Chaetomugilins and Chaetoviridins—Promising Natural Metabolites: Structures, Separation, Characterization, Biosynthesis, Bioactivities, Molecular Docking, and Molecular Dynamics

Fungi are recognized as luxuriant metabolic artists that generate propitious biometabolites. Historically, fungal metabolites have largely been investigated as leads for various therapeutic agents. Chaetomugilins and the closely related chaetoviridins are fungal metabolites, and each has an oxygenated bicyclic pyranoquinone core. They are mainly produced by various Chaetomaceae species. These metabolites display unique chemical features and diversified bioactivities. The current review gives an overview of research about fungal chaetomugilins and chaetoviridins regarding their structures, separation, characterization, biosynthesis, and bioactivities. Additionally, their antiviral potential towards the SARS-CoV-2 protease was evaluated using docking studies and molecular dynamics (MD) simulations. We report on the docking and predictive binding energy estimations using reported crystal structures of the main protease (PDB ID: 6M2N, 6W81, and 7K0f) at variable resolutions—i.e., 2.20, 1.55, and 1.65 Å, respectively. Chaetovirdin D (43) exhibited highly negative docking scores of −7.944, −8.141, and −6.615 kcal/mol, when complexed with 6M2N, 6W81, and 7K0f, respectively. The reference inhibitors exhibited the following scores: −5.377, −6.995, and −8.159 kcal/mol, when complexed with 6M2N, 6W81, and 7K0f, respectively. By using molecular dynamics simulations, chaetovirdin D’s stability in complexes with the viral protease was analyzed, and it was found to be stable over the course of 100 ns.


