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. 2022 Mar 31;27(7):2287. doi: 10.3390/molecules27072287

Ligand and Structure-Based In Silico Determination of the Most Promising SARS-CoV-2 nsp16-nsp10 2′-o-Methyltransferase Complex Inhibitors among 3009 FDA Approved Drugs

Ibrahim H Eissa 1,*, Mohamed S Alesawy 1, Abdulrahman M Saleh 1, Eslam B Elkaeed 2, Bshra A Alsfouk 3, Abdul-Aziz M M El-Attar 4, Ahmed M Metwaly 5,6,*
Editors: Anna Maria Almerico, Imtiaz Khan, Sumera Zaib
PMCID: PMC9000629  PMID: 35408684

Abstract

As a continuation of our earlier work against SARS-CoV-2, seven FDA-approved drugs were designated as the best SARS-CoV-2 nsp16-nsp10 2′-o-methyltransferase (2′OMTase) inhibitors through 3009 compounds. The in silico inhibitory potential of the examined compounds against SARS-CoV-2 nsp16-nsp10 2′-o-methyltransferase (PDB ID: (6W4H) was conducted through a multi-step screening approach. At the beginning, molecular fingerprints experiment with SAM (S-Adenosylmethionine), the co-crystallized ligand of the targeted enzyme, unveiled the resemblance of 147 drugs. Then, a structural similarity experiment recommended 26 compounds. Therefore, the 26 compounds were docked against 2′OMTase to reveal the potential inhibitory effect of seven promising compounds (Protirelin, (1187), Calcium folinate (1913), Raltegravir (1995), Regadenoson (2176), Ertapenem (2396), Methylergometrine (2532), and Thiamine pyrophosphate hydrochloride (2612)). Out of the docked ligands, Ertapenem (2396) showed an ideal binding mode like that of the co-crystallized ligand (SAM). It occupied all sub-pockets of the active site and bound the crucial amino acids. Accordingly, some MD simulation experiments (RMSD, RMSF, Rg, SASA, and H-bonding) have been conducted for the 2′OMTase—Ertapenem complex over 100 ns. The performed MD experiments verified the correct binding mode of Ertapenem against 2′OMTase exhibiting low energy and optimal dynamics. Finally, MM-PBSA studies indicated that Ertapenem bonded advantageously to the targeted protein with a free energy value of −43 KJ/mol. Furthermore, the binding free energy analysis revealed the essential amino acids of 2′OMTase that served positively to the binding. The achieved results bring hope to find a treatment for COVID-19 via in vitro and in vivo studies for the pointed compounds.

Keywords: SARS-CoV-2 nsp16-nsp10 2′-o-methyltransferase, FDA approved drugs, molecular fingerprints, structural similarity, molecular docking, MD simulations, MMPBSA

1. Introduction

The WHO, addressed on 16 February 2022, confirmed that the worldwide infections of COVID-19 were 414,525,183. Grievously, this number includes 5,832,333 deaths [1]. Although 10,227,670,521 vaccinations have been administered [1], the virus can still infect and spread widely [2]. Responding to these numbers, massive work is demanded from scientists all over the world to find a cure.

The regular process of new drug discovery is highly expensive and takes much time. The average required time for the complete development of a new drug is about 12 years, with a cost of 2.6 billion USD [3]. In contrast, drug repurposing or repositioning is a much faster technique in which the exploration of new pharmacological use for an old or existing drug occurs [4]. The strategy of drug repurposing was applied successfully in the discovery of anti-cancer [5], COVID-19 [6], anti-inflammatory [7], antibacterial [8], anti-parasitic [9], and anti-viral [10] drugs.

The tremendous applications of computational chemistry in drug discovery are due to different factors. First, the exploration of accurate 3D structures of different protein targets in the human body [11]. Second, the vast advancements in the fields of computer hardware and software [12]. Finally, the development of structure–activity relationship (SAR) principles [13]. Consequently, computational chemistry methods were applied to estimate various pharmacodynamic and pharmacokinetic parameters that relate the chemical structure of compounds to its activity and also to characterize the interaction of compounds with biological targets such as structure similarity [14], molecular fingerprints [15], QSAR [16], pharmacophores [17], homology models [18], molecular modeling [19], drug molecular design [20], rational drug design [21,22], molecular docking [23], MD simulations [24], absorption [25], distribution [26], metabolism [27], excretion [28], and toxicity properties [29], as well as physicochemical characterization [30] and DFT [31].

