Computational Investigation Of Benzalacetophenone Derivatives Against SARS-CoV-2 As Potential Multi-target Bioactive Compounds Ⅱ

3.7.2. Stability of 3CLpro-carmofur complex 

The complex 3CLpro-carmofur showed stable dynamics during the 150 ns of simulation after an equilibration period (60 ns). The average RMSD value for the backbone and complex was 2.34 Å and 2.81 Å, respectively. The N and C- terminal residues showed maximum residual fluctuations (~10 Å). However, the residues engaged in the stable and conserved non-bonded interactions showed relatively much lesser fluctuations (~2.0 Å). The Rg value revealed a folding pattern during ~30 ns (Fig. 10) and was found to express partial unfolding indicating stable ligand binding. In addition, it was observed that the initial and final average surface area occupied by 3CLpro and carmofur docked complex was 145.97 nm2 and 148.49 nm2 respectively. The average hydrophobic surface area occupied by the complex was 148.32 nm2 which represented a protein unfolding and flexibility of the binding pocket. The supplementary movie (S2) represents the detailed binding mode and stable dynamics of carmofur to 3CLpro. This complex formed 6 stable H-bonds of which 4 were consistent throughout the simulations. It was believed that these stable H-bond interactions promoted stable complex formation. The estimated relative binding energy of the complex 3CLpro-carmofur complex was − 16.67 kcal/mol. Further, the major residues contributing to the binding energy were identified by calculating per residue decomposition energy. The residues Thr25, Met49, Cys142, Met165, Leu167, Arg188, and Gln189 favored the stable complex formation. However, residues Asn142 and Glu166 did not favor the interactions. Among these residues, Met165 showed significant contributions to the binding energy as it had the least contribution energy (− 9.12 kJ/mol). However, the contribution energy for other interacting residues varied between − 1.42 to − 5.601 kJ/mol and also participated in stable complex formation. 

3.7.3. Stability of PLpro - 4-hydroxycordoin (c30) complex 

The PLpro–4-hydroxycordoin (c30) complex showed stable dynamics and a similar trend throughout 150 ns. The RMSD value was stable up to ~80 ns from ~1.2 to ~1.5 Å and ~1.8 to ~2.2 Å for backbone and complex, respectively. After ~80 ns, the RMSD was found to be relatively higher (~1.5–2.3 Å and ~2.2 to 3.5 Å, respectively) due to the increased surface area of protein. The residual fluctuations plotted for the Cα revealed the formation of stable non-bonded contacts in residues with fewer fluctuations observed in 4-hydroxycordoin (c30) i.e. Val203, Met207, Tyr208, Met209, Ile223, Pro224, and Pro248 compared to other non-interacting residues. The Rg value showed stable complex formation during the MD simulation by forming a compact globular shape as revealed by a steady decrease in the Rg value. The supplementary movie (S3) presents the binding mode of 4-hydroxycordoin (c30) with PLpro. It was observed that the loop formed by residues between two sheets was close to the binding pocket and possessed maximum contact with the molecule. However, due to the flexible nature of this loop, it showed the opening of the binding pocket resulting in increased SASA and ligand movement during the MD simulation after ~85 ns. The initial and final surface area occupied by PLpro and 4-hydroxycordoin (c30) docked complex was 169.50 nm2 and 170.29 nm2 respectively. The average surface area occupied by the complex was 170 nm2 . The complex formed a 3 H-bonds of which 2 were consistent. The binding affinity of the 4- hydroxycordoin (c30) with PLpro was estimated by calculating relative binding energy. The complex showed binding energy of − 16.28 kcal/ mol. To gain more structural insights into the contribution of individual residues in the binding energy, the residue decomposition energy was analyzed. It was observed that 7 residues significantly contributed to the stable complex formation and favored the existing non-bonded interactions i.e. Val203, Met207, Tyr208, Met209, Ile223, Pro224, and Pro248 (Fig. 11). Most importantly, the residues Tyr208, Met209, Ile223, and Pro224 showed significant contributions to the binding affinity by scoring the lowest contribution energy of − 2.97, − 3.89, − 3.82, and − 2.91 kJ/mol, respectively. Supplementary video related to this article can be found at https://d oi.org/10.1016/j.compbiomed.2022.105668. 

