The COVID-19 pandemic, caused by SARS-CoV-2, highlighted the urgent need for effective therapeutic strategies. Drug repurposing has proven a valuable approach, accelerating the development of treatments. The SARS-CoV-2 M PRO, a cysteine protease essential for viral replication and transcription, is a particularly attractive drug target. It processes viral polyproteins at 11 conserved sites, generating 12 non-structural proteins. The enzyme's mechanism involves dimerization of two monomers (A and B), each comprising three domains. The catalytic site (S1') is located between domains I and II, involving the Cys145/His41 catalytic dyad. Other subsites (S1, S2, S3/S4) contribute to substrate binding. A potential allosteric site, involved in dimerization, is located between domains II and III. The high substrate specificity of M PRO, unlike any known human protease, makes it an ideal target for selective antiviral therapy. This research aimed to identify novel dual-binding site inhibitors of SARS-CoV-2 M PRO, targeting both the catalytic and dimerization regions to more effectively inhibit viral replication.

Extensive research has focused on targeting the SARS-CoV-2 M PRO for antiviral drug development. Numerous studies have utilized in silico methods, such as virtual screening and molecular docking, to identify potential inhibitors. Several studies have explored targeting the catalytic site, identifying various classes of inhibitors including α-ketoamides, and covalent inhibitors. However, targeting the allosteric dimerization site has been less explored, despite its potential to offer a broader spectrum of activity and resistance to mutations. This study aims to bridge this gap by focusing on the identification of dual-binding site inhibitors.

A hybrid virtual screening approach was employed, integrating ligand-based and structure-based methods. Initially, the DRUDIT Biotarget Predictor Tool (BPT) was used to screen an in-house database of approximately 10,000 heterocyclic structures. This ligand-based approach, using a template of the SARS-CoV-2 M PRO binding site, identified two clusters of benzo[b]thiophene and benzo[b]furan derivatives with a Drudit Affinity Score (DAS) above 0.8. The 24 selected compounds were then assessed for their ADME (Absorption, Distribution, Metabolism, Excretion) properties using SwissADME. Structure-based molecular docking studies, using induced fit docking (IFD), were performed on the catalytic site (PDB code 7VH8) to validate the ligand-based results and assess binding interactions. Principal Component Analysis (PCA) was then used to identify compounds with potential affinity for the allosteric dimerization site, using pelitinib as a reference. IFD simulations were subsequently performed at the dimerization site (PDB code 7AXM). Finally, molecular dynamic simulations were conducted to assess the stability of selected ligand-protein complexes.

The DRUDIT BPT identified ethyl 3-benzoylamino-5-[(1H-imidazol-4-yl-methyl)-amino]-benzo[b]thiophene-2-carboxylate (compound 1) and ethyl 3-benzoylamino-5-[(1H-imidazol-4-yl-methyl)-amino]-benzo[b]furan-2-carboxylate (compound 2) as promising candidates. SwissADME analysis indicated that most compounds met the criteria for bioactivity. Induced fit docking at the catalytic site confirmed the high affinity of several benzo[b]thiophene and benzo[b]furan derivatives, some even surpassing nirmatrelvir. Key interactions were observed with conserved amino acids in the S1, S1', S2, and S3/S4 subsites. PCA, based on molecular descriptors and using pelitinib as a reference, identified compounds 1b, c, g-i, l and 2a-c, g-i, l as potential dimerization site inhibitors. Subsequent IFD at the allosteric site revealed that compounds 1b, c, i, l and 2i, l exhibited high affinity for this site. Molecular dynamic simulations confirmed the stability of the complexes formed between the selected compounds and the protein.

This study successfully identified novel dual-binding site inhibitors of SARS-CoV-2 M PRO using a novel computational workflow. The compounds identified demonstrate promising binding affinities to both the catalytic and allosteric sites, suggesting a potential for enhanced efficacy and reduced risk of resistance development compared to single-site inhibitors. The results highlight the effectiveness of combining ligand-based and structure-based virtual screening techniques, coupled with multivariate analysis. The high conservation of amino acids in both binding pockets suggests that these inhibitors might retain activity against emerging SARS-CoV-2 variants. This approach presents a novel strategy for designing broad-spectrum antiviral agents.

This research presents a novel computational strategy for identifying dual-binding site inhibitors of SARS-CoV-2 M PRO. The identified compounds, 1b, c, i, l and 2i, l, show strong potential as dual inhibitors with favorable ADME properties. Future research should focus on in vitro and in vivo validation of these compounds, further optimizing their properties and exploring their potential against other coronaviruses. This work highlights the value of utilizing hybrid in silico methods for efficient and cost-effective drug discovery.

The study is limited by its in silico nature. Experimental validation is crucial to confirm the predicted binding affinities and inhibitory activities. The accuracy of the in silico predictions relies on the quality of the protein structures and force fields used. Furthermore, the study did not explore potential off-target effects of the identified compounds.