| Literature DB >> 33986405 |
Syed Hani Abidi1, Nahlah Makki Almansour2, Daulet Amerzhanov3, Khaled S Allemailem4, Wardah Rafaqat5, Mahmoud A A Ibrahim6, Philip la Fleur3, Martin Lukac7, Syed Ali8.
Abstract
As the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic engulfs millions worldwide, the quest for vaccines or drugs against the virus continues. The helicase protein of SARS-CoV-2 represents an attractive target for drug discovery since inhibition of helicase activity can suppress viral replication. Using in silico approaches, we have identified drugs that interact with SARS-CoV-2 helicase based on the presence of amino acid arrangements matching binding sites of drugs in previously annotated protein structures. The drugs exhibiting an RMSD of ≤ 3.0 Å were further analyzed using molecular docking, molecular dynamics (MD) simulation, and post-MD analyses. Using these approaches, we found 12 drugs that showed strong interactions with SARS-CoV-2 helicase amino acids. The analyses were performed using the recently available SARS-CoV-2 helicase structure (PDB ID: 5RL6). Based on the MM-GBSA approach, out of the 12 drugs, two drugs, namely posaconazole and grazoprevir, showed the most favorable binding energy, - 54.8 and - 49.1 kcal/mol, respectively. Furthermore, of the amino acids found conserved among all human coronaviruses, 10/11 and 10/12 were targeted by, respectively, grazoprevir and posaconazole. These residues are part of the crucial DEAD-like helicase C and DEXXQc_Upf1-like/ DEAD-like helicase domains. Strong interactions of posaconazole and grazoprevir with conserved amino acids indicate that the drugs can be potent against SARS-CoV-2. Since the amino acids are conserved among the human coronaviruses, the virus is unlikely to develop resistance mutations against these drugs. Since these drugs are already in use, they may be immediately repurposed for SARS-CoV-2 therapy.Entities:
Year: 2021 PMID: 33986405 PMCID: PMC8119689 DOI: 10.1038/s41598-021-89724-0
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Protein and domain classification. Conserved domains in the SARS-CoV-2 structure were mapped using the NCBI Conserved Domain Search (CDD) tool v3.19. The SARS-CoV-2 helicase was found to be a DNA2 superfamily helicase with two significant domains: DEAD-like helicase C (spanning amino acids 323–592) and DEXXQc_Upf1-like (spanning amino acids 272–443), containing Walker A motif (GTGKSH) at N-terminus that is involved in ATP binding. Two additional functional domains ZBD_cv_Nsp13-like (spanning amino acids 1–95) and 1B_cv_Nsp13-like (spanning amino acids 150–228) were also found in the sequence. (note: the figure is an original image generated by CDD v3.19 tool).
Domain architecture conservation in viruses.
| No | Identifier | Description | Organism |
|---|---|---|---|
| 1 | ACU31046 | Helicase, partial | Bat SARS-CoV Rs806/2006 |
| 2 | YP_008439223 | nsp13 | Bat coronavirus CDPHE15/USA/2006 |
| 3 | YP_459942 | nsp13 | Human coronavirus HKU1 |
| 4 | NP_742139 | Coronavirus nsp10 (MB, NTPase/HEL) | Bovine coronavirus |
| 5 | ABB77060 | Helicase, partial | Pipistrellus bat coronavirus HKU5 |
| 6 | ABB77058 | Helicase, partial | Pipistrellus bat coronavirus HKU5 |
| 7 | ABB77061 | Helicase, partial | Bat coronavirus HKU6 |
| 8 | ABB77050 | Helicase, partial | Rhinolophus bat coronavirus HKU2 |
| 9 | ABB77053 | Helicase, partial | Tylonycteris bat coronavirus HKU4 |
| 10 | ABB77054 | Helicase, partial | Tylonycteris bat coronavirus HKU4 |
| 11 | ABB77057 | Helicase, partial | Pipistrellus bat coronavirus HKU5 |
| 12 | ABB77056 | Helicase, partial | Pipistrellus bat coronavirus HKU5 |
| 13 | ABB77051 | Helicase, partial | Rhinolophus bat coronavirus HKU2 |
| 14 | ABB77052 | Helicase, partial | Tylonycteris bat coronavirus HKU4 |
| 15 | ABB77055 | Helicase, partial | Tylonycteris bat coronavirus HKU4 |
| 16 | NP_839966 | Putative coronavirus nsp10 (MB, NTPase/HEL) | Porcine epidemic diarrhea virus |
| 17 | YP_209240 | nsp13; zinc-binding domain and helicase | Murine hepatitis virus strain JHM |