In this regard, our team employed the strategies of computer-based chemistry to discover the potential inhibitive effects of the secondary metabolites of Asteriscus hierochunticus [32], Monanchora sp. [33], Artemisia sublessingiana [34], and Artemisia sp. [35], as well as 69 isoflavonoids [36] against SARS-CoV-2. Additionally, we designed a multi-step in silico selection method to prime the most active inhibitor drugs against a SASRS-CoV-2 protein amongst a vast number of compounds. As an exemplification, amongst 310 natural metabolite and 69 semisynthetic compounds, the highest potential inhibitors against SARS-CoV-2 nsp10 [37] and the SARS-CoV-2 PLpro [38], respectively, were decided

In this research, a panel of 3009 FDA-approved compounds was retrieved from the internet [39] to be screened depending on various computational methods to distinguish the most potent SARS-CoV-2 nsp16-nsp10 2′-o-methyltransferase complex inhibitor.

The starting point in our study was (S-Adenosylmethionine, SAM), the co-crystallized ligand of the essential COVID-19 protein, 2′OMTase (PDB ID: (6W4H), that showed high binding affinity against it. Firstly, the selected compounds were subjected to two ligand-based computational techniques (molecular fingerprints and similarity) successively to select the most similar candidates to SAM. Then, several structure-based computational methods (molecular docking and MD simulations) were conducted to confirm the binding modes, energies, and dynamic behaviors of the singled-out candidates.

2. Results and Discussion

2.1. Filter Using Fingerprint

Molecular fingerprint is a ligand-based computational (in silico) computational technique. This approach can predict the biological activity of a molecule based on its chemical structure [40]. The scientific base of ligand-based calculations is influenced by the principles of target– structure–activity relationships (SAR). It can set a relationship between the measured bio response/s exerted by a molecule and its chemical structure. Accordingly, compounds with similar chemical structures are expected to exert similar activities [41].

A co-crystallized ligand is one that exerts an excellent binding affinity with the corresponding protein forming a crystallizable ligand–protein complex [42]. In accordance, the chemical structure of that ligand could be employed as a model to design and develop an inhibitor that can bind strongly to the target protein. The molecular fingerprints study was performed using Discovery Studio against SAM. The experiment examined the next variables: H-bond acceptor and donor [43], charge [44], hybridization [45], positive and negative ionizable [46], halogen, aromatic, or none of the above besides the ALogP of atoms and fragments.

In structural terms, the chemical structures of the examined molecules are encoded and transformed binary bit strings (sequences of 0′s and 1′s). Every bit corresponds to a “pre-defined/determined” structural descriptor or feature of substructure or fragment. If the examined molecule has that feature, the bit position that corresponds to this descriptor is set to 1 (ON). If it is absent, it is set to 0 (OFF) [47].

SA describes the number bits that were computed in the FDA-approved drugs and the SAM. SB identifies the number bits that were found in the FDA-approved drugs, but not SAM. SC refers to the number bits that were discovered in SAM, but not in the FDA-approved drugs.

The study (Table 1) favored 147 compounds. These compounds showed the highest fingerprint similarity with SAM.

Table 1.

Fingerprint similarity between the tested compounds and SAM.