3.7.4. Stability of PLpro-GRL-0617 complex

The PLpro-GRL-0617 complex was stable and exhibited similar RMSD values up to 120 ns. The RMSD value for the backbone ranged from ~1.3 Å to ~3.0 Å and ~1.8 Å to ~4.5 Å for the complex. The steady decrease in the backbone RMSD value was observed after ~120 ns (from ~3.0 Å to 2.0 Å) and remained stable throughout the MD simulation period (150 ns). Similarly, the complex RMSD value showed a similar steady decrease in the RMSD value ranging from ~4.5 Å to ~3.0 Å. After ~120 ns, the RMSD value further increased up to 3.8 Å till 150 ns. The residual fluctuations of Gly164, Asp165, Thr211, Leu212, Asn216, Ile223, Ala247, Pro248, and Tyr265 were relatively less compared to other non-interacting residues. Although Cys225, Val226, and Cys227 showed maximum residual fluctuation up to 6 Å due to increased local flexibility, ligand interaction was observed during the simulation. Further, the Rg value showed a stable complex formation up to ~70 ns. In addition, due to the flexibility of a loop region adjacent to the ligandbinding pocket “Lys158 to Val166”, the ligand movement was observed towards other binding pockets (supplementary movie S4) which were also evidenced by an increase in the Rg value ~70 ns. In addition, GRL-0617 formed the stable non-bonded contacts throughout the 150 ns MD simulation as supported by the stable Rg pattern. Initially, the SASA showed a flexible binding pocket and increased SASA value. This may have triggered the reorientation of the ligand GRL- 0617. The initial and final surface area occupied by PLpro and GRL- 0617 docked complex was noted as 164.32 nm2 and 162.263 nm2 respectively. The average surface area occupied by the complex was 165.02 nm2 . Similarly, the increased SASA values indicated the binding pocket opening for stable complex formation which was favored mainly due to the flexible nature of the binding pocket residues. The complex formed 4 H-bonds of which 2 H-bonds were consistent during the simulation period. Further, the PLpro-GRL-0617 complex showed binding energy of − 11.83 kcal/mol. In addition, the structural insights into the contribution of individual residues in the binding energy were quantified by calculating the per residue decomposition energy. It was observed that 9 residues had a significant contribution to the stable complex formation and favored the existing non-bonded interactions i.e. Thr211, Leu212, Asn216, Ile223, Cys225, Val226, Cys227, Ala247, and Pro248 (Fig. 12). Most importantly, the residues Ile223, Cys225, Val226, and Cys227 showed significant contributions in the binding affinity by scoring the lowest contribution energy of − 0.91, − 0.74, − 1.86, and − 1.08 kJ/mol, respectively.

Supplementary video related to this article can be found at https://d oi.org/10.1016/j.compbiomed.2022.105668. 

Fig. 5. GO analyses of regulated proteins by benzalacetophenone derivatives presenting cellular components, molecular function and biological processes. 

3.7.5. Stability of spike protein - mallotophilippen D (c42) Complex

The spike protein-mallotophilippen D (c42) complex showed stable dynamics after an equilibration period of 100 ns similar to the other studied complexes. The RMSD value varied between ~1.2 Å to 3 Å and 1.8 Å to ~4 Å for backbone and complex, respectively. The simulation was further extended to 200 ns as this complex reached an equilibration state after 100 ns. The average backbone and complex RMSD values observed were ~2.6 Å and ~3.8 Å, respectively. The residual fluctuations plotted for the Cα, revealed fewer fluctuations for the residues participating in the non-bonded contacts with mallotophilippen D (c42) compared to other non-interacting residues. However, the flexible loop region formed by residues Alal344-Trp353 and Glu516-Thr523 was highly dynamic and showed higher fluctuations (~3 Å). Residues actively engaged in the ligand-protein interactions including Phe342, Leu368, and Ile434 showed the least fluctuation (supplementary movie S5). Further, a stable complex was formed during the MD simulation and established a compact globular shape as revealed by a decrease in the Rg value after 10 ns. The complex followed a stable Rg value after 100 ns indicating the proper folding that was required to form a stable complex between ligand and protein. The initial and final surface area occupied by spike protein and mallotophilippen D (c42) docked complex was 112.38 nm2 and 112.6 nm2 respectively. The average surface area occupied by the complex was 111.4 nm2 . The supplementary movie (S5) demonstrates the detailed binding mode of mallotophilippen D (c42) with spike protein. The complex formed 6 H-bonds of which 3 were consistent. The binding affinity of the mallotophilippen D (c42) to spike protein was estimated by calculating relative binding energy. In addition, the complex showed binding energy of − 34.10 kcal/mol. Further, the per residue contribution energy revealed 12 residues from the binding pocket namely Phe342, Ala363, Asp364, Tyr365, Leu368, Leu371, Ala372, Phe374, Ile434, Trp436, Val511, and Leu513 to contribute significantly in the stable complex formation (Fig. 13). The residues Phe342, Leu368, Ile434, and Trp436 from the binding pocket showed significant contributions to the binding affinity by scoring the least residue decomposition/contribution energy of − 5.78, − 9.39, − 4.71, and − 4.20 kJ/mol respectively. 

