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. 2023 Feb 28;251:115226. doi: 10.1016/j.ejmech.2023.115226

Korupensamine A, but not its atropisomer, korupensamine B, inhibits SARS-CoV-2 in vitro by targeting its main protease (Mpro)

Ahmed M Sayed a, Alyaa Hatem Ibrahim b, Nasir Tajuddeen c, Jürgen Seibel d, Jochen Bodem e, Nina Geiger e, Kathrin Striffler e, Gerhard Bringmann d,∗, Usama Ramadan Abdelmohsen f,g,∗∗
PMCID: PMC9972725  PMID: 36893625

Abstract

By combining docking and molecular dynamics simulations, we explored a library of 65 mostly axially chiral naphthylisoquinoline alkaloids and their analogues, with most different molecular architectures and structural analogues, for their activity against SARS-CoV-2. Although natural biaryls are often regarded without consideration of their axial chirality, they can bind to protein targets in an atroposelective manner. By combining docking results with steered molecular dynamics simulations, we identified one alkaloid, korupensamine A, that atropisomer-specifically inhibited the main protease (Mpro) activity of SARS-CoV-2 significantly in comparison to the reference covalent inhibitor GC376 (IC50 = 2.52 ± 0.14 and 0.88 ± 0.15 μM, respectively) and reduced viral growth by five orders of magnitude in vitro (EC50 = 4.23 ± 1.31 μM). To investigate the binding pathway and mode of interaction of korupensamine A within the active site of the protease, we utilized Gaussian accelerated molecular dynamics simulations, which reproduced the docking pose of korupensamine A inside the active site of the enzyme. The study presents naphthylisoquinoline alkaloids as a new class of potential anti-COVID-19 agents.

Keywords: Alkaloids, Natural products, Naphthylisoquinolines, SARS-CoV-2, Mpro, Steered molecular dynamics

Graphical abstract

Image 1

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1. Introduction

Since the first identified cases of the greatly contagious coronavirus disease 2019 (COVID-19) in December 2019, the world has been facing a critical fight against this newly discovered disease, with more than 622 million diagnosed cases and more than 6.5 million deaths up till November 2022 [1,2]. The COVID-19 pandemic is caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [3], triggering an acute disease that can eventually result in respiratory failure and death [4]. The SARS-CoV-2 infection has a high transmission rate but a relatively low death rate (1.0–3.5%), except for older people with other comorbidities. Severe pneumonia is observed in 15–20% of the infected people, and 5–10% of the patients require critical-care services [5,6]. SARS-CoV-2 is characterized by a spherical morphology with spike projections on its surface. The spike glycoprotein of the virus controls its entry into the human host cell [7]. SARS-CoV-2 infects lung type II alveolar cells, which may explain the severe alveolar damage during the infection [8]. Although a number of vaccines against SARS-CoV-2 have been successfully developed and administered [9,10], the world is still lacking an effective antiviral treatment against the disease [11].

Medical drugs currently in use are, so far, remdesivir, an antiviral agent that demonstrated benefits in decreasing the rate and the duration of hospitalization [12,13], and dexamethasone, a broad-spectrum anti-inflammatory drug offering assistance to patients with respiratory failure requiring respiratory support through the inhibition of a cytokine storm [14,15]. Also, nirmatrelvir, an orally active 3C-like protease inhibitor in combination with ritonavir, also known as paxlovid, is an antiviral drug against COVID-19 [16].

SARS-CoV-2 contains several polypeptides that promote proteolytic breakdown to produce 20 additional proteins during their lifecycle; one of them is the main protease (Mpro), which is essential for virus replication [17]. It consists of 306 amino acid residues and resembles the Mpro of SARS-CoV in structure and sequence [11,18,19]. This essential protease is a dimer, and mutations that prevent its conserved dimerization greatly reduce its catalytic activity. There are three domains in each monomer (domains I-III), of which domains I and II form the catalytic binding pocket, and domain III is responsible for enzyme dimerization [20,21]. The functional Mpro must have a conserved HIS-41-CYS-145 catalytic dyad in its active site. As a result, the catalytic activity of the enzyme will degenerate to the point where it is no longer functional if these catalytic residues are altered [22]. Several non-competitive inhibitors have been reported to form covalent bonds with CYS-145 like e.g., nirmatrelvir, ensiltrelvir, narlaprevir, and boceprevir, but there has been much less research into competitive non-covalent inhibitors [23,24]. Therefore, efforts have focused on investigating the main protease of that virus, to discover new specific non-covalent inhibitors against COVID-19 [7,25]. For more details on the discovery of inhibitors of various SARS-CoV-2 proteins, including Mpro, see Refs. [[26], [27], [28]].

