Biotransformation of medicarpin from homopterocarpin by Aspergillus niger and its biological characterization

Abstract

The objective of this study was to convert homopterocarpin derived from Pterocarpus macrocarpus Kurz. heartwood to medicarpin using Aspergillus niger (strain UI X-172) and assess its antioxidant, antiplasmodial, and anticancer activities in silico and in vitro. This study highlighted biotransformation of homopterocarpin to medicarpin via demethylation. Medicarpin demonstrated antioxidant activity against 2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS, IC₅₀ = 0.61 ± 0.05 µg/mL) and 1,1-diphenyl-2-picrylhydrazyl (DPPH, IC₅₀ = 7.50 ± 1.6 µg/mL), antiplasmodial activity against the Plasmodium falciparum strain 3D7 (IC₅₀ = 0.45 ± 0.35 µg/mL), and anticancer efficacy against a hepatocyte-derived carcinoma cell line (Huh7it-1 cells, IC₅₀ = 34.32 ± 5.56 µg/mL). Medicarpin also showed favorable antioxidant, antiplasmodial, and anticancer properties in silico with a binding affinity lower than commercial drugs. These results highlight the green synthesis of medicarpin by microbial transformation using A. niger, which demonstrates promising in vitro and computational activity, however, further studies are required for clinical development.

Introduction

Natural compounds from medicinal plants are used by approximately 80% of the global population since their initial traditional use^1,2. The search for novel and beneficial compounds has been increasing annually in tandem with initiatives to enhance their bioavailability and quality³. Several biotransformation studies have identified analogous compounds with potent pharmacological activities and low toxicities⁴. Microbial transformations can reduce toxicity, improve solubility, and introduce new biologically active derivatives from natural products for pharmaceutical applications⁵. Aspergillus niger, a common aerobic fungus that proliferates on diverse substrates, is actively used in biotransformation³. This species generates broad-spectrum epoxide hydrolases, which have been commercially purified and employed to catalyze numerous reactions⁶.

Medicarpin, a pterocarpan, is an isoflavonoid isolated from various medicinal plants, including Medicago truncatula Gaertn^7,8. Sophora japonica L., Zollernia paraensis Huber., Medicaria verniciflua L., Canavalia lineata (Thunb.) DC⁹. Platymiscium floribundum Vogel., Glycyrrhiza glabra L., and Glycyrrhiza uralensis Fisch¹⁰. Medicarpin has been reported to exhibit diverse bioactivities, including anticancer, anti-inflammatory, and neuroprotective effects^{11, 12, 13–14}.

However, medicarpin is produced only in small quantities in plants, thus creating supply challenges. The chemical synthesis of medicarpin is a low-yield, complicated process. Medicarpin can also be produced by plant tissue culture; however, this method is relatively unfeasible owing to the slow growth of plant cells and unstable medicarpin yields. Lu et al.¹⁰ reported that medicarpin can be heterologously synthesized in yeast using liquiritigenin as a substrate. However, this substrate is expensive, and the method requires advanced and costly technologies. Hence, improved medicarpin synthesis methods are required.

Biotransformation is a process of green synthesis with growing research interest. Biotransformation has many benefits in industrial practices. In drug development, biotransformation enhances the solubility and bioavailbility properties by modifying the structure. They are more effective and less toxic¹⁵. Biotransformation is an organic technology for drug properties synthesis¹⁶. The use of biotransformation to manufacture medicarpins is a cost-effective and efficient approach for the advancement of biological manufacturing, which involves the production of valuable compounds.

One of Thailand’s endemic plants, Pterocarpus macrocarpus Kurz. (Fabaceae) has many bioactive compounds, including homopterocarpin. Homopterocarpin was first abundantly isolated from P. macropcarpus Kurz. heartwood². Homopterocarpin has lower economic value than medicarpin. Hence, this study focuses on optimizing its conversion into medicarpin through microbial biotransformation. Thin layer chromatography (TLC), gas chromatography-mass spectra (GC-MS), and nuclear magnetic resonance (NMR) were used to analyze the metabolite profiles. We also examined the antioxidant, antiplasmodial, and anticancer (liver cancer) acvities of medicarpin in vitro and silico.

Materials and methods

Homopterocarpin and Aspergillus niger strain

Homopterocarpins were isolated from the n-hexane extract of heartwood from Pterocarpus macrocarpus Kurz. P. macrocarpus Kurz. was obtained from a traditional market in Bangkok, Thailand. The sample was authenticated in the Plant Systematic Laboratory, Department of Biology, Faculty of Science and Technology, Universitas Airlangga by Dr. Junairiah. A voucher specimen was deposited in the Plant Systematic Laboratory, Department of Biology, Faculty of Science and Technology, Universitas Airlangga (No. PM.0210292021)². The transfer material agreement was approved by the Memorandum of Understanding (MoU) between Universitas Airlangga and Chulalongkorn University.

The heartwood of P. macrocarpus Kurz. was air-dried at 30 ± 2 ºC until it reached its desiccated weight. One kilogram of dry wood was subsequently pulverized (40 mesh size) at room temperature (28 ± 2 ºC). The powder was macerated with n-hexane thrice for 7 d at room temperature (28 ± 2 ºC). The extract was then subjected to evaporation at 60 ºC. Subsequently, the n-hexane extract was crystallized five times at low temperature (4 ± 2 ºC) using n-hexane until the formation of white crystals. The white crystal is homopterocarpin².

The A. niger strain, UI X-172, was provided by the Plant Biomass Utilization Research Unit, Department of Botany, Chulalongkorn University. The spore bank was maintained at 20 °C in 1 mL of soybean meal (SBM) broth medium and 0.5 mL glycerol. Soybean meal (SBM) medium was prepared by dissolving glucose (20 g), yeast extract (5 g), NaCl (5 g), KH₂PO₄ (5 g), and soybean meal (5 g) in 1 L of distilled water¹⁷. Aspergillus niger is generally recognized as safe (GRAS) by Food and Drug Administration (FDA), United State of America (USA)¹⁷.

Microbial transformation

The SBM medium was used for microbial transformation culture. The SBM medium was sterilized by autoclaving at 121 °C for 15 min and 1.2 atm pressure. The solution pH was then adjusted to 7. One milliliter of A. niger spores (1 × 10⁶ in 1% Tween 80) from the spore bank was cultured in agar slant (culture stock). Subsequently, 50 mL of SBM was added to 1 mL of A. niger spores (1 × 10⁶ in 1% Tween 80) sourced from an agar slant. The mixture was then incubated at 27 ± 2 °C on a rotary agitator set to 150 rpm for 2 days. Further, 5 mL of the culture was added to 50 mL of SBM medium, and the mixture was incubated at 27 ± 2 °C on a rotary agitator spinning at 150 rpm. After 24 h of incubation, 40 mg of homopterocarpin was added to 50 mL of culture medium. After 7 days, the culture was collected, filtered, and extracted three times with an equivalent amount of dichloromethane (DCM) at 24 h intervals following a 7-d incubation period. The extracts were collected and evaporated using a low-pressure rotary evaporator. Thin-layer chromatography was used to examine the DCM-solubilized residue. The chemicals were obtained by fractionation and purification of the extracts.

