A computational and bioinformatic analysis of ACE2: an elucidation of its dual role in COVID-19 pathology and finding its associated partners as potential therapeutic targets

Abstract

Despite the continued global spread of the current COVID-19 pandemic, the nonavailability of a vaccine or targeted drug against this disease is still prevailing. The most established mechanism of viral entry into the body is considered to be via angiotensin-converting enzyme 2 (ACE2) acting as a receptor for viral spike protein thereby facilitating its entry in the cell. However, ACE2 is also involved in providing the protection from severe pathological changes. This article provides a computational and bioinformatics-based analysis of ACE2 with an objective of providing further insight into the earnest efforts to determine its true position in COVID-19 pathology. The results of this study show that ACE2 has strikingly low expression in healthy human lung tissue and was absent from the list of differentially expressed genes. However, when transcription factors were analyzed, we found a significant upregulation of FOS and downregulation of FOXO4 and FOXP2. Moreover, the miRNA prediction analysis revealed that miR-1246, whose upregulation has been experimentally established to be a cause of acute respiratory distress syndrome (ARDS), was found to be targeting the coding DNA sequence (CDS) of ACE2. This study presents a wide range of potentially important transcription factors as well as miRNA targets associated with ACE2 which can be potentially used for drug designing amid this challenging pandemic situation.

Communicated by Ramaswamy H. Sarma

Keywords:

• Angiotensin-converting enzyme -2
• Acute respiratory distress syndrome Predicted ACE2 structure
• miRNA-1246
• FOXO4
• FOS
• MiR-212-5p

Disclosure statement

No potential conflict of interest was reported by the authors.

Author contributions

Abeedha Tu-Allah Khan designed the study and worked on prediction of miRNAs, prediction of TFs, RNA seq analysis and analysis of cellular pathways. Zumama Khalid, Muhammad Abrar Yousaf and Hafsa Zahid contributed in Phylogenetic analysis, physiochemical characterization, protein structure building and SNPs, methylation, PTM and functional network analysis. Abdul Rauf Shakoori supervised and guided the whole study.

Figure 12. Plotting to view the differentially expressed genes. Left – MDplot; and right – volcano plot.