Hyrtios sp.-associated Cladosporium sp. UR3 as a potential source of antiproliferative metabolites

Abstract

Background

Sponge-associated microorganisms are promising resources for the production of bioactive compounds with cytotoxic potential. The main goal of our study is to isolate the fungal endophytes from the Red Sea sponge Hyrtios sp. followed by investigating their cytotoxicity against number of cell lines.

Results

The fungal strain UR3 was isolated from the Red Sea sponge using Sabouraud dextrose agar media. It was identified based on partial 18 S rRNA gene and ITS sequence analyses as Cladosporium sp. UR3. The in vitro cytotoxic potential of the ethyl acetate extract of the fungal isolate was evaluated using MTT assay against three cancer cell lines: CACO2, MCF7, and HEPG2. Metabolomics profiling of the obtained ethyl acetate extract using LC-HR-ESI-MS, along with molecular docking and pharmacological network studies for the dereplicated compounds were performed to explore its chemical profile and the possible cytotoxic mechanism of the sponge-associated fungi.

Conclusion

These results highlighted the role of sponge-associated fungi as a fruitful resource for the discovery of cytotoxic metabolites.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-024-03560-6.

Introduction

Cancer remains one of the most lethal disease worldwide [1]. It is caused by uncontrolled cell division, abnormal cell growth as well as gene mutations [2]. Numerous factors such as lifestyle, nutrition, continuous exposure to radiation, and smoking are the main causes of carcinogenesis [3]. It is reported that the current rate for developing cancer is 1 to 5 in men and 1 to 8 in women. Additionally, the most common cancer types include lung cancer, breast cancer, prostate cancer, colorectal cancer, stomach cancer, and liver cancer [4]. There are major side effects of the currently available chemotherapeutic regimens as they affect the rapidly dividing tissues and cells such as hair follicles, gastrointestinal tract cells, and bone marrow. Additionally, these medications also responsible for the development of cancer stem cells and multi-drug-resistance [5]. Therefore, there is a great demand for the discovery of natural-derived chemotherapeutic agents with less side effects.

Natural products with their large chemical diversity have proven to be a fertile field of potential therapeutic candidates [6]. There is always a continuous demand for the discovery of novel natural bioactive metabolites due to the rise of cancer and infectious outbreaks [7–10]. Different classes of metabolites, such as alkaloids, flavonoids, and terpenoids are all obtained from different natural resources [11]. These metabolites exhibited various bioactivities as anti-inflammatory, anti-oxidant, neuroprotective, and anticancer potential [11]. Since the past decades, great efforts have been made to isolate natural metabolites with anticancer potential. These tremendous efforts had led to the discovery of a great number of anticancer drugs [12]. Many natural compounds can interfere directly with the main signaling pathways incorporated in the carcinogenesis [13]. Till now, some of those anticancer drugs still the mainstay approaches in cancer therapy, such as vincristine, paclitaxel, etoposide, which were obtained from plants, while, actinomycin D, mitomycin C, and bleomycin, were obtained from bacteria and marine resources, respectively [14]. On the other hand, marine-sponge is considered as a promising source of bioactive metabolites with unique scaffolds [15–18]. They showed different bioactivities as antibacterial, antiviral, anticancer, anti-inflammatory, and immunosuppressive agents [12].

Oceans biodiversity represent nearly 50% of all the globes biodiversity [19]. Accordingly, marine microorganisms are considered as a sustainable resource of diverse bioactive molecules [20]. They are also a promising source of kinase and proteasome inhibitors which are in clinical trials for cancer therapy [21]. Marine-associated fungi produce a wealth of secondary metabolites, which are bioactive with pharmaceutical importance [22]. Besides, some marine fungal-derived metabolites met the criteria for formulating suitable pharmaceuticals as they showed suitable oral bioavailability, and appropriate physico-chemical properties [23]. The genus Cladosporium is renowned as a fruitful resource of different classes of metabolites and for its implication in medical aspects [24]. They produce different metabolites such as alkaloids, pyrones, macrolides, fatty acids, terpenes, sterols, lactones, and tetramic acid derivatives [25]. They also showed various bioactivities as antimicrobial, antioxidant, cytotoxic, insecticidal [26].