A particularly interesting – and stereochemically intriguing – group of natural products are the naphthylisoquinoline (NIQ) alkaloids like korupensamine A (1a, see Fig. 1 ) [29]. They are composed of a naphthalene and an isoquinoline moiety. Following the principle of phenol-oxidative coupling, the two molecular portions are joined together in different ways, always ortho or para to oxygen functions [30,31]. These coupling types determine the molecular shapes of the alkaloids; Fig. 1 shows a selection of differently coupled NIQs, with representatives linked via the 5,8′-positions (like in compounds 1a/1b-4), via 5,1' (NIQs 5, 6, and ent-6), 7,8' (compound 7), or 7,1' (alkaloids 8 and 9). NIQ alkaloids are chiral compounds, characterized by the presence of stereogenic centers and a usually likewise chiral C,C- or N,C-axis between the two molecular moieties, the isoquinoline and the naphthalene portions. Due to the existence of more or less bulky ortho-substituents, most of these alkaloids show the phenomenon of hindered rotation about that central biaryl axis, which – in most cases - leads to rotationally stable atropisomers [[30], [31], [32], [33]]. Atropisomerism as an important structural feature of these alkaloids constitutes a synthetic challenge for their directed, stereoselective production that has been addressed in numerous elegant total syntheses [34,35]. One motivation for these synthetic efforts is the fact that, depending on their individual structures, naphthylisoquinoline alkaloids exhibit pronounced anti-malarial [32,[36], [37], [38], [39]], anti-trypanosomal [30,32,40], anti-leishmanial [31,32,[40], [41], [42], [43]], anti-bacterial [32,44], anti-fungal [32], larvicidal [45], molluscicidal [46,47], insecticidal [48,49], antibabesial [50], or cytotoxic activities against leukemia [51] and various cancer cell lines [[52], [53], [54], [55]]. Moreover, some dimeric naphthylisoquinolines, like michellamine B [56] (for the structure, see Table S1), show potent antiviral activities; they display anti-HIV effects by inhibition of certain viral enzymes like, for instance, reverse transcriptases (RTs) of both HIV type 1 and 2, as well as human alpha and beta DNA polymerases. Additionally, they can interfere with the late stages of the virus replication cycle by inhibiting cellular fusion and syncytium formation [[56], [57], [58], [59]].

Fig. 1.

Fig. 1

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Structures of the eleven out of 65 selected top-scoring compounds with different molecular shapes retrieved from the docking step, among them 5,8′-coupled alkaloids (compounds 1a/1b-4) as well as representatives with 5,1’- (5, 6, and ent-6), 7,8’- (7), or 7,1′-axes (8, 9).

Scientists have embarked on developing an effective and safe treatment for COVID-19 [26], which stimulated us to conduct the present study to search for new drug leads against SARS-CoV-2 infection. In this paper, we describe the first investigation of a library of structurally most different mono- and dimeric NIQ alkaloids and selected structural analogues for their activity against SARS-CoV-2. Additionally, we investigated an integrated docking-MDS (molecular dynamics simulations) approach for speeding up and improving the selection of potentially active compounds among a group of closely related structures.

2. Results and discussion

2.1. General approach

In the frame of our continued search for potential anti-SARS-CoV-2 therapeutics [21,[60], [61], [62], [63], [64]], we investigated a small library of bioactive NIQs in the quest for inhibitors of the Mpro of SARS-CoV-2. Most of the compounds of this library (53 out of 65 structures) are atropisomerically well-defined biaryls (Table S1). Since atropisomers are stereoisomers resulting from impeded rotation about a single bond, their structures are intrinsically less flexible than those of the corresponding freely rotating conformers, and hence they are of lower entropy. Drugs with lower entropy are likely to have a higher affinity for receptors and enzymes, as the binding process will result in less loss of entropy. From this point, we started a molecular docking-based screening of the NIQ library against the structure of the Mpro of SARS-CoV-2 to find possible binders and, thus, potential inhibitors.

