Mechanism of dimer selectivity and binding cooperativity of BRAF inhibitors

  1. Joseph Clayton
  2. Aarion Romany
  3. Evangelia Matenoglou
  4. Evripidis Gavathiotis
  5. Poulikos I Poulikakos
  6. Jana Shen

  • Curated by eLife

    eLife logo

    eLife Assessment

    This fundamental study illuminates the dynamics of BRAF in its monomeric and dimeric forms, both in the absence and presence of inhibitors, through a convincing combination of traditional experiments and sophisticated computational analyses. By revealing novel insights into the selectivity and cooperative processes of BRAF inhibitors, it holds significant promise for the development of future therapeutics, particularly against mutant isoforms in cancer. Overall, these findings will be of great interest to structural biologists, medicinal chemists, and pharmacologists.

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Aberrant signaling of BRAF V600E is a major cancer driver. Current FDA-approved RAF inhibitors selectively inhibit the monomeric BRAF V600E and suffer from tumor resistance. Recently, dimer-selective and equipotent RAF inhibitors have been developed; however, the mechanism of dimer selectivity is poorly understood. Here, we report extensive molecular dynamics (MD) simulations of the monomeric and dimeric BRAF V600E in the apo form or in complex with one or two dimer-selective (PHI1) or equipotent (LY3009120) inhibitor(s). The simulations uncovered the unprecedented details of the remarkable allostery in BRAF V600E dimerization and inhibitor binding. Specifically, dimerization retrains and shifts the αC helix inward and increases the flexibility of the DFG motif; dimer compatibility is due to the promotion of the αC-in conformation, which is stabilized by a hydrogen bond formation between the inhibitor and the αC Glu501. A more stable hydrogen bond further restrains and shifts the αC helix inward, which incurs a larger entropic penalty that disfavors monomer binding. This mechanism led us to propose an empirical way based on the co-crystal structure to assess the dimer selectivity of a BRAF V600E inhibitor. Simulations also revealed that the positive cooperativity of PHI1 is due to its ability to preorganize the αC and DFG conformation in the opposite protomer, priming it for binding the second inhibitor. The atomically detailed view of the interplay between BRAF dimerization and inhibitor allostery as well as cooperativity has implications for understanding kinase signaling and contributes to the design of protomer selective RAF inhibitors.

Article activity feed

  1. Version published to 10.7554/elife.95334.4 on eLife
  2. Version published to 10.7554/elife.95334 on eLife
  3. Version published to 10.7554/elife.95334.3 on eLife
  4. eLife

    eLife Assessment

    This fundamental study illuminates the dynamics of BRAF in its monomeric and dimeric forms, both in the absence and presence of inhibitors, through a convincing combination of traditional experiments and sophisticated computational analyses. By revealing novel insights into the selectivity and cooperative processes of BRAF inhibitors, it holds significant promise for the development of future therapeutics, particularly against mutant isoforms in cancer. Overall, these findings will be of great interest to structural biologists, medicinal chemists, and pharmacologists.

  5. eLife

    Reviewer #1 (Public Review):

    Summary:

    This manuscript from Clayton and co-authors aims to clarify the molecular mechanism of BRAF dimer selectivity. Indeed, first generation BRAF inhibitors, targeting monomeric BRAFV600E, are ineffective in treating resistant dimeric BRAF isoforms. Here, the authors employed molecular dynamics simulations to study the conformational dynamics of monomeric and dimeric BRAF, in the presence and absence of inhibitors. Multi-microseconds MD simulations showed an inward shift of the αC helix in the BRAFV600E mutant dimer. This helped identify a hydrogen bond between the inhibitors and the BRAF residue Glu501 as critical for dimer compatibility. The stability of the aforementioned interaction seems to be important to distinguish between dimer-selective and equipotent inhibitors.

    Strengths:

    The study is overall valuable and robust. The authors used the recently developed particle mesh Ewald constant pH molecular dynamics, a state-of-the-art method, to investigate the correct histidines protonation considering the dynamics of the protein. Then, multi-microsecond simulations showed differences in the flexibility of the αC helix and DFG motif. The dimerization restricts the αC position in the inward conformation, in agreement with the result that dimer-compatible inhibitors are able to stabilize the αC-in state. Noteworthy, the MD simulations were used to study the interactions between the inhibitors and the protein, suggesting a critical role for a hydrogen bond with Glu501. Finally, simulations of a mixed state of BRAF (one protomer bound to the inhibitor and the other apo) indicate that the ability to stabilize the inward αC state of the apo protomer could be at the basis of the positive cooperativity of PHI1.

  6. eLife

    Reviewer #2 (Public Review):

    Summary:

    The authors employ molecular dynamics simulations to understand the selectivity of FDA approved inhibitors within dimeric and monomeric BRAF species. Through these comprehensive simulations, they shed light on the selectivity of BRAF inhibitors by delineating the main structural changes occurring during dimerization and inhibitor action. Notably, they identify the two pivotal elements in this process: the movement and conformational changes involving the alpha-C helix and the formation of a hydrogen bond involving the Glu-501 residue. These findings find support in the analyses of various structures crystallized from dimers and co-crystallized monomers in the presence of inhibitors. The elucidation of this mechanism holds significant potential for advancing our understanding of kinase signalling and the development of future BRAF inhibitor drugs.