Fig. 7. Predicted anti-viral spectra of benzalacetophenone derivatives against multiple viruses. It was predicted that the majority of the benzalacetophenone derivatives were active against the Herpes virus (12.57%) and the least towards Trachoma (0.57%). 

3.7.6. Stability of spike protein - DRI-C23041 complex 

The spike protein-DRI-C23041 complex also showed stable dynamics after an equilibration period of 100 ns similar to the spike protein mallotophilippen D (c42) complex. Initially, the backbone and complex RMSD values gradually increased from ~1.8 Å to 5 Å and ~2 Å to ~5.1 Å for backbone and complex respectively. The residues Val367, Leu368, Asp339, Asp364, Asp389, and Leu441 showed relatively fewer fluctuations (~4.0 Å) as they participate in stable non-bonded interactions with DRI-C23041. The flexible loop formed by the residues Ala475 to Asn487 showed maximum residual fluctuations (~11.0 Å). In addition, a stable complex was formed by a steady Rg value of ~18 Å. In addition, the anticlockwise rotation of the ligand was observed at about ~63 ns upon the partial unfolding of the complexes which was also evidenced by the increased Rg value to 19.5 Å (supplementary movie S6). However, the ligand regained its original position and occupied stable conformations, and the complex formed compact globular shapes as supported by a decrease in the Rg value to 18.3 Å. This structural transition of ligand favored the stable complex formation during the 150 ns MD simulation. The initial and final surface area occupied by spike protein and DRI-C23041 docked complex was 109.379 nm2 and 107.334 nm2. The average surface area occupied by the complex was 110.57 nm2 . The complex formed 4 H-bonds of which 2 were consistent. The relative binding energy between DRI-C23041 to spike protein was found to be − 3.10 kcal/mol. The per residue contribution energy revealed 11 residues from the binding pocket namely Asp339, Glu340, Asp364, Asp389, Asp398, Asp405, Glu406, Asp427, Asp428, Asp442, and Glu516 to contribute significantly in forming the stable complex (Fig. 14) and these residues scored the least per residue decomposition/ contribution energy that varied from − 11.90 kJ/mol to − 27.17 kJ/mol respectively. 

3.7.7. Principal component and dynamic cross-correlation matrix

We performed principal component analysis to explore the conformational flexibility and diversity of conformations that emerge from the stable trajectory obtained from 150 ns MD simulations i.e. 100–150 ns for five complexes and 150–200 ns for spike protein-mallotophilippen D complex. The maximum collective motion is captured by the first 10 eigenvectors/principal components. Therefore, we precisely studied the first two eigenvectors/PCs (Principal components) in detail. Fig. 15 represents the 2D projection of the first two eigenvectors. It was observed that standard molecules used in the present study namely Carmofur, GRL-0617, and DRI-C23041, targeting 3CLpro, PLpro, and spike protein, respectively showed larger diversity of conformations during the simulations (shown as a red line in Fig. 15A–C) However, selected ligands namely 3’-(3-methyl-2-butenyl)-4′ -O-β-D-glucopyranosyl-4,2′ -dihydroxychalcone, 4-hydroxycordoin, and mallotophilippen D targeting 3CLpro, PLpro, and spike protein, respectively showed less diversity of conformations during simulation. This reveals that complexes 3’-(3-methyl-2-butenyl)-4′ -O-β-D-glucopyranosyl-4,2′ -dihydroxychalcone with 3CLpro, 4-hydroxycordoin with PLpro and mallotophilippen D with spike protein are well equilibrated and stabilized during the simulation. In addition, the larger conformational space occupied by the complexes (standard molecules) exhibited higher conformational flexibility with the maximum number of diverse conformations. Interestingly, the compounds 3’-(3-methyl-2-butenyl)-4′ -O- β-D-glucopyranosyl-4,2′ -dihydroxychalcone, 4-hydroxycordoin, and mallotophilippen D with 3CLpro, PLpro, and spike protein occupied relatively much lesser conformational space compared to their respective controls/standard. Thus, we propose that screened molecules could be more effective than standard drugs (Fig. 15D–F). 

