Systemic In Silico Screening in Drug Discovery for Coronavirus Disease (COVID-19) with an Online Interactive Web Server

Antiparasitic nitazoxanide potentiates colistin against colistin-resistant Acinetobacter baumannii and Escherichia coli in vitro and in vivo

IMPORTANCE

Colistin is used as a last resort in many infections caused by multidrug-resistant Gram-negative bacteria; however, colistin-resistant (COL-R) is on the rise. Hence, it is critical to develop new antimicrobial strategies to overcome COL-R. We found that nitazoxanide (NTZ) combined with colistin showed notable synergetic antibacterial activity. These findings suggest that the NTZ/colistin combination may provide an effective alternative route to combat COL-R A. baumannii and COL-R Escherichia coli infections.

The Potential Protective Role of GS-441524, a Metabolite of the Prodrug Remdesivir, in Vaccine Breakthrough SARS-CoV-2 Infections

Cases of vaccine breakthrough, especially in variants of concern (VOCs) infections, are emerging in coronavirus disease (COVID-19). Due to mutations of structural proteins (SPs) (e.g., Spike proteins), increased transmissibility and risk of escaping from vaccine-induced immunity have been reported amongst the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Remdesivir was the first to be granted emergency use authorization but showed little impact on survival in patients with severe COVID-19. Remdesivir is a prodrug of the nucleoside analogue GS-441524 which is converted into the active nucleotide triphosphate to disrupt viral genome of the conserved non-structural proteins (NSPs) and thus block viral replication. GS-441524 exerts a number of pharmacological advantages over Remdesivir: (1) it needs fewer conversions for bioactivation to nucleotide triphosphate; (2) it requires only nucleoside kinase, while Remdesivir requires several hepato-renal enzymes, for bioactivation; (3) it is a smaller molecule and has a potency for aerosol and oral administration; (4) it is less toxic allowing higher pulmonary concentrations; (5) it is easier to be synthesized. The current article will focus on the discussion of interactions between GS-441524 and NSPs of VOCs to suggest potential application of GS-441524 in breakthrough SARS-CoV-2 infections.

Supplementary Information

The online version contains supplementary material available at 10.1007/s44231-022-00021-4.

Discovery of putative inhibitors against main drivers of SARS-CoV-2 infection: Insight from quantum mechanical evaluation and molecular modeling

SARS-CoV-2 triggered a worldwide medical crisis, affecting the world’s social, emotional, physical, and economic equilibrium. However, treatment choices and targets for finding a solution to COVID-19’s threat are becoming limited. A viable approach to combating the threat of COVID-19 is by unraveling newer pharmacological and therapeutic targets pertinent in the viral survival and adaptive mechanisms within the host biological milieu which in turn provides the opportunity to discover promising inhibitors against COVID-19. Therefore, using high-throughput virtual screening, manually curated compounds library from some medicinal plants were screened against four main drivers of SARS-CoV-2 (spike glycoprotein, PLpro, 3CLpro, and RdRp). In addition, molecular docking, Prime MM/GBSA (molecular mechanics/generalized Born surface area) analysis, molecular dynamics (MD) simulation, and drug-likeness screening were performed to identify potential phytodrugs candidates for COVID-19 treatment. In support of these approaches, we used a series of computational modeling approaches to develop therapeutic agents against COVID-19. Out of the screened compounds against the selected SARS-CoV-2 therapeutic targets, only compounds with no violations of Lipinski’s rule of five and high binding affinity were considered as potential anti-COVID-19 drugs. However, lonchocarpol A, diplacol, and broussonol E (lead compounds) were recorded as the best compounds that satisfied this requirement, and they demonstrated their highest binding affinity against 3CLpro. Therefore, the 3CLpro target and the three lead compounds were selected for further analysis. Through protein–ligand mapping and interaction profiling, the three lead compounds formed essential interactions such as hydrogen bonds and hydrophobic interactions with amino acid residues at the binding pocket of 3CLpro. The key amino acid residues at the 3CLpro active site participating in the hydrophobic and polar inter/intra molecular interaction were TYR54, PRO52, CYS44, MET49, MET165, CYS145, HIS41, THR26, THR25, GLN189, and THR190. The compounds demonstrated stable protein–ligand complexes in the active site of the target (3CLpro) over a 100 ns simulation period with stable protein–ligand trajectories. Drug-likeness screening shows that the compounds are druggable molecules, and the toxicity descriptors established that the compounds demonstrated a good biosafety profile. Furthermore, the compounds were chemically reactive with promising molecular electron potential properties. Collectively, we propose that the discovered lead compounds may open the way for establishing phytodrugs to manage COVID-19 pandemics and new chemical libraries to prevent COVID-19 entry into the host based on the findings of this computational investigation.