    Strengths:

    The authors employ a diverse array of computational techniques to characterize the binding sites and interactions between inhibitors and the active site of BRAF in both dimeric and monomeric forms. They combine traditional and advanced molecular dynamics simulation techniques such as CpHMD (All-atom continuous constant pH molecular dynamics) to provide mechanistic explanations. Additionally, the paper introduces methods for identifying and characterizing the formation of the hydrogen bond involving the Glu501 residue without the need for extensive molecular dynamics simulations. This approach facilitates the rapid identification of future BRAF inhibitor candidates.

  7. eLife

    Author response:

    The following is the authors’ response to the previous reviews.

    Reviewer #1 (Public review):

    Comment 1: This manuscript from Clayton and co-authors, entitled ”Mechanism of dimer selectivity and binding cooperativity of BRAF inhibitors”, aims to clarify the molecular mechanism of BRAF dimer selectivity. Indeed, first-generation BRAF inhibitors, targeting monomeric BRAFV600E, are ineffective in treating resistant dimeric BRAF isoforms. Here, the authors employed molecular dynamics simulations to study the conformational dynamics of monomeric and dimeric BRAF, in the presence and absence of inhibitors. Multi-microsecond MD simulations showed an inward shift of the αC helix in the BRAFV600E mutant dimer. This helped in identifying a hydrogen bond between the inhibitors and the BRAF residue Glu501 as critical for dimer compatibility. The stability of the aforementioned interaction seems to be important to distinguish between dimer-selective and equipotent inhibitors.

    The study is overall valuable and robust. The authors used the recently developed particle mesh Ewald constant pH molecular dynamics, a state-of-the-art method, to investigate the correct histidine protonation considering the dynamics of the protein. Then, multi-microsecond simulations showed differences in the flexibility of the αC helix and DFG motif. The dimerization restricts the αC position in the inward conformation, in agreement with the result that dimer-compatible inhibitors can stabilize the αC-in state. Noteworthy, the MD simulations were used to study the interactions between the inhibitors and the protein, suggesting a critical role for a hydrogen bond with Glu501. Finally, simulations of a mixed state of BRAF (one protomer bound to the inhibitor and the other apo) indicate that the ability to stabilize the inward αC state of the apo protomer could be at the basis of the positive cooperativity of PHI1.

    We thank the reviewer for the positive evaluation of our work.

    Comment 2a: Regarding the analyses of the mixed state simulations, the DFG dihedral probability densities for the apo protomer (Fig. 5a right) are highly overlapping. It is not convincing that a slight shift can support the conclusion that the binding in one protomer is enough to shift the DFG motif outward allosterically. Moreover, the DFG dihedral time-series for the apo protomer (Supplementary Figure 9) clearly shows that the measured quantities are affected by significant fluctuations and poor consistency between the three replicates. The apo protomer of the mixed state simulations could be affected by the same problem that the authors pointed out in the case of the apo dimer simulations, where the amount of sampling is insufficient to model the DFG-out/-in transition properly.

    While the reviewer is correct there are large fluctuations in the DFG pseudo dihedral over the course of the apo simulations, these fluctuations occur primarily in the first 2 µs of the simulations, which were removed from our analysis. The reviewer is also correct that these simulations do not sufficiently model the DFG-out/-in transition; however, a full transition is not necessary for our analysis, as we are only interested in the shift of the DFG pseudo dihedral. As to the reviewer’s comment on the overlapping DFG distributions, we agree that the difference is very subtle. We revised the text.

    On page 9, second paragraph from the bottom:

    “While PHI1 or LY binding clearly perturbs the αC helix of the opposite apo protomer, the effect on the DFG conformation is less clear when comparing the DFG dihedral distribution of the the apo protomer in the PHI1 or LY-mixed dimer with that of the apo dimer (blue, orange, and grey, Figure 5a right). All three distributions are broad, covering a range of 160-330°. It appears that, relative to the apo dimer, the DFG of the apo protomer in the PHI1-mixed dimer is slightly shifted to the right, whereas that of the LY-mixed dimer is slightly shifted to the left; however, these differences are very subtle and warrant further investigation in future studies.”

    Comment 2b: There is similar concern with the Lys483-Glu501 salt bridge measured for the apo protomers of the mixed simulations. As it can be observed from the probabilities bar plot (Fig. 5a middle), the standard deviation is too high to support a significant role for this interaction in the allosteric modulation of the apo protomer.

    As for the salt bridge, the fluctuation in the apo dimer and LY-mixed dimer is indeed large, and together with the lower average probability suggests that the salt bridge is weaker, which is consistent with the αC helix moving outward. To clarify this, we revised the text.

