From the journal RSC Chemical Biology Peer review history

Helix-based screening with structure prediction using artificial intelligence has potential for the rapid development of peptide inhibitors targeting class I viral fusion

Round 1

Manuscript submitted on 04 Sep 2023
 

Berlin, 23 September 2023

Dear Dr Hayashi:

Manuscript ID: CB-ART-09-2023-000166
TITLE: Helix-based screening with structure prediction using artificial intelligence has potential for the rapid development of peptide inhibitors targeting class I viral fusion

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Technische Universität Berlin
Faculty II - Mathematics and Natural Sciences
RSC Chemical Biology Associate Editor

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Reviewer 1

This manuscript describes design of peptides as SARS-CoV-2 fusion inhibitors. The authors established a screening system for peptide-based inhibitors containing an alpha-helix region (SPICA). Using SPICA and an artificial intelligence structure-prediction system (AlphaFold2), they identified that critical amino acid regions played a pivotal role in SARS-CoV-2 fusion. These peptides containing critical amino acid regions could become inhibitors. It is proven that the combination of SPICA and AlphaFold2 is a powerful tool to design viral fusion inhibitors. Some inhibitors have significant inhibitory activities against SARS-CoV-2. The present results are considered to be an important finding. But, critical revisions are required.

1. Characterization data of new synthesized peptides are required. In addition, N- and C-terminal forms of these peptides should be clarified: N-terminal free or acetylated, C-terminal carboxy-free or carboxyamidated.
2. For design of peptides, the authors used the amino acid sequences, which are derived from the entire Wuhan strain spike protein. In assay systems, which strain did they use? In the quantification of SARS-CoV-2, the SARS-CoV-2 detection kit, N1 set (Toyobo, Ltd., Biotech Support Department, Osaka, Japan) was used. Which strain is included? There are some mutated amino acids in the spike protein among several strains. If the authors use strains except for the Wuhan strain in assays, is it OK?

Reviewer 2

it is strongly recommended to study binding modes using HDX mass spectrometry/ imaging/ FRET/ or other structural imaging techniques to validate the binding site, otherwise the claim made by the authors is useless " Here, we identified that critical amino acid regions, DVDLGD (amino acids 1163–1168 in the S protein), IQKEIDRLNE (1179–1188), and NLNESLIDL (1192–1200), played a pivotal role in SARS-CoV-2 fusion. Peptides containing these critical amino acid regions efficiently blocked viral replication. We also demonstrated that AlphaFold2 could successfully predict structures similar to the reported crystal and cryo-electron microscopy structures of the post-fusion form of the SARS-CoV-2 S protein. Notably, the predicted structures of the HR1 region and the peptide-based fusion inhibitors corresponded well with the antiviral effects of each
fusion inhibitor"

I would recommend to choose one strong validation technique, which would strengthen. the impact of this work.


 

Oct. 13th, 2023
Re: CB-ART-09-2023-000166 (Helix-based screening with structure prediction using artificial intelligence has potential for the rapid development of peptide inhibitors targeting class I viral fusion)

Dear Editor and Reviewer
Please find the attached files of our revised manuscript entitled “Helix-based screening with structure prediction using artificial intelligence has potential for the rapid development of peptide inhibitors targeting class I viral fusion”, co-authored by Satoshi Suzuki et al. We are pleased to have received favorable reviews from you and two Referees. We are also thankful for the helpful review by two Referees. Please allow us to outline the revised manuscript in response to the Referees’ criticisms.
Additionally, we have corrected a few careless mistakes outside of the referee's remarks, which are shown below. We believe these mistakes do not affect the conclusion of this paper.

Page 4, Line 1 to 2 of the revised manuscript
BEFORE: Analysis of structure-activity relationships using crystal and predictive structures
AFTER: Analysis of structure–activity relationships using crystal and cryo-electron microscopy structures
Page 10 and 11, Table S2 of the revised supplementary information
In Table S2, we added several amino acids forming the HR1-HR2 interaction revealed during the reanalysis of crystal structure (PDB code: 6LXT). Please see Page 10, Table S2 of the revised supplementary information or Page 9 to 10 of this Reply letter. Interacting amino acids around three critical regions in the revised version of Table S2 are consistent with the amino acids located at chain A shown in the revised version of Fig S5 to S7.