Comp. Similarity SA SB SC Comp. Similarity SA SB SC
SAM 1 237 0 0 1670 0.57 257 214 −20
4 0.497396 191 147 46 1694 0.5 191 145 46
42 0.597 138 −6 99 1737 0.506944 146 51 91
50 0.651 157 4 80 1740 0.491582 146 60 91
51 0.581 137 −1 100 1756 0.506912 220 197 17
56 0.665 171 20 66 1761 0.523404 246 233 −9
58 0.491525 174 117 63 1766 0.54321 176 87 61
74 0.495652 171 108 66 1778 0.511299 181 117 56
91 0.496241 132 29 105 1792 0.50211 238 237 −1
113 0.485714 170 113 67 1793 0.494792 285 339 −48
130 0.490463 180 130 57 1802 0.56 237 186 0
152 0.624 143 −8 94 1805 0.501433 175 112 62
158 0.5 189 141 48 1818 0.508475 210 176 27
186 0.644 150 −4 87 1860 0.494024 124 14 113
189 0.5 122 7 115 1886 0.493478 227 223 10
190 0.492958 175 118 62 1911 0.490683 158 85 79
214 0.515723 164 81 73 1913 0.494033 207 182 30
241 0.717 160 −14 77 1917 0.929 235 16 2
251 0.490956 190 150 47 1919 0.488701 173 117 64
272 0.508403 121 1 116 1927 0.489796 216 204 21
281 0.510806 260 272 −23 1928 0.488636 215 203 22
304 0.488938 221 215 16 1932 0.50303 166 93 71
310 0.717 160 −14 77 1949 0.505464 185 129 52
322 0.486154 158 88 79 1960 0.48995 195 161 42
380 0.514563 159 72 78 1993 0.522599 185 117 52
390 0.52862 157 60 80 1995 0.488998 200 172 37
404 0.535211 190 118 47 2002 0.49 147 63 90
428 0.498623 181 126 56 2009 0.511364 135 27 102
446 0.50641 158 75 79 2017 0.663 193 54 44
458 0.488136 144 58 93 2023 0.627 168 31 69
461 0.507837 162 82 75 2024 0.527378 183 110 54
470 0.491803 180 129 57 2031 0.57 147 21 90
515 0.501493 168 98 69 2036 0.487179 171 114 66
516 0.561 165 57 72 2042 0.664 172 22 65
539 0.519149 122 −2 115 2174 0.488318 209 191 28
562 0.489496 233 239 4 2176 0.661 199 64 38
573 0.491049 192 154 45 2232 0.642 265 176 −28
598 0.510504 243 239 −6 2233 0.701 202 51 35
659 0.540816 159 57 78 2256 0.543662 193 118 44
663 0.492537 198 165 39 2268 0.538776 132 8 105
672 0.48913 135 39 102 2303 0.503597 210 180 27
679 0.501661 151 64 86 2306 0.494737 188 143 49
683 0.488798 240 254 −3 2333 0.494595 183 133 54
711 0.566 137 5 100 2376 0.643 160 12 77
723 0.561 142 16 95 2396 0.491525 232 235 5
736 0.5 169 101 68 2410 0.513587 189 131 48
753 0.504425 228 215 9 2437 0.489189 181 133 56
771 0.486076 192 158 45 2467 0.503086 163 87 74
772 0.489703 214 200 23 2483 0.539185 172 82 65
781 0.487603 177 126 60 2488 0.542274 186 106 51
816 0.497297 184 133 53 2496 0.522099 189 125 48
821 0.493369 186 140 51 2501 0.496711 151 67 86
824 0.492958 175 118 62 2530 0.495468 164 94 73
874 0.553531 243 202 −6 2532 0.491667 236 243 1
919 0.504032 125 11 112 2538 0.501887 133 28 104
1129 0.5 186 135 51 2581 0.486141 228 232 9
1179 0.488701 173 117 64 2585 0.524 131 13 106
1185 0.571 348 372 −111 2612 0.504792 158 76 79
1187 0.510989 186 127 51 2618 0.489028 156 82 81
1249 0.497222 179 123 58 2717 0.555556 190 105 47
1274 0.502 251 263 −14 2732 0.571 140 8 97
1315 0.514368 179 111 58 2751 0.490667 184 138 53
1391 0.494005 206 180 31 2786 0.562 140 12 97
1401 0.490446 154 77 83 2831 0.603 155 20 82
1411 0.491803 180 129 57 2853 0.52214 283 305 −46
1444 0.495238 156 78 81 2861 0.522822 252 245 −15
1458 0.5 166 95 71 2876 0.635 223 114 14
1478 0.558074 197 116 40 2877 0.519651 238 221 −1
1587 0.485849 206 187 31 2879 0.7 168 3 69
1595 0.547414 127 −5 110 2884 0.486425 215 205 22
1604 0.489189 181 133 56 2894 0.494279 216 200 21
1642 0.603 225 136 12 2907 0.488889 220 213 17
1651 0.586 309 290 −72 2918 0.490028 172 114 65
1662 0.507576 134 27 103 2959 0.489362 230 233 7
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SA: The number bits in both SAM and the test set. SB: The number bits in the test set, but not SAM. SC: The number bits in SAM but not the test set.