Introduction
Fungi are a wealthy and substantial pool of many secondary metabolites with many different structures and diversified bioactivities [1][2][3][4][5][6][7][8][9][10][11]. These metabolites attract much attention as lead metabolites for pharmaceutical agents, and for plant protection [1,[8][9][10][11][12][13][14][15][16]. Fungal polyketides (FPKs) represent one of the largest and most structurally diverse groups of fungal metabolites. They range from simple and aromatic to highly macrocyclic and complex [10,13,17]. Their backbone is biosynthesized by the condensation of acyl-CoA thioesters [18]. Their structural variations originate from differences in the starting and extending units, methylation pattern, chain length, degree of reduction, and modifications by tailoring enzymes [19]. Mycotoxins and pigments are among the FPKs that have had remarkable contributions in the field of drug discovery [20]. Azaphilones (azaphilonoids or isochromenes) are fungal pigments belonging to FPKs. Structurally, they have an isochromene skeleton that contains an oxygenated bicyclic pyrano-quinone core and a quaternary carbon center [21]. Biosynthetically, the O atom in the pyran chromophore could be exchanged by an N atom in the existence of primary amines, and accordingly, the pigment color will shift to red [22]. They are produced by various basidiomycetous and ascomycetous fungi, including Chaetomium, Penicillium, Aspergillus, Talaromyces, Phomopsis, Monascus, Emericella, Epicoccum, Hypoxylon, and Pestalotiopsis, where they are accountable for the green, red, or yellow color of mycelia and/or fruiting bodies [23]. They possess myriad bioactivities: antitumor, cytotoxic, antimicrobial, anti-inflammatory, antioxidant, enzyme inhibitory, antiviral, insecticidal, and antileishmanial [24]. Chaetomugilins and closely related chaetoviridins are azaphilones featuring a C-7-methyl group and C-5 chlorineexcept for chaetomugilins T (29) and U (30)-and a C-3-branched pentenyl chain ( Figure 1). However, chaetomugiline P (24) differs from the others in that it has no substituent at C-7 and a methyl group at C-5. 3-Methyl-4-hydroxy-1-pentyl chains at C-3 are found in some chaetomugilins and chaetoviridins. Sometimes, they bear a five-membered lactone and/or a fused tetrahydrofuran/δ-lactone [25]. The 7-OH group can have (S) or (R) configuration, though (7S) isomers are the most common among these metabolites. On the other hand, the 7-hydroxyl can be part of a furanone ring [26]. These fungal metabolites are produced by various Chaetomium species. Chaetoviridins were firstly reported by Takahashi et al. from Chaetomium globosum var. flavoviride [27]. Chaetomugilins are known as cytotoxic metabolites, whereas chaetoviridins have antifungal and antibiotic activities [28]. Recently, these metabolites have been recognized as a unique family of fungal metabolites in view of their interesting structural features and prominent bioactivities, which could provoke enormous attention from natural products chemists and pharmacologists. The current review focuses on chaetomugilins and chaetoviridins from fungal sources, including isolation, structural characterization, biosynthesis, and bioactivities (Tables 1 and 2). Some of the metabolites have been reported with the same names, despite having different structures and molecular formulae-e.g., chaetomugilin S, chaetoviridin B, and chaetoviridin G. Moreover, the structures of some compounds have been revised and renamed: in such cases, both structures have been drawn in the figures, highlighting the new names and corresponding references. Additionally, the emergence of the COVID-19 pandemic motivated us to investigate the potential of these metabolites as antiviral agents towards SARS-CoV-2 using docking studies and molecular dynamics (MD) simulations. Literature searching was carried out using diverse databases-Web of Science, PubMed (MedLine), GoogleScholar, Scopus, and SciFinder-and different publishers-Springer-Link (Cham,
The absolute configurations of these metabolites have been established with the aid of optical rotation sign, X-ray crystallography, CD (circular dichroism), the modified Mosher's method, and chemical transformation studies, including derivatization and degradation [22,27,35,41,48,60,75]. It has been reported that the absolute configuration at C(7) controls signs of the specific rotation [35]. Compounds with (S) C-11 and C-7 had negative optical rotation values; however, when C-7 was (R), the sign switched to positive with the same magnitude [50]. The absolute (S) configuration at C-7 was determined by the negative Cotton effect in the CD spectrum [58]. Mass spectra of these compounds displayed an isotopic peak [M+H] + /[M+H+2] + in a ratio 3:1, characterizing the presence of a single chlorine atom. Moreover, their IR spectrum exhibited characteristic bands for a hydroxyl group (3405-3450 cm −1 ), lactone (1718-1780 cm −1 ), and α,β-unsaturated ketone (1616-1684 cm −1 ). Characteristic UV bands of a highly extended conjugation system were observed at 283-429 nm.  Table 2). It is noteworthy that compounds 7 and 13 exhibited remarkable cytotoxicity towards P388 and HL-60 cell lines (IC 50 3.6 and 3.3 µM and 2.7 and 1.3 µM, respectively), nearly equal to that of 5-fluorouracil (IC 50 1.7 and 2.7 µM, respectively). While other compounds had moderate to weak cytotoxicity (IC 50 ranging from 6.8 to 24.1 µM) [38,39]. Further, 2, 7, and 13 displayed selective cytotoxicity towards a panel of 39 disease-related human cell lines, including breast, CNS, colon, lung, melanoma, ovary, kidney, stomach, and prostate cancer cells with range and delta values of 2 (1.24 and 1.13, respectively), 7 (1.19 and 0.71, respectively), and 13 (1.21 and 1.97, respectively) [38,40]. It was suggested that the existence of C-12-hydroxyl and C-3-methoxyl groups had little effect on the activity [40]. Evaluation of the differential cytotoxicity patterns using COMPARE revealed that the modes of action for 2, 7, and 13 might be different from those of other anticancer drugs [40]. On the other hand, chaetomugilins A (2) biosynthesized by C. globosum Z1 isolated from Broussonetia papyrifera bark had no in vitro effectiveness towards SMMC-7721, MG-63 and A-549 cell lines (IC 50 > 50 µg/mL) in the MTT assay in comparison to doxorubicin [44].    C. globosum OUPS-T106B-6 isolated from M. cephalus yielded two new metabolites that demonstrated moderate cytotoxicity towards HL-60 and P388 cell lines (IC 50 ranged from 10.3 to 24.1 µM, respectively), compared to 5-FU (IC 50 2.7 and 1.7 µM) in the MTT assay [41]: chaetomugilins G (14) and H (15).
Hu et al. proved that chaetomugilin J (18) combined with low-dose cisplatin decreased cell viability and boosted cisplatin-produced apoptosis in ovarian A2780 cells independently of the endoplasmic reticulum apoptotic pathway. It significantly induced mitochondrial dysfunction and apoptosis via increasing the intracellular and mitochondrial ROS levels and decreasing mitochondrial membrane potential. It also prohibited parkin/PINK1 induced mitophagy, resulting in weakening the mitophagy protective effect that led to apoptosis and increased sensitivity to cisplatin [34]. Chaetomugilin D (8), chaetoviridin A (31), and chaetoviridin E (44) purified from a deep sea-derived Chaetomium sp. NA-S01-R1 displayed moderate to weak cytotoxicity toward HeLa, A549, and HepG2, in comparison to doxorubicin (IC 50 0.1-1.1 µM) using the CCK-8 assay [25] (Figure 7). Additionally, chaetoviridin A (31) and chaetoviridin E (44) were inactive towards AGS and MGC803 [71].
C. globosum CEF-082, isolated from cotton plants, produced chaetoviridin A (31), which possesses significant antifungal activity towards Verticillium dahlia, which causes cotton Verticillium wilt (CVW). It induced mycelial deformation and cell necrosis, increased NO and ROS production, prohibited the germination of microsclerotia of V. dahliae, and boosted the cotton defensive response [69].