In view of this point, our current research aims to describe the isolation and identification of a fungal strain associated with the Red Sea sponge Hyrtios sp. The cytotoxic potential of the fungal strain was investigated against three cancer cell lines. Moreover, the ethyl acetate extract of the fungi was explored by LC-HRMS-based metabolomics. The identified compounds were afterward subjected to in silico molecular docking and pharmacological network analyses.

Materials and methods

Sponge material

The sponge biomass used during our work was previously collected by Safwat Ahmed (Suez Canal University) from Sharm el-Sheikh, Red Sea, Egyptian coasts by scuba diving at a depth of 9.14 m. The collected biomass was frozen and stored at − 20 °C till investigation. The biomass was identified by van Soest (Institute of Systematic Population Biology, Amesradam University, The Netherlands). A voucher specimen (Dr-Ph-01) was deposited at the Department of Pharmacognosy, Faculty of Pharmacy, Deraya University, Egypt.

Isolation and purification of fungal strains

After collecting the sponge biomass, it was twice cleaned with sterile saltwater, dried, and then bathed in 70% ethanol for a minute or two to surface sterilise it before being allowed to air dry. Furthermore, the inside tissues of the sponge were divided into tiny sections, each measuring 0.5 cm³, using a sterile knife in a sterile environment. The tiny segments were surface streaked on Sabouraud dextrose agar plates (the SDA were dissolved in sea water and given with amoxicillin and flucloxacillin 0.05 g/L to suppress bacterial growth). For a maximum of two weeks, the plates were incubated at 28 °C, and any growth was regularly observed. The fungi were taken out of their hyphal tips and placed on a new Sabouraud dextrose agar medium. Duplicate plates were manufactured to lower the risk of contamination. Subcultures were carried out repeatedly until pure isolates were gathered. For every isolate, morphological identification was performed [27, 28].

Molecular identification and phylogenetic analysis of fungal strain UR3

For molecular identification and phylogenetic analysis, genomic DNA from fresh fungal biomass scraped from agar plates was extracted using the MasterPure Yeast DNA extraction kit (epicenter, Madison, Wisconsin). The internal transcribed spacer (ITS) region, which contains ITS 1, the 5.8 S ribosomal RNA gene, and ITS 2, was amplified and sequenced using the Sanger sequencing technology, as well as the small subunit ribosomal RNA gene (18 S rRNA gene). ITS-4 (5´- TTCCTCCGCTTATTGATATGC-3´) and NS1 (5´-GTAGTCATATGCTTGTCTC-3´) were the primer systems employed for this amplification [29]) Using MEGA11 version 11.0.13, the sequences were manually corrected [30]. The ITS region and the small subunit ribosomal RNA gene were individually uploaded to GenBank and assigned Accession Numbers OR900633.1 and OR900731.1. The fungal type material with the highest sequence similarities was found using the National Centre for Biotechnology Information (NCBI) Nucleotide BLAST and the rRNA/ITS NCBI RefSeq curated databases for the appropriate DNA sections (Bioproject PRJNA224725; updated 2023-12-19). The ITS and 18 S rRNA gene sequences (type material) of the subsequent related fungal strains were obtained from the NCBI and added to MEGA 11. The sequences were aligned using ClustalW. After manually adjusting the alignments, the Kimura 2-parameter model was used to generate Maximum Likelihood trees [31]. The first tree or trees for the heuristic search were automatically produced by using the Neighbor-Join and BioNJ algorithms on a matrix of pairwise distances computed using the Maximum Composite Likelihood (MCL) technique. The next topology selected was the one with the highest log probability value. For the 18 S rRNA gene sequence analysis, the final dataset has 59 sequences and 1,143 nucleotide positions; for the ITS sequence analysis, it contains 71 sequences and 666 nucleotide positions.