A point-by-point response to the Referee #1’s comments
Comments to the Author
This manuscript describes design of peptides as SARS-CoV-2 fusion inhibitors. The authors established a screening system for peptide-based inhibitors containing an alpha-helix region (SPICA). Using SPICA and an artificial intelligence structure-prediction system (AlphaFold2), they identified that critical amino acid regions played a pivotal role in SARS-CoV-2 fusion. These peptides containing critical amino acid regions could become inhibitors. It is proven that the combination of SPICA and AlphaFold2 is a powerful tool to design viral fusion inhibitors. Some inhibitors have significant inhibitory activities against SARS-CoV-2. The present results are considered to be an important finding. But, critical revisions are required.
Our Response to Referee #1:
We appreciate Reviewer #1’s comment that our research is considered to be an important finding.

1. Characterization data of new synthesized peptides are required. In addition, N- and C-terminal forms of these peptides should be clarified: N-terminal free or acetylated, C-terminal carboxy-free or carboxyamidated.
We appreciate Referee #1’s comment. In this study, we employed the fusion inhibitors, which were reported in the previous studies (refs. 17, 18, 22, 25, 37 and 43 of the revised manuscript). N- and C-terminal forms of these inhibitors are shown in Table 2 of the previous and revised manuscripts. Table 1 of our manuscript shows amino acid sequences of alkaline phosphatase (ALP) fused peptides, which are produced by protein expression system using E. coli (Please see Fig. S2 in Supplemental Information). Therefore, N-terminals of peptides in Table 1 are fused to ALP and C-terminals are carboxy-free form. To clarify this point, we added information about N- and C-terminals in Table 1 of the revised manuscript (Please see Page 4, Table 1 of the revised manuscript, or Page 5 in this Reply letter).

2. For design of peptides, the authors used the amino acid sequences, which are derived from the entire Wuhan strain spike protein. In assay systems, which strain did they use? In the quantification of SARS-CoV-2, the SARS-CoV-2 detection kit, N1 set (Toyobo, Ltd., Biotech Support Department, Osaka, Japan) was used. Which strain is included? There are some mutated amino acids in the spike protein among several strains. If the authors use strains except for the Wuhan strain in assays, is it OK?
Thank you for Referee #1’s comment. For antiviral assay, we used SARS-CoV-2 strain JPN/TY/WK-521 [GISAID: EPI_ISL_408667], which is a variant of Wuhan strain isolated in Japan. Toyobo kit has been used for detection of this virus (additional ref. 55 and 56). To clarify this point, we added information about viral strain in the Experimental section and the Fig. 5 legend of the revised manuscript (Page 8, Line 70 and Page 6, Fig. 5 of the revised manuscript). Furthermore, we added two references.

Added the information in the Experimental section of the revised manuscript. (Page 8, Line 70)
BEFORE: SARS-CoV-2 and VeroE6/TMPRSS2 cells (2.0 × 104 cells/well) were added to the plates and the plates were incubated for 3 days.
AFTER: SARS-CoV-2 strain JPN/TY/WK-521 (GISAID: EPI_ISL_408667) , which is a variant of Wuhan strain isolated in Japan, and VeroE6/TMPRSS2 cells (2.0 × 104 cells/well) were added to the plates and the plates were incubated for 3 days.

Additional sentence in the Fig. 5 legend in the revised manuscript.
In this assay, SARS-CoV-2 strain JPN/TY/WK-521 is used.