Phytotoxic Activity
The EtOAc extract of C. globosum associated with Amaranthus viridis yielded chaetomugilin D (8) and chaetomugilin J (18), which exhibited phytotoxic potential against lettuce (Lactuca sativa) seed germination with IC 50 24.2 and 22.6 ppm, respectively, for root growth inhibition, and IC 50 27.8 and 21.9 ppm, respectively, for shoot growth inhibition. The results revealed the potential of these metabolites as herbicides or weedicides that can replace hazardous synthetic compounds [51]. Chaetomugilin A (2), D (8), S (28), I (16), J (18), Q (25), and O (23) isolated from C. globosum TY1 exhibited allelopathic activity towards Brassica campestris, Cucumis sativus, Eruca sativa, Daucus carota, Lactuca sativa, Scrophularia ningpoensis, Brassica rapa, and Spinacia oleracea. Among them, 23 exhibited higher germination and root and shoot elongation inhibitory potential with lower IC 50 values and higher response indexes than glyphosate (positive control). Moreover, 2, 8, and 28 exhibited similar or better inhibitory effects than glyphosate. At the same time, 2, 8, and 23 were more powerful growth inhibitors than 16, 18, and 25, which could be attributed to the existence of a tetrahydrofuran moiety. On the other hand, 23 had a higher growth-suppression effect than those of 2, 8, and 28, suggesting that the lactone rings may reduce the inhibitory effects [45].

Cholesteryl Ester Transfer Protein Inhibitory Activity
CETP allows the transfer and exchange of neutral lipids such as CE (cholesteryl ester) and TG (triacylglycerol) between plasma and lipoproteins. It is proven to play important role in atherosclerosis [79]. Tomoda et al. reported that chaetoviridin B (37) showed CETP (cholesteryl ester transfer protein) inhibitory activity with an IC 50 < 6.3 µM, whereas chaetoviridin A (31) had moderate inhibitory activity (IC 50 31.6 µM) [80]. It was indicated that the existence of an electrophilic enone(s) and/or ketone(s) at both C-8 and C-6 of isochromane core is substantial for eliciting activity [80].