Using In Silico Bioinformatics Algorithms for the Accurate Prediction of the Impact of Spike Protein Mutations on the Pathogenicity, Stability, and Functionality of the SARS-CoV-2 Virus and Analysis of Potential Therapeutic Targets

Coronavirus disease 2019 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We have used bioinformatics to investigate seventeen mutations in the spike protein of SARS-CoV-2, as this mediates infection of human cells and is the target of most vaccine strategies and antibody-based therapies. Two mutations, H146Y and S221W, were identified as being most pathogenic. Mutations at positions D614G, A829T, and P1263L might also have deleterious effects on protein function. We hypothesized that candidate small molecules may be repurposed to combat viral infection. We investigated changes in binding energies of the ligands and the mutant proteins by assessing molecular docking. For an understanding of cellular function and organization, protein-protein interactions are also critical. Protein-protein docking for naïve and mutated structures of SARS-CoV-2 S protein was evaluated for their binding energy with the angiotensin-converting enzyme 2 (ACE2). These interactions might limit the binding of the SARS-CoV-2 spike protein to the ACE2 receptor or may have a deleterious effect on protein function that may limit infection. These results may have important implications for the transmission of SARS-CoV-2, its pathogenesis, and the potential for drug repurposing and immune therapies.

D3AI-CoV: a deep learning platform for predicting drug targets and for virtual screening against COVID-19

Target prediction and virtual screening are two powerful tools of computer-aided drug design. Target identification is of great significance for hit discovery, lead optimization, drug repurposing and elucidation of the mechanism. Virtual screening can improve the hit rate of drug screening to shorten the cycle of drug discovery and development. Therefore, target prediction and virtual screening are of great importance for developing highly effective drugs against COVID-19. Here we present D3AI-CoV, a platform for target prediction and virtual screening for the discovery of anti-COVID-19 drugs. The platform is composed of three newly developed deep learning-based models i.e., MultiDTI, MPNNs-CNN and MPNNs-CNN-R models. To compare the predictive performance of D3AI-CoV with other methods, an external test set, named Test-78, was prepared, which consists of 39 newly published independent active compounds and 39 inactive compounds from DrugBank. For target prediction, the areas under the receiver operating characteristic curves (AUCs) of MultiDTI and MPNNs-CNN models are 0.93 and 0.91, respectively, whereas the AUCs of the other reported approaches range from 0.51 to 0.74. For virtual screening, the hit rate of D3AI-CoV is also better than other methods. D3AI-CoV is available for free as a web application at http://www.d3pharma.com/D3Targets-2019-nCoV/D3AI-CoV/index.php, which can serve as a rapid online tool for predicting potential targets for active compounds and for identifying active molecules against a specific target protein for COVID-19 treatment.

COVID-19: A systematic review and update on prevention, diagnosis, and treatment

Since the rapid onset of the COVID-19 or SARS-CoV-2 pandemic in the world in 2019, extensive studies have been conducted to unveil the behavior and emission pattern of the virus in order to determine the best ways to diagnosis of virus and thereof formulate effective drugs or vaccines to combat the disease. The emergence of novel diagnostic and therapeutic techniques considering the multiplicity of reports from one side and contradictions in assessments from the other side necessitates instantaneous updates on the progress of clinical investigations. There is also growing public anxiety from time to time mutation of COVID-19, as reflected in considerable mortality and transmission, respectively, from delta and Omicron variants. We comprehensively review and summarize different aspects of prevention, diagnosis, and treatment of COVID-19. First, biological characteristics of COVID-19 were explained from diagnosis standpoint. Thereafter, the preclinical animal models of COVID-19 were discussed to frame the symptoms and clinical effects of COVID-19 from patient to patient with treatment strategies and in-silico/computational biology. Finally, the opportunities and challenges of nanoscience/nanotechnology in identification, diagnosis, and treatment of COVID-19 were discussed. This review covers almost all SARS-CoV-2-related topics extensively to deepen the understanding of the latest achievements (last updated on January 11, 2022).

