key: cord-0857848-cba4950y
authors: Singh, Jitender; Raina, Ashvinder; Sangwan, Namrata; Chauhan, Arushi; Khanduja, Krishan L.; Avti, Pramod K.
title: Identification of homologous human miRNAs as antivirals towards COVID‐19 genome
date: 2021-10-10
journal: Adv Cell Gene Ther
DOI: 10.1002/acg2.114
sha: 35830b4fc080d3828d4b76b66bc012e96150d94f
doc_id: 857848
cord_uid: cba4950y

The COVID‐19 fatality rate is ~57% worldwide. The investigation of possible antiviral therapy using host microRNA (miRNA) to inhibit viral replication and transmission is the need of the hour. Computational techniques were used to predict the hairpin precursor miRNA (pre‐miRNAs) of COVID‐19 genome with high homology towards human (host) miRNA. Top 21 host miRNAs with >80% homology towards 18 viral pre miRNAs were identified. The Gibbs free energy (ΔG) between host miRNAs and viral pre‐miRNAs hybridization resulted in the best 5 host miRNAs having the highest base‐pair complementarity. miR‐4476 had the strongest binding with viral pre‐miRNA (ΔG = −21.8 kcal/mol) due to maximum base pairing in the seed sequence. Pre‐miR‐651 secondary structure was most stable due to the (1) least minimum free energy (ΔG = −24.4 kcal/mol), energy frequency, and noncanonical base pairing and (2) maximum number of stem base pairing and small loop size. Host miRNAs–viral mRNAs interaction can effectively inhibit viral transmission and replication. Furthermore, miRNAs gene network and gene‐ontology studies indicate top 5 host miRNAs interaction with host genes involved in transmembrane‐receptor signaling, cell migration, RNA splicing, nervous system formation, and tumor necrosis factor‐mediated signaling in respiratory diseases. This study identifies host miRNA/virus pre‐miRNAs strong interaction, structural stability, and their gene‐network analysis provides strong evidence of host miRNAs as antiviral COVID‐19 agents.

coronavirus, there is still a significant gap in our knowledge of SARS-CoV-2/COVID-19 pathology. 8 One of the recent emerging areas for effective treatment strategies for COVID-19 is the field of microRNAs (miRNAs). miRNAs are genomically encoded small noncoding RNA molecules that are 20-25 nucleotides base pairs in length and regulate the expression of post-transcriptional genes. 9 It is well known that miRNAs are encoded by the intronic region of the DNA from animals, plants, and certain viruses to regulate their various molecular and biological processes. 10, 11 Approximately, 30 424 mature miRNAs were found in 206 animals, whereas the human genome encodes approximately 3000 miRNAs. 12 The viral miRNAs not only regulate the host gene expression but also regulate their own gene expression. 13 RNA polymerase-II transcribes miRNA genes and forms primary miRNA in the nucleus. Through enzymatic action of the RNase III ribonuclease disease, primary miRNAs are divided into 70-90 long nucleotide base-pair precursor hairpin called precursor miRNA (pre-miRNA). 13, 14 The pre-miRNAs are bound with exportin-5 enzymes and Ran in the nucleus and are exported to the cytoplasm where biogenesis of miRNAs occur. 14 RNase III ribonuclease Dicer further cleaves the pre-miRNAs to the hairpin loop structure known as duplex mature miRNA. 14 The duplex RNA guided strand (active strand) is loaded into an RNA-induced silencing complex (RISC) aimed at degrading or repressing translational activity by messenger RNA. 13 Perfect complementary between the viral mRNA's 3 0 -untranslated region (UTR) and the mature host miRNA seed sequence (2-7 base pair) is sufficient to lead to cleavage, but imperfect complementary can hinder viral mRNA translation. 13, 15 It is known that miRNAs have a potential role in the immunological process and are involved in the regulation of the immune system through the activation of the immune cells. 16 Studies investigated the miRNAs role as an antiviral agent against many diseases, including human immunodeficiency virus-1, 17 herpes simplex virus, 18 dengue, 19 influenza virus, 15 and hepatitis C virus. 20 To prevent and treat the highly pathogenic coronavirus with the help of the antiviral agent is important. As a result, it is highly recommended that new biological strategies for the treatment of viral diseases be created. 21 In the epithelial cells, the expression change of the host miRNAs has a role in the pathogenesis of chronic and severe acute respiratory tract infections. 22 Our recent studies have shown how the viral RNA stabilizes monomeric and dimeric subunits of the protein complex by suitable interactions that have been mimicked by screening compounds from various drug-approved databases, which show high inhibitory potential against viral mRNA. 1 This study computed any possible human miRNA targets for the SARS-2 (severe acute respiratory syndrome coronavirus-2) genome. It also emphasizes the host miRNAs and COVID-19 viral genome interaction that will help better understand the role of host pathogens and establish new antiviral therapy against COVID-19.