Metabolite profiling using gas chromatography-mass spectrometry (GC-MS) analysis of A. niger-transformation culture

Phytochemical profiles of the homopterocarpin-transformed extract from A. niger-transformation culture were assessed using gas chromatography-mass spectrometry (GC-MS) after 1 week of cultivation. Microbial cultures (50 mL) were collected after 0, 3, 5, and 7 d of incubation. Samples were collected daily from three separate cultures. The cultures were dehydrated in a freeze dryer and triturated with 10 mL of a 9:1 methanol/water solution. Thereafter, the cells were incubated at ambient temperature (27 ± 2 °C) for 24 h; crude extracts were then collected and refrigerated. The GC-MS method was performed as described by Wahyuni et al.². The peaks in the chromatogram were identified based on their mass spectra based on the library. The compounds were identified through comparisons of their mass spectra with those in the Standard Reference Database (version 02. L; National Institute of Standards and Technology, Gaithersburg, MD, USA). Compounds with similarities > 80% were used in this study. The relative percentage of each component was calculated as the relative percentage of the total peak area in the chromatograph.

Separation of homopterocarpin-transformed compounds from A. niger-transformation culture

An n-hexane/ethyl acetate gradient system was used to chromatograph the combined DCM extract of the biotransformed homopterocarpin compounds on a silica gel column and was isolated in fractions 25–29. Thin-layer chromatography plates were used for further purification. The mobile phase used was n-hexane: ethyl acetate (7:3). The purified compounds (white) were obtained via evaporation.

Spectrophotometric analysis of the biotransformation-derived compound

The biotransformation products were characterized using a GC-MS setup similar to that described by Wahyuni et al.². Mass spectra of the chromatographic peaks were analyzed using the rules of the National Institute of Standards and Technology (NIST). The mass spectra of the phytochemicals were compared with those of known compounds archived in the NIST collection. The cumulative peak area in the chromatogram was used to determine the relative proportion of each constituent. Nuclear magnetic resonance (NMR, JEOL JNM-ECA Equipment) ¹H and ¹³C spectra of the compounds in chloroform were obtained at a frequency of 400 MHz to validate compound identification.

Antioxidant assays of the isolated compounds

The 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH) assay was performed as described by Prieto¹⁸. Briefly, 100 µL of the sample was mixed with 100 µL of 0.2 mM DPPH reagent in methanol and incubated at room temperature (26 ± 2 ºC) for 30 min under subdued light. A SpectraMax M3 reader was used to calculate DPPH inhibition at 517 nm.

The 2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) test was performed according to the approach established by Fu et al.¹⁹. For the assay, 25 mL of acetic buffer was used to dissolve 86.02 mg ABTS (solution A), and 100 mL of acetic buffer was used to dissolve 66.24 mg of potassium persulfate (solution B). Solution C was then prepared by combining 5 mL of solutions A and B and maintaining them at ambient temperature (26 ± 2 ºC) in the dark for 12–16 h. Subsequently, 2.8 mL of solution C was mixed with 65 mL of acetic buffer and incubated at 26 ± 2 °C for 30 min. The absorbance of the resulting ABTS solution at 734 nm was verified to be between 0.7 and 0.72. One hundred microliters of the ABTS reagent was mixed with 100 µL of the sample and incubated at room temperature in subdued lighting for 6 min. A SpectraMax M3 reader was used to quantify the ABTS inhibition at 734 nm.

Both assays used ascorbic acid and trolox as positive controls. Methanol and solution C were a negative control for DPPH and ABTS assays respectively. The concentrations of samples and control were set to 1.075, 3.15, 6.25, 10, 15, 25, 35, 50, 75, 100, 150, and 200 µg/mL. The computation of % inhibition and half-maximal inhibitory concentration (IC₅₀) values was analogous to a previously described DPPH inhibition experiment^2,20.

The following formula adapted from Prieto¹⁸ was used to determine the percentage DPPH inhibition:

where A_control is the absorbance of the DPPH or ABTS reagent, and A_sample is the absorbance of the samples. To identify the IC₅₀ value, the percentage inhibition data for different concentrations were plotted and subjected to linear regression analysis. IC₅₀ denotes the concentration of the sample resulting in 50% inhibition of DPPH or ABTS². All chemicals for antioxidant activity assay were from Sigma-Aldrich, St. Louis, MO, USA.

In vitro antiplasmodial assay

Strain 3D7 of Plasmodium falciparum was used for in vitro antiplasmodial testing^20,21. The medium comprised 10% human O⁺ plasma, hypoxanthine, sodium bicarbonate (NaHCO₃), 22.3 mM N-2-hydroxyethylpiperazine-N-2-ethanesulfonic acid ) (Sigma-Aldrich, Darmstadt, Germany), 5% hematocrit in Roswell Park Memorial Institute 1640 (RPMI 1640) (Gibco BRL, USA), and human O⁺ red blood cells. Chloroquine diphosphate was used as the positive control whereas the parasitized cultures without medicarpin and homopterocarpin was served as negative controls. A total mass of 1 mg was obtained by dissolving the sample in 100 µL DMSO. Sequential dilutions were prepared from the standard solutions. Ring-stage parasites exhibited approximately 1% (5% hematocrit) parasitemia. Extract concentrations of 100, 10, 1, 0.1, and 0.01 µg/mL were used in this experiment. Each well of a 96-well plate received 2 µL of test solutions with varying concentrations, followed by supplementation with 198 µL of the parasite suspension. Subsequently, gas mixtures consisting of O₂, CO₂, and N₂ in concentrations of 5% and 90% were introduced into the test wells inside the chamber. The test wells were kept in the chamber for 48 h at 37 °C. A thin blood smear was prepared and stained with 20% Giemsa. The number of infected erythrocytes per 1000 normal erythrocytes was quantified microscopically (1000× magnification). Data were analyzed to determine the growth percentage and percentage inhibition. The percentage growth was calculated using the formula employed by Wahyuni et al.²⁰.

In vitro anticancer assay

The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) test²² was performed to evaluate the effect of the test compound on liver cancer using hepatocyte-derived cellular carcinoma (Huh7it-1) cells. Dimethyl sulfoxide (DMSO) 0.01% was used to dissolve the extracts, then they were diluted with medium to obtain the required concentrations (6.25, 12.5, 25, 50, 100, 200, 400, 600, 800, and 1000 µg/mL). Human hepatic cell lines were cultured in complete Dulbecco’s modified Eagle’s medium (DMEM, Invitrogen, Carlsbad, CA, USA) supplemented with 10% fecal bovine serum (FBS), 4mM L-Glutamin, and 1% penicillin-streptomycin (Gibco-Thermo Fisher Scientific, Waltham, Massachusetts, AS) at 37 °C under an atmosphere of 5% of carbon dioxide atmosphere and 95% humidity, after which 15 µL of 5 mg/mL MTT solution (thiazolyl blue tetrazolium bromide, Sigma-Aldrich Chemie GmbH, Steinheim, Germany) in phosphate saline buffer (PBS, Biowest, Nuaille, France) to each well. The cells were seeded at the concentration 2.4 × 10⁴ per well for 24 h before treatment. The volume of the medium to incubate cells was 100 µL. The culture was incubated in various concentrations of sample for 48 h. Then the solution was removed with 100 µL of 0.01% DMSO to remove the precipitate. The assay was done in duplicate wells three times. The cell numbers were determined by measuring the absorbance at 560 nm (formazan) and 750 nm (corrector/background) using a multi-plate reader (Promega Glomax Multi Detection System) and the viability was assessed. The viability of cells was calculated using the equation:

where A_sample was the absorbance sample at 560 nm-Absorbance sample at 750 nm and A_control was the absorbance DMEM medium. The percentage of cell viability was then plotted and regressed linearly to obtain the IC₅₀ values,