2.2. Docking-based screening

At the beginning of the docking step, we validated the docking protocol by AutoDock Vina [65], re-docking the co-crystallized ligands of two previously reported [66,67] SARS-CoV-2 Mpro structures (PDB ID: 7DPP and 7LTJ). The resulting top-scoring docking poses of these inhibitors aligned with the co-crystallized ones with acceptable root-mean-square deviation (RMSD) values of 1.26 Å and 0.89 Å, respectively.

The modeled structures of the compounds of the library were prepared and docked into the active site of Mpro using the AutoDock Vina software [65]. Since all of the compounds in the used library contained basic - secondary or tertiary - amino functions, we also investigated the protonated forms of the compounds for the docking step. AutoDock Vina does not take steric hindrance into consideration during the docking process, where it makes the structures of the molecules free to rotate independently of the energetics of the whole molecules. For this reason, the resulting poses for each structure in the library were filtered according to the correct and low-energy conformations. A binding score of −7 kcal/mol was another filter criterion for selection, according to which the structures and poses of lower scores were neglected.

As a result, 11 out of the 65 initially considered structures were selected as top candidates for the subsequent in silico and in vitro testing (Figs. 1 and 2A ). It is worth noting that all generated poses for each of the top-scoring structures had almost the same binding mode. They aligned perfectly with each other, with a low RMSD value of 0.947 Å. This observation can be attributed to the low flexibility of the docked structures, where the number of available conformations that can generate different poses was limited. Such a uniformity of the docking poses indicated that the top-ranked pose of each docked structure was likely to be the correct one. However, further refinement, based on molecular dynamics simulation, was required, particularly the calculation of ΔG binding for each generated pose. This docking-based step managed to filter out ancistrocladine (docking score = −6.7 kcal/mol; for the structure, see Table S1) from its atropisomer, hamatine (6) (−8.2 kcal/mol), while it was not able to discriminate between the atropo-diastereomeric alkaloids korupensamine A (1a) and korupensamine B (1b), where both structures got the same score (−7.9 kcal/mol).

Fig. 2.

Fig. 2

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(A) Score distribution of the docked structures in the NIQ library against the Mpro of SARS-CoV-2. Structures with docking scores < -7 kcal/mol (17.5%) were selected for validation by MDS and ΔGbinding calculation. (B) Docking scores in comparison with the ΔGbinding values of the top-scoring compounds selected from the docking step, along with those of the co-crystallized inhibitors YD1 and myricetin. Green arrows indicate compounds that were selected for in vitro antiviral testing.

2.3. ΔGbinding-based refinement

Using the alchemical Free Energy Perturbation (FEP) method [68], we then determined the ΔG binding for the top candidates. By this procedure, ΔG binding values were extracted by running a series of MDS experiments. The 11 selected structures (Fig. 1) exhibited ΔG binding values ranging from −5.38 to −8.85 kcal/mol (Figs. 1 and 2B), indicating good affinities towards the active site of Mpro and, in turn, potential antiviral activity against SARSCoV-2. Based on the binding affinity values, it was hard to discriminate between these selected structures regarding their potential activity. Moreover, the two atropo-diastereomeric alkaloids korupensamine A (1a) and korupensamine B (1b), possessing the same gross structure, showed no significant difference in the calculated ΔG binding values (ΔΔG binding = −1.5 kcal/mol, see Fig. 1). Such a minor difference was not large enough to prefer one atropisomer over the other. This was not the case with the second pair of atropisomers investigated, ancistrocladine (for the structure, see Table S1) and hamatine (6), whose calculated ΔG binding values were significantly different (−3.88 kcal/mol and −7.23 kcal/mol, respectively; hence ΔΔG binding = −3.35 kcal/mol).