2.2. Molecular Similarity

The connection between chemical structures and biological activities of different compounds has always been an interesting area for research [48]. Consequently, the implementation of different molecular similarity strategies in drug design and development have been competently increased effectively [49]. Many descriptors have been considered in molecular similarity studies.

The examined descriptors are of a molecular type, such as molecular weight (M.W.) [50], hydrogen bond donors (HBA) [51], hydrogen bond acceptors (HBD) [52], partition coefficient (ALog p), which is the ratio of the concentration of a substance in the lipid phase to the concentration in the aqueous phase when the two concentrations are at equilibrium [53], number of rotatable bonds [54], number of rings, and aromatic rings [55], as well as the molecular fractional polar surface area (MFPSA) [56]. The examined compound is represented as a binary array (number of binary bits) to be computed.

The mentioned descriptors were calculated for the FDA-approved drugs then compared with the co-crystallized ligand of 2′OMTase (SAM) using Discovery studio software.

Figure 1 represented the co-crystalized ligand (SAM) (red ball), compounds with good similarities (green balls), and compounds with diminished similarities (blue balls). The degree of molecular likeness or similarity between two compounds depends on a similarity coefficient that is utilized to compute a quantitative score. That calculated score is equivalent to the degree of similarity and is based on the computed values of several structural descriptors. Similarity between two compounds is inversely proportional to the calculated distance between them in the descriptor space [57]. In this work, the distances between the several descriptors were computed to determine descriptor similarity among test compounds and SAM [58]. The computed distances describe the shortest distance between two points. Typed graph distances (Figure 1) show the overall similarity of behavior of the FDA-approved drugs compared to SAM. The study preferred 26 compounds among the most suitable 30 metabolites (Figure 1 and Figure 2, and Table 2).

Figure 1.

Figure 1

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The molecular similarity of the examined compounds and SAM.

Figure 2.

Figure 2

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Twenty-six compounds with good molecular similarity with the co-crystallized ligand (SAM) of 2′OMTase (PDB ID: (6W4H).

Table 2.

Molecular descriptors of the examined 26 compounds and SAM.

Comp. ALog p MW HBA HBD Rotatable Bonds Rings Aromatic Rings MFPSA Minimum Distance
SAM −4.25 399.45 9 4 7 3 2 0.483 0
50 −1.38 297.27 9 4 3 3 2 0.508 0.768
56 −1.38 365.21 11 5 4 3 2 0.602 0.738
152 −0.77 287.21 8 3 5 2 2 0.502 0.836
186 −1.31 285.23 8 4 2 3 2 0.52 0.884
190 −1.04 435.43 11 4 7 2 1 0.576 0.874
214 −0.17 395.41 9 4 5 3 1 0.577 0.91
241 −1.88 267.24 8 4 2 3 2 0.539 0.877
310 −1.88 267.24 8 4 2 3 2 0.539 0.877
1129 −2.81 476.49 11 1 7 4 2 0.624 0.896
1187 −2.39 362.38 5 4 6 3 1 0.414 0.801
1444 −0.64 383.4 9 3 5 3 1 0.56 0.874
1478 −3.74 434.45 9 3 7 3 2 0.316 0.478
1913 −3.05 511.5 12 5 9 3 2 0.545 0.67
1995 −0.99 482.51 7 2 6 3 2 0.442 0.796
2017 −2.16 365.24 12 6 4 3 2 0.655 0.856
2036 −1.59 440.48 11 2 7 4 2 0.594 0.781
2042 −2.09 285.26 9 5 2 3 2 0.589 0.874
2176 −1.93 390.35 10 5 4 4 3 0.491 0.838
2376 −1.32 269.26 8 4 2 3 2 0.54 0.917
2396 −4.6 497.5 9 4 7 4 1 0.484 0.705
2467 −2.12 405.39 9 2 5 3 1 0.628 0.87
2532 −0.73 469.53 7 4 6 4 2 0.266 0.909
2612 −1.98 460.77 10 4 8 2 2 0.572 0.594
2732 −0.82 299.22 8 3 5 3 2 0.504 0.752
2831 −0.98 305.23 9 4 5 2 2 0.55 0.76
2879 −1.26 294.31 8 3 3 3 2 0.395 0.846
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ALog p: lipid–water partition coefficient, MWt: molecular weight, HBA: hydrogen bond acceptor, HBD: hydrogen bond donor, Rotatable bonds: any single non-ring bond, attached to a non-terminal, non-hydrogen atom, Rings: non-aromatic rings, MFPSA: molecular fractional polar surface area, Minimum Distance: the shortest distance between a tested compound and the reference one.

