Many fundamental cellular processes such as gene expression are tightly regulated by protein allostery. Allosteric signal propagation from the regulatory to the active site requires long-range communication, the molecular mechanism of which remains a matter of debate. A classical example for long-range allostery is the activation of the methionine repressor MetJ, a transcription factor. Binding of its co-repressor SAM increases its affinity for DNA several-fold, but has no visible conformational effect on its DNA binding interface. Our molecular dynamics simulations indicate correlated domain motions within MetJ, and quenching of these dynamics upon SAM binding entropically favors DNA binding. From monitoring conformational fluctuations alone, it is not obvious how the presence of SAM is communicated through the largely rigid core of MetJ and how SAM thereby is able to regulate MetJ dynamics. We here directly monitored the propagation of internal forces through the MetJ structure, instead of relying on conformational changes as conventionally done. Our force distribution analysis successfully revealed the molecular network for strain propagation, which connects collective domain motions through the protein core. Parts of the network are directly affected by SAM binding, giving rise to the observed quenching of fluctuations. Our results are in good agreement with experimental data. The force distribution analysis suggests itself as a valuable tool to gain insight into the molecular function of a whole class of allosteric proteins.
Protein allostery plays a key role in the regulation of cellular functions such as transcription or enzymatic action [1]. It crucially governs the formation of protein or protein-DNA complexes as well as the functional activity of individual proteins. Allosteric signals used by nature are diverse, ranging from ligand binding to reversible covalent modifications such as phosphorylation, or changes in the environment like pH or temperature. Intriguing examples are allosteric proteins in which effector molecules bind distal to the active site [2], [3]. A fundamental question is how the allosteric perturbation is transmitted through the protein to the active site for functional regulation. Can we understand and predict the mechanism and the network of interactions that propagate an allosteric signal? Answering this question is a prerequisite for functional mutagenesis and rational design of allostery. Sequence-based statistical analysis has proven highly successful to detect signal propagation pathways within and between allosteric proteins on the basis of evolutionary constraints [4], [5]. On the theoretical side, various thermodynamic concepts for inter-domain communication in allosteric proteins have been established [6], [7]. As yet, the molecular basis for long-range allosteric coupling between the regulatory and active site of a protein remains a matter of debate. This is why a range of experimental and computational techniques to monitor conformational changes involved in allostery have been developed and applied [7], [8], among others NMR [9], molecular dynamics (MD) simulations [10], [11], normal mode analysis and elastic network models [12], [13]. The basic premise of the above approaches is a conformational transition between two distinct states or a shift in a pre-existing conformational ensemble upon allosteric perturbation. In a commonly accepted picture, allosteric signals cause a perturbation at the regulatory site of the protein, analogous to an externally applied force. The perturbation then dissipates as internal strain or energetic coupling through the protein to the active site [14]. Signal propagation in turn causes conformational rearrangements, inducing an enhancement or decrease in the protein' s activity. However, examples of long-range allosteric communication in the absence of any obvious conformational changes [9], [15] question this picture, showing that allostery does not necessarily rely on a change in mean atomic coordinates. Instead, allosteric strain can dissipate through rigid scaffolds without detectable conformational rearrangements. A more fundamental understanding of allostery would thus require a way to directly follow strain propagation through proteins. This could reveal the allosteric network in a protein even in the absence of - or prior to the occurrence of - conformational changes. We recently presented a method termed force distribution analysis (FDA), based on MD simulations, that allows to detect propagation of internal strain caused by an external signal through proteins. The high sensitivity of the method makes it possible to even detect propagation through stiff materials, where a signal will propagate causing only minimal conformational changes that are below the threshold of experimentally accessible resolution. We have previously demonstrated the feasibility of FDA to detect force propagation in two mechanically perturbed proteins, namely the highly robust titin immunoglobulin domain I27 [16], and silk crystalline units [17]. While classical approaches focus on conformational changes or ensemble redistributions as a consequence of the signal-induced strain, such as normal mode analysis or essential dynamics [18], FDA sets out from the strain