Anti-SARS-CoV-2 Activity
The COVID-19 pandemic has affected global health since 2019. COVID-19 can lead to acute respiratory distress syndrome [81]. It is produced by a novel type of coronavirus (CoV) called SARS-CoV-2 that was first found in Wuhan City, China, and then spread worldwide [82,83]. It is considered a highly pathogenic CoV in the human population. The SARS-CoV-2 genome encodes two polyproteins which are processed by a 3C-like protease (3CLpro) and a papain-like protease [84]. 3CLpro (3C-like protease) and PLpro (papain-like protease) are needed for processing the polyproteins into mature nonstructural proteins, such as helicase and RdRp (RNA-dependent RNA polymerase), which are substantial for viral replication and transcription [85]. 3CLpro has high substrate specificity and is also referred to as Mpro (main protease) [86]. 3CLpro's substrate specificity makes this enzyme an ideal target for developing broad-spectrum antiviral agents [87]. Its inhibitors are expected to have selective toxicity towards the virus [88].
Fungi are a treasure that can provide a remarkable pool of secondary metabolites with antiviral activities [89]. The characterization and discovery of antiviral fungal metabolites is an emerging and promising research field. Recently, many reports have been published on the structure-based virtual screening approach for the repurposing of natural metabolites, hoping to accelerate and assist in the discovery of agents for COVID-19 treatment [82]. We carried out a computational study on the reported fungal chaetomugilins and chaetoviridins was carried out to identify their 3CLpro inhibitory potential, using docking calculations and MD simulations (Tables 3-7). Three crystal structures containing non-covalent inhibitors for the protease (PDB entry: 6W81, 6M2N, and 7K0F) were selected. All the listed metabolites were docked with extra precision for maximum accuracy. The docking method was validated by redocking the inhibitors that co-crystallized with 6W81, 6M2N, and 7K0F; and RMSD values were within an acceptable range and less than 1.50 Å. All the redocked inhibitors revealed the same binding interaction with the active site in the original pose. Further, in silico ADMET (drug absorption, distribution, metabolism, excretion, and toxicity) predictions of the properties of the investigated compounds were carried out. Finally, a molecular dynamics simulation was conducted to evaluate the nature of the ligand-target interaction under simulated physiological conditions for the most compatible drug-like molecule that could be used in pursuit of a truly adequate medication for COVID-19.

Preparations of Ligands and Proteins
By using LigPrep, the conversion of 2D structures to 3D, tautomerization, and ionization yielded 254 minimized 3D structures. The minimized 3D structures were used for docking with the crystal structure of the 3CL hydrolase (Mpro). Preparation of the viral protease (6M2N, 6W81, and 7K0f) by the Protein Preparation Wizard tool optimized the H-bonding network and minimized the geometry. Assurance of assigning the proper formal charges and force field treatments was achieved by adding missing hydrogens and correct ionization states (Figure 9).

Molecular Docking Studies
After defining the grid box in the prepared viral protease via the Receptor Grid Generation tool of Glide in Maestro, the prepared 3D molecular structures were docked into the co-crystallized inhibitor binding site of the viral protease. Table 3 shows the results of the top-score docked ligands chosen based on the most negative docking scores. These scores represent the best bound ligand conformations and relative binding affinities. Chaetovirdin D (43) exhibited the highly negative docking scores of −7.944, −8.141, and −6.615 kcal/mol, complexed with 6M2N, 6W81, and 7K0f, respectively. The reference inhibitor exhibited the following scores: −5.377, −6.995, and −8.159 kcal/mol, complexed with 6M2N, 6W81, and 7K0f, respectively.
The docking analysis was updated by re-docking the selected chaetomugilins and chaetoviridins with the three crystal structures of the 3CL pro-hydrolase (PDB ID: 6M2N, 6W81, and 7K0f) at variable resolutions, 2.20, 1.55, and 1.65A, respectively. Analysis of the docking scores of these compounds with the inhibitor binding sites of 2019-nCoV main protease (PDB ID: 6M2N, 6W81, and 7K0f) revealed different docking scores, and hence binding affinities (Tables 4-6). These differences can be attributed to the differences in the