    On page 9, second paragraph from the bottom:

    “Consistent with the inward shift of the αC helix, the Glu501–Lys483 salt bridge has a lower average probability and a larger fluctuation in the apo dimer and the apo protomer of the LY-mixed dimer, as compared to the apo protomer of the PHI1-mixed dimer.”

    Reviewer #2 (Public review):

    Comment 1: The authors employ molecular dynamics simulations to understand the selectivity of FDA approved inhibitors within dimeric and monomeric BRAF species. Through these comprehensive simulations, they shed light on the selectivity of BRAF inhibitors by delineating the main structural changes occurring during dimerization and inhibitor action. Notably, they identify the two pivotal elements in this process: the movement and conformational changes involving the alpha-C helix and the formation of a hydrogen bond involving the Glu-501 residue. These findings find support in the analyses of various structures crystallized from dimers and co-crystallized monomers in the presence of inhibitors. The elucidation of this mechanism holds significant potential for advancing our understanding of kinase signalling and the development of future BRAF inhibitor drugs.

    The authors employ a diverse array of computational techniques to characterize the binding sites and interactions between inhibitors and the active site of BRAF in both dimeric and monomeric forms. They combine traditional and advanced molecular dynamics simulation techniques such as CpHMD (all-atom continuous constant pH molecular dynamics) to provide mechanistic explanations. Additionally, the paper introduces methods for identifying and characterizing the formation of the hydrogen bond involving the Glu501 residue without the need for extensive molecular dynamics simulations. This approach facilitates the rapid identification of future BRAF inhibitor candidates.

    We thank the reviewer for the positive evaluation of our work.

    Comment 2: Despite the use of molecular dynamics yields crucial structural insights and outlines a mechanism to elucidate dimer selectivity and cooperativity in these systems, the authors could consider adoption of free energy methods to estimate the values of hydrogen bond energies and hydrophobic interactions, thereby enhancing the depth of their analysis.

    As mentioned in our previous response, current free energy methods are capable of giving accurate estimates of the relative binding free energies of similar ligands; however, accurate calculations of the absolute free energies of hydrogen bond and hydrophobic interactions are not feasible yet. Thus, we decided not to pursue the calculations.

    Reviewer #1 (Recommendations to author):

    Comment 1: It would be useful to cite all supplementary figures in the main text (where relevant). In the present version, only Supplementary Figures 2,3, and 4 are cited in the main text.

    This was an oversight; supplementary figures 5 through 9 are now cited in the text, to point to the time-series of the quantity discussed. We note that supplementary figures 10 and 11 show the time-series of the root mean squared deviation (RMSD) of each protomer in both all monomeric and dimeric simulations; these quantities are not discussed in the manuscript but are provided for further insight.

    Comment 2: It is unclear whether the present data could support a direct involvement of the DFG movement in the allosteric mechanism proposed. The same argument applies to the Lys483Glu501 interaction in the apo protomer of the mixed state simulations. The current simulation data could only support a different stabilization of the αC-helix position. The authors should either remove/tone down the claim or extend the simulations to sample a ”converged” distribution of the DFG dihedral and the Lys483-Glu501 salt bridge of the apo protomers.

    We agree that the DFG change in the apo protomer of the PH1-mixed dimer is very subtle (see our response and revision to comment 2); however, the allosteric involvement of DFG is clearly demonstrated in Figure 5 (right panel in 5a and 5b). We compare three states: apo protomer in the mixed dimer, PHI1-bound protomer in the mixed dimer, and holo dimer (i.e., with two PHI1) Binding of the first PHI1 restricts the DFG conformation to the larger DFG dihedrals (blue curves in the top and bottom right panels). This effect (DFG outward and more restricted) is even strong when the second PHI1 binds, locking the DFG in both protomers to a narrow dihedral range 270–330 degree (green and blue curves in Figure 5b, right panel). These are allosteric effects, demonstrating that the second PH1 binding induces conformational change of the DFG in the first protomer. This is why in Figure 6, the DFG of the PHI1-bound protomer in the mixed dimer is labeled as “almost out”, while the DFG in the holo dimer is labeled as “fully out”.

    The effect of second PHI1 on the DFG of the first protomer is consistent with that the αC helix position, in which case, the second PH1 induces an inward movement of the αC of the first protomer (illustrated as “fully in” in the schematic Figure 6). Through the aC movement, the salt-bridge strength is affected, as we discussed in our response and revision to Reviewer’s comment 2a. To clarify these points, we revised the discussion of Figure 5. We made the x axis range of the DFG dihedral distributions the same between the top and bottom panels in Figure 5. To remove the claim of priming effect on DFG, we revised Figure 6.

    Page 10, Figure 5:

    we made the x axis range of the DFG dihedral distributions on the top and bottom panels the same to facilitate comparison.