Statistical analyses

The data are presented as the mean ± standard deviation. IBM SPSS Statistics for Windows (version 20.0; IBM Corporation, Armonk, NY, USA) was used to compute the IC₅₀ values for in vitro antimalarial activity using probit analysis. The IC₅₀ values for in vitro antiplasmodial, anticancer, and antioxidant activities were determined using the linear regression function of Microsoft Excel (version 20.0; IBM Corporation, Armonk, NY, USA).

Computational analysis

Ligand sample collection

The bioactive compounds used as ligands in this study were analyzed using GC-MS (Table 1). The PubChem database was used to acquire ligand information, specifically the CID, SMILE Canonical, and file structure data format (SDF) (Supplementary Data I). Open Babel v3.1.1 was employed to obtain the three-dimensional structure of the ligand through energy minimization^23,24.

Table 1. Phytochemical components from GC/MS analysis of Pterocarpus macrocarpus kurz. heartwood n-hexane extract in seven days culture.

No.	Compound	Retention time (min)	Relative area percentage (peak area relative to the total peak area (%)
			First day	Third day	Fifth day	Seventh day
1	2,5-Furandione, 3-methyl-	3.81				36.76
2	Glycerin	3.98	41.67	100	55.15	79.86
3	2,4-Dihydroxy-2,5-dimethyl-3(2 H)-furan-3-one	4.30	35.34
4	Maltol	5.87	100	44.39
5	5-Hydroxymethylfurfural	8.69	34.21		35.97
6	1,2,3-Propanetriol, 1-acetate	8.97	82.22	31.87
7	4 H-Pyran-4-one, 2,3-dihydro-3,5-dihydroxy-6-methyl-	9.72	93.17	40.34	37.27
8	2,4-Hexadienedioic acid	11.47			41.84	57.11
9	4,4-Dimethyl-3-(3-methylbut-3-enylidene)-2-methylenebicyclo[4.1.0]heptane	16.69			20.69
10	7-Hydroxymethylbicyclo{2.2.1}heptane-1-carboxylic acid, methyl ester	18.34		24.60
11	3.beta.,9.beta.-Dihydroxy-3,5.alpha.,8-trimethyltricyclo[6.3.1.0(1,5)]dodecane	19.56				8.98
12	6-Isopropenyl-4,8a-dimethyl-1,2,3,5,6,7,8,8a-octahydro-naphthalen-2-ol	19.729		37.92	100	100
13	Perhydrocyclopropa[e]azulene-4,5,6-triol, 1,1,4,6-tetramethyl	21.10			12.84	14.60
14	9-Octadecenamide, (Z)-	26.00	85.32	55.85	11.54	54.58
15	Medicarpin	28.47			9.84	12.60

Target preparation

Screening for potential bioactive compounds in this study was aimed at investigating their anticancer, antioxidant, and antimalarial activities by targeting several key proteins. These included catalase (Cat), superoxide dismutase 1 (SOD1), epidermal growth factor receptor (EGFR), platelet-derived growth factor receptor (PDGFR), vascular endothelial growth factor (VEGFR), human epidermal growth factor receptor 2 (HER2), P. falciparum plasmepsin V (PfPMV), and P. falciparum lactate dehydrogenase (PfLDH) (Supplementary Data II).

Analysis of drug-like properties

The similarity of a query compound to a drug is determined based on drug-like molecular rules consisting of the Lipinski, Ghose, Veber, Egan, and Muegge rules. Compounds with positive predictions must fulfill at least one of these rules. Bioavailability, water solubility, and absorption values were obtained to determine the absorption rate, solubility, and circulation ability of the query compound, respectively. SwissADME (http://www.swissadme.ch/) was used for the profile analysis of drug-like properties^24,25.

Bioactivity prediction

All query compounds possessed inhibitory properties; the classification of inhibitor types in the query compounds consisting of kinases, proteases, and enzymes was predicted using Molinspiration (https://www.molinspiration.com/cgi/properties), with SDF files as input data²⁶. The probability values of the anticancer, antioxidant, and antiplasmodial agents were predicted using PASSOnline (https://www.way2drug.com/passonline/), and a probability value of activation (Pa) greater than that of inhibition (Pi) was considered to trigger the activity of the query compounds^27,28.

Analysis of drug binding and structural visualization

Drug-binding analysis was performed using PyRx v.1.1.0 with an academic license²⁴. This method allows the identification of compounds with anticancer, antioxidant, and antiplasmodial properties. Vincristine and vinblastine were used as a positive control for anticancer, trolox and orbic acid were used as a positive control for antioxidant, and chloroquine was as a positive control for antiplasmodial. The binding affinity parameter was used to predict the ligand-binding activity in the target domain^29,30. Three-dimensional structures of ligand-protein molecular complexes with cartoons, transparent surfaces, and sticks were obtained using PyMol v2.5.0 (Schrödinger, LLC) with an academic license²⁴.

Molecular interaction analysis

Ligand interactions with proteins can trigger the formation of weak hydrogen, van der Waals, hydrophobic, pi, alkyl, and electrostatic bonds³¹. Weak bonds can affect the activity of the ligand on the target, such as its inhibitory ability; these bond interactions were identified using the Discovery Studio v2016 software^32,33.

Dynamic simulation

The stability of ligand interactions in the hotspot region was assessed via molecular dynamics simulations using CABS-flex v2.0 (https://biocomp.chem.uw.edu.pl/CABSflex2/index)³⁴. The server utilizes the root mean square fluctuation (RMSF) metric to assess the stability of bond interactions, with values below 3 Ų⁵. Molecular complexes (ligand-protein) with stable bonds can trigger certain biological functions³⁴.

Results and discussion

This study elucidates the biotransformation of homopterocarpin obtained from Pterocarpus macrocarpus Kurz. heartwood using A. niger and biotransformed-compound characterization.

Metabolite profiles obtained using GC-MS during biotransformation

Metabolite profiling was performed using GC-MS during biotransformation by A. niger (Table 1; Fig. 1). GC-MS analysis revealed that 15 compounds were distributed as seven, nine, and eight compounds on the third, fifth, and seventh day of culture, respectively. Maltol, glycerine, and 6-isopropenyl-4,8a-dimethyl-1,2,3,5,6,7,8,8a-octahydro-2-ol were the major compounds on the first, third, and fifth to seventh days of culture, respectively. All these compounds exhibit antioxidant, anticancer, antimicrobial, and antifungal activities^24,35,36.