Molecular Docking Studies
After defining the grid box in the prepared viral protease via the Receptor Grid Generation tool of Glide in Maestro, the prepared 3D molecular structures were docked into the co-crystallized inhibitor binding site of the viral protease. Table 3 shows the results of the top-score docked ligands chosen based on the most negative docking scores. These scores represent the best bound ligand conformations and relative binding affinities. Chaetovirdin D (43) exhibited the highly negative docking scores of −7.944, −8.141, and −6.615 kcal/mol, complexed with 6M2N, 6W81, and 7K0f, respectively. The reference inhibitor exhibited the following scores: −5.377, −6.995, and −8.159 kcal/mol, complexed with 6M2N, 6W81, and 7K0f, respectively.
The docking analysis was updated by re-docking the selected chaetomugilins and chaetoviridins with the three crystal structures of the 3CL pro-hydrolase (PDB ID: 6M2N, 6W81, and 7K0f) at variable resolutions, 2.20, 1.55, and 1.65A, respectively. Analysis of the docking scores of these compounds with the inhibitor binding sites of 2019-nCoV main protease (PDB ID: 6M2N, 6W81, and 7K0f) revealed different docking scores, and hence binding affinities (Tables 4-6). These differences can be attributed to the differences in the grid formation due to the presence of different inhibitors in the binding sites of the three crystal structures.
Analysis of the docking of 43 revealed that it interacted through hydrogen bonds ( Figure 10) with the binding site residues of SARS-CoV-2 main protease (6W81). The binding site residues Asn141, Gly142, and Thr189 of the viral protease exhibited hydrogen bonding with the various hydroxyl groups of 43. Additionally, 43 interacted through hydrogen bonds ( Figure 11) with the binding site residues of SARS-CoV-2 main protease (6M2N). The binding site residues Asn142 and Thr190 of the viral protease showed hydrogen bonding with the various hydroxyl groups of 43. Its interactions through hydrogen bonds with the binding site residues of SARS-CoV-2 main protease (7K0F) are shown in Figure 12 Table 7. ADMET analysis describes and determines the biological function, drug-likeness, physicochemical characters, and expected toxicity of compounds. This is meant to evaluate the usefulness of the molecules. The examined descriptors, such as drug-likeness, molecular weight, solvent accessible surface area, dipole moment, hydrogen bond acceptors, donor traits, aqueous solubility, octanol/water coefficient, binding to hu-man serum albumin, number of likely metabolic reactions, brain-blood partition coefficient, human oral absorption, IC 50 value for blockage of HERG K + channels, central nervous system activity, and number of reactive functional groups, were predicted for the reported metabolites. The values obtained for all the compounds are in the recommended ranges.