The dynamic cross-correlation of Cα atoms observed in complexes gains more structural insights into the collective motion of the ligandbinding domains. Fig. 16 represents the concerted residual motion of the Cα atoms in all the simulated complexes. The diagonal amber-coloured line shows a strong self-correlation of each residue with itself. The amplitude of correlation to anticorrelation is scaled from amber to blue color respectively. In complex 3’-(3-methyl-2-butenyl)-4′ -O-β-Dglucopyranosyl-4,2′ -dihydroxy chalcone-3CLpro, the binding site residues show anti-correlation with the N-terminal domain of the 3CLpro. However, the amplitude of anticorrelation is moderate while complex 3CLpro-carmofur (standard) showed similar anticorrelation with much lesser amplitude. Thus, we propose binding of 3’-(3-methyl-2-butenyl)- 4′ -O-β-D-glucopyranosyl-4,2′ -dihydroxychalcone that would favor the conformational transition and promote the stable complex formation with enhanced non-bonded interactions compared to its standard molecule i.e. carmofur. Likewise, another complex 4-hydroxycordoinPLpro showed a strong correlation between the residues 50–175, however, the same residues in complex with standard drug GRL-0617 bound to PLpro showed relatively weaker cooperative motion. The cooperative motion expressed by the binding pocket residues ranging from 175 to 240 with the N-terminal region revealed the significance of the active site residues in stabilizing the GRL-0617-PLpro complex. The binding pocket correlation was lost in the complex GRL-0617-PLpro. The standard molecule DRI-C23041-spike protein complex showed strong cooperative motion for residues 390 to 470 with itself, while these residues in complex spike-mallotophilippen D showed anti-cooperative motion. Moreover, the spike-mallotophilippen D complex showed anticooperative motion except for strong self-correlation expressed by all the residues. 

Thus, the dynamic cross-correlation matrix showed the cooperative and anti-cooperative motion in the protein highlighting the conformational flexibility of the studied complexes and stable nonbonded interactions medicated by non-cooperative motion on the opposite side triggered the opening and closing of the binding pocket residues facilitating the stable complex formation during the MD simulation.

Fig. 9. Parameters describing 3CLpro-3’-(3-methyl-2-butenyl)-4′-O-β-D-glucopyranosyl-4,2′-dihydroxychalcone complex structural stabilities. (a) RMSD of backbone and complex, (b) RMSF, (c) Rg, (d) SASA, (e) number of H-bond interactions, and (f) contribution energy plot highlighting the importance of the binding pocket residues in stable complex formation. 

Table 6

MM-PBSA calculations of the binding free energy and interaction energies of top hit complexes. 

4. Discussion 

It has been indicated that immune boosters could play a chief role in prophylaxis against multiple infectious pandemics including COVID-19 as they are more prevalent in compromised immunity. Previously, the immune boosters’ role in dealing with COVID-19 has been explained using cheminformatics and bioinformatics approaches [34]. Similarly, the present work attempted to investigate benzalacetophenones (precursors of flavonoids) [35] as immune boosters and anti-viral agents against novel coronavirus.

Initially, the compounds were retrieved and subjected to druglikeness prediction based on the molecular weight, H-bond donors, acceptors, and lipophilicity as explained by Lipinski’s rule of five. Here, the majority of the benzalacetophenones were identified with positive drug-likeness scores suggesting their oral bioavailability [16]. In addition, a few modifications can be made in the structure of benzalaceto phenones with negative drug-likeness scores to enhance their oral bioavailability. However, it is to be noted that their biological function should not be affected. Further, the top 5 ligands with positive drug-likeness scores i.e. abyssinone VI (c1), isobavachalcone (c11), 4-hydroxycordoin (c30), mallotophilippen E (c31), and oxygenated xanthohumol (c39) were predicted for their lipophilicity, water-solubility, pharmacokinetics, and druglikeness as these are central constraints to be considered for the drug action. Interestingly, none of these 5 hits violated Lipkinski (molecular weight <500, number of H-bond acceptors <10, number of H-bond donors <5, and XLogP<5) [36] and Veber (number of rotatable bonds ≤10, and the total polar surface area ≤140, also questions 500 molecular weight cutoff in Lipinski rule of 5) [37] rules. 

