Comment on a PREreview of "Mechanistic Studies of Small Molecule Ligands Selective to RNA Single G Bulges"
Creators: name: Stephanie Wankowicz
Publisher: name: Zenodo
Year: 2024

description: This Zenodo record is a permanently preserved version of a comment on a PREreview. You can view the complete PREreview and comments at https://prereview.org/reviews/14450597.


This review had mistakes in it. Please see the updated review below:
This publication aims to develop a platform of methods to identify small molecule ligand and RNA substrate interactions. Using a library of coumarin derivatives, they discovered a small molecule, C30, with high affinity binding to RNA single G bulges over other bulges (A, U, and C). The authors used Gaussian accelerated Molecular Dynamics (GaMD) simulations to study interactions, NMR to confirm the binding site location, and lasso regression to identify molecular descriptors for structure-activity relationships. The other narrative in this paper argues that this methodology could be used to develop better RNA-small molecule ligands for therapeutic purposes. 
   Major Revisions:


To strengthen the novel aspects of the authors' methodology, it would be beneficial to add context on why this method is more advantageous than previous workflow paths. 

Additionally, to drive this home in the conclusion, it would be beneficial to summarize the novel nature of this workflow and how it was used to discover these new ligands.

We suggest clarifying and justifying the type of RNA substrate used in each assay (ssRNA, dsRNA, etc.). For example, we suggest clarifying if the modeled version of "SL5RNA" used in the Fig 2 in vitro assay is the same as the additional FP simulations. 

For Fig. 3, in these FP simulations, please clarify if this "DNA version" of the RNA5 and RNA1 substrains is dsDNA or ssDNA. If it is a helical dsDNA version of the substrate, a justification as to why this was used to probe a minor groove binding mechanism for a seemingly bulged ssRNA substrate would be beneficial.

We would suggest integrating some of the supplementary figures, like Supplementary Figure 6, into the main text. This could enhance the reader's understanding of the electrostatic interactions in RNA-ligand binding and the significance of Ring A's positive charge in identifying binding pockets. 

Additionally, we suggest exploring alternative feature selection methods such as SHAP or Markov trees. These could potentially capture more nuanced, nonlinear interactions that might be missed by a linear selection method like LASSO.
Minor Revisions:


In the introduction, we suggest that the authors clarify the importance of preventing deep hydrophobic binding pockets in a pharmaceutical context, including a more streamlined discussion of coumarin derivatives and their therapeutic potential for SARS-CoV-2.

We suggest in Fig. 2D that the graphs' y-axes should be scaled the same and these curves should be labeled "GA-rich" and "G" for clarity. 

For Fig. 3A, we suggest the legend be enhanced and a scale bar added for clarity. 

For Fig 3D, it is difficult to identify the yellow, grey, and orange dashed lines. Please make this more obvious to highlight.

          
Competing interests

          

            The author of this comment declares that they have no competing interests.