distribution itself. This renders FDA a perfectly fitted tool to elucidate the mechanism underlying allosteric signaling in proteins in general, be it with or without the involvement of structural rearrangements. We here chose to test the feasibility of FDA to detect allosteric networks in proteins using the classical textbook example of the methionine repressor protein MetJ [19]. MetJ is a challenging candidate, as it features long-range allosteric communication, yet without any noticeable changes in protein structure upon effector binding. MetJ is a transcription factor in the met regulon of Escherichia coli, the gene regulatory control system for methionine biosynthesis [20]. MetJ regulates the transcriptional levels of its own gene and those of several other proteins. Repressor activity results from binding to its operator, a specific 8 bp DNA sequence (the “metbox”), located in the promoter regions of genes regulated by MetJ. Changes in sequence of the metboxes are supposed to explain different regulatory activity [20], [21]. MetJ forms a homodimer in its native state [22]. In case of multiple adjacent metboxes it may form complexes of several homodimers arranged in a wheel-like structure around the DNA [23]. DNA binding of MetJ is regulated by its co-repressor, S-adenosylmethionine (SAM), an end product of methionine biosynthesis, Fig. 1A. Sensitivity for DNA is increased several-fold [24], [25] upon co-repressor binding. Of special interest is that SAM binds distant from the DNA binding site, with a minimal SAM-DNA distance of in crystal structures [26]. Holo and apo structures do not show significant structural changes [15]. For this reason it remains controversial how SAM influences DNA binding. S-adenosylhomocysteine (SAH), a SAM analogue, binds MetJ with a binding affinity similar to SAM, but has no effect on its affinity for the operator (S. Philipps, Leeds Univ, 2009, personal communication). The main difference between SAM and SAH (Fig. 1B) is a positive charge on the sulfur atom of SAM, and it has been suggested that the increased sensitivity upon co-repressor binding is of purely electrostatic nature [27]. On the other hand, introduction of positive charges by a series of point mutations could not substitute the need for co-repressor [28]. Based on the force distribution pattern observed within the MetJ homodimer, we here propose a new model for MetJ activation upon cofactor binding. We measure directed propagation of internal strain from the SAM binding site to distinct residues in the DNA binding interface, through a specific network of a few key residues. The consequence is a wide-spread quenching of slow fluctuations and relocation and stiffening of specific side chains at the MetJ-DNA interface, leading to increased protein - DNA interaction. A distinct interaction pattern of individual residues with the co-repressor allows MetJ to fine-tune its response to co-repressor binding, explaining the inability of SAH to act as a co-repressor. Our results yield a molecular basis for MetJ allosteric function and are consistent with previous experimental studies.
We carried out extensive MD simulations to elucidate the force distribution and conformational properties of MetJ. We used crystal structures of MetJ (PDB code 1CMC [15]) and MetJ in complex with DNA (PDB code 1CMA [26]) as starting point for our simulations. Throughout the manuscript, we will use the terms MetJ for the system without DNA and MetJ-dna for the MetJ-DNA complex. In both cases, simulations of the holo and apo forms were performed for comparison. Apo forms were created by deleting the bound SAM molecules from the crystal structures. An apo structure of MetJ is available, but as force distribution analysis is very sensitive to structural changes we decided to use the same crystal structure as basis for our simulations. Structures for Q44K, a mutant not relying on cooperativity to be functional [29], exist as well. Yet, as the altered charge distribution alters the DNA recognition pattern, though not the allosteric effect itself, we decided not to further investigate Q44K. For each of the five systems, 10 independent 30 ns MD simulations were performed, totaling 300 ns of simulation time, respectively. In agreement with crystallographic data [15], our simulations do not show major deviations between holo and apo forms. The overall backbone root mean square deviation (RMSD) of average structures is 0. 66 Å for MetJ-dna and 0. 64 Å for MetJ. This compares well with the crystal structures where we find a backbone RMSD for holo and apo structures of 1. 63 Å which lowers to 0. 