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Fig. 1

Chromatogram profile of the biotransformation culture of homopterocarpin from Pterocarpus macrocarpus Kurz. heartwood by Aspergillus niger. (A) First day of culture, (B) Third day of culture, (C) Fifth day of culture, (D) Seventh day of culture. (1) Glycerine; (2) 4 H-Pyran-4-one,2,3-dihydro-3,5-dihydroxy-6-methyl-; (3) 6-Isopropenyl-4,8a-dimethyl-1,2,3,5,6,7,8,8a-octahy-dronaphthalen-2-ol; (4) 9-Octadecenamide, (Z)-; (5) Medicarpin ((6aR,11aR)-9-methoxy-6a,11a-dihydro-6H-[1]benzofuro[3,2-c]chromen-3-ol).

Biotransformation-derived compounds

The compound was obtained as a colorless amorphous solid (molecular formula, C₁₆H₁₄O₄; molecular weight, 270.27 g/mol; GC-MS m/z (molecular formula), 270.3 g/mol (C₁₆H₁₄O₄); ¹HNMR (400 MHz, CDCl₃); and ¹³NMR (400 MHz, CDCl₃)) (Fig. 2; Table 2). The compound was identified as demethylhomopterocarpin/3-hydroxy-9-methoxycar-pan (medicarpin) based on spectral analyses (GC-MS-MS and NMR) and references. The mass of this compound was 270.3 g/mol, which was 13.8 mass units lower than that of the substrate (homopterocarpin, mz 284.1 g/mol), as indicated by the mass spectra. In addition, the mass spectra demonstrated the removal of CH₂ (14 mass units). This transformation involves demethylation (Fig. 3). Based on the metabolite profiling analysis during 7 days of culture, medicarpin appeared on the fifth to seventh days of culture. Medicarpin belonged to the same group as homopterocapin (Pterocarpans Group)^2,7.The aerobic fungus A. niger is widely prevalent and thrives on various substrates³. A. niger has been successfully used by Kang et al.³ to transform lanthanum, Chatla et al.⁵ to transform quercetin into kaempferol, and Sponchiado et al.³⁷ to transform rifampicin. A. niger strains produce hydrolases, amylases, pectinases, and chitinases^6,38. Demethylation, hydroxylation, cyclization, and esterification are common transformation mechanisms in A. niger³⁹. The important enzymes with a demethylation key role from Aspergillus niger are pectin methylesterase (PME)⁴⁰ and laccase⁴¹. The present study highlights the transformation of homopterocarpins from Pterocarpus macrocarpus Kurz. heartwood into medicarpin by A. niger (green synthesis) via demethylation. However, the enzyme has not been identified. Further research to explore the enzyme is needed for commercial purposes.

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Fig. 2

Structures of homopterocarpin (1) and medicarpin (2).

Table 2. ¹H- and ¹³C-chemical shift assignments of homopterocarpin and medicarpin.

Carbon no.	Type	1H-		13C-
		Homopterocarpin δH (mult, J Hz)	Medicarpin δH (mult, J Hz)	Homopterocarpin δC (mult, J Hz)	Medicarpin Δc (mult, J Hz)
1	CH	7.43 (d, 8.6)	7.43 (d, 9.2)	131.9	131.93
2	CH	6.64 (dd, 8.6; 2.5)	6.64 (dd, 8.6; 2.6)	109.3	109.27
3	C	–	–	161.2	161.2
4	CH	6.47 (d, 2.5)	6.47 (d, 2.6)	101.7	101.7
4a	C	–	–	156.7	156.7
6	CH2	3.64 (t, 11.0) 4.25 (dd, 11.0; 5.3)	3.63 (t, 11.0) 4.24 (ddd, 11.20; 5.3; 1.0)	66.7	66.7
6a	CH	3.53 (m)	3.53 (ddd, 11.1, 6.8, 5.0)	39.6	39.6
6b	C	–	–	119.2	119.2
7	CH	7.13 (d, 8.5)	7.08 (d, 8.6)	124.8	125.22
8	CH	6.46 (dd,8.5; 2.3)	6.47 (dd,8.5; 2.6)	106.4	107.66
9	C	–	–	161.1	161.1
10	C	6.44 (d, 2.3)	6.44 (m)	97.1	97.1
10a	C	–	–	160.8	160.8
11a	CH	5.51 (d, 6.8)	5.51 (d, 6.9)	78.7	78.7
11b	C	–	–	112.4	112.4
3-OCH3	C-OCH3	3.77 (s)	–
9-OCH3	C-OCH3	3.79 (s)	3.79 (s)	55.5	55.5

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Fig. 3

Chromatogram profile of medicarpin. (A) TLC Chromatogram (A1. Homopterocarpin; A2. Biotransforntation extract). (B) GC-MS chromatogram (B1. medicarpin library spectra with retention time; B2. medicarpin (sample) of spectra) (C) NMR Chromatogram (C1. ^HNMR chromatogram; C2. ^CNMR chromatogram).

In vitro antioxidant, anticancer, and antiplasmodial activities

The antioxidant, anticancer, and antiplasmodial activities of homopterocarpin and medicarpin were determined. The IC₅₀ values of the antioxidant bioactive compounds were 7.50 ± 0.16 µg/mL (medicarpin) and114.08 ± 0.21 µg/mL (homopterocarpin) for DPPH assay, then 0.61 ± 0.05 µg/mL (medicarpin) and 30. 61 ± 0.63 µg/mL (homopterocarpin) for ABTS assay (Table 3). These data demonstrate that medicarpin exhibited an IC₅₀ lower than that of homopterocarpin in both the DPPH and ABTS assays, despite both these compounds being categorized as potent antioxidants²⁰. Medicarpin (an isoflavone) has been reported to exhibit antioxidant activity and upregulate antioxidant gene expression⁴².

Table 3. In vitro antioxidant, anticancer, and antiplasmodial activities of Pterocarpus macrocarpus kurz. Heartwood extract.

No.	Extract	Antioxidant activity, IC50 (µg/ml)		In vitro anticancer activity, IC50 (µg/ml)	In vitro antiplasmodial activity, IC50 (µg/ml)
		DPPH	ABTS
1	Medicarpin	7.50 ± 0.16b	0.61 ± 0.05cd	34.32 ± 0.56 a	0.45 ± 0.35b
2	Homopterocarpin	14.08 ± 0.21a	30. 61 ± 0.63ab	254.22 ± 8.13b	0.55 ± 0.03a
3	Ascorbic acid	5.23 ± 0.12 c	2.95 ± 0.16abc
4	Trolox	0,96 ± 0.07d	0.92 ± 0.03bcd
5	Chloroquine diphosphate				0.014 ± 0.01c

The anticancer activities of medicarpin and homopterocarpin are represented as IC₅₀ values of 34.32 ± 0.56 and 254.22 ± 8.13 µg/mL, respectively, against Huh7it-1 cells. Medicarpin is known to exhibit anticancer activity⁴² against breast cancer, leukemia⁴³, lung cancer⁴⁴ and brain cancer⁴⁵. However, to our knowledge, the use of medicarpin for treating liver cancer has not been reported.