Cultivation of pure fungal strain UR3 and extraction of fungal culture

For the purpose of conducting cytotoxic activity testing and LC/MS chemical profiling, the pure, isolated fungal strain UR3 has been produced. The isolated fungal strain Cladosporium sp. UR3 was fermented using the solid-state fermentation protocol [10, 32, 33]. In this method, 150 µl of the isolated fungal strain was inoculated and streaked over ten solid plates containing the media Sabouraud Dextrose Agar (10 g peptone, 40 g dextrose, and 20 g agar prepare in 1 L. distilled water). The plates were kept at 30 °C for 10 days for their optimum growth. After that, the plates were chopped into small pieces and macerated in flasks containing ethyl acetate (300 ml each) to obtain most of secondary metabolites produced during the fermentation process. Finally, the extract was prepared by evaporating the ethyl acetate solvent using rotary evaporator (Heidolph^®, 45 °C, 154 r.p.m).

Cytotoxic potential

The cytotoxic potential of the ethyl acetate extract of Cladosporium sp. UR3 was evaluated using the MTT assay against three human tumour cell lines: HEPG2 hepatocellular carcinoma (ATCC NO. HB-8065), CACO2 colorectal cancer (ATCC NO. HTB-37), and MCF7 breast cancer (ATCC NO. HTB-22) [34]. The acquired cell lines came from the American Type Culture Collection (Manassas, VA, USA). Invitrogen/Life Technologies, USA’s DMEM was utilised to cultivate the cells, together with 10% FBS (Hyclone, USA), 10 µg ml − 1 insulin (Sigma-Aldrich, Germany), and 1% penicillin-streptomycin. Cells were grown in 96-well plates prior to investigation, with a volume of 100 µl per well for each complete growth medium and the item under examination, and a density of 1.2–1.8 × 104 cells per well. A full day was spent with the cells. The MTT solution was reconstituted using three millilitres of the medium or a balanced salt solution free of serum or phenol red. Additionally, 10% of the culture medium’s volume was added to it. Depending on the type of cell and the maximum cell density, cultures were then incubated for two to four hours (two hours was generally adequate, but it was extended for low cell densities or cells demonstrating poor metabolic potential). After the incubation period, formazan crystals were dissolved by adding DMSO in a volume equivalent to the initial culture media. The absorbance of every plate was then determined by spectrophotometry using an ELISA plate reader (Model 550, Bio-Rad, USA) set to 570 nm. Three distinct experiments were carried out. GraphPad Prism 5 (Version 5.01, GraphPad Software, San Diego, CA, USA) was used to calculate IC50 values, or the concentration at which 50% of cell growth is inhibited.

Metabolomics analysis

An Acquity Ultra Performance Liquid Chromatography system and a Synapt G2 HDMS quadrupole time-of-flight hybrid mass spectrometer were used to perform metabolomics profiling on the crude extract of the fungal culture, as described by [35] (Supplementary file).

Computational study

Network pharmacology-based analysis

Screening of Cladosporium sp. UR3 extract related targets genes

Based on chemical similarities, pharmacophore models, and protein interactions, the target genes of compounds identified from Cladosporium sp. UR3 extract were found through searches conducted in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database (https://old.tcmsp-e.com/index.php) [36], the Comparative Toxicogenomics Database (CTD) (http://ctdbase.org/) [37], and the Swiss Target Prediction Database (http://www.swisstargetprediction.ch/). After that, these target genes were translated into their corresponding gene names using the UniProt database (https://www.uniprot.org/) [38].

Screening of human colorectal adenocarcinoma related target genes

Genes associated with human colorectal adenocarcinoma were obtained from the Cancer Cell Line Encyclopaedia (CCLE) database by using the keywords “human colorectal adenocarcinoma, colon carcinoma, and colon cancer” and the species limitation set to “Homo sapiens” [39]. The DisGeNET database (https://www.disgenet.org/) and the Comparative Toxicogenomic Database (https://ctdbase.org/) databases. Based on interactivenn (http://www.interactivenn.net/) [40] intersections, proteins associated with the disease and those linked to components overlapped and were recognised as potential targets of these components in human colorectal adenocarcinoma after duplicate targets were eliminated.