59 Å after excluding poorly resolved loop regions having different conformation (residues 12–20 and 77–84), Fig. 1C. Crystal waters in the protein-DNA interface of 1CMA were found to quickly move into the bulk solvent and are thus unlikely to bridge specific interactions. To elucidate distribution of the allosteric signal induced by co-repressor binding, we directly calculated forces between each pair of atoms and from our MD trajectories. We here analyze scalar pair-wise forces, which in contrast to the vectorial representation are unaffected by rotation of the system during the simulations. Observing pairwise forces has the advantage that forces do not average to zero over time, thus being the measure of choice for internal strain in systems equilibrated under a perturbation. Forces are calculated individually for bonded and non-bonded (electrostatic and van der Waals) interactions below the cutoff distance using the interaction potential defined by the Amber03 [30] force field. Long-range interactions as well as solvation effects such as screening of electrostatic forces and hydrophobic forces are not directly included in, which is calculated only for the solutes and within the non-bonded cut-off. We however indirectly accounted for these effects by calculating forces from a system simulated in explicit solvent and with full electrostatics. Details are given in Methods. Propagation of the mechanical perturbation caused by SAM binding is measured as the difference in pairwise force, , between the apo and holo forms of MetJ/MetJ-dna. For convergence, forces for each system were averaged over all ten equilibrium trajectories, each 30 ns in length. To reduce noise further, mainly resulting from slow side chain fluctuations that cannot equilibrate during simulation time, data were normalized as described in Methods. Dimensionless normalized changes in force are denoted. The MetJ homodimer has a high degree of symmetry, and we thus expect the force distribution pattern to be highly symmetric as well. We checked this by calculating correlation coefficients between residue wise forces, see Methods. Indeed, we find the force propagation pattern for the monomers to be very similar in all systems. For MetJ, residue wise forces correlate with, Fig. S2A. The MetJ-dna structure shows a less symmetric pattern, with, Fig. S2B. The lower symmetry of MetJ-dna might be a result of the lower resolution of the 1CMA crystal structure (2. 8 Å for 1CMA vs. 1. 8 Å for 1CMC) or of the only partially resolved DNA. Force distribution at the DNA binding site (Fig. 2A) reveals that remote MetJ binding induces a high degree of strain at distinct regions of the MetJ-DNA interface. In particular, Arg40 and a loop formed by residues 50–53 are subjected to high strain. The presence of the co-repressor thus is sensed by the DNA binding site, apparently via a long-range propagation of force from the bound SAM molecule through the protein scaffold to the MetJ-DNA interface. Importantly, the force distribution pattern was equally observed in the absence of DNA, Fig. 2B. In fact, forces in MetJ and MetJ-dna distribute in a very similar way, yielding a correlation of, Fig. 2C. First, this is strong evidence that the observed change in forces is a result of SAM binding, independent from the presence of DNA. Second, as the initial crystal structures differ in resolution and conformation, the significant correlation highlights that the distribution pattern is robust with regard to the starting structure. On the basis of FDA, we next investigated which protein structural elements are key to the strain distribution, allowing communication between SAM and the protein-DNA interface over a distance of more than 1 nm. Within the protein scaffold, we observe force propagation through helix B (B′) and forces are transmitted via side chain interactions onto helix A (A′), which in turn forms various side chain contacts with the DNA, Fig. 3A+B. Force propagation is highly non-isotropic and directed. This is to say, when compared to helix A and B, we see relatively little changes in pair-wise forces for the and the loops formed by residues 12–20, both in direct contact with the DNA, as well as for helix C (C′), Fig. 3C. In agreement with the low allosteric strain in the, this motif, even though binding to the major groove of the metbox, has been found to play a role in DNA sequence specificity, but not in the allosteric regulation of DNA binding affinity [31]. Only a few side chains of helix A show significant changes in pair wise force, the strongest of which is observed for Glu39, Arg40, Arg42 and Arg43. Out of these residues only Arg40 is in direct contact with the DNA. This observation is remarkable as an almost complete loss of binding affinity was reported for mutation of Arg40 and its spacial neighbor Thr37, but not for mutation of others in direct contact with DNA [31]. Thr37, however, has been suggested to be involved in enhancing cooperativity, thereby only indirectly regulating DNA affinity. In agreement, we do not find Thr37 to be under SAM-induced strain. We find two inter-related mechanisms of force propagation responsible for the specific targeting of the above mentioned structural elements. First, SAM strongly exerts a direct strain onto a set of MetJ residues, as reflected by extra-ordinarily high forces between the co-repressor and these residues, , Fig. 3D. Most importantly, the adenosyl group of SAM strongly interacts with Glu39 and Arg42 in helix A, influencing their dynamics (see below and Fig. 3D). Second, SAM features repulsive forces with helix B, inducing a high strain in the helix backbone hydrogen bonds. This apparently involves slight helix bending, Fig. 4A. Indeed, measuring the angle defined by the atoms of residues Ala64, Cys58 and Asn53 shows a bending upon SAM binding of for MetJ and for MetJ-dna. We note that it is the significant difference in hydrogen bond forces, not in the mere atomic coordinates, between