2.4. Steered molecular dynamics simulation

For this reason, we present herein the advantage of using steered molecular dynamics (SMD) in the discrimination between related congeners in terms of their affinity towards the active site of Mpro, by the determination of their relative binding affinity.

To do so, the top-ranked docking poses for each structure of the previously selected 11 compounds alongside the co-crystallized inhibitors (myricetin and YD1) were prepared and subjected to a number of SMD runs, where an external force was applied to each structure to pull it out of the Mpro active pocket, and hence, these applied forces can be traced over the course of the steering simulation.

Remarkably, the force needed to unbind korupensamine A (compound 1a, 1283 pN) was comparable to those needed to unbind the previously reported co-crystallized inhibitors myricetin and YD (1522 pN and 1323 pN, respectively). In addition, their steering force profiles clustered together away from those of all of the remaining structures, including the structurally so closely related korupensamine B (1b). The unbinding forces of those other structures did not exceed 480 pN (Fig. 3 A and B).

Fig. 3.

Fig. 3

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(A) Comparison of the unbinding force profiles of the selected 11 structures shown in Fig. 1, alongside that of the co-crystallized inhibitors (myricetin and YD1; co-crystallized ligands 1 and 2, respectively). The plots show the resulting mean values from averaging the force profiles from three different SMD runs (n = 3) for each structure. (B) Unbinding force profiles of korupensamine A (1a) versus its atropisomer korupensamine B (1b), showing the significant difference in the relative affinity of the two structures toward the active site of Mpro. (C) The golden-yellow arrow indicates the pulling direction for the ligand-unbinding pathway.

2.5. Atropo-selective Mpro inhibitory activity of korupensamine A (1a) in vitro

In vitro validation on the Mpro activity assay supported these findings (Fig. 4 ), where korupensamine A (1a) suppressed the catalytic activity of the enzyme in a dose-dependent manner, with an IC50 value of 2.53 ± 0.138 μM (K i = 1.42 ± 0.12 μM), while its atropo-diastereomer, korupensamine B (1b), i.e., with the same constitution as 1a, and possessing the same absolute configuration at both stereocenters, differing only by the axial configuration, was inactive up to 50 μM (IC50 = 71.89 ± 0.49 μM).

Fig. 4.

Fig. 4

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Inhibition of the activity of the SARS-CoV-2 Mpro by korupensamine A (1a) and korupensamine B (1b) at increasing concentrations of the inhibitor. The enzyme activity is reduced by 50% at a korupensamine A (1a) concentration of 2.52 ± 0.14 μM (A) in comparison to that of korupensamine B (1b) at a concentration of 71.89 ± 0.49 μM (B) and that of the reference inhibitor GC376 [70] at a concentration of 0.88 ± 0.15 μM (C).

These enzyme inhibitory results clearly showed the superior affinity of korupensamine A (1a) over its atropisomer korupensamine B (1b) – and over all of the other remaining compounds. This result emphasized, once again, the impact of axial chirality for the bioactivity of rotationally hindered biaryl agents in general, and in this particular case, the pronounced structure-specificity of the inhibitory activity of korupensamine A (1a). Additionally, the results highlighted the efficacy of the SMD approach in the differentiation between atropisomers in terms of their biomolecular interactions.

SMD had previously been reported to be an effective method of discerning between flavonoids in terms of their enzyme inhibition activity [69]. Here, once again, this fast and reliable in silico method proved its ability in pointing out the active anti-SARS-CoV-2 representative among a group of structurally most similar potential candidates.