| 18 | ABD15361 | HELICASE, partial | Miniopterus bat coronavirus HKU8 |
| 19 | YP_009555254 | nsp10 | Human coronavirus OC43 |
| 20 | ABO88148 | Helicase, partial | Bat coronavirus Anhui/911/2005 |
| 21 | ABG11967 | Helicase, partial | Bat coronavirus (BtCoV/A434/2005) |
| 22 | ABG11968 | HELICASE, partial | Bat coronavirus A515/2005 |
| 23 | YP_009047224 | nsp13 protein | Middle East respiratory syndrome-related coronavirus |
| 24 | NP_828870 | nsp13-pp1ab (ZD, NTPase/HEL) | Severe acute respiratory syndrome-related coronavirus |
| 25 | ABG11969 | Helicase, partial | Bat coronavirus A527/2005 |
| 26 | ABG11966 | Helicase, partial | Bat coronavirus (BtCoV/355A/2005) |
| 27 | 5WWPA | Chain A, Crystal Structure Of Middle East Respiratory Syndrome Coronavirus Helicase (MERS-CoV Nsp13) | Human betacoronavirus 2c EMC/2012 |
| 28 | 5WWPB | Chain B, Crystal Structure Of Middle East Respiratory Syndrome Coronavirus Helicase (MERS-CoV Nsp13) | Human betacoronavirus 2c EMC/2012 |
CDART and SPARCLE tools were used to identify sequences sharing of domain architecture with our query (SARS-CoV-2 helicase) sequence. The search was refined to identify only human virus sequences, identified by NCBI identifier in column 2, which are shown in the Table. The Table also describes the nature of protein in all the shortlisted sequences and the organism to which they belong.
Figure 2Validation of structure and docking strategy: (A) Structure of SARS-CoV-2 helicase used in the study, (B) Ramachandran plots for SARS-CoV-2 helicase structure (PDB ID: 5RL6) used in the study, and (C) Docking strategy was validated by re-docking a previously published inhibitor ITMN-3479 on its receptor. Poses of ligand bound to the receptor generated after docking in our study (left, ligand, and protein are shown in red and dark grey, respectively) and retrieved from PDB (right; ligand and protein are shown in pink and green, respectively) are shown, while the bottom panel shows amino acid interactions reported for each ligand and observed in our study.
Figure 32D representations of the predicted binding modes and scores of the investigated twelve drugs inside the active site of the SARS-CoV-2 helicase.
Figure 4Calculated MM-GBSA binding energies for the investigated drugs as SARS-CoV-2 helicase inhibitors.
MM-GBSA binding energies decomposition for the top two investigated drugs in complex with SARS-CoV-2 helicase through the MD course of 100 ns.
| Drug | Estimated MM-GBSA binding energy (kcal/mol) | ||||||
|---|---|---|---|---|---|---|---|
| ∆ | ∆ | ∆ | ∆ | ∆ | ∆ | ∆ | |
| Posaconazole | − 77.9 | − 24.6 | 56.8 | − 9.1 | − 99.8 | 47.7 | − 54.8 |
| Grazoprevir | − 68.7 | − 28.4 | 56.7 | − 8.7 | − 96.9 | 48.0 | − 49.1 |
Figure 5Evaluated MM-GBSA binding energy per frame for posaconazole (in black) and grazoprevir (in red) towards SARS-CoV-2 helicase throughout 100 ns MD simulation.
Hydrogen bonds exhibited between the key residues and the most promising drugs against SARS-CoV-2 helicase.
| Drug | Acceptor | Donor | Distance (Å)a | Angle (°)a | Occupied (%)b |
|---|---|---|---|---|---|
| Posaconazole | ASP315@OD1 | Posaconazole597@O2-H41 | 2.7 | 164 | 95.6 |
| Grazoprevir | LEU412@O | Grazoprevir597@N4-H48 | 2.8 | 161 | 93.9 |
aThe hydrogen bonds are inspected by the acceptor–donor atom distance of < 3.5 Å and acceptor-H-donor angle of > 120°.
bOccupancy is employed to estimate the stability and strength of the hydrogen bond.
Figure 6Root mean square deviation (RMSD) of the backbone atoms from the initial structure for posaconazole (in black) and grazoprevir (in red) with the SARS-CoV-2 helicase over 100 ns MD simulations.
Figure 7Sequence alignment of known human coronaviruses sharing helicase domain architecture: Multiple sequence alignment (ranging from amino acid 3–596, numbered according to their position in the helicase protein) was performed employing ‘Clustal W’. Conserved residues/sites are highlighted in black color, residues conserved in two or more sequences are shown in black font, while differences are shown in grey font. Publication quality alignment was prepared using the ENDscript server[45].