The Structural Dynamics of IRE1 and its Interaction with Unfolded Peptides

Reviewer #1 (Public review):

Summary:

This work provides structural and mechanistic insights into the disordered protein recognition process inside the endoplasmic reticulum by the inositol-requiring enzyme 1. Using state-of-the-art molecular dynamics simulation tools, the authors propose a mechanism of disordered protein recognition that reconciles contradictory findings of biochemical and structural biology experiments.

Strengths:

(1) All MD simulations have been carried out in triplicate, and several different folded conformations were generated using alphafold2. This provides adequate statistics to draw meaningful conclusions from the simulations.

(2) Potential limitations of the disordered protein force fields and water models have been taken into consideration. Particularly, performing the simulation in both TIP3P and TIP4PD water models ensures that the conclusions drawn are not influenced by the force field choice.

(3) The binding of a large number of disordered peptides was investigated, ensuring that the conclusions drawn about disordered peptide recognition are sufficiently general.

Weaknesses:

(1) The timescales of the peptide recognition and unbinding process are much longer than what can be sampled from unbiased simulations. Therefore, the proposed mechanism of recognition should only be considered a hypothesis based on the results presented here. For example, peptides that do not dissociate within one one-microsecond MD simulation are considered to be stable binders. However, they may not have a viable way to bind to the narrow protein cleft in the first place.

(2) Oftentimes, representative structures sampled from MD simulation are used to draw conclusions (e.g., Figure 4 about the role of R161 mutation in binding affinity). This is not appropriate as one unbinding event being observed or not observed in a microsecond-long trajectory does not provide sufficient information about the binding strength of the free energy difference.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors investigated the interactions between IRE and unfolded peptides using all-atom molecular dynamics simulations. The interactions between a couple of unfolded peptides and IRE might shed light on the activation of the UPR.

Strengths:

(1) Well-written manuscript tailored for a biology audience.

(2) State-of-the-art structural predictions and all-atom simulations.

(3) Validation with existing experimental data

(4) Clear schematic diagram summarizing the mechanisms learned from simulations.

(5) Shared simulation data and code in a public repository.

Weaknesses:

(1) Improving presentation to include more computational details.

(2) More quantitative analysis in addition to visual structures.

Reviewer #3 (Public review):

Summary:

In this important work, the authors use extensive MD simulations to study how the IRE1 protein can detect unfolded peptides. Their study consolidates contradicting experimental results and offers a unique view of the different sensing models that have been proposed in the literature. Overall, it is an excellent study that is quite extensive. The research is solid, meticulous, and carefully performed, leading to convincing conclusions.

Strengths:

The strength of this work is the extensive and meticulous molecular dynamics simulations. The authors use and investigate different structural models, for example, carefully comparing a model based on a PDB structure with reconstructed loops with an AlphaFold 2 Multimer model. The author also investigates a wide range of different protein structural models that probe different aspects of the peptide sensing process. These solid and meticulous MD simulations allow the authors to obtain convincing conclusions concerning the peptide sensing process of the IRE1 protein.

Weaknesses:

A potential weakness of the study is the usage of equilibrium (unbiased) molecular dynamics simulations, so that processes and conformational changes on the microsecond time scale can be probed. Furthermore, there can be inaccuracies and biases in the description of unfolded peptides and protein segments due to the protein force fields. Here, it should be noted that the authors do acknowledge these possible limitations of their study in the conclusions.

Author response:

Reviewer #1:

We appreciate the Reviewer's positive feedback on the strengths of our study.

The timescales of the peptide recognition and unbinding process are much longer than what can be sampled from unbiased simulations. Therefore, the proposed mechanism of recognition should only be considered a hypothesis based on the results presented here. For example, peptides that do not dissociate within one one-microsecond MD simulation are considered to be stable binders. However, they may not have a viable way to bind to the narrow protein cleft in the first place.

We thank the Reviewer for this valuable feedback. We agree with the Reviewer. Our work on the IRE1 cLD activation mechanism is focused on generating hypotheses of the binding mechanism driven by MD simulations. We recognize the limitations in defining a stable binder due to the time scales sampled. However, our primary focus was to sample and characterize a possible binding pose in the center of the cLD dimer. We will contextualize our statements about stable binders and limit our claims to stating that the protein-peptide complex is stable within 1 μs-long simulations. However, we believe that our finding that the cLD dimer groove is not able to accommodate peptides is solid, as the steric impediment described is present in all our replicas, both with and without peptides, in a cumulative sampling time of 72 μs. Additionally, we will include a plot showing the distribution of groove width across all replicas.

Oftentimes, representative structures sampled from MD simulation are used to draw conclusions (e.g., Figure 4 about the role of R161 mutation in binding affinity). This is not appropriate as one unbinding event being observed or not observed in a microsecond-long trajectory does not provide sufficient information about the binding strength of the free energy difference.

We thank the Reviewer for the insightful comment. As explained in the previous point, we believe that our simulations provide useful hypotheses, and we agree that we do not currently have data to comment on binding affinity. We will, therefore, remove all references to this term. We are aware of the limitations due to the timescale and agree that these limitations cannot be overcome with standard equilibrium simulations. To address these limitations, we plan to use orthogonal methods, namely MM/PB(GB)SA calculations for calculating binding free energies from existing trajectories (as performed by https://doi.org/10.1021/acs.jcim.4c00975). We will add predictions of all the peptides using AlphaFold 3, to confirm the binding region.

Reviewer #2:

We thank the Reviewer for their positive feedback.

Improving presentation to include more computational details.

We thank the Reviewer for raising this critical point. We agree that the manuscript is tailored for a biology audience, as the data are particularly relevant for that community. Nevertheless, we also understand the importance of providing sufficient methodological detail for computational readers. We will add appropriate computational information in the main text.

More quantitative analysis in addition to visual structures.

We will add an uncertainty estimate for the HDX calculations using bootstrapping and include additional information on bond distances for Y161. We will also incorporate time-series data showing the distance of the peptide from the groove across all replicas.

Reviewer #3:

We appreciate the Reviewer's positive feedback on our work.

A potential weakness of the study is the usage of equilibrium (unbiased) molecular dynamics simulations so that processes and conformational changes on the microsecond time scale can be probed. Furthermore, there can be inaccuracies and biases in the description of unfolded peptides and protein segments due to the protein force fields. Here, it should be noted that the authors do acknowledge these possible limitations of their study in the conclusions.

We appreciate the Reviewer's thoughtful comment. As noted in our response to Reviewer 1, we plan to address the concern about sampling by applying orthogonal methods. We agree with the Reviewer that some form of enhanced sampling is necessary if we want to assess binding in a more quantitative way, e.g., via free energy calculations. However, we also realize that applying any enhanced sampling scheme to our system is very challenging, given its large size and the complex peptide-protein interactions, which are not easily captured in a few collective variables. After a careful assessment and some preliminary tests, we decided that estimating free energies using enhanced sampling would necessitate a separate paper due to both the conceptual complexity of the project and the size of the necessary sampling campaign.