The nsp15 Nuclease as a Good Target to Combat SARS-CoV-2: Mechanism of Action and Its Inactivation with FDA-Approved Drugs

The pandemic caused by SARS-CoV-2 is not over yet, despite all the efforts from the scientific community. Vaccination is a crucial weapon to fight this virus; however, we still urge the development of antivirals to reduce the severity and progression of the COVID-19 disease. For that, a deep understanding of the mechanisms involved in viral replication is necessary. nsp15 is an endoribonuclease critical for the degradation of viral polyuridine sequences that activate host immune sensors. This enzyme is known as one of the major interferon antagonists from SARS-CoV-2. In this work, a biochemical characterization of SARS-CoV-2 nsp15 was performed. We saw that nsp15 is active as a hexamer, and zinc can block its activity. The role of conserved residues from SARS-CoV-2 nsp15 was investigated, and N164 was found to be important for protein hexamerization and to contribute to the specificity to degrade uridines. Several chemical groups that impact the activity of this ribonuclease were also identified. Additionally, FDA-approved drugs with the capacity to inhibit the in vitro activity of nsp15 are reported in this work. This study is of utmost importance by adding highly valuable information that can be used for the development and rational design of therapeutic strategies.

Entrectinib-A SARS-CoV-2 Inhibitor in Human Lung Tissue (HLT) Cells

Since the start of the COVID-19 outbreak, pharmaceutical companies and research groups have focused on the development of vaccines and antiviral drugs against SARS-CoV-2. Here, we apply a drug repurposing strategy to identify drug candidates that are able to block the entrance of the virus into human cells. By combining virtual screening with in vitro pseudovirus assays and antiviral assays in Human Lung Tissue (HLT) cells, we identify entrectinib as a potential antiviral drug.

Discovery of Zafirlukast as a novel SARS-CoV-2 helicase inhibitor using in silico modelling and a FRET-based assay

The coronavirus helicase is an essential enzyme required for viral replication/transcription pathways. Structural studies revealed a sulphate moiety that interacts with key residues within the nucleotide-binding site of the helicase. Compounds with a sulphoxide or a sulphone moiety could interfere with these interactions and consequently inhibit the enzyme. The molecular operating environment (MOE) was used to dock 189 sulphoxide and sulphone-containing FDA-approved compounds to the nucleotide-binding site. Zafirlukast, a leukotriene receptor antagonist used to treat chronic asthma, achieved the lowest docking score at -8.75 kcals/mol. The inhibitory effect of the compounds on the SARS-CoV-2 helicase dsDNA unwinding activity was tested by a FRET-based assay. Zafirlukast was the only compound to inhibit the enzyme (IC50 = 16.3 µM). The treatment of Vero E6 cells with 25 µM zafirlukast prior to SARS-CoV-2 infection decreased the cytopathic effects of SARS-CoV-2 significantly. These results suggest that zafirlukast alleviates SARS-CoV-2 pathogenicity by inhibiting the viral helicase and impairing the viral replication/transcription pathway. Zafirlukast could be clinically developed as a new antiviral treatment for SARS-CoV-2 and other coronavirus diseases. This discovery is based on molecular modelling, in vitro inhibition of the SARS-CoV helicase activity and cell-based SARS-CoV-2 viral replication.

Drug Repurposing to Identify Nilotinib as a Potential SARS-CoV-2 Main Protease Inhibitor: Insights from a Computational and In Vitro Study

COVID-19, an acute viral pneumonia, has emerged as a devastating pandemic. Drug repurposing allows researchers to find different indications of FDA-approved or investigational drugs. In this current study, a sequence of pharmacophore and molecular modeling-based screening against COVID-19 Mpro (PDB: 6LU7) suggested a subset of drugs, from the Drug Bank database, which may have antiviral activity. A total of 44 out of 8823 of the most promising virtual hits from the Drug Bank were subjected to molecular dynamics simulation experiments to explore the strength of their interactions with the SARS-CoV-2 Mpro active site. MD findings point toward three drugs (DB04020, DB12411, and DB11779) with very low relative free energies for SARS-CoV-2 Mpro with interactions at His41 and Met49. MD simulations identified an additional interaction with Glu166, which enhanced the binding affinity significantly. Therefore, Glu166 could be an interesting target for structure-based drug design. Quantitative structural-activity relationship analysis was performed on the 44 most promising hits from molecular docking-based virtual screening. Partial least square regression accurately predicted the values of independent drug candidates' binding energy with impressively high accuracy. Finally, the EC50 and CC50 of 10 drug candidates were measured against SARS-CoV-2 in cell culture. Nilotinib and bemcentinib had EC50 values of 2.6 and 1.1 μM, respectively. In summary, the results of our computer-aided drug design provide a roadmap for rational drug design of Mpro inhibitors and the discovery of certified medications as COVID-19 antiviral therapeutics.