    Page 11, second and third paragraphs:

    “Consistent with the change in the DFG conformation between the holo (two inhibitor) and apo dimers (Figure 3c,3f), DFG is rigidified upon binding of the first inhibitor, as evident from the narrower DFG dihedral distribution of the PHI1 or LY-bound protomer in the mixed protomer (Figure 5b right) compared to the apo protomer in the mixed dimer (Figure 5a right). Importantly, the DFG dihedral is right shifted in the occupied vs. apo protomer, demonstrating that the inhibitor pushes the DFG outward.”

    “Consistent with the effect of the second PHI1 on the αC position of the first PHI1-bound protomer, binding of the second PHI1 shifts the peak of the DFG distribution for both protomers further outward, as shown by the 30° larger DFG pseudo dihedral in the holo dimer relative to the mixed dimer (green and blue in Figure 5b right; Supplementary Figures 6,9). In contrast, there is no significant difference in the DFG pseudo dihedral between the LY-mixed and holo dimers. These data suggest that while the binding of the first PHI1 pushes the DFG outward, binding of the second PHI1 has an allosteric effect, shifting the DFG of the opposite protomer further outward.”

    On page 12, the last paragraph of Conclusion, we remove the claim of the priming effect for DFG:

    “The first PHI1 binding in the BRAFV600E dimer restricts the motion of the αC helix and DFG, shifting them slightly inward and outward, respectively (Figure 6, bottom right panel). Intriguingly, the first PHI1 binding primes the apo protomer by making the αC more favorable for binding, i.e., shifting the αC inward (Figure 6, bottom right panel). Importantly, upon binding the second PHI1, the αC helix is shifted further inward and the DFG is shifted further outward in both protomers.”

    On page 13, Figure 6:

    we removed the label “slightly outward” for DFG.

    Comment 3: An alternative approach could be using enhanced sampling methods to enhance the diffusion along these coordinates.

    We thank the reviewer for bringing up this point. While that the allostery and cooperativity effects are apparent from our simulation data, we agree that enhanced sampling methods in principle could be used to further converge the conformational sampling; however, these approaches face significant challenges. First, BRAF dimer is weakly associated, with αC helix forming a part of the dimer interface. Enhanced sampling of αC helix would likely result in dimer dissociation. On the other hand, simply using RMSD as a reaction coordinate or progress variable would not necessarily enhance the motion of αC helix or DFG or activation loop, which are all coupled. Second, our extensive simulations of a monomer kinase with metadynamics demonstrated that the kinase conformation becomes distorted when a biasing potential is placed to enhance the motion of DFG. This is likely because the other parts of the protein do not have enough time to relax to accommodate the conformational change. To our knowledge, this aspect has not been discussed in the current metadynamics literature, which focuses on the free energy differences and (local) conformational changes along the reaction coordinate. To clarify these points, we added a discussion.

    Page 6, end of the first paragraph:

    “We note that enhanced sampling methods were not used due to several challenges. First, the BRAF dimer is weakly associated, with αC helix forming a part of the dimer interface (Figure 1a). Enhanced sampling (particularly of αC helix) would likely lead to dimer dissociation. Second, biased sampling methods such as metadynamics may lead to unrealistic conformational states due to the slow relaxation of some parts of the protein to accommodate the conformational change directed by the reaction coordinate. For example, our unpublished metadynamics simulations of a monomer kinase showed that enhancing the DFG conformational change resulted in distortion of the kinase structure.”

    We thank the reviewers again for their valuable comments. We believe our revision has further elevated the quality of the manuscript.

  8. Version published to 10.1101/2023.12.12.571293v3 on bioRxiv
  9. Version published to 10.7554/elife.95334.2 on eLife
  10. eLife

    Author response:

    The following is the authors’ response to the original reviews.

    Reviewer #1 (Public review):

    Comment 1: This manuscript from Clayton and co-authors, entitled ”Mechanism of dimer selectivity and binding cooperativity of BRAF inhibitors”, aims to clarify the molecular mechanism of BRAF dimer selectivity. Indeed, first-generation BRAF inhibitors, targeting monomeric BRAFV600E, are ineffective in treating resistant dimeric BRAF isoforms. Here, the authors employed molecular dynamics simulations to study the conformational dynamics of monomeric and dimeric BRAF, in the presence and absence of inhibitors. Multi-microsecond MD simulations showed an inward shift of the αC helix in the BRAFV600E mutant dimer. This helped in identifying a hydrogen bond between the inhibitors and the BRAF residue Glu501 as critical for dimer compatibility. The stability of the aforementioned interaction seems to be important to distinguish between dimer-selective and equipotent inhibitors.

    The study is overall valuable and robust. The authors used the recently developed particle mesh Ewald constant pH molecular dynamics, a state-of-the-art method, to investigate the correct histidine protonation considering the dynamics of the protein. Then, multi-microsecond simulations showed differences in the flexibility of the αC helix and DFG motif. The dimerization restricts the αC position in the inward conformation, in agreement with the result that dimer-compatible inhibitors can stabilize the αC-in state. Noteworthy, the MD simulations were used to study the interactions between the inhibitors and the protein, suggesting a critical role for a hydrogen bond with Glu501. Finally, simulations of a mixed state of BRAF (one protomer bound to the inhibitor and the other apo) indicate that the ability to stabilize the inward αC state of the apo protomer could be at the basis of the positive cooperativity of PHI1.