To our knowledge, this is the first study to investigate the novel application of medicarpin as an antiplasmodial agent. The IC₅₀ values for the antiplasmodial activity of medicarpin and homopterocarpin were 0.45 ± 0.35 and 0.55 ± 0.03 µg/mL, respectively. Notably, the IC₅₀ of medicarpin is lower than that of homopterocarpin². Furthermore, the IC₅₀ of medicarpin was lower than that of another pterocarpan, melilotocarpan (41.8 ± 5.2 µM), reported previously⁴⁶. This finding was also superior to those of calopogonium isoflavone B and isoerythrin A-4′-(3-methylbut2-enyl) ether, which exhibit marginal activities against the 3D7 and Dd2 strains of P. falciparum (70–90% inhibition at 40 µM)⁴⁷.

Computational analysis of medicarpin

Computational analysis of medicarpin included drug-likeness analysis, bioactivity prediction (inhibitory activity), molecular docking, and molecular interaction analysis. All compound samples with canonical CID and SMILE data were obtained from PubChem (Supplementary Data I). Target proteins, including EGFR, PDGFR, VEGFR, HER2, Cat, SOD1, PfPMV, and PfLDH, obtained from RCSB PDB were displayed using PyMol v2.5.0 (Schrödinger, LLC) with an academic license; the targets are shown as cartoons and colored by secondary structures consisting of helices (red), sheets (yellow), and loops (green) (Supplementary Data II).

Drug-likeness analysis and molecular docking

Drug-likeness analysis is used to evaluate a compound as a drug. Drug-likeness analysis is Drug-likeness of the query compounds was predicted using SwissADME based on the rules of Lipinski, Ghose, Veber, Egan, and Muegge. Parameters such as the molecular weight, log P, number of hydrogen bonds, and molar refractivity were included in the Lipinski rule. Ghose’s rule refers to log P, molecular weight, and the rotatable bond level⁴⁸. The predicted polar surface area was added according to Egan’s rule, and other chemical parameters such as lipophilicity (XLOGP3), cyclic rings, and heteroatoms were added according to Muegge’s rule^49,50. Water solubility, bioavailability, and absorption help identify the ability of the query compound to circulate, cross the target cell membrane, and successfully reach the precise binding destination⁵¹. All query compounds were drug-like molecules because they satisfied at least one drug-likeness parameter with water solubility characteristics and good absorption rates. Although one compound exhibited low absorption, it still met the other drug-likeness parameters and could be considered as a potential drug-like molecule for further analysis (Table 4).

Table 4. Druglikeness profile of query compounds.

No	Compounds	Weight (g/mol)	Lipinski	Ghose	Veber	Egan	Muegge	BA	Probable	Water solubility	Absorption
1	2,5-Furandione, 3-methyl-	112.08	Yes	No	Yes	Yes	No	0.55	Drug-like molecule	Very Soluble	High
2	Glycerin	92.09	Yes	No	Yes	Yes	No	0.55	Drug-like molecule	High Soluble	High
3	2,4-Dihydroxy-2,5-dimethyl-3(2 H)-furan-3-one	144.13	Yes	No	Yes	Yes	No	0.85	Drug-like molecule	Very Soluble	High
4	Maltol	126.11	Yes	No	Yes	Yes	No	0.55	Drug-like molecule	Very Soluble	High
5	5-Hydroxymethylfurfural	126.11	Yes	No	Yes	Yes	No	0.55	Drug-like molecule	Very Soluble	High
6	1,2,3-Propanetriol, 1-acetate	134.13	Yes	No	Yes	Yes	No	0.55	Drug-like molecule	Highly Soluble	High
7	4 H-Pyran-4-one, 2,3-dihydro-3,5-dihydroxy-6-methyl-	144.13	Yes	No	Yes	Yes	No	0.85	Drug-like molecule	Very Soluble	High
8	2,4-Hexadienedioic acid	142.11	Yes	No	Yes	Yes	No	0.85	Drug-like molecule	Very Soluble	High
9	4,4-Dimethyl-3-(3-methylbut-3-enylidene)-2-methylenebicyclo[4.1.0]heptane	202.34	Yes	Yes	Yes	Yes	No	0.55	Drug-like molecule	Soluble	Low
10	7-Hydroxymethylbicyclo{2.2.1}heptane-1-carboxylic acid, methyl ester	154.21	Yes	No	Yes	Yes	No	0.55	Drug-like molecule	Soluble	High
11	3.beta.,9.beta.-Dihydroxy-3,5.alpha.,8-trimethyltricyclo[6.3.1.0(1,5)]dodecane	238.37	Yes	Yes	Yes	Yes	Yes	0.55	Drug-like molecule	Soluble	High
12	6-Isopropenyl-4,8a-dimethyl-1,2,3,5,6,7,8,8a-octahydro-naphthalen-2-ol	220.35	Yes	Yes	Yes	Yes	No	0.55	Drug-like molecule	Soluble	High
13	Perhydrocyclopropa[e]azulene-4,5,6-triol, 1,1,4,6-tetramethyl	254.37	Yes	Yes	Yes	Yes	Yes	0.55	Drug-like molecule	Soluble	High
14	9-Octadecenamide, (Z)-	281.48	Yes	Yes	No	Yes	No	0.55	Drug-like molecule	Moderately Soluble	High
15	Medicarpin	270.28	Yes	Yes	Yes	Yes	Yes	0.55	Drug-like molecule	Soluble	High
16	Homopterocarpin	284.31	Yes	Yes	Yes	Yes	Yes	0.55	Drug-like molecule	Soluble	High

Molinspiration v2022.08 (https://www.molinspiration.com/cgi/properties) was used to predict the inhibitory activity of the detected compounds. The classification of inhibitor activity consists of kinases, proteases, and enzymes, referring to drug targets in general, and probability scores with more positive values indicating inhibitory characteristics of the query compounds^52,53. The activity of a compound can trigger specific therapeutic effects; this study aimed to screen the anticancer, antioxidant, and antiplasmodial activities of the query compound. Medium-confidence activation probability (Pa) values for the three activities were theoretically determined using PASSOnline (https://www.way2drug.com/passonline/)⁵⁴. The analysis identified inhibitory properties in all query compounds, including antineoplastic properties against cervical, breast, and colorectal cancers and the potential for treating cancer-associated disorders. Antioxidant activity classifications, including nitric oxide and oxygen scavengers, as well as antiplasmodial potentials, were also identified in the query compounds (Table 5).

Table 5. Bioactivity of query compounds.

