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Research Articles

Structural-based design of HD-TAC7 PROteolysis TArgeting chimeras (PROTACs) candidate transformations to abrogate SARS-CoV-2 infection

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Pages 14566-14581 | Received 27 Dec 2022, Accepted 16 Feb 2023, Published online: 25 Feb 2023
 

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for about 672 million infections and 6.85 million deaths worldwide. Upon SARS-CoV-2 infection, Histone deacetylases (HDACs) hyperactivate the pro-inflammatory response resulting in stimulation of Acetyl-Coenzyme A and cholesterol for viral entry. HDAC3 inhibition results in the anti-inflammatory activity and reduction of pro-inflammatory cytokines that may restrict COVID-19 progression. Here, we have designed 44 conformational ensembles of previously known HD-TAC7 by enumerating torsions of dihedral angles tested for their binding preferences against HDAC3. Through scrutinizing their placements at active site and binding affinities, three hits were isolated. Cereblon (CRBN) is a well-known E3 ligase that facilitates Proteolysis Targeting Chimeras (PROTACs) targeting. Three entities, including HDAC3-binding moiety (4-acetamido-N-(2-amino-4 fluorophenyl) benzamide), a 6-carbon linker, and CRBN binding ligand (pomalidomide) were assembled to design 4 PROTACs followed by energy minimization and docking against HDAC3 and CRBN, respectively. Subsequent molecular dynamics (MD) and free energy analyses corroborated similar binding trends and favorable energy values. Among all cases, Met88, GLu106, Pro352, Trp380 and Trp388 residues of CRBN, and Pro23, Arg28, Lys194, Phe199, Leu266, Thr299 and Ile346 residues of HDAC3 were engaged in PROTAC binding. Thus, conformational dynamics of both HDAC3 and CRBN moieties are essential for the placement of PROTAC, resulting in target degradation. Overall, the proposed bifunctional small molecules may effectively target HDAC3, stimulating innate immune response to restrict COVID-19 hyperinflammation. This study supports the basis for designing new PROTACs by limiting the conformational search space that may prove more efficient for targeting the protein of interest.

Communicated by Ramaswamy H. Sarma

Acknowledgments

We acknowledge members of Functional Informatics Lab, National Center for Bioinformatics for encouragement, especially Mehreen Gul and Muhammad Fakhar for helpful discussions. I am highly indebted to my family members, Shazia Kanwal, Muhammad Faraz Ali and Arsal Faraz for their indispensable support.

Author contributions

Conceptualization, Sajid Rashid; Methodology, Sana Zahid, Yasir Ali, Sajid Rashid; Formal Analysis, Yasir Ali and Sana Zahid; Writing – original draft preparation, Sana Zahid; Writing – review and editing, Sajid Rashid, Sana Zahid; Supervision and Sajid Rashid. All authors have read and agreed to the published version of the manuscript.

Disclosure statement

The authors declare no conflict of interest.

Data and software availability statement

The authors confirm that the data supporting the findings of this study are available within the article and its Supplementary materials. All the software’s employed in this study are freely available online.

Additional information

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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