    Response: We thank the reviewer for the positive evaluation of our work.

    Comment 2: One potential weakness in the manuscript is the lack of reported uncertainties related to the analyzed quantities. Providing this information would significantly enhance the clarity regarding the reliability of the analyses and the confidence in the claims presented.

    Response and revision: We agree with the reviewer that reporting uncertainties will clarify and strengthen our arguments. Following this suggestion, we have added error bars to Figures 3 and 5 representing the standard deviation of the K-E salt bridge probability. This shows that the deviation across replicas of how often the salt bridge is present. Thus, it better supports our claim that this salt bridge is promoted by the presence of PHI1, as the deviation of the salt bridge is minimal for protomers containing PHI1. In addition to these error bars, we have also included a table to the Supplementary Information (Supplementary Table 2) containing the mean and standard deviation of the αC position, K-E distance, and DFG pseudo dihedral for each protomer in our dimer simulations.

    Reviewer #2 (Public review):

    Comment 1: The authors employ molecular dynamics simulations to understand the selectivity of FDA-approved inhibitors within dimeric and monomeric BRAF species. Through these comprehensive simulations, they shed light on the selectivity of BRAF inhibitors by delineating the main structural changes occurring during dimerization and inhibitor action. Notably, they identify the two pivotal elements in this process: the movement and conformational changes involving the alpha-C helix and the formation of a hydrogen bond involving the Glu-501 residue. These findings find support in the analyses of various structures crystallized from dimers and co-crystallized monomers in the presence of inhibitors. The elucidation of this mechanism holds significant potential for advancing our understanding of kinase signaling and the development of future BRAF inhibitor drugs.

    The authors employ a diverse array of computational techniques to characterize the binding sites and interactions between inhibitors and the active site of BRAF in both dimeric and monomeric forms. They combine traditional and advanced molecular dynamics simulation techniques such as CpHMD (all-atom continuous constant pH molecular dynamics) to provide mechanistic explanations. Additionally, the paper introduces methods for identifying and characterizing the formation of the hydrogen bond involving the Glu501 residue without the need for extensive molecular dynamics simulations. This approach facilitates the rapid identification of future BRAF inhibitor candidates.

    Response: We thank the reviewer for the positive evaluation of our work.

    Comment 2: The use of molecular dynamics yields crucial structural insights and outlines a mechanism to elucidate dimer selectivity and cooperativity in these systems. However, the authors could consider the adoption of free energy methods to estimate the values of hydrogen bond energies and hydrophobic interactions, thereby enhancing the depth of their analysis.

    Response: The current free energy methods are capable of giving accurate estimates of the relative binding free energies of similar ligands; however, accurate calculations of the absolute free energies of hydrogen bond and hydrophobic interactions are not feasible yet. Thus, we decided not to pursue the calculations.

    Reviewer #1 (Suggestions to author)

    Comment 1: The general recommendation is to give more details about the procedure for the analyses performed and, when possible, show the uncertainties relative to the analyzed quantities. This would clearly indicate the reliability of the analyses and the confidence of the claims. Moreover, it is not always clear how the analyses were performed.

    Response and revision: As previously mentioned, we have added uncertainties to our bar graphs in Figures 3 and 5 as well as Supplemental Table 2. In regards to the clarity of our analysis, we added more detail on how the probability distributions were created, which we will discuss in our response to Comment 3.

    Comment 2: It is not clear why the authors decided to titrate only the histidines without considering the other charged residues. In particular, the authors show in Supplementary Figure 2 a network of which Asp595 (protomer A) is a part and that, given the direct interaction, could affect the protonation state of His477 (protomer B).

    Response: The reviewer is correct in that Asp595 directly interacts with His477 on the opposite protomer. This is exactly the reason why we did not consider titrating Asp595 – the interaction with His477 should further stabilize the charged state of Asp595 and downshift its pKa from the solution value of about 3.8. Thus, Asp595 will be charged at physiological pH and does not need to be titrated in the CpHMD simulations.

    Comment 3: Regarding the probability density plots (Figures 3 and 5), clarify if you used all the data from all the replicas and all the protomers. If possible, show a comparison between each replica in the Supplementary Figures. A Supplementary Table with the probability values for the measured K-E salt bridge could be helpful since the bar plots are hard to compare. Also in this case please report the uncertainty or a comparison between the replicas.

    Response and revision: To clarify how we created the probability density plots, the following line was added to the Methods section:

    On page 15, third paragraph: All probability distributions were created by combining the last three µs of each replica for each system, with each distribution consisting of 50 bins. Unless specified, distributions contain quantities from both protomers in dimeric simulations.