apo and holo form, that serves as robust indication for SAM-induced signal propagation. Helix bending in turn imposes strain on the salt bridge between Glu59 in helix B and Arg43 in helix A by minor conformational rearrangements, Fig. 4A+B. We measure high change in force between these residues, suggesting this electrostatic interaction, buried in the protein core, to propagate force between helix B and helix A. Both mechanisms, direct forces imposed from SAM onto key residues in helix A, and propagation of forces from SAM via bending of helix B, result in inconspicuous rearrangements at the DNA binding interface; most notably in the loop linking helices A and B (residues 50–53) and Arg40, as described above, Fig. 2A+B. Repositioning of Arg40 upon SAM binding is accompanied by an adjustment of the side chain packing with its direct neighbors, Thr37 and Asn53, Fig. 4C. Again, pairwise forces here served as a measure for signal propagation, rather than the only minor, yet reproducible coordinate changes (as for example a change of the angle in Asn53 between, and found for both, MetJ-dna as well as MetJ). The described rearrangement of Arg40 caused by propagation of strain entails a strengthening of its saltbridge with DNA. From FDA, we measured an increase in attraction between Arg40 and DNA of. Overall, the potential energy between MetJ and DNA decreases by from in the holo to in the apo form, as a result of allosteric signaling by the co-repressor. The loops formed by residues 12–20 (referred to as loop 1) suggest themselves to be involved in the allosteric mechanism, as they strongly differ in conformation between the 1CMC (MetJ) and 1CMA (MetJ-dna) crystal structures and are in direct contact with the DNA, Fig. 1C. NMR data for these loops shows a strong quenching of ns time-scale fluctuations upon co-repressor binding (Steve Homans, Leeds University, 2009, personal communication). In good agreement with these experimental findings our simulations of the MetJ-dna system show a strong decrease in backbone RMSF for loop 1 residues upon SAM binding, as well as stiffening of helix C, Fig. 5A–C. Quenching is observed for both the MetJ and MetJ-dna system, though less pronounced for the former (see below). Remarkably, principal component analysis (PCA) on the trajectory data reveals the dynamics of the distal loop 1 and helix C regions to be highly coupled, Fig. 5D, and the dynamics of both MetJ monomers to be highly cooperative. The lowest frequency mode (Eigenvectors 1–3) for apo and holo structures of MetJ-dna describe highly similar fluctuations, yet at very different amplitudes. Strong quenching of fluctuations is reflected by a decrease of the highest Eigenvalue from 120 (apo) to 28 (holo), Fig. S1. These observations are supported by entropy calculations based on Schlitter' s formula [32]. Upon SAM binding, we find a decrease in entropy of for MetJ-dna and for MetJ, see also Table 1. The quantitatively different, yet qualitatively equivalent, results might be caused by the different crystal structures used, i. e the differences for loop 1 and adjacent residues. Overall, we find the stiffening effect of SAM to be independent from the presence of DNA. The question arises how the distal helix C and loop 1 regions are dynamically linked through a largely rigid core of the MetJ-DNA system. To elucidate the communication pathway, we performed PCA on residue averaged pair-wise forces, , here termed force-PCA. Again, observing forces directly has the unique advantage to allow for following the complete propagation pathway, including parts showing only subtle coordinate changes. Force-PCA on MetJ-dna revealed a network of correlated changes in pair-wise forces, Fig. 5E. The network spans through the protein core, linking helix C and loop 1, the latter of which is connected to the rest of the network via residues Tyr11, Ile28, Lys31 and Glu55. Synchronization of the fluctuations between both monomers is achieved by force propagation along helix A and the. We found the allosteric signal caused by SAM binding to target large parts of helix A, in particular Glu39, Arg40 and Arg42, resulting in wide-spread stiffening, Fig 4C. Helix A accounts for a large part of the network propagating fluctuations, moreover it directly is part of the link between helix C and loop 1, Fig. 5E. In summary, SAM binding alters correlated forces linking loop 1 and helix C thus affecting the dynamics of these regions. The SAM analogue SAH has no regulatory function, i. e. no impact on the MetJ activity for binding to DNA, yet has the same binding mode and similar binding affinities as SAM (S. Philipps, Leeds University, 2009, personal communication). Based on this observation, an entirely electrostatic activation of MetJ by the positively charged SAM has been suggested [27]. We decided to elucidate differences between SAM and SAH binding, and to this end performed simulations of MetJ-dna in complex with SAH as co-repressor. We modeled the MetJ-SAH structure by removing the group from the sulfur atom of SAM in the 1CMA crystal structure used as template. The overall conformation of MetJ-dna is not affected when replacing SAM by SAH, both structures have a backbone RMSD of only 0. 