No	Compounds	Probability score
		Molinspiration	PASSOnline
1.	2,5-Furandione, 3-methyl-	Kinase Inhibitor: − 3.27 Protease Inhibitor: − 3.07 Enzyme Inhibitor: − 2.02 Probable: inhibitor	Pa: 0.780 (Antineoplastic) Pa: 0.414 (Antineoplastic of cervical cancer) Pa: 0.357 (Antineoplastic of breast cancer) Pa: 0.325 (Antineoplastic of colorectal cancer) Pa: 0.329 (Antioxidant) Pa: 0.449 (Antiplasmodial)
2.	Glycerin	Kinase inhibitor: − 3.54 Protease inhibitor: − 3.52 Enzyme inhibitor: − 3.17 Probable: inhibitor	Pa: 0.449 Antiplasmodial Pa: 0.382 (Cancer associated disorders treatment) Pa: 0.329 (Antioxidant)
3.	2,4-Dihydroxy-2,5-dimethyl-3(2 H)-furan-3-one	Kinase inhibitor: − 1.98 Protease inhibitor: − 1.54 Enzyme inhibitor: − 0.52 Probable: inhibitor	Pa: 0.887 (Apoptosis agonist for cancer) Pa: 0.474 (Antioxidant) Pa: 0.407 (Antiplasmodial)
4.	Maltol	Kinase inhibitor: − 3.19 Protease inhibitor: − 2.85 Enzyme inhibitor: − 1.81 Probable: inhibitor	Pa: 0.930 (Apoptosis agonist for cancer) Pa: 0.619 (Antioxidant) Pa: 0.437 (Antiplasmodial) Pa: 0.436 (Prostate cancer treatment)
5.	5-Hydroxymethylfurfural	Kinase inhibitor: − 2.92 Protease inhibitor: − 3.21 Enzyme inhibitor: − 2.24 Probable: inhibitor	Pa: 0.439 (Antioxidant via oxygen scavenger) Pa: 0.489 (Antineoplastic of renal cancer) Pa: 0.407 (Antineoplastic of bone cancer) Pa: 0.292 (Antiplasmodial)
6.	1,2,3-Propanetriol, 1-acetate	Kinase inhibitor: − 2.36 Protease inhibitor: − 2.06 Enzyme inhibitor: − 1.23 Probable: inhibitor	Pa: 0.601 (Oxygen scavenger) Pa: 0.587 (Antiplasmodial) Pa: 0.345 (Cancer associated disorders treatment)
7.	4 H-Pyran-4-one, 2,3-dihydro-3,5-dihydroxy-6-methyl-	Kinase inhibitor: − 2.25 Protease inhibitor: − 1.53 Enzyme inhibitor: − 0.65 Probable: inhibitor	Pa: 0.587 (Antioxidant) Pa: 0.394 (Antiplasmodial) Pa: 0.337 (Antineoplastic of breast cancer)
8.	2,4-Hexadienedioic acid	Kinase inhibitor: − 1.27 Protease inhibitor: − 0.87 Enzyme inhibitor: − 0.27 Probable: inhibitor	Pa: 0.567 (Antioxidant) Pa: 0.467 (Antiplasmodial) Pa: 0.381 (Cancer associated disorders treatment)
9.	4,4-Dimethyl-3-(3-methylbut-3-enylidene)-2-methylenebicyclo[4.1.0]heptane	Kinase inhibitor: − 0.96 Protease inhibitor: − 0.61 Enzyme inhibitor: 0.13 Probable: inhibitor	Pa: 0.816 (Antineoplastic of breast cancer) Pa: 0.606 (Antiplasmodial) Pa: 0.309 (Antioxidant)
10.	7-Hydroxymethylbicyclo{2.2.1}heptane-1-carboxylic acid, methyl ester	Kinase inhibitor: − 1.95 Protease inhibitor: − 1.08 Enzyme inhibitor: − 0.41 Probable: inhibitor	Pa: 0.521 (Antiplasmodial) Pa: 0.287 (Nitric oxide scavenger) Pa: 0.201 (Antineoplastic for thyroid cancer)
11.	3.beta.,9.beta.-Dihydroxy-3,5.alpha.,8-trimethyltricyclo[6.3.1.0(1,5)]dodecane	Kinase inhibitor: − 0.53 Protease inhibitor: − 0.20 Enzyme inhibitor: 0.36 Probable: inhibitor	Pa: 0.650 (Antineoplastic of lung cancer) Pa: 0.267 (Antioxidant) Pa: 0.250 (Antiplasmodial)
12.	6-Isopropenyl-4,8a-dimethyl-1,2,3,5,6,7,8,8a-octahydro-naphthalen-2-ol	Kinase inhibitor: − 1.04 Protease inhibitor: − 0.42 Enzyme inhibitor: 0.45 Probable: inhibitor	Pa: 0.499 (Antineoplastic of lung cancer) Pa: 0.410 (Antiplasmodial) Pa: 0.345 (Nitric oxide scavenger)
13.	Perhydrocyclopropa[e]azulene-4,5,6-triol, 1,1,4,6-tetramethyl	Kinase inhibitor: − 0.51 Protease inhibitor: − 0.12 Enzyme inhibitor: − 0.03 Probable: inhibitor	Pa: 0.356 (Antiplasmodial) Pa: 0.299 (Nitric oxide scavenger) Pa: 0.290 (Cancer associated disorders treatment)
14.	9-Octadecenamide, (Z)-	Kinase inhibitor: − 0.12 Protease inhibitor: 0.07 Enzyme inhibitor: 0.12 Probable: inhibitor	Pa: 0.682 (Oxygen scavenger) Pa: 0.535 (Antiplasmodial) Pa: 0.382 (Cancer associated disorders treatment)
15.	Medicarpin	Kinase inhibitor: − 0.09 Protease inhibitor: − 0.36 Enzyme inhibitor: 0.48 Probable: inhibitor	Pa: 0.634 (Antineoplastic breast cancer) Pa: 0.495 (Prostate cancer treatment) Pa: 0.303 (Antineoplastic for cell lung cancer) Pa: 0.408 (Antioxidant) Pa: 0.258 (Antiplasmodial)
16.	Homopterocarpin	Kinase inhibitor: − 0.11 Protease inhibitor: − 0.33 Enzyme inhibitor: 0.40 Probable: inhibitor	Pa: 0.641 (Antineoplastic of breast cancer) Pa: 0.508 (Prostate cancer treatment) Pa: 0,355 (Antioxidant) Pa: 0.249 (Antiplasmodial)

Molecular docking simulations play a role in identifying ligand activity on a target through binding affinity values⁵⁵. A negative binding affinity value indicates the strength of target binding, such as inhibitory activity^56,57. Molecular docking simulations were implemented to predict antioxidant, anticancer, and antiplasmodial properties. The binding affinities of 4,4-dimethyl-3-(3-methylbut-3-enylidene)-2-methyl-enebicyclo[4.1.0] heptane were as follows: 6-isopropenyl-4,8a-dimethyl-1,2,3,5,6,7,8,8a-octahydro-naphtha-len-2-ol; 3.beta.,9.beta.-dihydroxy-3,5.alpha.8trimethyl-tricyclo[6.3.1.0(1,5)]-dodecane; perhydrocy-clopropane [e]azulene-4,5,6-triol, 1,1,4,6-tetramethyl; medicarpin and homopterocarpin exhibited more negative binding affinities for catalase (Cat) than ascorbic acid and trolox (Table 6). The negative binding affinities of 3.beta.,9.beta.-dihydroxy-3,5. alpha.,8trimethyl-tricyclo[6.3.1.0(1,5)]-dodecane, medicarpin, and homopterocarpin for SOD1 were higher than those of ascorbic acid and trolox (Table 6).