In addition, a total of 55 different pathways were regulated by the benzalacetophenones under investigations in which hypoxia-inducible factor (HIF)-1, p53, nuclear factor kappa B (NF-kB), toll-like receptor, tumor necrosis factor (TNF), forkhead box, sub-group O (FoxO), estrogen, Wnt, NOD-like receptor, and interleukin-17 (IL-17) signaling pathway and cytokine-cytokine receptor interaction were identified to be concerned in regulating the immune. It has been reported that the HIF expression and stabilization are triggered by hypoxia and microbes-associated pathogenesis. Further, HIF regulates the host immune function, boosting phagocyte microbicidal capacity and differentiation of T cells followed by a cytotoxic activity. In addition, the HIF signaling pathway plays a prime role in inflammation, macrophage metabolism and polarization, microbial infection (both viral and bacterial), antigen presentation, and innate immunity [38]. Similarly, the HIF-1 signaling pathway (hsa04066) was identified to be regulated via the modulation of FLT1, GAPDH, HMOX1, NOS2, TFRC, and TIMP1 genes which would play an important role in manipulating the immune system in coronavirus infections and deal with the inflammation in the affected tissue. Also, the p53 signaling pathway manipulates the immune response via the transactivation of key regulators of immune signaling pathways.  

Fig. 10. Parameters describing 3CLpro-Carmofur complex structural stabilities. (a) RMSD of backbone and complex, (b) RMSF, (c) Rg, (d) SASA, (e) number of Hbond interactions, and (f) contribution energy plot highlighting the importance of the binding pocket residues in stable complex formation. 

Fig. 11. Parameters describing PLpro-4-hydroxycordoin complex structural stabilities. (a) RMSD of backbone and complex, (b) RMSF, (c) Rg, (d) SASA, (e) number of H-bond interactions, and (f) contribution energy plot highlighting the importance of the binding pocket residues in stable complex formation. 

Further, multiple genes from the p53 signaling pathways are also reported in cytokine production, pathogen sensing, inflammation, and clearance of dead cells [39]. Hence, the benzalacetophenones could be involved in regulating CASP8, CCND2, CHEK1, and MDM2 genes from the p53 signaling pathway (hsa04115), and may trigger the cytokines to boost the immunity followed by clearance of dead tissues from the body. Inflammatory cytokines like TNF or ILs influence innate and adaptive immune responses. In addition, their importance has been illustrated by accepting the pathogenesis generated via the blockage of single cytokines like IL-6 or TNF [40]. Herein, benzalacetophenones were also predicated to modulate multiple pathways like NF-kB (hsa04064), TNF (hsa04668), and IL-17 (hsa04657) signaling pathway and cytokine-cytokine receptor interaction (hsa04060) which are directly concerned with inflammatory cytokines. Toll-like receptors are usually expressed in sentinel cells (dendritic cells and macrophages) to recognize microbe-derived structurally conserved molecules and play a key role in the innate immune system. In addition, they recruit specific adaptor molecules, activate transcription factors like NF-kB, state the outcome of innate immune responses, and play an important role in multiple aspects of the innate immune response to pathogens [41]. Herein, the benzalacetophenones were identified to regulate the three proteins i.e. CASP8, CD14, and CD86 in the toll-like receptor signaling pathway. Further, the FoxO subfamily of the forehead (Fox) transcription factors play a crucial role in the cell and homeostatic function of immune-relevant cells including T cells, B cells, neutrophils, and other non-lymphoid lineages [42]. Further, benzalacetophenones regulated the FoxO signaling pathway (hsa04068) by modulating three proteins (CAT, CCND2, and MDM2) against 130 background proteins with a false discovery rate of 0.0137. Similarly, estrogen receptors have been acknowledged to develop the immune cells followed by their participation in membrane-initiated steroid signaling. In addition, they produce type I interferon and also innate cytokine production and develop or function the response of innate immune cells [43]. Likewise, the present work demonstrated benzalacetophenones to regulate the estrogen signaling pathway (hsa04915) via the modulation of three proteins i.e. MMP2, PGR, and RARA which may trigger the interferons and cytokines production and help in the rapid response of immune cells. Similarly, Wnt signal plays an important role in multiple biological processes including immune cell regulation which is very diverse in the natural killer cells development, T-cells initiation, macrophage action on tissue repair, and T-cells thymopoiesis [44]. Herein, benzalaceto phenones regulated the Wnt signaling pathway (hsa04310) via the modulation of three proteins i.e. CCND2, CTNNB1, and MMP7, and may contribute to developing and regulating the natural killer cells, T-cells, and macrophages. Similarly, NOD-like receptors function in microbial recognition, and host defense mechanisms are reported and also trigger the host’s innate immune response. Additionally, the NOD-like receptor family is concerned with host-pathogen interactions and inflammatory responses [45] which have been regulated via the modulation of 3 proteins i.e. CASP8, CCL2, and CYBA. 