2.6. Dynamic mode of interaction

To get some insight into the dynamic binding interactions of korupensamine A (1a) inside the active site of Mpro in comparison to those of its atropo-diastereomer (i.e., korupensamine B, 1b), the selected poses of both compounds were subjected to 100-ns MDS runs. The dynamic interactions of the two structures were then extracted and analyzed (see Fig. 5 ). As shown in Fig. 5D, the binding stability of the two compounds inside the active site of the enzyme was comparable to an average RMSDs of 2.43 Å and 3.72 Å for korupensamines A (1a) and B (1b), respectively. On the one hand, both structures formed stable H-bonds with GLY-143 over the course of the simulation (Fig. 5A and B), but, on the other hand, only korupensamine A (1a) formed three additional stable H-bonds with SER-144, HIS-163, and ARG-188, while only korupensamine B (1b) established another single H-bond with THR-190. Moreover, korupensamine A (1a) had stable hydrophobic interactions with MET-165 and CYS-145, while korupensamine B (1b) revealed a single stable hydrophobic interaction with MET-49. Accordingly, korupensamine A (1a) exhibited thermodynamically more stable interactions inside the Mpro active site than its atropisomer, korupensamine B (1b). This explains why much more force was required to steer 1a out of the active site of the enzyme than the one needed in the case of 1b (Fig. 3B). Alignment of the structure of korupensamine A (1a) with that of the reference inhibitor GC376 (Fig. 5C) indicated that both structures have four common hydrophilic interactions (i.e., H-bonds) with GLY-143, SER-144, HIS-163, and ARG-188. Accordingly, H-bonding to these residues might be essential for good binding and inhibition of the Mpro of SARS CoV-2.

Fig. 5.

Fig. 5

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Ligand-protein interactions extracted from the 100-ns long MDS experiments of (A) korupensamine A (1a) and (B) korupensamine B (1b). 3D binding mode of korupensamine A (1a, in blue) in alignment with the reference inhibitor GC376 (brick-red structures) inside the active site of Mpro (C). The cyan-colored amino acid residues interact with both structures (i.e., korupensamine A and GC376), while white-colored amino acid residues interact with GC376 only. RMSDs of korupensamines A (1a) and B (1b) over the course of their MDS runs (D). Colored arrows in (A) and (B) indicate the percentage of interaction with each amino acid residue during the MDS runs.

2.7. Gaussian accelerated molecular dynamics (GaMD) simulations

In order to explore the binding pathway of korupensamine A (1a) to the active site of Mpro, three independent Gaussian accelerated molecular dynamics simulations (GaMD) were carried out. In each 400-ns long simulation, five replicates of the structure of korupensamine A (1a) were placed in the solvent box at least 20 Å away from the modeled Mpro structure. In one of the three simulations, ligand binding was observed after 115.92 ns and remained stable inside the Mpro active site until the end of the simulation (Fig. 6 A). Interestingly, the final binding state (Fig. 6B) was almost identical to that of the top-scoring docking pose selected earlier (RMSD = 1.63 Å), indicating that this binding pose is the most likely one.

Fig. 6.

Fig. 6

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(A) Binding event of korupensamine A (1a) with the Mpro active site observed in GaMD simulation after 115.92 ns (the green arrow indicates the beginning of the binding event). (B) Structure alignment of the docking pose of korupensamine A (1a, orange structure) on its most populated structure after its binding inside the active site of Mpro during the GaMD simulation (blue structure). RMSD value between the two states = 1.63 Å. A video showing the binding event of korupensamine A (1a) inside the active site of Mpro can be found on the Zenodo website: https://zenodo.org/record/7312007#.Y35sVXbP2M9.

Additionally, the four amino acid residues that had earlier been found to interact with korupensamine A (1a) via H-bonding (GLY-143, SER-144, HIS-163, and ARG-188) were also the interacting ones upon korupensamine A binding.

2.8. Korupensamine A (1a) inhibits SARS-CoV-2 in cell culture

Due to a quantity limitation, we selected five out of the top potentially active 11 alkaloids (Figs. 1 and 2B), along with another three compounds predicted to be inactive - the dimeric alkaloids michellamine A, which is the 6′,6″-dimer of korupensamine A (1a), michellamine B, i.e. the mixed dimer of korupensamines A (1a) and B (1b), and plumbagin, the oxidized naphthalene part of the presented NIQs (for the structures, see Table S1) - for in vitro antiviral testing against SARS-CoV-2. Surprisingly, only korupensamine A (1a) was active against SARS-CoV-2, it reduced the viral replication at 30 μM by five orders of magnitude (EC50 = 4.23 ± 1.31 μM; CC50 = 35.1 μM) (Fig. S2). From this observation it can be concluded that docking and ΔG binding calculation were good in predicting active compounds, but not sufficient to discriminate between compounds of convergent scores and between atropisomers, here korupensamine A (1a) versus korupensamine B (1b), whereas SMD demonstrated its efficacy in identifying the one anti-SARS-CoV-2 agent from of a pool of structurally similar compounds.