42 Å. Also, the potential energy between protein and DNA is quasi identical to the energy measured for MetJ-SAM and DNA. As for the co-repressor, our simulations show strong quenching of fluctuations upon SAH binding, yet quenching is less distinct. This is reflected by higher backbone-RMSF for MetJ-SAH throughout the protein, Fig, 5B, as well as a higher eigenvalue of 48 for the first eigenvector, what is significantly above 28, the value measured for SAM. Both eigenvectors describe a very similar mode of fluctuation, Fig. S1C. The flexibility of the bound ligand itself is increased as well. We measured an almost twofold increase in RMSF for SAH when compared to SAM (0. 89 Å vs. 0. 57 Å), apparently due to the loss of backbone interactions with SAM' s positive charge. Indeed, and unsurprisingly, the changes in direct interactions between the co-repressor and individual residues are significant, Fig. 6A. Removing the positive charge alters the charge distribution of SAM' s whole methionine group, and we see changes in interaction even for residues as far as in helix A (residues 39 to 43), though most of the observed changes affect residues in direct proximity to the sulfur atom (residues 59 to 67). These changes lead to wide-spread alterations in the overall force propagation pattern, which are most pronounced in helix C and the proceeding loop, Fig. 6C. Interestingly, we find high changes in forces for Tyr11 and Ile28, both of which were found to link fluctuations of loop 1 with helix C by force-PCA. However, this effect is only present in the domain with the full DNA fragment resolved (residues 106–209 in the 1CMA structure), and thus further validation is necessary. As the differences in binding affinity between SAM and SAH are of primarily entropic nature, we performed entropy calculations on MetJ-dna based on Schlitter' s formula [32]. Vibrational entropies were calculated on the whole trajectory data totaling 300 ns per system and are sufficiently converged to allow semi-quantitative comparisons between SAM and SAH, Fig. S3. We found an entropy difference of between SAM and SAH as co-repressor, of which the protein dynamics with accounts for the major contribution. All values are given in Table 1. The absolute conformational entropies of (apo) and (holo) per residue are in agreement with previous estimates for other proteins [33], [34]. The values clearly show that there is a significant increase in entropy when substituting SAM by SAH, consistent with the observed difference in regulatory function. Both, the overall RMSF and the entropies suggest SAM to reduce MetJ flexibility more efficiently than SAH.
We have analyzed force distribution and dynamics in MetJ, a stiff allosteric protein regulated by SAM, its co-repressor. FDA allowed us to identify the network of interactions guiding force modulation within MetJ by cofactor binding. Experimental data, among others the inactivity of SAH as a co-repressor, suggest that a long range electrostatic interaction between DNA and the positive charge on SAM may exclusively explain MetJ activation [35]. Notwithstanding, there is evidence from mutagenesis experiments that charge alone cannot explain MetJ activation [28]. We here suggest strain propagation by subtle alterations of the MetJ structure as an important mode of allosteric signal propagation. The highly anisotropic distribution of internal strain leads to conformational re-adjustments at the interaction interface, mainly of Glu39, Arg40, Arg42, Arg43 and residues 50–53. Our simulations thus predict adjustments of these specific protein-DNA interactions to be an important factor for efficient DNA binding. Such a mechanism would allow MetJ to easily move along or between DNA strands until the target side is found, thereby speeding up target site location as recently proposed [36]. While the importance of this communication pathway has been experimentally probed by the loss of allosteric function upon mutation of residues identified as key residues by FDA, it is independent of the positive charge on SAM, as we find it similarly for SAH. This pathway therefore apparently causes or is complemented by an additional allosteric mechanism unique to SAM. We find the major SAM-dependent allosteric function of MetJ to come from an entropic contribution due to quenching of slow backbone and fast side chain dynamics. Only for SAM, the force network communicating the allosteric signal between loop 1 and helix C can substantially reduce correlated fluctuations. This is supported by theoretical models [37] as well as NMR data that suggest dynamics to play an important role (Steve Homans, Leeds University, 2009, personal communication). The major correlated motion that is quenched involves parts distant to each other as well as to the co-repressor binding site. Again, measuring correlated forces instead of coordinates revealed the role of the protein core in this long-range communication and allosteric regulation. We find a strong increase in entropy when substituting SAM by SAH, suggesting that the regulatory difference between SAM and SAH is of entirely entropic nature. It is the differential effect of SAM and SAH on the correlated forces involved in this motion that is likely to be responsible for the observed difference in allostery. Dynamics are increasingly revealed as a regulatory driving