for each subset , and fitted with a double-Gaussian fit function and fixed peak positions from Figure 3—figure supplement 2 . Relative populations were obtained for each histogram . This was repeated for 1000 subsets . We report the means of 1000 such populations , and as an uncertainty measure their standard deviations ( rounded upwards to 0 . 5 ) . See also Supplementary file 1A . SMACKS is based on two-dimensional semi-ensemble Hidden Markov models ( HMMs ) , as described in detail earlier ( Schmid et al . , 2016 ) . In brief , smFRET donor and acceptor fluorescence traces serve as input data . SMACKS comes in two steps . First , individual HMMs are optimized for each molecule separately , to allow for the experimentally observed intensity differences between different molecules . The resulting emission parameters for each molecule – that is Gaussian mean and variance representing the fluorescence intensity levels - are then used for the second step: the semi-ensemble HMM optimization . Now the kinetic parameters – so-called start and transition probabilities – are ensemble-optimized based on an entire dataset , using the individual emission parameters of the first step . The transition probabilities are converted into rate constants by considering the sampling rate of the experiment ( frames per second ) . Several such HMM optimizations with increasing model size ( i . e . numbers of states ) are calculated , and compared using the Bayesian Information Criterion ( BIC ) , which reproducibly yields four states for Hsp90’s characteristic conformational dynamics: two open , two closed . Within the four-state model , we determine the most likely number of links using likelihood ratio tests following the hierarchical search for simplified models described in Bruno et al . , 2005 . ATPase activity was measured at 37°C coupled to NADH oxidation , which was followed as a decrease in absorption at 340 nm using an ATP regenerative assay similar to Tamura and Gellert , 1990: 0 . 2 mM NADH Di-Na ( Roche , Basel , CH ) ; 2 mM phosphoenol pyruvate K-salt ( Bachem , Bubendorf , CH ) ; 2 U/ml pyruvate kinase , Roche; 10 U/ml lactate dehydrogenase , Roche; in 40 mM Hepes , 150 mM KCl , 10 mM MgCl2 , pH 7 . 5 .
In a living cell , protein function is regulated in several ways , including post-translational modifications ( PTMs ) , protein-protein interaction , or by the global environment ( e . g . crowding or phase separation ) . While site-specific PTMs act very locally on the protein , specific protein interactions typically affect larger ( sub- ) domains , and global changes affect the whole protein non-specifically . Herein , we directly observe protein regulation under three different degrees of localization , and present the effects on the Hsp90 chaperone system at the levels of conformational steady states , kinetics and protein function . Interestingly using single-molecule FRET , we find that similar functional and conformational steady states are caused by completely different underlying kinetics . We disentangle specific and non-specific effects that control Hsp90’s ATPase function , which has remained a puzzle up to now . Lastly , we introduce a new mechanistic concept: functional stimulation through conformational confinement . Our results demonstrate how cellular protein regulation works by fine-tuning the conformational state space of proteins .
Proteins play a wide variety of roles in the cell and interact with many other molecules . The behavior of proteins depends on their structure; yet , proteins are often flexible and will change shape , much like a tree in the wind . Nevertheless , for some of the activities that it performs , a protein must adopt one specific shape . Therefore , the likelihood that the protein will take on this specific shape directly determines how efficiently that protein can perform a specific job . The shape of a protein can be regulated by changes at several levels; these could include modifying one of the amino acid building blocks that make up that protein , binding to another protein , or by placing the protein in a part of the cell that is crowded with other large molecules . Schmid and Hugel wanted to understand how these three different types of regulation affect the structure of a protein and how they relate to its activities . The protein Hsp90 was used as a test case . It typically exists with two copies of the protein bound together , either in a parallel or a V-shape . Hsp90 plays several important roles in metabolism and can break down molecules of ATP , the so-called energy currency of the cell . All three types of regulation favored the Hsp90 pairs taking the parallel structure and increased its breakdown of ATP . The results suggest that the Hsp90 pair has a flexible structure , and that reducing this flexibility can improve Hsp90’s efficiency in carrying out its role . It was particularly unexpected that the large-scale , unspecific effect of placing the protein in a crowded environment could have such similar results to a small-scale , precise change of a single amino acid within the protein . While all three forms of regulation help to stabilize the parallel structure for Hsp90 , they do this through different mechanisms , which influence the speed and the way that the protein transitions between the two structures . Schmid and Hugel believe that these results offer a new perspective on how diversely the shape and function of proteins is controlled at the molecular level , which could have wider implications for medical diagnostics and treatment .