    As previously mentioned, we have included Supplemental Table 2 which contains the mean and standard deviation of the K-E distance across systems. For comparison between replicas, we found the time series of the K-E distance in the inhibitor-bound monomer and dimer systems in Supplemental Figure 7 to be sufficient.

    Comment 4: It would be better to define the claim: ”it is clear that the timescale of the DFG-out to DFG-in transition is longer than our simulation timeframe of a few microseconds” (lines 208-209). To me it is not obvious why this should be ”clear”.

    Response and revision: Our original statement was to convey that, as DFG-in is sampled very rarely, our simulations cannot accurately represent DFG transitions. We have revised the manuscript to the following:

    On page 6, fourth paragraph: While this does suggest dimerization loosens the DFG motif, our simulations do not appropriately model the DFG-out/-in transition as the DFG-in state is only occasionally sampled.

    Comment 5: In the case of the inhibited monomer simulations, the authors state: ”the PHI1Glu501 interaction can become completely disrupted, with the distance moving beyond 6 A to˚ as high as 12 A; correlated with the disruption of the PHI1-Glu501 interaction, the˚ αC position is shifted out to the range of 21 A-24˚ A” (lines 241-244). However, the plot of the PHI1-Glu501˚ interaction time-series (Supplementary Figure 7) shows that just in one replica of one protomer (Protomer A), the interaction is disrupted, and the αC position never exceeds 21 A (time-series˚ reported in Supplementary Figure 6). None of the fluctuations of the αC position appear to be correlated with the disruption of the ligand-Glu501 interaction. The time-series reported in Supplementary Figures 6 and 7 suggest that the two events are uncorrelated. Please explain this aspect or quantify the correlation to support your claim.

    Response: We believe the source of this confusion is because we did not include a time series of αC for inhibited monomer simulations–Supplementary Figure 6 mentioned in the comment is of dimeric BRAF. Thus, We have added Supplementary Figure 8, a timeseries plot of the αC position for inhibited monomer and dimer protomers.

    Comment 6: Regarding the analyses of the positive cooperativity, the DFG dihedral probability densities for the apo protomer (Figure 5a) are highly overlapping. Thus, it is hard to believe that these small differences support the claim that ”PHI1 binding in one protomer can allosterically shift the DFG motif outward, making it favorable for binding a second inhibitor” (lines 300-302). The authors should show that the differences in the DFG distributions (in particular, apo dimer vs PHI1 mixed) are statistically significant. Only in this case, the data could support the claim that PHI1 bound to one protomer modulates the DFG conformation in the second one. In my opinion, the overlap between the DFG dihedral probability (Figure 5a) is too high to support the claim that PHI1 is able to allosterically modulate this region in the second apo protomer. Please provide an appropriate statistical test that demonstrates that those distributions are significantly different.

    Response and revision: We have adjusted this statement based on the new Supplementary Table 2 to read as the following:

    On page 9, third paragraph: Although the shift is small (the differences between means is approximately one standard deviation, see Supplementary Table 2), it suggests that PHI1 binding in one protomer can allosterically shift the DFG motif outward, making it favorable for binding a second inhibitor. In contrast, the DFG dihedral of the apo protomer in the LY-bound mixed dimer appears to be slightly smaller than the apo dimer with difference between means of approximately one standard deviation (Supplementary Table 2), which is unfavorable for binding the second inhibitor (orange and grey, Figure 5a right).

    Comment 7: Regarding the dimer holo simulations, I agree that in the LY-bound dimer simulations, the hydrogen bond between the ligand and the E501 is weaker, but I do not understand the sentence ”as seen from the local density maximum centered at∼3.4 A” at line 233, since the 2D˚ density plot (Figure 3h) shows that the highest peak is close to 5 A. Also, it would be useful to˚ clarify how these 2D density plots reported in Figure 3 were obtained.

    Response and revision: While the highest peak in Figure 3h is close to 5 A, we were more˚ interested in the local peak close to 3.4 A. To avoid confusion we have modified the line to separate˚ both peaks:

    On page 7, second paragraph: In the LY-bound dimer simulations, however, the LY–Glu501 h-bond is weaker and less stable than the counterpart of the PHI1-bound dimer, as seen from the local density maximum centered at ∼3.4 and the global maximum near ∼4.5 A (Figure 3g,h).˚

    Comment 8: I have a comment on the strategy suggested to empirically classify the inhibitors by comparing the Glu501-Lys483 distance and the αC position in the two protomers of the crystal structures (in the Concluding Discussion section). The authors suggest that differences below 1 A could determine whether the flexibility of these regions is restricted or not (and whether the˚ inhibitor is equipotent or dimer-selective). However, differences below 1 A, in structures where˚ the average resolution is 2.5 A, might be highly unreliable. In fact, as the authors pointed out, LY˚ and Ponatinib would be classified (erroneously) as dimer-selective inhibitors according to these criteria.

