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by
  • André Fischer1,†,
  • Manuel Sellner1,† and
  • Karolina Mitusińska2,†
  • et al.

Reviewer 1: Anonymous Reviewer 2: Anonymous

Round 1

Reviewer 1 Report

It is a nicely written article about using computational methods to access protease inhibitors against sars-cov2. I recommend publication of this article in IJMS.

Author Response

Thank you very much for the positive feedback!

Reviewer 2 Report

This is a well-done piece of work. The authors applied a series of computational approaches to assess the selectivity and potential toxicity of 33 reported SARS-CoV-2 Mpro inhibitors. In this work, the potential off-targets were chosen reasonably, the protocols for computational methods were validated using existing experimental data, the results were solid, and the discussion was insightful. I believe this work will be a useful guide for both academia and industry.

My major suggestion:

  1. Since there is no experimental result to support the conclusion in this work, which is understandable, I would suggest applying more expensive free energy calculations (e.g., MM-PBSA, QM-MM) to a subset of the docking results to further validate the robustness of the conclusion. But this is not absolutely required.

A few minor points:

  1. During the reviewing process, a few vaccines were already released. Please adjust the introduction accordingly.
  2. Please provide brief descriptions in Table 1 about why each protein is considered as an anti-target or not.
  3. Please consider explaining why these eight proteases were selected in the study early in the introduction.
  4. I am not sure how useful or easy-to-understand the binding-mode images in the figures are. I feel the authors could present the information in simpler 2D images.

 

Author Response

We would like to thank Reviewer 2 for constructive comments on our manuscript. We hope the changes alleviated all concerns.

Please, consult the attached file with all answers.

Author Response File: Author Response.pdf