3. Conclusion

Understanding the interactions between ligands and proteins is essential for a rational structure-based drug design. In this work, several methods combining docking and MDS (molecular docking simulations) have been utilized to investigate the mode of interaction of pharmaceutically relevant complexes in the field of axially chiral naphthylisoquinoline (NIQ) alkaloids and their analogues. To identify potential ligands for the SARS-CoV-2 Mpro, we used docking-based virtual screening in conjunction with ΔG binding calculations to examine a library of 65 structures of such alkaloids.

The top-scoring structures were subjected to binding free energy and SMD experiments to determine their relative affinity towards the active site of the enzyme and hence, distinguishing the most probably active candidate, korupensamine A (1a). Upon in vitro validation, 1a was found to be the only actual Mpro inhibitor, possessing an IC50 value of 2.52 μM, with significant antiviral activity against SARS-CoV-2, comparable to that of the reference inhibitor GC376 (IC50 = 0.88 μM). Accordingly, from a collection of structurally related, atropisomerically defined NIQ alkaloids, SMD simulation was found to be a fast and accurate method for predicting the best Mpro inhibitor.

Finally, using Gaussian accelerated molecular dynamics (GaMD) simulations over 400 ns, we explored the binding pathway and the mode of recognition and interaction of korupensamine A (1a) within the active site of Mpro.

Intriguingly, GaMD simulations managed to simulate the binding process of korupensamine A (1a) and to reproduce its docking position within the active site of the enzyme, demonstrating the validity of our approach from the outset. The study shows that using computational chemistry methods helps the drug discovery process move forward. Our strategy presented here could effectively supplement commonly used docking simulations, especially when there are only minor structural differences within a series of analogues, where docking studies may have failed to properly rank the binding affinities.

The work furthermore reveals naphthylisoquinoline alkaloids as a highly promising new class of potential anti-SARS-CoV-2 agents. The highlight among these axially chiral alkaloids is korupensamine A (1a), which does not only bind strongly to the main protease of the virus in silico, but is also active in vitro, with a high structure specificity: All of the numerous other alkaloids, whether ring-opened, ring-contracted or quinoid, as well as their non-coupled isoquinoline and naphthalene moieties (see Table S1), were inactive, also the respective dimers, even including the closely related korupensamine B (1b), which differs from 1a only by the configuration at the rotationally hindered biaryl axis. This pinpoints, once again, the importance of axially chirality, which dictates the molecular shape of a bioactive compound, and thus, determines its bioactivity.

4. Experimental

4.1. Naphthylisoquinoline alkaloids and related compounds

The NIQs experimentally investigated in the present study and their analogues were prepared by isolation from their plant sources [56,[71], [72], [73], [74], [75], [76]] or by total synthesis [77], as described previously (for further details, see Table S1), and have been deposited in our in-house natural products library.

4.2. Molecular docking

4.2.1. Structure generation

The structures of the NIQs and their analogues used in the present study were generated using ChemDraw (12.0). Their rotational-energy profiles were calculated after energy minimization using Chem3D (12.0).

4.2.2. Ligand preparation

All torsions of the collected structures were assigned and their Gasteiger charges were added for all atoms in the compound structures using the AutoDockTools v.4.2 package [78].

4.2.3. Receptor preparation

For docking screening, the Mpro structures with the co-crystallized ligands myricetin and YD1 (PDB codes: 7DPP and 7LTJ, respectively) were used. The downloaded structures were curated on PDBfixer [79] to repair lost atoms and residues, and for removing co-crystallized water molecules. Polar hydrogens and Gasteiger charges were then added to all receptor structures using AutoDockTools v.4.2 [78].