    Response and revision: We agree that this proposed method could be unreliable; we intend this strategy to be used as a “quick and dirty” method for analyzing future structures in order to assess selectivity for dimeric BRAF. To convey this, we added the following sentence:

    On page 12, second paragraph: Given that the resolution of a resolved structure is often ∼23 A, this proposed assessment is not intended to replace more rigorous tests, i.e. utilizing MD˚ simulations.

    Comment 9: A suggestion is to include representative snapshots of the MD simulation in the GitHub repository could allow the reader to better appreciate the results described in the present study.

    Response and revision: In order to convey the difference between induced effects of PHI1 and LY, we have added a new folder named snapshots to the GitHub repository which contains the snapshots from the simulations of one LY or one PHI1 bound BRAF (visualized in Figure 5c) in the form of PDB files.

  11. eLife

    eLife assessment

    This important work illuminates the dynamics of BRAF in both its monomeric and dimeric forms, with or without inhibitors, combining traditional techniques and sophisticated computational analyses. The evidence presented is convincing and suggests a potential allosteric effect, though substantiating the exact mechanism will require further studies. The work has implications for understanding kinase signaling and the development of potential drug candidates. This study will be of interest to structural biologists, medicinal chemists, and pharmacologists.

  12. eLife

    Reviewer #1 (Public Review):

    Summary:

    This manuscript from Clayton and co-authors, entitled "Mechanism of dimer selectivity and binding cooperativity of BRAF inhibitors", aims at clarifying the molecular mechanism of BRAF dimer selectivity. Indeed, first generation BRAF inhibitors, targeting monomeric BRAFV600E, are ineffective in treating resistant dimeric BRAF isoforms. Here, the authors employed molecular dynamics simulations to study the conformational dynamics of monomeric and dimeric BRAF, in the presence and absence of inhibitors. Multi-microseconds MD simulations showed an inward shift of the αC helix in the BRAFV600E mutant dimer. This helped identify a hydrogen bond between the inhibitors and the BRAF residue Glu501 as critical for dimer compatibility. The stability of the aforementioned interaction seems to be important to distinguish between dimer-selective and equipotent inhibitors.

    Strengths:

    The study is overall valuable and robust. The authors used the recently developed particle mesh Ewald constant pH molecular dynamics, a state-of-the-art method, to investigate the correct histidines protonation considering the dynamics of the protein. Then, multi-microsecond simulations showed differences in the flexibility of the αC helix and DFG motif. The dimerization restricts the αC position in the inward conformation, in agreement with the result that dimer-compatible inhibitors are able to stabilize the αC-in state. Noteworthy, the MD simulations were used to study the interactions between the inhibitors and the protein, suggesting a critical role for a hydrogen bond with Glu501. Finally, simulations of a mixed state of BRAF (one protomer bound to the inhibitor and the other apo) indicate that the ability to stabilize the inward αC state of the apo protomer could be at the basis of the positive cooperativity of PHI1.

    Weaknesses:

    Regarding the analyses of the mixed state simulations, the DFG dihedral probability densities for the apo protomer (Fig. 5a right) are highly overlapping. It is not convincing that a slight shift can support the conclusion that the binding in one protomer is enough to shift the DFG motif outward allosterically. Moreover, the DFG dihedral time-series for the apo protomer (Supplementary Figure 9) clearly shows that the measured quantities are affected by significant fluctuations and poor consistency between the three replicates. The apo protomer of the mixed state simulations could be affected by the same problem that the authors pointed out in the case of the apo dimer simulations, where the amount of sampling is insufficient to model the DFG-out/-in transition properly. There is similar concern with the Lys483-Glu501 salt bridge measured for the apo protomers of the mixed simulations. As it can be observed from the probabilities bar plot (Fig. 5a middle), the standard deviation is too high to support a significant role for this interaction in the allosteric modulation of the apo protomer.

  13. eLife

    Reviewer #2 (Public Review):

    Summary:

    The authors employ molecular dynamics simulations to understand the selectivity of FDA approved inhibitors within dimeric and monomeric BRAF species. Through these comprehensive simulations, they shed light on the selectivity of BRAF inhibitors by delineating the main structural changes occurring during dimerization and inhibitor action. Notably, they identify the two pivotal elements in this process: the movement and conformational changes involving the alpha-C helix and the formation of a hydrogen bond involving the Glu-501 residue. These findings find support in the analyses of various structures crystallized from dimers and co-crystallized monomers in the presence of inhibitors. The elucidation of this mechanism holds significant potential for advancing our understanding of kinase signalling and the development of future BRAF inhibitor drugs.

    Strengths:

    The authors employ a diverse array of computational techniques to characterize the binding sites and interactions between inhibitors and the active site of BRAF in both dimeric and monomeric forms. They combine traditional and advanced molecular dynamics simulation techniques such as CpHMD (All-atom continuous constant pH molecular dynamics) to provide mechanistic explanations. Additionally, the paper introduces methods for identifying and characterizing the formation of the hydrogen bond involving the Glu501 residue without the need for extensive molecular dynamics simulations. This approach facilitates the rapid identification of future BRAF inhibitor candidates.