The complete genome sequence (NC 045512.2) of COVID-19 was obtained from the NCBI database to predict the pre-miRNAs sequence. A flowchart diagram of the entire theoretical analysis process is shown in (Figure 1 ) to classify the possible miRNAs.

To predict miRNAs hairpin precursors, the entire viral genome was scanned using a miRNA Fold web tool to find the hairpinstructured miRNA precursors to find the expected results (https:// evryrna.ibisc.univ-evry.fr/miRNAFold). miRNA fold is now devoted to discovering miRNA precursors in genomes on a wide scale and enables miRNA hairpin structures to be predicted rapidly and with high sensitivity. The scanned hairpins were visualized in the mRNA fold, whereas candidate miRNA precursor 69 sequences of possible hairpin-like forms were extracted. We filtered outputs using F I G U R E 1 Study design of human microRNA (miRNA) prediction on SARS-2 (COVID-19) viral genome configuration options to prevent bonafide pre-miRNAs structured hairpins with sliding window size (200), minimum hairpin size (30), the maximal thermodynamic value of hairpins (50), and percentage of verified features (95%).

For the identification of specific homologs, the sequences of the candidate viral miRNA precursors were compared among all host miRNAs using the miRBase database's SEARCH menu (http://www.mirbase. org/search.shtml). 12 In this phase of the research, we identified 18 sequences called potential miRNA precursors (hairpin-like structure) based on their highest sequence resemblance to human miRNAs.

The RNA hybrid (http://bibiserv2.cebitec.uni-bielefeld.de/rnahybrid/) web server was used to investigate the hybridization between viral (COVID-19) pre-miRNAs and possible human mature miRNAs. 23, 24 The RNAhybrid method was used to evaluate the effective hybridization between target host miRNA and viral pre-miRNA. RNAhybrid is a method for determining the minimum free energy (MFE) of long and short RNA hybridization and is commonly used to estimate miRNA targets.

To predict the top best viral pre-miRNAs secondary structures of COVID-19, the RNAfold online tools (http://rna.tbi.univie.ac.at/cgibin/RNAfold.cgi) were used. The RNAfold program predicts secondary structures of single-stranded RNA and DNA sequences. 25 An RNA sequence's MFE is the secondary structure that contains the minimum amount of free energy. A loop-based estimation model and the genetic algorithm method are used to predict such a structure. 26 The secondary structure of RNA can be disassembled into loops (internal and external) and external bases (bulges) in a unique manner. 

The PANTHER (Protein Analysis by Ancestral Relationships) classification system database (http://www.pantherdb.org) was used to classify the gene ontology of selected target genes involved in the miR-gene network and also to obtain insight into the product of the target genes molecular structure, biological mechanism, and cellular components. DisGeNET (https://www.disgenet.org/) database was used to figure out the associated genes with human diseases evidence via expert-curated collections, genome-wide interaction analyses, research literature, and animal models are all integrated into Dis-GeNET. 28 The DisGeNET scoring mechanisms include the use of various sources used (level of curation, organisms) and the data from different types of studies are considered for GDAs. In contrast, the score for VDAs is based on sources and literature analysis, and scores vary from 0 to 1.

The complete genome sequence of COVID-19 was acquired from the NCBI with ID (NC 045512.2). The sequenced COVID-19 genome is made up of a single positive-stranded RNA with a length of 29 811 nucleotides. We compared our genome sequence with other COVID-19 strains through the Clustalw multiple sequence alignment (MSA) program. The MSA results show that the sequence ID NC_045512.2 is highly conserved with different selected sequences (Data S1).

Prediction of COVID-19 viral genome pre-miRNA hairpins with their sequence length and score was obtained using miRNA fold computational web tools. A total of 69 probable viral pre-miRNA hairpins were considered as the potential hairpins with the maximum thermodynamic value of hairpin (50 J/mol) and perfect hairpin precursor length (>70 nt) for further analysis.