In the benzalacetophenones-targets-pathways interaction, multiple parameters of the whole network were evaluated. The average connectivity of all the nodes with their neighbors is defined by the “neighborhood connectivity” [46]. This variable was defined in the above-mentioned network by neighbors at 63.8%. In addition, “betweenness centrality” measures the node frequency to be present on the shortest path between other nodes. This points the node to act as a bridge between the nodes in the network. This helps to identify the shortest path and the frequency of independent nodes to fall on one [47] which was observed to be correlated with neighbor count by 1. Similarly, "closeness centrality" tallies each node based on their ‘closeness’ to other nodes and calculates the shortest path between the nodes. This helps to understand the individual node’s influence over the given network most quickly [47]. In the present work, closeness centrality was observed to be dependent on the neighbors by 2%. 

During the identification of new antiviral agents for the novel virus, tracing the anti-viral property towards a well-recognized virus could play an easy game. Assuming this, we investigated the benzalaceto phenones of interest in the anti-viral biological spectrum. In this, it was observed that selected benzalacetophenones possessed anti-viral properties against adeno, cytomegalo, hepatitis, herpes, trachoma,influenza, parainfluenza, picorna, pox, rhino, and human immunodeficiency virus. Further, GO analysis also identified the regulation of the infectious disease pathways i.e. human papillomavirus infection (hsa05165), Kaposi’s sarcoma-associated herpesvirus infection (hsa05167), viral carcinogenesis (hsa05203), HTLV-I infection (hsa05166), herpes simplex infection (hsa05168), and viral myocarditis (hsa05416) that are concerned to viral infection concerning KEGG database. These results further kindled us to investigate the probable anti-viral property of benzalacetophenones against the novel coronavirus. 

To evaluate the probable anti-viral action of benzalacetophenones against SARS-CoV-2, we used the in silico molecular docking and all-atom explicit MD simulations to investigate the binding affinity of ligands against 3 targets of novel coronavirus i.e. 3CLpro, PLpro, and spike protein receptor-binding domain. Here, all the benzalacetophenones scored binding energy less than − 5.0 kcal/mol. Further compounds interacted with all the three targets with a minimum of one H-bond interaction except a few i.e. 4-chlorochalcone (c4), obochalcolactone (c17), 4′ -O-methylbavachalcone (c22), and mallotophilippen E (c31) with the 3CLpro,2′ -hydroxychalcone (c2), 4-chlorochalcone (c4), 4- hydroxychalcone (c5), okanin (c7), 2′ ,3,4,4′ ,6′ -pentahydroxychalcone (c8), chalcone (c10), (+)-tephrosone (c12), pinocembrinchalcone (c13), 4′ -O-methylbavachalcone (c22), and 2′ ,4′ -dihydroxy-6′ - methoxy-3′ ,5′ -dimethylchalcone (c43) with PLpro and 2′ -hydroxychalcone (c2), 4-chlorochalcone (c4), chalcone (c10), desmethylxanthohumol (c21), 4′ -O-methylbavachalcone (c22), 7- methoxypraecansone B (c29), mallotophilippen C (c41), and 2′ ,4′ - dihydroxy-6′ -methoxy-3′ ,5′ -dimethylchalcone (c43) with spike protein. In addition, 3CLpro is present in nsp5 that undergoes auto cleavage and releases all downstream replicase subunits to alter the ubiquitin system affecting the functional proteins [48] which were chiefly targeted by obochalcolactone (c17) with a − 8.5 kcal/mol binding energy however it had no H-bond interactions. The viral cycle of coronavirus is regulated by replicase proteins triggered via pp1a and pp1ab and is processed by the PLpro [49] which was chiefly modulated by 4-hydroxycordoin (c30), and xanthohumol (c38) with a binding affinity of − 8.2 kcal/mol by both ligands. Likewise, the coronavirus utilizes the ACE2 as a gateway to enter the host cell [50,51] and was majorly targeted by abyssinone VI (c1). These results reflect multiple molecules (of a similar category) that may be utilized to target the various sites of virus anatomy due to their affinities towards multiple proteins via the “multi-compound (s)-multi protein(s)” interaction theory. One of the important aspects of the presented study is the identification of viral entry inhibitors which covered 7.71% of total benzalacetophenones under investigation (Fig. 7). Hence, the binding of benzalacetophenones with spike protein receptor-binding domain was added as spike protein and is a direct key to rub the normal cell homeostasis. In addition, one of the important aspects to be considered is that “right molecule-right target-right duration” as an irrational assessment may cause tachyphylaxis towards the pathogenesis of interest including COVID-19 which could be solved via “multi component-multi protein” interaction over “single compound-single target” interaction theory. In addition, this study pointed to the regulation of some specific pathways i.e. TNF, NF-kB, and IL-17 signaling pathways and cytokine-cytokine receptor interaction (Fig. 17) that are directly concerned with the immune regulation and also manipulate the cytokine storm. 