    Weaknesses:

    Despite the use of molecular dynamics yields crucial structural insights and outlines a mechanism to elucidate dimer selectivity and cooperativity in these systems, the authors could consider adoption of free energy methods to estimate the values of hydrogen bond energies and hydrophobic interactions, thereby enhancing the depth of their analysis.

  14. Version published to 10.1101/2023.12.12.571293v2 on bioRxiv
  15. Version published to 10.7554/elife.95334.1 on eLife
  16. eLife

    Author Response

    We thank both reviewers for the positive evaluation of our work and suggestions on how to improve it.

    We agree with Reviewer #1 that reporting uncertainties will both clarify and strengthen our arguments. Where applicable, uncertainties will be added in a revised version.

    To Reviewer #2’s suggestion of including free energy calculations to estimate the free energies of hydrogen bond and hydrophobic interactions, the current free energy methods are capable of given accurate estimates of the relative binding free energies of similar ligands; however, accurate calculations of the absolute free energies of hydrogen bond and hydrophobic interactions are not feasible yet.

    Again, we thank the reviewers for their assessment and suggestions. We will update the manuscript as we have outlined above.

  17. eLife

    eLife assessment

    This important work illuminates the dynamics of BRAF in both its monomeric and dimeric forms, with or without inhibitors, combining traditional techniques and sophisticated computational analyses. The evidence presented is convincing, though a more detailed description of the analyses could enhance reproducibility and the quality of the results. This study will interest structural biologists, medicinal chemists, and pharmacologists.

  18. eLife

    Reviewer #1 (Public Review):

    This manuscript from Clayton and co-authors, entitled "Mechanism of dimer selectivity and binding cooperativity of BRAF inhibitors", aims to clarify the molecular mechanism of BRAF dimer selectivity. Indeed, first-generation BRAF inhibitors, targeting monomeric BRAFV600E, are ineffective in treating resistant dimeric BRAF isoforms. Here, the authors employed molecular dynamics simulations to study the conformational dynamics of monomeric and dimeric BRAF, in the presence and absence of inhibitors. Multi-microsecond MD simulations showed an inward shift of the αC helix in the BRAFV600E mutant dimer. This helped in identifying a hydrogen bond between the inhibitors and the BRAF residue Glu501 as critical for dimer compatibility. The stability of the aforementioned interaction seems to be important to distinguish between dimer-selective and equipotent inhibitors.

    The study is overall valuable and robust. The authors used the recently developed particle mesh Ewald constant pH molecular dynamics, a state-of-the-art method, to investigate the correct histidine protonation considering the dynamics of the protein. Then, multi-microsecond simulations showed differences in the flexibility of the αC helix and DFG motif. The dimerization restricts the αC position in the inward conformation, in agreement with the result that dimer-compatible inhibitors can stabilize the αC-in state. Noteworthy, the MD simulations were used to study the interactions between the inhibitors and the protein, suggesting a critical role for a hydrogen bond with Glu501. Finally, simulations of a mixed state of BRAF (one protomer bound to the inhibitor and the other apo) indicate that the ability to stabilize the inward αC state of the apo protomer could be at the basis of the positive cooperativity of PHI1.

    One potential weakness in the manuscript is the lack of reported uncertainties related to the analyzed quantities. Providing this information would significantly enhance the clarity regarding the reliability of the analyses and the confidence in the claims presented.

  19. eLife

    Reviewer #2 (Public Review):

    The authors employ molecular dynamics simulations to understand the selectivity of FDA-approved inhibitors within dimeric and monomeric BRAF species. Through these comprehensive simulations, they shed light on the selectivity of BRAF inhibitors by delineating the main structural changes occurring during dimerization and inhibitor action. Notably, they identify the two pivotal elements in this process: the movement and conformational changes involving the alpha-C helix and the formation of a hydrogen bond involving the Glu-501 residue. These findings find support in the analyses of various structures crystallized from dimers and co-crystallized monomers in the presence of inhibitors. The elucidation of this mechanism holds significant potential for advancing our understanding of kinase signaling and the development of future BRAF inhibitor drugs.

    The authors employ a diverse array of computational techniques to characterize the binding sites and interactions between inhibitors and the active site of BRAF in both dimeric and monomeric forms. They combine traditional and advanced molecular dynamics simulation techniques such as CpHMD (all-atom continuous constant pH molecular dynamics) to provide mechanistic explanations. Additionally, the paper introduces methods for identifying and characterizing the formation of the hydrogen bond involving the Glu501 residue without the need for extensive molecular dynamics simulations. This approach facilitates the rapid identification of future BRAF inhibitor candidates.

    The use of molecular dynamics yields crucial structural insights and outlines a mechanism to elucidate dimer selectivity and cooperativity in these systems. However, the authors could consider the adoption of free energy methods to estimate the values of hydrogen bond energies and hydrophobic interactions, thereby enhancing the depth of their analysis.

  20. Version published to 10.1101/2023.12.12.571293v1 on bioRxiv