We employed the miRBase database to find the homologs of human miRNAs from the COVID-19 precursors. Every sequence of the viral pre-miRNA was searched for nucleotide resemblance among human miRNAs by using the human miRNA query from the miRBase database's SEARCH menu (http://www.mirbase.org/search.shtml). The search identified 18 potential viral pre-miRNA sequences of the 

After 

The secondary structure of viral pre-miRNAs was analyzed using the 3.6 | Disease association and network analysis HMDD (https://www.cuilab.cn/hmdd) was used to find out the host miRNA with the disease association, miR network,. This is a F I G U R E 2 Hybridization between host microRNAs (miRNAs) and viral precursor miRNAs (pre-miRNAs) using RNA hybrid program. Table 2 ). The predicted miR-gene network showed a strong association between specific genes (SDC4, SMU1, NAV2, and SPATA2). It is depicted to play a role in cell migration, RNA splicing, nervous system development,

tumor necrosis factor-mediated signaling pathway, and molecular adaptor activity (Figure 7) . We further performed STRING database search to identify the physical interaction among the four genes identified from HMDD analysis. Results showed that there were many other essential genes having interactions with these selected four genes involved in the various biological process like positive regulation of extracellular exosome assembly, exosomal secretion, catabolic process, cell migration, angiogenesis, etc., molecular function like, wnt signaling pathway, integrin binding, growth factor receptor binding, heparin-binding, and signaling receptor binding.

( Figure S1 ).

The PANTHER (Protein Analysis by Evolutionary Relationship) classification scheme (http://www.pantherdb.org) was to gain insight into the molecular structures, biological mechanisms, and cells of used to Table 3 ). The results from the DisGeNET database were filtered out for the respiratory tract disease associated with the identified four host genes. Gene SDC4 is involved in neoplasms of the lungs, respiratory tract diseases, and infections; NAV2 is involved in respiratory tract diseases, immune system diseases; SPATA2 is implicated in nonsmall cell lung carcinoma, primary malignancy of the lungs, and SMU1 is involved in cardiomyopathy, genetic, neonatal cancers and defects, neoplasms, and respiratory system disorders (Table 4) . F I G U R E 7 Network diagram showing the interaction between host microRNAs (miRNAs) and genes using mienturnet database reactions. From the results of the secondary structure of viral pre-miRNA sequence, we predict that the pre-miR-651 has the highly stable structure due to the MFE (ΔG = À24.40 kcal/mol), three internal loops, one hairpin loop, two bulges, and a minimal number of noncanonical base pairs with maximum base-pairing stems in comparison to other secondary structures ( Figure 4A ). For miRNA at equilibrium, the structure having the least free energy is the most stable. Similarly, the pre-miR-548-1d has two internal loops, one hairpin loop, three bulges, and a minimum number of non-canonical base-pairing and least number of stem base paring so, the pre-miR-548-1d is less stable than pre-miR-651 ( Figure 4B) . A similar trend is observed for the other pre-miRNAs and accordingly is arranged in the decreasing order of stability (Figure 4) . The viral pre-miRNA sequence's centroid structure is the secondary structure having the shortest base-pair distance.

Our results suggest that pre-miR-651 ( Figure 5A ) has the best centroid structure because this pre-miRNA structure showed minimum base-pair distance and has MFE and minimum thermodynamic ensemble (pf), which leads to higher structural stability as compared with other precursor secondary structures ( Figure 5A ). 36 (Table 3) . Further, STRING online database search of these four genes (SDC4, NAV2, SMU1, and SPATA2) suggested their roles in having primary interactions ( Figure S1 ) with various biological processes and also has the disease association link including the respiratory tract disease ( structure prediction results suggest that pre-miR-651 is a highly stable structure (ΔG = À24.40 kcal/mol MFE), the minimum frequency of ensemble, due to the maximum number of stem base pairing, which helps stabilize the structure.

The interaction analysis from the host miRNAs-viral mRNA might help in identifying the critical regions of the formed duplex secondary structure between the miRNA and mRNA. This type of duplex secondary structure with its high base-pair complementarity interactions will help understand the type of drug candidates needed to develop the new chemical entities or screening the approved drugs for repurposing as druggable candidates. Therefore, these findings not only help obtain insight into the structure-activity relationship of the viral pre-miRNAs and the host miRNAs to develop as antiviral agents but also provide information about the strong physical interactions among them that can inhibit the viral replication and transmission efficiently.

The clinical implications for the present treatment strategies for SARS-CoV-2 are in progress globally with the use of mRNA or viral vector based vaccines. However, the ability of SARS-CoV-2 variant generation is one of the major issue facing the clinical implications with the above vaccines. Therefore, the present study focus could provide effective solution due to the expression of host miRNAs efficiently targeting the pre-miRNAs of SARS-CoV-2 genome. This targeting approach of specific host miRNA expression could effectively consider any variant of pre-miRNAs of SARS-CoV-2 expressed in the host.

None.

JS was responsible for the execution, analysis, and writing of the manuscript; AR was responsible for the manuscript writting, NS was responsible for the manuscript writing, result analysis, and discussion;

AC was responsible for the manuscript editing and result analysis;

KLK was responsible for the study design; PKA conceived the study, design, analysis, writing and revising the manuscript.

Not required.

Data sharing not applicable to this article as no datasets were generated during the current study ORCID Pramod K. Avti https://orcid.org/0000-0001-5603-4523

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