Molecular Dynamics Simulation
The docking studies took a static view for the binding of each molecule in the active site of the protein. A molecular dynamics (MD) simulation computes the atoms movements over time. By using Desmond software, the stability and frequency of the 43 complex with the proteases-PDB ID 6M2N, 6W81, and 7K0f-were studied. Three MD simulations were run for complexes with 43 for 100 ns of simulated time; the complexes' structures were optimized at pH 7.0 ± 2.0. Complex stability was checked by analysis of the interaction map and the RMSD (root mean square deviation) plot of the ligand and protein.
The RMSD plots in Figure 13a for the chaetovirdin D-SARS-CoV-2 main protease (PDB ID 6W81) complex, Figure 13b for the chaetovirdin D-SARS-CoV-2 main protease (PDB ID 7K0F) complex, and Figure 13c for the chaetovirdin D-SARS-CoV-2 main protease (PDB ID 6M2N) indicate that the complexes tended to stabilize during the simulations (100 ns) with respect to a reference frame at time 0 ns. There were slight fluctuations during the simulations, but within the permissible range of 1-3 Å; hence, they can be considered non-significant. Since the RMSD plots of 43 and protein backbone lie over each other, the formation of a stable complex can be inferred.  The simulated time of 100 ns shows the formation of a stable complex without any significant conformational changes in protein structure. Figure 14a shows the residue interactions of chaetovirdin D with SARS-CoV-2 main protease (PDB ID 6W81) (the docked poses were retained during the simulation of 100 ns)i.e., molecular interactions with His41, Asp141, and Glu165 residues. Moreover, a hydrophobic interaction was also established between the Leu165 and aliphatic hydrocarbons of 43. In Figure 14b, the viral protease (PDB ID 7K0F)-chaetovirdin D contacts over the course of 100 ns are categorized into water bridges, hydrogen bonds, and hydrophobic interactions. The initial docked pose of 43 shows that the important hydrogen bonds (Thr24, His41, Asn142, Gly143, Ser144, Cys145) did not change during the MD simulation. Hydrogen bonding with residue Cys145 was retained for more than 70% of the simulation time. Figure 14c reveals that the viral protease (PDB ID 6M2N)-chaetovirdin D contacts over the course of 100 ns were categorized into water bridges, hydrogen bonds, and hydrophobic interactions. The bar chart shows that hydrogen bonds, hydrophobic contacts, and water bridges prevailed during the course of the simulation. The important hydrogen bonds observed in the initial docked pose of 43 (Thr26, His41, Glu166, Thr190, Gln192) did not change during the MD simulation. Hydrogen bonding with residue Thr26 was retained for more than 5% of the simulation time.

Materials and Methods Preparation of PDB Structures
The three PDB structures (PDB ID: 6M2N, 6W81, and 7K0f) were downloaded from the Protein Data Bank (Protein Data Bank; available online, prepared, and optimized by using "Protein preparation wizard" tool of Schrödinger suite (Schrödinger Release 2021-4: LigPrep, Schrödinger, LLC, New York, NY, USA, 2021) [90]. For this purpose, the bond orders for untemplated residues and known HET groups were assigned and hydrogens were added. Bonds to metals were broken, zero-order bonds between metals and nearby atoms were added, and formal charges to metals and neighboring atoms were corrected. Disulfide bonds were created. Water molecules beyond 5 Å from HET groups were deleted. For ligands, cofactors and metals het states were generated at pH 7.0 ± 2.0 using LigPrep (Schrödinger Release 2021-4: LigPrep, Schrödinger, LLC, New York, NY, USA, 2021). Finally, H-bonds were optimized by using PROPKA [91] at pH 7.0, water molecules beyond 3 Å from HET groups were removed, and restrained minimization was done using the OPLS4 force field.

Predictions of ADME Properties
The ADME properties and drug-likeness of selected compounds were determined in terms of distribution, absorption, metabolism, excretion, etc., via the QikProp module of Maestro Schrodinger (Schrödinger Release 2021-4: QikProp, Schrödinger, LLC, New York, NY, USA, 2021).

Receptor Grids Generation and Docking
Glide (Schrödinger Release 2021-4: Glide, Schrödinger, LLC, New York, NY, USA, 2021) was utilized for both grid generation and ligands docking. For docking of fiftythree fungal chaetomugilins and chaetoviridins, three grids were generated using the PDB: 6M2N, 6W81, and 7K0f. For the first grid of PDB 6M2N, the binding region was defined by selecting 3WL. For the second grid PDB 6W81, the binding region was defined by selecting X77. For the third grid PDB 7K0f, the binding region was defined by selecting VR4. The non-polar atoms were set for the VdW radii scaling factor to 1.0, and the partial charge cut-off was 0.25. The ligands docking was performed by using the "ligand docking" tool of Schrödinger suite [92]. The selected protocol was standard precision (SP), the ligand sampling method was flexible, and all the other settings were maintained as default.  6M2N, 6W81, and 7K0f were retrieved from docking results and first tuned through the "System Builder" tool. The solvent model TIP3P and then orthorhombic shape box shape were selected. The side distances box was set to 10 Å, and the system was neutralized by adding Na + ions. The MD calculations were run for 100 ns per trajectory, with the number of atoms, pressure, and the temperature kept maintained constant (NPT ensemble). Pressure was set to 1.01325 bar and temperature 300.0 K, and the force field was set as OPLS4.