Table 6. Binding affinity of antioxidant, anticancer, and antiplasmodial candidate compounds.

No	Compounds	CID	Binding affinity (kcal/mol)
			Antioxidant activity		Anticancer activity				Antiplasmodial activity
			Catalase (PDB ID: 1DGH)	SOD1 (PDB ID: 5YTU)	EGFR (PDB ID: 6P8Q)	PDGFR (PDB ID: 5K5X)	VEGFR (PDB ID: 3HNG)	HER2 (PDB ID: 3PP0)	PfPMV (PDB ID: 4ZL4)	PfLDH (PDB ID: 1CEQ)
1.	2,5-Furandione, 3-methyl-	12,012	− 6.1	− 4.6	− 4.8	− 4.9	− 5.1	− 5.6	− 5.1	− 4.8
2.	Glycerin	753	− 4.3	− 3.6	− 4.2	− 3.8	− 4.5	− 3.8	− 4.3	− 3.6
3.	2,4-Dihydroxy-2,5-dimethyl-3(2 H)-furan-3-one	538,757	− 6.7	− 5.0	− 5.8	− 5.2	− 5.5	− 6.0	− 5.5	− 4.6
4.	Maltol	8369	− 5.8	− 4.6	− 5.3	− 4.6	− 4.9	− 5.4	− 5.1	− 4.8
5.	5-Hydroxymethylfurfural	237,332	− 5.7	− 4.9	− 5.2	− 5.2	− 4.8	− 5.4	− 4.6	− 4.6
6.	1,2,3-Propanetriol, 1-acetate	33,510	− 5.0	− 4.1	− 5.0	− 4.4	− 4.3	− 4.9	− 4.5	− 4.4
7.	4 H-Pyran-4-one, 2,3-dihydro-3,5-dihydroxy-6-methyl-	119,838	− 6.4	− 5.0	− 5.4	− 4.8	− 5.4	− 5.9	− 5.4	− 4.9
8.	2,4-Hexadienedioic acid	5,356,793	− 6.2	− 4.8	− 6.0	− 5.3	− 5.4	− 5.8	− 5.0	− 5.1
9.	4,4-Dimethyl-3-(3-methylbut-3-enylidene)-2-methylenebicyclo[4.1.0]heptane	5,371,839	− 7.4	− 6.3	− 7.3	− 6.3	− 6.9	− 6.8	− 6.5	− 6.0
10.	7-Hydroxymethylbicyclo{2.2.1}heptane-1-carboxylic acid, methyl ester	261,531	− 6.8	− 5.0	− 6.0	− 5.4	− 6.4	− 5.7	− 5.7	− 5.0
11.	3.beta.,9.beta.-Dihydroxy-3,5.alpha.,8-trimethyltricyclo[6.3.1.0(1,5)]dodecane	15,599,877	− 7.2	− 7.2	− 8.4	− 6.5	− 7.2	− 6.6	− 6.7	− 6.4
12.	6-Isopropenyl-4,8a-dimethyl-1,2,3,5,6,7,8,8a-octahydro-naphthalen-2-ol	594,234	− 8.4	− 7.5	− 8.5	− 6.5	− 7.6	− 7.5	− 6.5	− 6.1
13.	Perhydrocyclopropa[e]azulene-4,5,6-triol, 1,1,4,6-tetramethyl	536,447	− 8.4	− 6.6	− 9.1	− 7.1	− 6.4	− 7.8	− 7.2	− 6.3
14.	9-Octadecenamide, (Z)-	5,283,387	− 5.4	− 4.9	− 5.5	− 5.4	− 6.8	− 6.7	− 5.9	− 4.7
15.	Medicarpin	336,327	− 9.0	− 8.0	− 8.9	− 7.9	− 8.0	− 7.6	− 7.4	− 6.9
16.	Homopterocarpin	101,795	-8.3	-7.9	− 8.5	-7.8	− 7.7	− 7.4	− 7.3	− 6.8
17.	Vinblastine (Control 1)	13,342			− 8.0	-7.3	− 7.3	− 7.2
18.	Vincristine (Control 2)	5978			− 16.4	-15.4	− 15.3	− 16.3
19	Ascorbic acid (Control 1)	54,670,067	− 6.7	− 5.3
20	Trolox (Control 2)	40,634	− 7.0	− 6.7
21	Chloroquine (Control)	2719							− 5.4	− 5.4

Cat is an enzyme that regulates the cellular equilibrium of free radicals (oxidative stress) and antioxidants, demonstrating efficacy in reducing free radicals linked to diabetes mellitus, Parkinson’s disease, Alzheimer’s disease, cancer, and vitiligo, and can decompose detrimental compounds such as H₂O₂ into H₂O and O₂^58,59. SOD1 contains metal ions such as Zn, Cu, and Mn and acts as a scavenger to produce H₂O₂ by decomposing O_2- ⁵⁹. SOD1 acts as a cofactor for the catalytic activities necessary for cellular physiological responses⁶⁰. SOD1 and Cat protect DNA and cell membranes from ROS-induced damage⁶¹. Vitamin C and trolox reduce oxidative stress in human blood cells in vitro, and an ideal antioxidant combination can decrease free radical concentrations and increase cell membrane stability^62,63.

Compounds with negative binding affinities higher (> − 7.0 kcal/mol) than those of the two controls, ascorbic acid (vit. C) and trolox, were predicted to be potential antioxidant candidates (Table 6). The query compound may bind to the target and initiate the activation of both Cat and SOD1 to trigger an antioxidant response. Three-dimensional structure visualization was performed on ligand-protein complexes from the docking results, showing more negative binding affinity values than those of the control (Fig. 4).

[See PDF for image]

Fig. 4

Visualization of ligand-protein complexes from docking simulations and molecular interaction as antioxidant candidates. (A1) Medicarpin-Cat, (A2) Homopterocarpin-Cat, (B1) Medicarpin-SOD1, (B2) Homopterocarpin-Cat, Cat  Catalase, and SOD1  Superoxide dismutase 1.

The binding affinities of 4,4-dimethyl-3-(3-methylbut-3-enylidene)-2-methylenebicyclo[4.1.0]heptane; 6-isopropenyl-4,8a-dimethyl-1,2,3,5,6,7,8,8a-octahydro-naphthalen-2-ol; 3.beta.,9.beta.-dihydroxy-3,5-alpha.8-trimethyltricyclo[6.3.1.0(1,5)] are low, however, the inhibitory effects of perhydrocyclopropa[e]azulene-4,5,6-triol,1,1,4,6-tetramethyl, medicarpin, and homopterocarpin on EGFR were more pronounced than those of vinblastine (control 1). Perhydrocyclopropa[e]azulene-4,5,6-triol,1,1,4,6-tetramethyl, medicarpin, and homopterocarpin exhibited higher negative binding affinities for PDGFR than vinblastine (control 1). Medicarpin, homopterocarpin, 6-isopropenyl-4,8a-dimethyl-1,2,3,5,6,7,8,8a-octahydro-naphthalen-2-ol, and 3.beta.,9.beta.-dihydroxy-3,5,alpha.,8-trimethyltricyclo[6.3.1.0(1,5)] dodecane exhibited more negative binding affinities for VEGFR than vinblastine (control 1). It was determined that 6-isopropenyl-4,8a-dimethyl-1,2,3,5,6,7,8,8a-octahydro-naphthalen-2-ol, perhydrocyclopropa [e]azulene-4,5,6-triol, 1,1,4,6-tetramethyl, medicarpin, and homopterocarpin exhibited more negative binding affinity values for HER2 than vinblastine (control 1) (Table 6).