2.3. Docking Studies

Docking studies of the tested compounds were conducted using the MOE (Molecular Operating Environment) software [58] to understand the proposed binding mode and the orientations of such compounds with the prospective target 2′OMTase (PDB ID: (6W4H)).

The active site of 2′OMTase consists of some crucial amino acids which can form hydrogen bonds with the active ligands. These amino acids include: Asn6841, Gly6879, Gly6869, Asp6928, Asp6897, Met6929, and Cys6913. In addition, there are some hydrophobic amino acids which can be incorporated in hydrophobic attractions with the active ligand and the hydrophobic amnio acids such as Leu6898 and Met6929 (Figure 3).

Figure 3.

Figure 3

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Active site (3D and 2D) of 2′OMTase (PDB ID: (6W4H)).

The co-crystalized ligand s-adenosylmethionine (SAM) was used as a reference compound. First, the validation process was carried out to confirm the validity of the docking algorithm in obtaining accurate docking results. This was achieved by redocking the co-crystallized ligand (SAM) with 2′OMTase. The obtained low values of root mean square deviation (RMSD = 1.15 Å) between the native and redocked pose, in addition to the symmetrical superimposition in orientation between both the native (turquoise) and redocked (magenta) co-crystallized poses in Figure 4, guaranteed the valid performance of the docking protocol [36,38], in addition to the docking algorithm’s capability to obtain the reported binding mode of the co-crystalized ligand S-adenosylmethionine (SAM) [59].

Figure 4.

Figure 4

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Alignment of the co-crystallized ligand (turquoise) and the docking pose (rose) of the same ligand (SAM) in the active site of 2′OMTase.

In comparing the tested compounds, the binding free energy (ΔG) between the docked molecules and the active site, and also the proper binding mode, were properly considered. The estimated (ΔG) (binding free energies) of the investigated drugs and the reference molecule (SAM) against the 2′OMTase are presented in Table 3.

Table 3.

Binding free energies (calculated ΔG in kcal/mol) of the examined compounds and ligand SAM against 2′OMTase.

Comp. Name ΔG [kcal/mol]
SAM S-Adenosylmethionine −21.52
50 Arranon (Nelarabine) −13.84
56 Fludara (Fludarabine) −15.53
152 Tenofovir (PMPA) −13.58
186 Fludarabine −14.19
190 Azactam (aztreonam) −14.88
214 Cefdinir (cefdinir) −15.41
241 Adenosine −14.09
310 VIRA-A (vidarabine) −14.10
1129 Cefazolin −16.66
1187 Protirelin −18.68
1444 Ceftizoxime −10.99
1478 Xanthinol Nicotinate −16.19
1913 Calcium folinate −19.09
1995 Raltegravir −21.07
2017 Adenosine 5′-monophosphate −15.34
2036 Ceftezole −15.21
2042 Vidarabine −13.41
2176 Regadenoson −18.54
2376 2′-Deoxyadenosine −13.16
2396 Ertapenem −20.73
2467 Ceftizoxime −13.63
2532 Methylergometrine −20.46
2612 Thiamine pyrophosphate hydrochloride −18.03
2732 Besifovir −13.47
2831 Tenofovir −14.36
2879 Puromycin aminonucleoside −15.33
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The predicted binding mode of the redocked ligand (SAM) yielded an affinity value of −21.52 kcal/mol. It interacted with its 6-amino-purin moiety and formed one hydrogen bond with Asp6912, in addition to hydrophobic interactions with Leu6898 and Met6929. Moreover, the di hydroxy tetrahydrofuran moiety formed two hydrogen bonds with Tyr6930, and the sulfur atom was involved in electrostatic interaction with Asp6928. Additionally, the terminal NH2 group was found to form one hydrogen bond with Gly6869, and two electrostatic interactions with Asp6928. Finally, the terminal carboxylic group formed one hydrogen bond with Gly6879 (Figure 5).