Biosynthesis of Chaetomugilins and Chaetoviridins
The biosynthetic studies revealed that these metabolites are generated via a polyketide pathway [93][94][95][96]. Their main polyketide chain was produced from malonate and acetate units in a conventional way [93,95]. Briefly, a reduced triketide chain (I) was the starting unit to give the aromatic intermediate II, which was processed by the halogenase, followed by hydroxylation-stimulated cyclization catalyzed by monooxygenase to yield cazisochromene (III, chloropyranoquinone) [96]. Then, the addition of an oxidized triketide unit (IV) to III by acyltransferase formed the pyranoquinone V. The latter underwent a Knoevenagel reaction, resulting in chaetoviridin A (31). Chaetoviridin A (31) was converted into other chaetomugilins and chaetoviridins through reductions, oxidations, rearrangements, or reactions with amines [93] (Scheme 1).

Conclusions
Fungi are important sources of natural polyketide pharmaceuticals with structural complexities that make them interesting and beneficial biometabolites. Chaetomugilins and chaetoviridins are azaphilone derivatives that are mainly sourced from various Chaetomaceae species. In this work, fifty-six metabolites were isolated from four species, C. globosum, C. cochliodes, C. siamense, C. elatum, and C. subafine, in addition to unidentified Chaetomium species. Most of them were from C. globosum, as shown in Figure 15. The largest quantities of these metabolites were found in 2011 (18 compounds), 2009 (16 compounds), and 2017 (14 compounds) (Figure 16).