4.2.4. Structural docking

For the docking step, AutoDock Vina software integrated in the PyRx platform was used [80,81]. The binding site for the docking search was determined according to the co-crystallized ligand of the enzyme, 6G9. The coordinates of the grid box were: x = −7.58; y = 16.39; z = 2.44. The size of the grid box was set to be 10 Å3 (for small structures) and 20 Å3 (for larger structures). Exhaustiveness was set to be 24. Docking poses were analyzed and visualized using the PyMOL software [80]. The docking protocol was validated by re-docking the co-crystallized inhibitor (6G9). The resulting top-scoring pose (score = −7.12 kcal/mol) was found to achieve a good alignment with the original co-crystallizing pose, with a low RMSD value (1.26 Å). After docking the structures of the NIQ library, a cut-off value of −7.0 kcal/mol was set to select the best ligands. This cut-off value was set according to the lowest docking score of the co-crystallized ligands (6G9 and myricetin), which got scores of −7.12 and −8.82 kcal/mol, respectively.

4.3. Molecular dynamics and ΔGbinding determination

Molecular dynamics simulations (including SMD) and binding free energy determination were carried out as described earlier [82]. GaMD simulations were performed according to the previously reported method of Miao and co-workers [83]. The detailed procedures are described in the Supplementary data.

4.4. Mpro enzyme assay (in vitro)

Top-scoring compounds were assessed for their in vitro enzyme inhibition activities using 3CL Protease, tagged (SARS-CoV-2) Assay Kit (Catalogue #: 79955-1, BPS Bioscience, Inc., Allentown, PA, USA), according to manufacturer's protocol [5]. The in vitro FRET assay was monitored at an emission wavelength of 460 nm with an excitation at 360 nm, using a Flx800 fluorescence spectrophotometer (BioTek Instruments, Winooski, VT, USA).

4.5. In vitro antiviral assay

Vero cells were incubated with the compounds for 3 days to investigate cytotoxicity, and the relative cell growth was determined by automatic cell counting. Concentrations of 30 μM of 1a and 1b did not influence cell growth. The Vero cells were then incubated with the respective compounds at increasing concentrations and subsequently infected with patient-derived SARS-CoV-2 at an MOI (Multiplicity of Infection) of approximately 0.5. DMSO was used as a solvent control [84]. After 24 h, the medium was replaced by compound-containing medium, to remove inactive viruses. After 3 days, viral replication supernatants were collected, and viral RNA was extracted. Viral replication was quantified by real-time RTqPCR. All infections were performed in triplicate [84,85].

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work was supported by Deraya University and the University of Würzburg. The authors thank Dr. D. Feineis and Prof. C. Sotriffer for valuable advice, and Dr. W. Shamburger for initial help with the structures.

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.ejmech.2023.115226.

Abbreviations

cMD

Classical Molecular Dynamics

DMSO

Dimethyl Sulfoxide

FEP

Free Energy Perturbation

FF14SB

Force Field 14 Stony Brook

ΔGbinding

Absolute Binding Free Energy

GaMD

Gaussian Accelerated Molecular Dynamics

GPUs

Graphics Processing Unit

GUI

Graphical User Interface

IC50

Half Maximal Inhibitory Concentration

Ki

Inhibitor Constant

MDS

Molecular Dynamics Simulation

MOI

Multiplicity of Infection

Mpro

Main Protease

NAMD

Nanoscale Molecular Dynamics

NIQ

Naphthylisoquinoline

NPT

Constant Pressure and Temperature

OPLS

Optimized Potentials for Liquid Simulations

PCR

Polymerase Chain Reaction

PDB

Protein Data Bank

PME

Particle Mesh Ewald

pN

Piconewton

RMSD

Root-Mean-Square Deviation

RMSF

Root-Mean-Square Fluctuation

RT

Reverse Transcriptase

RTqPCR

Quantitative Reverse Transcription Polymerase Chain Reaction

SARS-CoV-2

Severe Acute Respiratory Syndrome Coronavirus-2

SHAKE

Secure Hash Algorithm Keccak

SMD

Steered Molecular Dynamics

TIP3P

Transferable Intermolecular Potential with 3 Points

VMD

Visual Molecular Dynamics

Appendix A. Supplementary data

The following is the Supplementary data to this article.

Multimedia component 1
mmc1.zip (1.5MB, zip)

Data availability

Data will be made available on request.

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Associated Data

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Supplementary Materials

Multimedia component 1
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Data Availability Statement

Data will be made available on request.

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