Figure 5.

Figure 5

Figure 5

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3D and 2D binding mode of the redocked ligand (SAM) in the active site of the target protein.

From the tested compounds, seven members showed good binding mode with high binding energy. These compounds are 1187 (Protirelin), 1913 (Calcium folinate), 1995 (Raltegravir), 2176 (Regadenoson), 2396 (Ertapenem), 2532 (Methylergometrine), and 2612 (Methylergometrine).

Compound 1187 has a docking score of −18.68 kcal/mol and formed four hydrogen bonds with the crucial amino acids in the active site of the 2′OMTase enzyme. The pyrrolidin-2-one moiety formed two hydrogen bonds with Asp6928 and Lys6968 via its NH and C=O groups, respectively. Furthermore, the NH group of the central amide moiety formed one hydrogen bond with Tyr6930. Moreover, the (S)-pyrrolidine-2-carboxamide moiety formed one hydrogen with Tyr6930 and two hydrophobic bonds with Met6929 and Leu6898 (Figure 6).

Figure 6.

Figure 6

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3D and 2D binding mode of compound 1187 in the active site of the target protein.

Compound 1913 has a docking score of −19.09 kcal/mol, forming six hydrogen bonds within the active site. The 2-amino-4-hydroxy-7,8-dihydropteridine-5(6H)-carbaldehyde moiety formed three hydrogen bonds with Cys6913, Gly6911, and Asp6912 via its NH2, OH groups, and the hetero nitrogen atom at 3-position. In addition, the glutamic acid moiety formed three hydrogen bonds with Asn6841, Gly6879, and Gly6871. Moreover, a carboxylate group of glutamic acid moiety formed one electrostatic interaction with Asp6873 (Figure 7).

Figure 7.

Figure 7

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3D and 2D binding mode of compound 1913 in the active site of the target protein.

With a docking score of −21.07 kcal/mol, compound 1995 fit well into the active site of the 2′OMTase enzyme and formed four hydrogen bonds. The fluorobenzene formed one hydrogen bond with Cys6913 and one hydrophobic interaction with Leu6898. The carbonyl group of the amide moiety formed one hydrogen bond with Tyr6930. The carbonyl group of 5-hydroxy-3-methylpyrimidin-4(3H)-one moiety formed one hydrogen bond with Asn6899. In addition, the 5-hydroxy-3-methylpyrimidin-4(3H)-one moiety formed hydrophobic bond with Gly6871. The NH group of 2-methyl-1,3,4-oxadiazole moiety formed one hydrogen bond with Lys6844 (Figure 8).

Figure 8.

Figure 8

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3D and 2D binding mode of compound 1995 in the active site of the target protein.

Compound 2176 showed a binding energy of −18.54 kcal/mol. This compound formed four hydrogen bonds in the active site of the target protein. The ribose sugar moiety formed three hydrogen bonds with Gly6879, Ala6870, and Gly6871. Furthermore, the NH group of the 9H-purin-6-amine moiety formed a hydrogen bond with Ty6930. Moreover, the N-methyl-1H-pyrazole-4-carboxamide moiety was incorporated in hydrophobic interaction with Met6929 and one electrostatic interaction with Asp6897 (Figure 9).

Figure 9.

Figure 9

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3D and 2D binding mode of compound 2176 in the active site of the target protein.