Conclusions
Fungi are important sources of natural polyketide pharmaceuticals with structural complexities that make them interesting and beneficial biometabolites. Chaetomugilins and chaetoviridins are azaphilone derivatives that are mainly sourced from various Chaetomaceae species. In this work, fifty-six metabolites were isolated from four species, C. globosum, C. cochliodes, C. siamense, C. elatum, and C. subafine, in addition to unidentified Chaetomium species. Most of them were from C. globosum, as shown in Figure 15. The largest quantities of these metabolites were found in 2011 (18 compounds  These metabolites have been evaluated for diverse bioactivities, such as cytotoxic, antimicrobial, phytotoxic, antimalarial, anti-mycobacterial, anti-inflammatory, antidiabetic, antioxidant, and antiviral ones; and caspase-3, cholesteryl ester transfer protein, and monoamine oxidase (MAO) inhibitory activities ( Figure 17). It was found that some chaetomugilins possessed remarkable cytotoxicity towards certain cancer cell lines, equal to or stronger than the effects of control anticancer drugs, such as chaetomugilins C (7), F (13), I (16), and J (18).  These metabolites have been evaluated for diverse bioactivities, such as cytotoxic, antimicrobial, phytotoxic, antimalarial, anti-mycobacterial, anti-inflammatory, antidiabetic, antioxidant, and antiviral ones; and caspase-3, cholesteryl ester transfer protein, and monoamine oxidase (MAO) inhibitory activities ( Figure 17). It was found that some chaetomugilins possessed remarkable cytotoxicity towards certain cancer cell lines, equal to or stronger than the effects of control anticancer drugs, such as chaetomugilins C (7), F (13), I (16), and J (18). These metabolites have been evaluated for diverse bioactivities, such as cytotoxic, antimicrobial, phytotoxic, antimalarial, anti-mycobacterial, anti-inflammatory, antidiabetic, antioxidant, and antiviral ones; and caspase-3, cholesteryl ester transfer protein, and monoamine oxidase (MAO) inhibitory activities ( Figure 17). It was found that some chaetomugilins possessed remarkable cytotoxicity towards certain cancer cell lines, equal to or stronger than the effects of control anticancer drugs, such as chaetomugilins C (7), F (13), I (16), and J (18). Some studies revealed that the use of some additional compounds alongside anticancer drugs increased the sensitivity of the cancer cell lines towards these drugs. These metabolites could be further developed into anticancer agents; however, extensive in vivo studies and explorations of their mechanisms of action are needed. Chaetoviridins, particularly chaetoviridin A (31), have substantial activity towards different plant pathogens; thus, they might be used as biocontrol agents. Additionally, some reports revealed that chaetomugilins (e.g., A (2), D (8), O (23), and S (28)) have serious phytotoxicity, more than the positive controls; therefore, they could be utilized for developing natural eco-friendly herbicides or weedicides that can replace hazardous synthetic compounds. However, extensive studies and field trials should be conducted.
In molecular docking studies, chaetovirdin D exhibited the highly negative docking scores of −7.944, −8.141, and −6.615 kcal/mol, in complexes with 6M2N, 6W81, and 7K0f respectively. The reference inhibitor exhibited the following scores: −5.377, −6.995, and −8.159 kcal/mol, in complexes with 6M2N, 6W81, and 7K0f, respectively. By using molecular dynamics simulations, chaetovirdin D's stability in complexes with the viral protease was analyzed, and it was found to be stable over the course of 100 ns simulation time.
Undoubtedly, chaetomugilins and chaetoviridins are fungi-derived metabolites that have multiple biological activities. They meet all the requirements for becoming drug leads in their respective therapeutic categories. They have varied chemical compositions that might provide the basis for the synthesis and design of novel and effective pharmaceutical agents. The different substituents at various positions in their skeleton play critical roles in the determination of some of their bioactivities. Finally, studies of the possible mechanisms, biosynthetic pathways, structure-activity relationships, and/or derivatization of these metabolites should be the focus of future research.  Some studies revealed that the use of some additional compounds alongside anticancer drugs increased the sensitivity of the cancer cell lines towards these drugs. These metabolites could be further developed into anticancer agents; however, extensive in vivo studies and explorations of their mechanisms of action are needed. Chaetoviridins, particularly chaetoviridin A (31), have substantial activity towards different plant pathogens; thus, they might be used as biocontrol agents. Additionally, some reports revealed that chaetomugilins (e.g., A (2), D (8), O (23), and S (28)) have serious phytotoxicity, more than the positive controls; therefore, they could be utilized for developing natural eco-friendly herbicides or weedicides that can replace hazardous synthetic compounds. However, extensive studies and field trials should be conducted.
In molecular docking studies, chaetovirdin D exhibited the highly negative docking scores of −7.944, −8.141, and −6.615 kcal/mol, in complexes with 6M2N, 6W81, and 7K0f respectively. The reference inhibitor exhibited the following scores: −5.377, −6.995, and −8.159 kcal/mol, in complexes with 6M2N, 6W81, and 7K0f, respectively. By using molecular dynamics simulations, chaetovirdin D's stability in complexes with the viral protease was analyzed, and it was found to be stable over the course of 100 ns simulation time.
Undoubtedly, chaetomugilins and chaetoviridins are fungi-derived metabolites that have multiple biological activities. They meet all the requirements for becoming drug leads in their respective therapeutic categories. They have varied chemical compositions that might provide the basis for the synthesis and design of novel and effective pharmaceutical agents. The different substituents at various positions in their skeleton play critical roles in the determination of some of their bioactivities. Finally, studies of the possible mechanisms, biosynthetic pathways, structure-activity relationships, and/or derivatization of these metabolites should be the focus of future research.