Protein–protein interaction (PPI) network construction

A target gene query list was used to generate STRING version 12.0 on a PPI network (https://string-db.org/) [41] which was then exported to the free molecular and genetic interaction network visualisation, modelling, and analysis software Cytoscape 3.10.1 (USA) [42]. The Cytohubba plug-in was then used to screen the top 10 important genes.

Gene ontology and kyoto encyclopedia of genes and genomes pathway analyses

We performed KEGG (Kyoto Encyclopaedia of Genes) enrichment analyses [43] for each putative target using the KEGG website (https://www.genome.jp/kegg), and we examined biological processes, cellular components, and related pathways using the Gene Ontology database (http://bioinformatics.sdstate.edu/go/) [44].

Molecular docking

The Protein Data Bank [45], which provides the crystal structures of nine potential target genes, such as AKT1 (PDB ID: 4EJN), STAT3 (PDB ID: 6NJS), EGFR (PDB ID: 1M17), and ESR-1 (PDB ID: 1A52), was utilised [46]. To create the input files for the identified chemical compounds, protein structures, and cocrystallized ligands, AutoDockTools [47] was utilised. AutoDock Vina [48] was utilised to molecularly dock the proteins that were the subject of the study to chemical substances. The sizes of the grid boxes were limited to 27,000–3, and their “exhaustiveness” was set to 32, which is the ideal value for working with small boxes. To validate the docking procedure, co-crystallized ligands were redocked for protein crystal structures in complexes with binding molecules. The Discovery Studio Visualizer 17.2.0 was used to study and assess the docked drugs and important proteins.

Results and discussion

Phylogenetic identification

Strain UR3 was assigned to the genus Cladosporium. It shared highest partial 18 S rRNA gene sequences (99.6% and 99.5%) with Cladosporium sphaerospermum CBS 193.54 (NG_062724.1) and Cladosporium sphaerospermum CBS 193.54 (NG_062720.1). In addition strain UR3 shared the identical ITS region sequence with C. sphaerospermum CBS 193.54 (NR_111222.1). The phylogenetic placement to next related strains (type material of fungal species) is further illustrated in respective phylogenetic trees (Figure S1 and S2).

Cytotoxic activity

The in vitro cytotoxic activity of the isolated fungal strain was examined against three cancer lines: colorectal carcinoma, breast cancer, and hepatocellular carcinoma (CACO2, MCF7, HEPG2), respectively. The ethyl acetate extract of Cladosporium sp. UR3 showed the highest potential against colon cancer followed by breast cancer, and hepatocellular carcinoma with IC₅₀ values of: 4.7 ± 0.09, 7.2 ± 0.12, and 9.3 ± 0.18, respectively (Figure S3).

