Peer-Review Record
Discovery of Novel Trace Amine-Associated Receptor 5 (TAAR5) Antagonists Using a Deep Convolutional Neural Network
Int. J. Mol. Sci. 2022, 23(6), 3127; https://doi.org/10.3390/ijms23063127
by
Carlotta Bon 1
, Ting-Rong Chern 2, Elena Cichero 3, Terrence E. O’Brien 2, Stefano Gustincich 1, Raul R. Gainetdinov 4,5 and Stefano Espinoza 1,6,*
, Ting-Rong Chern 2, Elena Cichero 3, Terrence E. O’Brien 2, Stefano Gustincich 1, Raul R. Gainetdinov 4,5 and Stefano Espinoza 1,6,*Reviewer 1:
Anonymous
Reviewer 2:
Anonymous
Int. J. Mol. Sci. 2022, 23(6), 3127; https://doi.org/10.3390/ijms23063127
Submission received: 5 February 2022
/
Revised: 6 March 2022
/
Accepted: 10 March 2022
/
Published: 14 March 2022
(This article belongs to the Special Issue Trace Amine-Associated Receptors in Neuropsychiatric Disorders)
Round 1
Reviewer 1 Report
Dear authors,
thank you for the manuscript. It can be considered interesting for the Journal's readership. However I have some major points.
- Please, provide detailed description of the AtomNet CNN and features that you used.
- Could you please describe all possible pharmacological and side effects for TAAR5 antagonists? Are there any other efforts to find TAAR5 antagonists? it would be great to provide this information in the text.
- What is the rationale under selection of ERK and CREB as the molecules, which were influenced by TAAR5 antagonists?
Author Response
Please see the attachment.
Author Response File: 
Author Response.docx
Reviewer 2 Report
Please refer to the attached document
Comments for author File: 
Comments.pdf
Author Response
Please see the attachment.
Author Response File: Author Response.docx