Compound 2396 (Ertapenem) has a docking score of −20.73 kcal/mol and created five hydrogen bonds with the crucial amino acids in the active site of the 2′OMTase enzyme. The benzoic acid moiety formed one hydrogen bond with Cys6913 via its carboxylic group, and two hydrophobic interactions with Met6929 and Leu6898. Furthermore, the NH group formed another hydrogen bond with Asp6897. Moreover, the carboxylate group at 2-position of 1-azabicyclo[3.2.0]hept-2-ene moiety formed one hydrogen and one electrostatic bond with Asp6873. The terminal hydroxyl group formed two hydrogen bonds with Asp6928 and Gly6869 (Figure 10). Although Ertapenem showed a binding energy less than Raltegravir, it showed an ideal binding mode like that of the co-crystallized ligand (SAM). It occupied all sub pockets of the active site and bound the crucial amino acids. Accordingly, it was used for further in silico testing via MD simulations.

Figure 10.

Figure 10

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3D and 2D binding mode of compound 2396 in the active site of the target protein.

The binding mode of compound 2532 (affinity value of −20.46 kcal/mol), which is extremely close to ligand SAM, revealed that the amide group formed two hydrogen bonds with fundamental amino acids Asp6928 and Gly6871. In addition, the OH group formed another hydrogen bond with the amino acid Asn6841. Furthermore, the terminal ethyl moiety was incorporated in hydrophobic interaction with His6867 and Tyr6845. The phenyl ring formed an electrostatic attraction with Asp6897 (Figure 11).

Figure 11.

Figure 11

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3D and 2D binding mode of compound 2532 in the active site of the target protein.

As demonstrated in Figure 12, compound 2612 had a high potential binding affinity (ΔG = −18.03 kcal/mol) with 2′OMTase enzyme active site. The strong binding affinity is assumed to be due to the formation of four hydrogen bonds in addition to many hydrophobic and electrostatic attractions. The terminal diphosphate moiety formed four hydrogen bonds with Gly6871, and Asn6841. It also formed three electrostatic attractions with Asp6928. In addition, the 4-methylthiazol-3-ium moiety formed a hydrophobic interaction with Gly6871 and an electrostatic attraction with Asp6897. Furthermore, the 2-methylpyrimidin-4-amine moiety was incorporated in a hydrophobic attraction with Phe6947.

Figure 12.

Figure 12

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3D and 2D binding mode of compound 2612 in the active site of the target protein.

2.4. Molecular Dynamic Simulation

Molecular dynamics (MD) simulations studies can be applied to examine almost every kind of biomacromolecule (protein, nucleic acid, or carbohydrate) of biological significance [60]. The MD experiments can afford abundant information regarding the dynamic structural of the studied system [61]. Additionally, it contributes large amounts of energetic data. Such data are essential to understand the structure–function relationship of the examined ligand, its target protein, as well as the protein–ligand interactions. Correspondingly, MD studies could be a vital guide in the drug design and discovery processes [62].

The dynamic, as well as conformational shifts of backbone atoms of 2′OMTase, Ertapenem in addition to 2′OMTase—Ertapenem complex, were estimated through the calculation of the root mean square deviation (RMSD) to distinguish the stability of the examined molecules before and after binding. RMSD investigation demonstrates both of conformational and dynamics changes [63] that occur after binding. Excitingly, the 2′OMTase—Ertapenem complex demonstrated low RMSD values with slight fluctuations from 40–70 ns~ and was stabilized later until the end of the study (Figure 13A) Fortunately, this slight fluctuation did not affect the integrity of the 2′OMTase—Ertapenem complex as the next experiments (Rg and SASA) did not record major changes in this time. However, the H-binding showed that the number of H-bonds decreased in this period (40–70 ns), from 3–4 bonds to 2 bonds. The study demonstrated that the number of H-bonds became 3–4 again after 70 ns. The flexibility of the evaluated complex was measured in the terms of RMSF to identify the fluctuated region of 2′OMTase during the 100 ns of the simulation. Favorably, the binding of Ertapenem does not make 2′OMTase very flexible (Figure 13B). The compactness of the 2′OMTase—Ertapenem complex was investigated by the computation of radius of gyration (Rg) of the evaluated enzyme. Complementarily, the Rg exhibited was noticed to be of lower value during the 100 ns of the experiment compared to the starting time (Figure 13C). In a similar manner, SASA (solvent accessible surface area) denotes the interaction between 2′OMTase—Ertapenem complex, and the surrounding solvents was measured. SASA value is an excellent indicator to the conformational changes that occurred during the simulation experiment because of binding interactions. Of note, the surface area of 2′OMTase (Figure 13D) displayed a considerable reduction in SASA values through the simulation time compared to the starting point. Finally, hydrogen bonding, as an essential factor in the binding of 2′OMTase—Ertapenem complex, was estimated. The greatest number of H-bonds that formed between 2′OMTase—Ertapenem complex was up to three H-bonds (Figure 13E).