Hybrid In Silico Approach Reveals Novel Inhibitors of Multiple SARS-CoV-2 Variants

The National Center for Advancing Translational Sciences (NCATS) has been actively generating SARS-CoV-2 high-throughput screening data and disseminates it through the OpenData Portal (https://opendata.ncats.nih.gov/covid19/). Here, we provide a hybrid approach that utilizes NCATS screening data from the SARS-CoV-2 cytopathic effect reduction assay to build predictive models, using both machine learning and pharmacophore-based modeling. Optimized models were used to perform two iterative rounds of virtual screening to predict small molecules active against SARS-CoV-2. Experimental testing with live virus provided 100 (∼16% of predicted hits) active compounds (efficacy > 30%, IC50 ≤ 15 μM). Systematic clustering analysis of active compounds revealed three promising chemotypes which have not been previously identified as inhibitors of SARS-CoV-2 infection. Further investigation resulted in the identification of allosteric binders to host receptor angiotensin-converting enzyme 2; these compounds were then shown to inhibit the entry of pseudoparticles bearing spike protein of wild-type SARS-CoV-2, as well as South African B.1.351 and UK B.1.1.7 variants.

Natural Bioactive Molecules as Potential Agents Against SARS-CoV-2

In the past two decades, pandemics of several fatal coronaviruses have posed enormous challenges for public health, including SARS-CoV (2003), MERS-CoV (2012), and SARS-CoV-2 (2019). Among these, SARS-CoV-2 continues to ravage the world today and has lead to millions of deaths and incalculable economic damage. Till now, there is no clinically proven antiviral drug available for SARS-CoV-2. However, the bioactive molecules of natural origin, especially medicinal plants, have been proven to be potential resources in the treatment of SARS-CoV-2, acting at different stages of the viral life cycle and targeting different viral or host proteins, such as PLpro, 3CLpro, RdRp, helicase, spike, ACE2, and TMPRSS2. They provide a viable strategy to develop therapeutic agents. This review presents fundamental biological information on SARS-CoV-2, including the viral biological characteristics and invasion mechanisms. It also summarizes the reported natural bioactive molecules with anti-coronavirus properties, arranged by their different targets in the life cycle of viral infection of human cells, and discusses the prospects of these bioactive molecules for the treatment of COVID-19.

Ligand-based approach for predicting drug targets and for virtual screening against COVID-19

Discovering efficient drugs and identifying target proteins are still an unmet but urgent need for curing coronavirus disease 2019 (COVID-19). Protein structure-based docking is a widely applied approach for discovering active compounds against drug targets and for predicting potential targets of active compounds. However, this approach has its inherent deficiency caused by e.g. various different conformations with largely varied binding pockets adopted by proteins, or the lack of true target proteins in the database. This deficiency may result in false negative results. As a complementary approach to the protein structure-based platform for COVID-19, termed as D3Docking in our previous work, we developed in this study a ligand-based method, named D3Similarity, which is based on the molecular similarity evaluation between the submitted molecule(s) and those in an active compound database. The database is constituted by all the reported bioactive molecules against the coronaviruses, viz., severe acute respiratory syndrome coronavirus (SARS), Middle East respiratory syndrome coronavirus (MERS), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), human betacoronavirus 2c EMC/2012 (HCoV-EMC), human CoV 229E (HCoV-229E) and feline infectious peritonitis virus (FIPV), some of which have target or mechanism information but some do not. Based on the two-dimensional (2D) and three-dimensional (3D) similarity evaluation of molecular structures, virtual screening and target prediction could be performed according to similarity ranking results. With two examples, we demonstrated the reliability and efficiency of D3Similarity by using 2D × 3D value as score for drug discovery and target prediction against COVID-19. The database, which will be updated regularly, is available free of charge at https://www.d3pharma.com/D3Targets-2019-nCoV/D3Similarity/index.php.