Metabolomics profiling of the culture extract

Metabolomics is considered as an important tool to explore the chemical profile of each organism. Moreover, it aids in the discovery of new bioactive molecules and prevent the re-isolation of the known ones. It helps to enhance the techniques used during fungal fermentation and control the isolation of certain molecules [49]. Metabolomics analysis of the ethyl acetate extract of Cladosporium sp. UR3 using LC–HR–ESI–MS for dereplication purposes has resulted in the identification of a range of varied secondary metabolites that were dominated by phenolics, pyranones, tetramic acid derivatives, xanthones (Fig. 1, S4, S5, table S1). The detected compounds were identified by coupling MZmine with some databases, namely Marinlit and DNP. In view of that, the mass ion peak at m/z 141.0185 for the suggested molecular formula C₆H₆O₄ was identified as Sumiki’s acid (1) which was previously isolated from C. herbarum [50]. Another mass ion peaks at m/z 165.0545, 177.0549, and 179.071, for the molecular formula C₉H₁₀O₃, C₁₀H₁₀O₃, C₁₀H₁₂O₃, respectively, were identified as α-Acetylorcinol (2), 4,8-Dihydroxy-1-tetralone (3), 1-(3,5-Dihydroxy-4-methylphenyl)propan-2-one (4), respectively. These metabolites were previously obtained from C. perangustm [51]. Whereas that at m/z 195.0659 for the molecular formula C₁₀H₁₂O₄ was identified as Cladosporactone A (5) that was previously isolated from C. cladosporioides [52]. Additionally, the mass ion peak at m/z 209.0446, corresponding to the proposed molecular formula C₁₀H₁₀O₅ was identified as Herbarin B (6). It was formerly isolated from C. herbarum [53]. Iso-Cladospolide B (7) was dereplicated at m/z 229.1449 for the suggested molecular formula C₁₂H₂₀O₄, previously obtained from C. herbarum [50]. Moreover, the mass ion peak at m/z 233.0727 and the predicted molecular formula C₁₃H₁₂O₄ was identified as Coniochaetone B (8), which was previously isolated from C. halotolerans [54]. The mass ion peak at m/z 234.1128 and the molecular formula C₁₃H₁₇NO₃ was identified as Cladosporiumin I (9), which was previously obtained from C. spherospermum [55]. On the other hand, the mass ion peaks at m/z 235.0603, 245.1143, and 249.1126 in accordance with the molecular formulas C₁₂H₁₂O₅, C₁₄H₁₆N₂O₂, and C₁₄H₁₆O₄ were recognized as Herbarin A, (3R,8aR)-Cyclo(phenylalanylprolyl), Cladosporin C (10, 11, 12). Those compounds were previously isolated from C. herbarum, C. cladosporioides, Cladosporium sp., respectively [53]. Furthermore, the mass ion peak at m/z 261.040 and the suggested molecular formula C₁₃H₁₀O₆ was identified as Coniochaetone K (13), which was earlier isolated from C. halotolerans [54].

Fig. 1.

Dereplicated metabolites from the ethyl acetate extract of Cladosporium sp. UR3

Likewise, the mass ion peaks at m/z 269.0486, 283.0715 and the suggested molecular formula C₁₅H₁₀O₅ and C₁₆H₁₂O₅ were identified as Vertixanthone and Methyl 8-hydroxy-6-methyl-9-oxo-9H-xanthene-1-carboxylate (14, 15), respectively, which were previously isolated from C. halotolerans [54]. Cladosporiumin H (16) was dereplicated at m/z 286.1526, which in agreement with the molecular formula C₁₄H₂₃NO₅. This compound was previously obtained from Cladosporium sp. [56]. The mass ion peak at m/z 291.1247 with the molecular formula C₂₀H₁₈O₂ was identified as altertoxin IX (17) which was formerly obtained from Cladosporium sp. [57].

Furthermore, Malettinin B (18) was dereplicated at m/z 293.1297 and in accordance with the molecular formula C₁₆H₂₀O₅, which was previously isolated from Cladosporium sp. [58]. Likewise, the mass ion peaks at m/z 299.0592, 315.0539, 321.0882 and the molecular formula C₁₆H₁₂O₆, C₁₆H₁₂O_7, C₁₆H₁₆O₇ were identified as Methyl 8-hydroxy-6-(hydroxymethyl)-9-oxo-9H-xanthene-1-carboxylate, Conioxanthone A, α-Diversonolic ester (19, 20, 21), respectively, which were previously isolated from C. halotolerans [54]. Additionally, the mass ion peak at m/z 321.1241 in keeping with the molecular formula C₂₀H₁₈O₄, was dereplicated as altertoxin XII (22), which was formerly purified from Cladosporium sp. [57]. Cladosporol H, F (23, 24) were characterized at m/z 337.0983, 351.1286 and the molecular formula C₂₀H₁₆O_5, C₂₁H₂₀O₅, respectively. These compounds were previously isolated from C. cladosporioides [59].