force [38]–[40] and have recently been found for another transcription factor, the CAP protein [9]. We here find a similar mechanism for MetJ, suggesting that changes in dynamics upon cofactor binding may be a commonly used regulation pattern. Long-range allostery in the absence of any noticeable conformational change as featured by MetJ has remained a challenge for structure-based experimental and theoretical approaches. In combination with conventional analysis of the MetJ dynamics, we find FDA an optimal tool to track an allosteric pathway in MetJ. Signal propagation was found to be largely hidden in unremarkable shifts in atomic coordinates. Yet, these mere conformational shifts, as revealed by FDA, can involve large changes in forces for strongly interacting atom pairs, resembling “stiff springs” in the protein interaction network. Monitoring forces instead of coordinates therefore renders FDA highly sensitive. Pure conformational analysis would simply overlook rearrangements of the magnitude reported here, especially as properties such as root-mean square deviations or fluctuations are easily dominated by slow sub-domain movements, as it is the case for MetJ, Fig. 5C. By considering pair-wise forces which are, by definition, dominated by strong and relatively short-ranged interactions, such large fluctuations have only minor influence. Pair-wise interactions have the additional advantage of being independent from any fitting scheme, as conventionally used for RMSD or RMSF calculations, thereby not introducing any bias by the arbitrary choice of a reference structure. The same multivariate statistical methods, such as PCA, that are used for the analysis of coordinate based trajectory data can be applied to pair-wise forces. Again, one has the advantage of being able to observe relations that would otherwise be below the sensitivity of the method. We recently determined the force bearing scaffold in a titin immunoglobulin domain, a protein mainly designed to withstand mechanical load by means of FDA [16]. Here, we present the first successful application to a stiff allosteric protein, opening the road to better understand the function of a whole class of proteins, including enzymes, by examining their internal force network. We note that FDA does not require extensive sampling of an allosteric conformational transition, which at current simulation time-scales is out of reach for most proteins. This is an unique advantage over other MD based simulation techniques used for studying protein allostery. FDA is content with monitoring the development of internal strain prior to the eventual shift in the protein conformational ensemble. We predict forces averaged over a total simulation time in the sub-microsecond range to suffice for the analysis of much slower allosteric signaling pathways. Importantly, while we here modified the Gromacs simulation suite to add FDA functionality, virtually any MD simulation package can be easily modified to include FDA at practically no additional computational expense, as pair-wise forces are anyways calculated at each time step. Our results highlight the strength of FDA as a tool supporting experimental design, as it can straightforwardly be verified by experimental studies. In particular, our results suggest Arg40, Thr37 and Asn53 at the MetJ-DNA interaction interface to be important for allosteric function. Mutations of Arg40 and Thr37 have indeed been previously shown to abolish SAM-dependent allosteric regulation of MetJ [31]. In addition, we predict mutation of Glu59 and Arg43, forming the salt bridge between helix A and B, and the crucial SAM interaction partners Glu39 and Arg42 to lower the co-repressor activity of SAM.
Proteins carry out most of the cellular processes, from metabolic reactions to the regulation and expression of genes. Tight and effective regulation of the executing protein machinery is commonly achieved by allostery. The only general requirement for allosteric communication is the transmission of a signal, e. g. , the binding of a cofactor, from the ligand binding site to the allosteric (active) protein site; in other words an internal propagation of strain. Based on molecular dynamics simulations, we recently presented a method that allows visualization of force distribution in proteins. We here applied this method to MetJ, a transcription factor whose activity is regulated by a co-repressor. Interestingly, co-repressor binding does not cause visible structural changes, yet increases DNA binding affinity manyfold. We were able to reveal a network linking fluctuations of distal parts of MetJ, including the DNA binding interface. Mechanical strain caused by SAM binding propagates to certain key residues, thereby altering fluctuations and finally resulting in increased DNA binding affinity. By directly monitoring ligand induced strain, instead of conformational changes, which might be absent or slow, our force distribution analysis suggests itself suitable to detect the mechanically crucial motifs in allosterically regulated protein machineries.
biophysics/biomacromolecule-ligand interactions
biophysics/cell signaling and trafficking structures
biophysics/theory and simulation
Dynamic Allostery in the Methionine Repressor Revealed by Force Distribution Analysis