Figure 13.

Figure 13

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Results of M D simulations of 2′OMTase—Ertapenem complex; (A) RMSD, (B) RMSF, (C) Rg, (D) SASA, and (E) H-bonding.

2.5. Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) Studies

The binding free energy of 2′OMTase—Ertapenem complex was investigated in the last 20 ns of the MD run with an interval of 100 ps from the produced MD trajectories. The MM/PBSA method was utilized with the MmPbSaStat.py script to compute the average free binding energy as well as its standard deviation/error. Interestingly, as shown in Figure 14A, Ertapenem demonstrated a low binding free energy with a value of −43 KJ/mol (equivalent to −10.28 kcal/mol) with 2′OMTase. The share of the different amino acid residues of 2′OMTase in respect of the binding energy compared to the binding with Ertapenem. Total binding free energy decomposing of the 2′OMTase—Ertapenem complex into per residue share energy was achieved. The following amino acid residues of 2′OMTase, GLY-6871, LEU-6898, ASP-6928, MET-6829, and GLU-7001, contributed the binding energy with values that are more than −3 KJ/mol (Figure 14B).

Figure 14.

Figure 14

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MM-PBSA study of 2′OMTase—Ertapenem; (A): total binding free energy, (B): analyzed binding free energy per amino acid residue.

3. Method

3.1. Molecular Similarity Detection

Discovery studio 4.0 software was used (see method part in Supplementary Materials).

3.2. Fingerprint Studies

Discovery studio 4.0 software was used (see method part in Supplementary Materials).

3.3. Docking Studies

Docking studies were performed against target enzymes using Discovery studio software [64] (see method part in Supplementary Materials).

3.4. Molecular Dynamics Simulation

The system was prepared using the web-based CHARMM-GUI [65,66,67] interface utilizing CHARMM36 force field [68] and NAMD 2.13 [69] package. The TIP3P explicit solvation model was used (see Supplementary Materials).

3.5. MM-PBSA Studies

The g_mmpbsa package of GROMACS was utilized to calculate the MM/PBSA (See Supplementary Materials).

4. Conclusions

Seven FDA-approved compounds (Protirelin, (1187), Calcium folinate (1913), Raltegravir (1995), Regadenoson (2176), Ertapenem (2396), Methylergometrine (2532), and Thiamine pyrophosphate hydrochloride (2612), out of 3009 were elected as the strongest 2′OMTase inhibitors. The selection of compounds was based on a multistep in silico study. The utilized studies included molecular fingerprints and structure similarity studies against SAM, the co-crystallized ligand of the targeted enzyme in addition to molecular docking studies. Ertapenem (2396) was subjected to MD simulation studies (RMSD, RMSF, Rg, SASA, and H-bonding) for 100 ns, confirming the excellent binding. These encouraging results could be a step to discover an effective cure against COVID-19 through further in vitro and in vivo studies for the pointed candidates.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/molecules27072287/s1, The method of Fingerprints; Molecular Similarity; Docking; Molecular dynamics; and MMPBSA studies.

Click here for additional data file. (125.8KB, zip)

Author Contributions

Conceptualization, I.H.E. and A.M.M.; Funding acquisition, B.A.A.; Project administration, I.H.E. and A.M.M.; Software, I.H.E., M.S.A., A.M.S. and E.B.E.; Writing—review and editing, E.B.E., B.A.A., A.-A.M.M.E.-A. and A.M.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Princess Nourah Bint Abdulrahman University Researchers Supporting Project number (PNURSP2022R142), Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data is contained in the published article.

Conflicts of Interest

The authors declare no conflict of interest.

Sample Availability

Samples of the compoundsre not available from the authors.

Footnotes

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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