Computational study

Network pharmacology-based analysis

Based on the remarkable cytotoxic activity demonstrated by the Cladosporium extract on the human colorectal adenocarcinoma cell line (CACO2), we recognize the utmost significance of constructing a gene network for human colorectal adenocarcinoma. This effort is critical for advancing our comprehension of the genetic components involved in the disease and for formulating personalized treatment strategies.

Screening of Cladosporium sp. UR3 extract related targets genes

A total of 430 target genes associated with twenty-four compounds dereplicated from Cladosporium sp. UR3 were gathered through data sources such as TCMSP, CTD, and Swiss Target Prediction. These genes were then converted into their canonical gene names utilizing the UniProt database.

Screening of human colorectal adenocarcinoma related target genes

A total of 1,469 common target genes, recognized for their relevance to human colorectal adenocarcinoma, were meticulously gathered from CCLE, CTD, and DisGeNET databases. These genes were extracted using specific search criteria, including the keywords " human colorectal adenocarcinoma, colon carcinoma and colon cancer " with a species restriction limited to “Homo sapiens.” After eliminating any duplicate entries, a Venn diagram was meticulously crafted to visualize the overlap between the target genes influenced by compounds dereplicated from Cladosporium sp. UR3 and the potential target genes associated with human colorectal adenocarcinoma. This visual representation revealed a total of 81 shared targets, as illustrated in (Fig. 2).

Fig. 2.

Venn diagram for the integrated analysis of the related targets of Cladosporium sp. UR3 dereplicated compounds and colorectal carcinoma

Protein–protein Interaction (PPI) Network Construction

The 81 common target genes were inputted into the STRING database to conduct an analysis of protein-protein interactions (PPI). The outcomes were then utilized to create a PPI network diagram using Cytoscape 3.10.1 software. This network consisted of 77 nodes (after excluding four nodes that were not connected) and 746 edges, with an average node connectivity of 19.26, as illustrated in Fig. 3. Subsequently, the Cytohubba plugin was employed to identify and extract the top ten significant genes based on their degree of connectivity within the network, as shown in Fig. 4. The greater the degree value of any gene, the more evident it will be in disease pathogenesis. These genes are STAT3, AKT1, EGFR, ESR1, SRC, HSP90AA1, CASP3, HIF1A, MMP9, and JAK2. The topological parameters, including node degree, betweenness, and closeness for each protein, were then summarized in Table 1.

Fig. 3.

Network nodes represent 77 protein targets, and the edges represent protein–protein interactions

Fig. 4.

Network nodes represent the top 10 hub genes: the darker the color, the higher the score and the stronger the connection

Table 1.

Topological parameters of top 10 hub genes

No.	Name	Target	Degree	Betweenness	Closeness
1	Signal transducer and activator of transcription 3	STAT3	56	0.1069	0.7700
2	RAC-alpha serine/threonine-protein kinase	AKT1	54	0.0836	0.7549
3	Epidermal growth Factor	EGFR	53	0.0995	0.7624
4	Estrogen receptor alpha	ESR1	47	0.0591	0.7064
5	Proto-oncogene tyrosine-protein kinase	SRC	45	0.0338	0.6937
6	Heat shock protein HSP 90-alpha	HSP90AA1	43	0.0281	0.6754
7	Caspase-3	CASP3	42	0.0431	0.6754
8	Hypoxia-inducible factor 1-alpha	HIF1A	42	0.0438	0.6875
9	Matrix metalloproteinase-9	MMP9	39	0.0341	0.6525
10	Tyrosine-protein kinase JAK2	JAK2	35	0.0137	0.6210

Gene ontology and kyoto encyclopedia of genes and genomes pathway analyses

To construct a network that links target genes with specific pathways, we created this network by connecting all the identified genes influenced by Cladosporium sp. UR3 dereplicated compounds and their interactions with colorectal carcinoma, using information from the KEGG database and ShinyGO database.