Establishing an Analogue Based In Silico Pipeline in the Pursuit of Novel Inhibitory Scaffolds against the SARS Coronavirus 2 Papain-Like Protease

The ongoing coronavirus pandemic has been a burden on the worldwide population, with mass fatalities and devastating socioeconomic consequences. It has particularly drawn attention to the lack of approved small-molecule drugs to inhibit SARS coronaviruses. Importantly, lessons learned from the SARS outbreak of 2002-2004, caused by severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1), can be applied to current drug discovery ventures. SARS-CoV-1 and SARS-CoV-2 both possess two cysteine proteases, the main protease (Mpro) and the papain-like protease (PLpro), which play a significant role in facilitating viral replication, and are important drug targets. The non-covalent inhibitor, GRL-0617, which was found to inhibit replication of SARS-CoV-1, and more recently SARS-CoV-2, is the only PLpro inhibitor co-crystallised with the recently solved SARS-CoV-2 PLpro crystal structure. Therefore, the GRL-0617 structural template and pharmacophore features are instrumental in the design and development of more potent PLpro inhibitors. In this work, we conducted scaffold hopping using GRL-0617 as a reference to screen over 339,000 ligands in the chemical space using the ChemDiv, MayBridge, and Enamine screening libraries. Twenty-four distinct scaffolds with structural and electrostatic similarity to GRL-0617 were obtained. These proceeded to molecular docking against PLpro using the AutoDock tools. Of two compounds that showed the most favourable predicted binding affinities to the target site, as well as comparable protein-ligand interactions to GRL-0617, one was chosen for further analogue-based work. Twenty-seven analogues of this compound were further docked against the PLpro, which resulted in two additional hits with promising docking profiles. Our in silico pipeline consisted of an integrative four-step approach: (1) ligand-based virtual screening (scaffold-hopping), (2) molecular docking, (3) an analogue search, and, (4) evaluation of scaffold drug-likeness, to identify promising scaffolds and eliminate those with undesirable properties. Overall, we present four novel, and lipophilic, scaffolds obtained from an exhaustive search of diverse and uncharted regions of chemical space, which may be further explored in vitro through structure-activity relationship (SAR) studies in the search for more potent inhibitors. Furthermore, these scaffolds were predicted to have fewer off-target interactions than GRL-0617. Lastly, to our knowledge, this work contains the largest ligand-based virtual screen performed against GRL-0617.

Testing of the inhibitory effects of loratadine and desloratadine on SARS-CoV-2 spike pseudotyped virus viropexis

Currently, there is an urgent need to find a treatment for the highly infectious coronavirus disease (COVID-19). However, the development of a new, effective, and safe vaccine or drug often requires years and poses great risks. At this critical stage, there is an advantage in using existing clinically approved drugs to treat COVID-19. In this study, in vitro severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) spike pseudotyped viral infection experiments indicated that histamine H₁ antagonists loratadine (LOR) and desloratadine (DES) could prevent entry of the pseudotyped virus into ACE2-overexpressing HEK293T cells and showed that DES was more effective. Further binding experiments using cell membrane chromatography and surface plasmon resonance demonstrated that both antagonists could bind to ACE2 and that the binding affinity of DES was much stronger than that of LOR. Molecular docking results elucidated that LOR and DES could bind to ACE2 on the interface of the SARS-CoV-2-binding area. Additionally, DES could form one hydrogen bond with LYS31 but LOR binding relied on non-hydrogen bonds. To our knowledge, this study is the first to demonstrate the inhibitory effect of LOR and DES on SARS-CoV-2 spike pseudotyped virus viropexis by blocking spike protein-ACE2 interaction. This study may provide a new strategy for finding an effective therapeutic option for COVID-19.