Fig. 16. Dynamic cross-correlation matrix of Cα atoms observed in complexes for benzalacetophenones (A, C, E) and standard drugs (B, D, F) with 3CLpro, PLpro, and spike protein, respectively. The positive regions, which are colored amber, represent strongly correlated motions of Cα atoms (Cij = 1), whereas the negative regions, which are colored blue, represent anticorrelated motions (Cij = -1). 

Previously, multiple investigations have been made to implement the homology modeling, molecular docking, MD simulations, and MM-PBSA evaluation to record the drug transport variability, identification of protein allosteric inhibition, the influence of chirality in selective enzyme inhibition, exploring the irrevocable mode of the receptors, and ligand-protein interactions assessment [52–56]. Similarly, in the present work, intermolecular interactions stability of identified potential lead compounds and standard molecules with their respective target were analyzed through classical MD simulation for 150 ns (spike protein - mallotophilippen D (c42) complex for 200 ns). Results revealed that 3’-(3-methyl-2-butenyl)-4′ -O-β-D-glucopyranosyl-4, 2′ -dihydroxychalcone (c35) exhibited stable dynamics with 3CLpro compared to a standard molecule carmofur. Previously, carmofur was reported to inhibit coronavirus replication in Vero E6 cells (EC50 = 24.30 μM) by interacting with the Cys145 residue of 3CLpro [57]. Similarly, in the present study, carmofur was predicted to interact with Cys145 residue by scoring contribution energy of − 1.42 kJ/mol, whereas, 3’-(3-methyl-2-butenyl)-4′ -O-β-D-glucopyranosyl-4,2′ -dihydroxychalcone compounds scored − 4.24 kJ/mol for Cys145. In addition, Cys145–His41 are the two catalytic dyad residues of 3CLpro to play an important role in the cleavage of SARS-CoV-2 polyproteins [58]. In addition, other research groups also reported the potential role of targeting Cys145 to design novel antivirals against 3CLpro [59,60]. Interestingly, we observed conserved binding site interactions (Thr25, Met49, and Met165) in both these compounds during the 150 ns MD simulation. Similarly, 4-hydroxycordoin (c30) was screened as an inhibitor of PLpro and formed a stable complex compared to a standard molecule GRL-0617. Previously, GRL-0617 has been reported as a potent PLpro inhibitor in SARS-CoV-2 infected Vero E6 cells with IC50 of 2.1 μM [61, 62]. In the present study, both GRL-0617 and 4-hydroxycordoin (c30) formed stable RMSD and shared common interactions with Ile223 and Pro248 throughout 150 ns and 200 ns MD production run, respectively, and revealed both as suitable hits as PLpro inhibitors.