The Gene Ontology (GO) functional analysis of selected genes suggested that transmembrane receptor protein tyrosine kinase signaling pathway, positive regulation of phosphorylation and positive regulation of phosphorous metabolic process are among the top pathways in the biological process category (Fig. 5A) correlated with colorectal cancer. Subsequently, we performed a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to pinpoint the significant signaling pathways linked to colorectal cancer. The KEGG analysis of the selected protein-coding genes revealed potential involvement in cancer through pathways including the VEGF signaling pathway, EGFR tyrosine kinase resistance, and the prolactin signaling pathway, as depicted in (Fig. 5B).

Fig. 5.

(A) Functional enrichment analysis of filtered 24 protein-coding genes by ShinyGO (Biological process); (B) KEGG pathway analysis

Molecular docking

Finally, docking studies were conducted to explore potential targets for those compounds that were identified within the extract. In our study, twenty-four annotated compounds were subjected to top four hub genes, STAT3 (pdb: 6NJS), AKT-1 (pdb: 4EJN), EGFR (pdb: 1M17) and ESR-1(pdb: 1A52), active sites. The docking scores of these compounds against these four target proteins are presented in Table 2. To validate the docking protocol, we also performed re-docking of co-crystallized ligands, ensuring that the RMSD between the crystal pose and the docked pose was less than 2 Å for a successful validation. In this context, we compared the docking score of the co-crystallized ligand with those of the tested compounds. Generally, several of the tested compounds displayed better docking scores especially in RAC-alpha serine/threonine-protein kinase (AKT-1), Epidermal growth factor (EGFR) and Estrogen receptor alpha (ESR-1) targets.

Table 2.

Docking scores of tested compounds

Compound No.	Docking Score (kcal/mol)
	Colorectal Carcinoma targets
	STAT3 (6NJS)	AKT-1 (4EJN)	EGFR (1M17)	ESR-1 (1A52)
1	-4.34	-4.86	-4.94	-4.88
2	-4.34	-6.63	-6.22	-6.52
3	-4.6	-6.64	-6.49	-7.19
4	-4.4	-7.02	-7.03	-7.34
5	-4.47	-5.95	-6.62	-6.56
6	-3.81	-6.68	-4.37	ND
7	-4.1	-3.45	-3.95	-3.59
8	-3.61	-6.48	-7.68	-7.95
9	ND	-6.74	-7.51	ND
10	-4.55	-5.77	-5	ND
11	-4.15	-7.65	-7.57	-7.07
12	-2.33	-6.78	-6.68	ND
13	-4.26	-6.3	-7.43	ND
14	-4.96	-7.48	-5.75	-7.42
15	-4.84	-7.56	-6.2	ND
16	-4.33	-6.43	-7.24	-6.4
17	-3.65	-8.33	-6.98	ND
18	-5.36	-6.45	-7.35	-7.91
19	-4.62	-8.35	-5.88	ND
20	-4.85	-8.58	-8.46	ND
21	-4.68	-6.57	-7.48	ND
22	-4.08	-5.73	-8.5	ND
23	-3.92	-6.8	-6.44	-8.02
24	-4.39	-6.45	-6.22	ND
Co-crystalized Ligand	-10.01	-14.46	-9.11	-11.15

ND: Not Detected

Upon docking, compound 18 within the active site of STAT3 showed good docking score = -5.36 kal/mol through formation of four hydrogen bond connections with the amino acid residues Ser 611, Glu 612, Ser 613, and Glu 638. Additionally, a hydrophobic interaction was established with the amino acid residue Pro 639 (as shown in Fig. 6A).

Fig. 6.