Additional references for SARS-CoV-2 strain and SARS-CoV-2 detection kit (Page 8, Line 77)
Ref. 55 Takeda et al. Antiviral efect of cetylpyridinium chloride in mouthwash on SARS‑CoV‑2. Scientific Reports, (2022) 12:14050, doi: 10.1038/s41598-022-18367-6
Ref. 56 Yoo et al. SARS-CoV-2 inhibits induction of the MHC class I pathway by targeting the STAT1-IRF1-NLRC5 axis. Nature Communications (2021) 12:6602, doi: 10.1038/s41467-021-26910-8

A point-by-point response to the Referee #2’s comments
Comments to the Author
it is strongly recommended to study binding modes using HDX mass spectrometry/ imaging/ FRET/ or other structural imaging techniques to validate the binding site, otherwise the claim made by the authors is useless " Here, we identified that critical amino acid regions, DVDLGD (amino acids 1163–1168 in the S protein), IQKEIDRLNE (1179–1188), and NLNESLIDL (1192–1200), played a pivotal role in SARS-CoV-2 fusion. Peptides containing these critical amino acid regions efficiently blocked viral replication. We also demonstrated that AlphaFold2 could successfully predict structures similar to the reported crystal and cryo-electron microscopy structures of the post-fusion form of the SARS-CoV-2 S protein. Notably, the predicted structures of the HR1 region and the peptide-based fusion inhibitors corresponded well with the antiviral effects of each fusion inhibitor"

I would recommend to choose one strong validation technique, which would strengthen. the impact of this work.
We appreciate Referee #2’s suggestion. The structure of HR1-HR2 complex of SARS-CoV-2 fusion protein was previously analyzed by crystal structural analysis and cryo-electron microscopy. Especially, the crystal structure includes all critical amino acid regions. Therefore, binding modes between these three regions and HR1 is clear. In the crystal structure, each amino acid chain showed slightly different binding mode. As Referee#2 mentions, analysis by HDX mass spectrometry may indeed lead to data that can estimate binding modes and assist in identifying binding modes. On the other hand, it is unlikely that HDX mass spectrometry results will provide more detailed information on peptide binding modes than crystal-structure analysis or cryo-EM.
To show the binding mode of the three critical regions in the crystal structure (PDB ID: 6LXT), we added Supplemental Figures (Fig. S6 to S8, Please see Page 6 to 8 of supplemental information or Page 6 to 8 of this reply letter) and added a sentence in the Results section of the revised manuscript.

Additional sentence in the Results section of the revised manuscript (Page 3, Line 32 to 35)
Finally, SPICA indicated three critical regions, DVDLGD (amino acids 1163–1168 in the S protein), IQKEIDRLNE (1179–1188), and NLNESLIDL (1192–1200) that formed hydrogen bonds and hydrophobic interactions to HR1 trimer (Fig. S5 to S7).




Round 2

Revised manuscript submitted on 13 Oct 2023
 

Berlin, 4 November 2023

Dear Dr Hayashi:

Manuscript ID: CB-ART-09-2023-000166.R1
TITLE: Helix-based screening with structure prediction using artificial intelligence has potential for the rapid development of peptide inhibitors targeting class I viral fusion

Thank you for submitting your revised manuscript to RSC Chemical Biology. I am pleased to accept your manuscript for publication in its current form. I have copied any final comments from the reviewer(s) below.

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Technische Universität Berlin
Faculty II - Mathematics and Natural Sciences
RSC Chemical Biology Associate Editor


 
Reviewer 1

accepted.

Reviewer 2

1. The authors didn't validate their AI model properly by producing experimental data. They have primarily reported their prediction accuracy by comparing the binding modes with some existing inhibitor dataset. The main point is , if AI could predict the actual binding modes, the experimental data will also support AI results . Instead of considering existing inhibitors, I would suggest them to consider a few other inhibitors to evaluate their model accuracy followed by experimental and structural validation (that would explain whether there were any bias or not).

2. Alpha fold2 or Colab fold is useful only when the homologs are available. The algorithms of alpha fold2 or Colab fold have not been optimized properly for de-novo modeling. In this study, it is expected to have good quality structure from Alpha fold, thus it doesn't explain any novelty of research. The homologs are already known and anyone could model it easily either locally by modifying script. The authors should justify the novelty of their work, for instance, what was the challenge before they did modeling and what did they actually achieve ? I would suggest the authors avoid jargon.

3. The pipeline of drug design and discovery requires at least some sort of structural evidence. In this study, the authors provide evidence based on the existing inhibitors and some other screened ones, which doesn't explain the rigor of their given modeling hypothesis.

Reviewer 3

Thanks for the opportunity to participate in the review process of this manuscript. The authors have been addressed all my comments and suggestions and have improved the quality of the article.




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