In silico exploration of novel protease inhibitors against coronavirus 2019 (COVID-19)

The spread of SARS-CoV-2 has affected human health globally. Hence, it is necessary to rapidly find the drug-candidates that can be used to treat the infection. Since the main protease (M^pro) is the key protein in the virus's life cycle, M^pro is served as one of the critical targets of antiviral treatment. We employed virtual screening tools to search for new inhibitors to accelerate the drug discovery process. The hit compounds were subsequently docked into the active site of SARS-CoV-2 main protease and ranked by their binding energy. Furthermore, in-silico ADME studies were performed to probe for adoption with the standard ranges. Finally, molecular dynamics simulations were applied to study the protein-drug complex's fluctuation over time in an aqueous medium. This study indicates that the interaction energy of the top ten retrieved compounds with COVID-19 main protease is much higher than the interaction energy of some currently in use protease drugs such as ML188, nelfinavir, lopinavir, ritonavir, and α-ketoamide. Among the discovered compounds, Pubchem44326934 showed druglike properties and was further analyzed by MD and MM/PBSA approaches. Besides, the constant binding free energy over MD trajectories suggests a probable drug possessing antiviral properties. MD simulations demonstrate that GLU166 and GLN189 are the most important residues of M^pro, which interact with inhibitors.

An In-silico Screening Strategy to the Prediction of New Inhibitors of COVID-19 Mpro Protein

The coronavirus disease-2019 (COVID-19) was first recognized in Wuhan, China, and quickly spread worldwide. Between all proposed research guidelines, inhibition of the main protease (M^pro) protein of the virus will be one of the main strategies for COVID-19 treatment. The present work was aimed to perform a computational study on FDA-approved drugs, similar to piperine scaffold, to find possible M^pro inhibitors. Firstly, virtual screening studies were performed on a library of FDA-approved drugs (43 medicinal compounds, similar to piperine scaffold). Among imported 43 drugs to virtual screening, 34 compounds were extracted. Four top-ranked drugs in terms of the highest interactions and the lowest binding energy were selected for the IFD study. Among these selections, lasofoxifene showed the lowest IFD score (-691.743 kcal mol^-1). The stability of lasofoxifene in the COVID-19 M^pro protein active site was confirmed with 100 ns MD simulation. Lasofoxifene binding free energy was obtained -107.09 and -173.97 kcal mol^-1, using Prime MM-GBSA and g_mmpbsa methods, respectively. The identified lasofoxifene by the presented computational approaches could be a suitable lead for inhibiting M^pro protein and COVID-19 treatment.

Interaction analyses of SARS-CoV-2 spike protein based on fragment molecular orbital calculations

At the stage of SARS-CoV-2 infection in human cells, the spike protein consisting of three chains, A, B, and C, with a total of 3300 residues plays a key role, and thus its structural properties and the binding nature of receptor proteins to host human cells or neutralizing antibodies has attracted considerable interest. Here, we report on interaction analyses of the spike protein in both closed (PDB-ID: 6VXX) and open (6VYB) structures, based on large-scale fragment molecular orbital (FMO) calculations at the level of up to the fourth-order Møller–Plesset perturbation with singles, doubles, and quadruples (MP4(SDQ)). Inter-chain interaction energies were evaluated for both structures, and a mutual comparison indicated considerable losses of stabilization energies in the open structure, especially in the receptor binding domain (RBD) of chain-B. The role of charged residues in inter-chain interactions was illuminated as well. By two separate calculations for the RBD complexes with angiotensin-converting enzyme 2 (ACE2) (6M0J) and B38 Fab antibody (7BZ5), it was found that the binding with ACE2 or antibody partially compensated for this stabilization loss of RBD.

Visualized IFIE results seen from chain-B of spike protein.

Novel Small-Molecule Scaffolds as Candidates against the SARS Coronavirus 2 Main Protease: A Fragment-Guided in Silico Approach

The ongoing pandemic caused by the novel coronavirus has been the greatest global health crisis since the Spanish flu pandemic of 1918. Thus far, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in over 1 million deaths, and there is no cure or vaccine to date. The recently solved crystal structure of the SARS-CoV-2 main protease has been a major focus for drug-discovery efforts. Here, we present a fragment-guided approach using ZINCPharmer, where 17 active fragments known to bind to the catalytic centre of the SARS-CoV-2 main protease (SARS-CoV-2 M^pro) were used as pharmacophore queries to search the ZINC databases of natural compounds and natural derivatives. This search yielded 134 hits that were then subjected to multiple rounds of in silico analyses, including blind and focused docking against the 3D structure of the main protease. We scrutinised the poses, scores, and protein-ligand interactions of 15 hits and selected 7. The scaffolds of the seven hits were structurally distinct from known inhibitor scaffolds, thus indicating scaffold novelty. Our work presents several novel scaffolds as potential candidates for experimental validation against SARS-CoV-2 M^pro.