2D and 3D interaction diagrams of (A) Compound 18 in STAT3 active site (PBD ID 6NJS), (B) Compound 20 in AKT-1 active site (PDB ID 4EJN), (C) compound 20 in EGFR active site (PDB ID 1M17), (D) Compound 22 in EGFR active site (PDB ID 1M17), (E) Compound 23 in ESR-1 active site (PDB ID 1A52)

Among docked compounds, the interaction of compound 20 against AKT-1 active site showed the least docking score of -8.58 kcal/mol. This remarkable interaction was characterized by the establishment of three hydrogen bond interactions with Ser 205 and Thr 211 amino acid residues alongside a series of hydrophobic interactions involving key amino acid residues, namely Gln 79, Trp 80, Leu 210, Leu 264, Val 270, and Tyr 272 (Fig. 6B).

When docking with the EGFR tyrosine kinase active site, both compounds 20 and 22 exhibited the most favorable S score values, with values of -8.46 and − 8.50 kcal/mol, respectively. Compound 20 established several hydrogen bond interactions, notably with the critical amino acid residue Met 769, which plays a crucial role in inhibiting EGFR activity, as illustrated in Fig. 6C. Furthermore, compound 20 also demonstrated hydrophobic interactions. On the other hand, compound 22 formed three hydrogen bond interactions within the EGFR active site, with two of these interactions involving the amino acid residue Met 769 and another involving the amino acid residue Met 742. Additionally, compound 22 engaged in hydrophobic interactions with amino acid residues Val 702, Ala 719, Lys 721, and Leu 820 (Fig. 6D).

When the dereplicated compounds were docked into the ESR-1 active site, it was observed that compound 23 displayed the lowest binding energy score, which was calculated at -8.02 kcal/mol. This interaction was characterized by the formation of three hydrogen bond interactions with the amino acid residues Leu 387, Arg 394, and Gly 521, along with engaging in hydrophobic interactions with the amino acid residues Leu 384, Leu 391, Phe 404, and Leu 525 (Fig. 6E).

Finally, we conclude that our study suggests the investigated metabolites of Cladosporium sp. UR3 might have activity against colorectal carcinoma, especially compounds 20, 22, and 23 targeting AKT-1, EGFR, and ESR-1. This rationale is based on the known crucial roles of these proteins in colorectal carcinoma development and progression.

Conclusion

Our current study described the isolation and purification of a fungal isolate from the Red Sea sponge, Hyrtios sp., which was molecularly identified as Cladosporium sp. UR3. This endophytic fungus has been shown to be a promising resource of natural metabolites particularly when it was fermented using SDA culture media. Additionally, investigating the in vitro cytotoxic potential of the crude extract of Cladosporium sp. UR3 revealed its powerful activity against colorectal, breast and hepatocellular carcinoma cell lines, with IC₅₀ values of 4.7 ± 0.09, 7.2 ± 0.12, and 9.3 ± 0.18 µg/mL, respectively. Interestingly, metabolomics profiling of the sponge-associated fungi lead to the characterization of 24 metabolites described as phenolics, pyranones, tetramic acid derivatives, and xanthones. Moreover, molecular docking analysis of the dereplicated secondary metabolites suggested their AKT-1, ESR-1, and EGFR tyrosine kinase inhibitory potential as a plausible mechanism for their cytotoxic activities. These findings highlighted the significance of marine fungi as an important reservoir of bioactive molecules for the discovery of cytotoxic medications with natural origin.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Author contributions

Conceptualization: URA, JW, OHA; methodology: URA, OHA; software: OHA, MH, SPG, PK; formal analysis: OHA, MH, SPG, PK; resources: OHA, AHE; data curation: URA, OHA, AHE; writing—original draft: OHA, MH, JW, SPG, PK; writing—review and editing: URA, OHA, MH. All authors have read and agreed to the published version of the manuscript.

Funding

This project China 25 was supported financially by the Science and Technology Development Fund (STDF), Egypt.

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB).

Data availability

“All data generated or analyzed during this study are included in this article (and its supplementary information files). The ITS region and the small subunit ribosomal RNA gene were individually uploaded to GenBank and assigned Accession Numbers OR900633.1 and OR900731.1.”

Declarations

Ethics approval and consent to participate

Sponge materials and experiments were conducted in accordance with relevant institutional, national, and international guidelines.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.