In addition, previously, Bojadzic et al. reported DRI-C23041 to inhibit spike protein RBD domain with IC50 of 0.52 μM [63]. In the present study, mallotophilippen D (c42) was identified as a spike protein regulator and showed a better binding affinity towards the RBD domain of spike protein compared to a standard molecule DRI-C23041. The MM-PBSA result revealed that the mallotophilippen D (c42) possesses the binding free energy of − 34.10 kcal/mol, whereas, − 3.10 kcal/mol by DRI-C23041 which indicated a higher affinity of mallotophilippen D (c42) to spike protein. Further, both DRI-C23041 and mallotophilippenD (c42) were found to interact with a common residue Leu368 of spike protein RBD domain during 150 ns MD simulation. The investigation of complexes for PCA and DCCM also demonstrated that chalcones with 3CLpro, PLpro, and spike protein are well equilibrated and stabilized during the simulation via occupying relatively much lesser conformational space and conformational flexibility with a minimum number of diverse conformations compared to standard molecules. Contemporary, 4-hydroxycordoin (c30), a compound with the highest drug-likeness score regulated 9 proteins i.e. FLT1, CD86, CASP8, RARA, KLK3, PLAT, CTNNB1, HMOX1, and TOP2A in which 6 proteins i. e. CASP8, CTNNB1, TOP2A, CD86, PLAT, and HMOX1 were traced to be concerned with the viral infection. CASP8 encodes caspase 8; a viral pathogen that targets the CASP8-dependent apoptotic cell and the necrotic cell death pathway that is dependent on the receptor-interacting protein (RIP) 1 and 3. Therefore, acquiring the CASP8 activity suppresses RIP1 and 3 to strengthen the role in host defense against intracellular viral pathogens [64]. Similarly, CTNNB1 codes catenin β-1 and is responsible for interferon protein synthesis [65], and are the chief modulator of the immune response. In addition, it can interfere with viral infections [66]. Likewise, TOP2A codes topoisomerase 2α and its inhibition induces telomeric deoxyribonucleic acid damage and T-cell dysfunction during chronic viral infection [67]. Further, CD86 codes T-lymphocyte activation antigen CD86 and controls antiviral CD8+ T-Cell function and immune surveillance [68]. PLAT codes plasminogen activator and contributes to the deleterious inflammation of the lungs and local fibrin clot formation; may be implicated in host defense against influenza virus infections [69]. Likewise, HMOX1 codes heme oxygenase 1. Previously, the SARS-CoV-2 open reading frame 3a protein was reported to bind to the human HMOX1 protein at high confidence. The HMOX1 pathway can inhibit platelet aggregation and can have anti-thrombotic and anti-inflammatory properties, amongst others, all of which are critical medical conditions observed in COVID-19 patients [70]. 

Previously, it has been indicated that the genomic RNA of SARS-CoV-2 can manipulate immune genes and deprive their function. In addition, it has been pointed out that genomic RNA could trigger interleukin interactions and may also trigger the cytokine storm [71]. Also, a study explores the bit part of microRNA (miRNA) in COVID infection to avoid the recognization and attack from the immune response. In an instant SARS-CoV-2 can act as cotton or sponge to absorb the miRNA and force the immune system dysfunction. In addition, it encodes its miRNA, enters the host cell, and is recognized by the host’s immune system [72]. 

Since benzalacetophenones (chalcones) are reported in manipulating the immune response [11], and RNA is concerned with the immune genes synthesis, their probable role in manipulating the genomic RNA interaction host needs to be further investigated. 

5. Conclusion

The present study investigated the multiple benzalacetophenones as an immune booster and their anti-viral spectra against SARS-CoV-2. This study reported probable lead antiviral agents namely abyssinone VI (c1), isobutrin (c16), obochalcolactone (c17), 4-hydroxycordoin (c30),3’-(3-methyl-2-butenyl)-4′-O-β-D-glucopyranosyl-4,2′-dihydrox ychalcone (c35), xanthohumol (c38), and 4-mallotophilippen D (c42) against COVID-19 by targeting 3CLpro, PLpro, and spike protein. In addition, enrichment analysis identified the regulation of various

pathways like HIF-1, p53, NF-kB, Toll-like receptor, TNF, FoxO, estrogen, Wnt, and IL-17. Also, NOD-like receptors and cytokine-cytokine receptors were triggered that are directly concerned with regulating the immune system and manipulating the cytokine storm. Similarly, there was a triggering of multiple pathways against viral and bacterial infection and endocrine deregulation where the immune system is chiefly compromised. These results suggest the therapeutic option of benzalacetophenone derivative(s) against COVID-19. Limiting to the present findings, we point out that the findings presented in this work are based on processor simulations which need to be further validated with wet lab experimental protocols.  

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