EGFR, PDGFR, VEGFR, and HER2 play important roles as growth factors for regulating the proliferation, survival, and metastasis of cancer cells, thus manifesting as ideal targets for anticancer candidates. EGFR signaling is necessary for growth, development, and survival under normal conditions; however, mutations in EGFR can increase the proportion of kinases in tumor cells, thus triggering uncontrolled proliferation and metastasis⁶⁴. PDGF/PDGFR is overexpressed in cancer cell oncogenesis and can promote invasion, metastasis, and angiogenesis through mitogen-activated protein kinase (MAPK) and protein kinase B pathways⁶⁵. The formation of vascular networks or angiogenesis in cancer cells is triggered by VEGFR activity because the tumor microenvironment develops hypoxic stress or hypoxia-inducible factor (HIF) expression, which triggers the upregulation of VEGFR transcription factors⁶⁵. HER2 and ERBB2 are included in the proto-oncogene located on chromosome 17q21, and mutations in these genes in cancer cells can upregulate HER2 to increase gene regulation related to cancer cell survival and metastasis⁶⁶. Moreover, HER2 mutations initiate immune response evasion in cancer cells through a negative feedback mechanism on PD-L1 to prevent recognition by cytotoxic T cells^67,68. Vincristine and vinblastine are alkaloid compounds that act as anticancer agents by inhibiting oncogenesis in cancer cells through apoptosis and by inhibiting several target proteins^68,69.

All compounds with binding affinity values more negative than those of vinblastine were − 8.0 kcal/mol. Therefore, the query compound may be the best anticancer candidate because its binding affinity exceeds that of a control for each target protein. Three-dimensional structure visualization was performed on ligand-protein complexes from the docking results, showing more negative binding affinity values than those of the control (Fig. 5).

[See PDF for image]

Fig. 5

Visualization of ligand-protein complexes from docking simulations and molecular interaction as anticancer candidates. (A1) Medicarpin-EGFR, (A2) Homopterocarpin-EGFR, (B1) Medicarpin-PDGFR, (B2) Homopterocarpin-PDGFR, (C1) Medicarpin-VEGFR, (C2) Homopterocarpin-VEGFR, (D1) Medicarpin-HER2, (D2) Homopterocarpin-HER2, EGFR = epidermal growth factor receptor, PDGFR = Platelet-derived growth factor receptor, VEGFR = Vascular Endothelial Growth Factor Receptor, and HER2 = human epidermal growth factor receptor 2.

Binding affinities of 6-isopropenyl-4,8a-dimethyl-1,2,3,5,6,7,8,8a-octahydro-naphthalen-2-ol; 4,4-dimethyl-3-(3-methylbut-3-enylidene)-2-methylenebicyclo[4.1.0]-heptane; 3-beta.,9.beta.-dihydroxy-3,5,alpha.,8-trimethyltricyclo[6.3.1.0(1,5)]dodecane; 7-hydroxymethylbicyclo{2.2.1}heptane-1-carboxylic acid methylester; perhydrocy-clopropa [e]azulene-4,5,6-triol,1,1,4,6-tetramethyl,9-octadecenamide, (z)-medicarpin, and homopterocarpin were more negative for PfPMV than those of chloroquine (Table 6). Furthermore, 4,4-dimethyl-3-(3-methylbut-3-enylidene)-2-methylenebicyclo-[4.1.0]heptane;6-isopropenyl-4,8a-dimethyl-1,2,3,5,6,7,8,8a-octahydro-naphthalen-2-ol; 3.beta.,9.beta.-dihydroxy-3,5,alpha,8-trimethyltricyclo[6.3.1.0(1,5)]dodecane; perhydrocyclopropa [e]azulene-4,5,6-triol,1,1,4,6-tetramethyl, medicarpin, and homopterocarpin exhibited more negative binding affinities for PfLDH than chloroquine (Table 6).

PfPMV can trigger increased virulence and intracellular transport of the parasite from the red blood cell membrane to the cytosol. Thus, PfPMV is a potential target for antimalarial agent inhibition, as it functions in parasite development and erythrocyte degradation^70,71. PfLDH inhibition can prevent the development and pathogenesis of malarial parasites. Under normal conditions, the enzyme plays a catalytic role in converting pyruvate into lactate for energy production in parasites^72,73. Chloroquine is a drug used to treat P. vivax and P. falciparum malaria and can interact with genetic material and functional proteins to inhibit the development of these parasites at a specific stage^74,75. All query compounds with binding affinity values more negative than that of chloroquine (control) (-5.4 kcal/mol) (Table 6) are predicted to be good antiplasmodial candidates because they can trigger the inhibition of PfPMV and PfLDH.

Overall, molecular analysis showed that medicarpin has a lower binding affinity compared to homopterocarpin. This indicated that the biological aspect of medicarpin is potential compared to homopterocarpin. The interaction of medicarpin with the target protein is easily released and bound. This is possible because medicarpine has a lighter molecular weight compared to homopterocarpin. In addition, medicarpin is more polar compared to homopterocarpin as its parent compound (Table 4).

Molecular interaction analyses

Antioxidant activity

Molecular interactions, including Van der Waals, conventional hydrogen, alkyl/pi-alkyl, pi-sigma, pi-anion, and pi-cation bonds, of the Cat domain candidate antioxidant ligands showed similar interactions at Tyr358, Ile165, Gly131, Gly147, Asn148, Val146, Phe153, His218, Leu299, Arg354, Met350, Phe161, Val74, and Val116. The ligand interactions in the SOD1 domain included van der Waals, conventional hydrogen, carbon-hydrogen, pi-cation, pi-sigma, pi-cation, and acyl/pi-alkyl bonds, with similar interaction positions at Gly85, Asn86, Gly130, Ser98, Glu100, Gly127, Thr135, Ile99, Pro74, Lys128, and Lys75 (Table 7). The ligand molecular interactions in the target domain are displayed using a two-dimensional plot (Fig. 5).

Table 7. Molecular interaction of antioxidant compounds on target domains.

Target	Compound	Interaction domain
Catalase	Medicarpin	Conventional Hydrogen: Ala418 Carbon Hydrogen/Pi-Donor Hydrogen: Val35, Ala345, Glu344, Ser337 van der Waals: Leu355, Gln53, Lys221, Ile343, Pro341, Asp37, Leu419, Gly36, Pro34, Val56 Pi-Anion: Glu420 Alkyl/Pi-Alkyl: Val55, Met339
	Homopterocarpin	Conventional Hydrogen: His362 van der Waals: Phe153, Asn148, Pro129, Gly131, Gly147, Phe132, Ala133, Val146, Phe334, Tyr358, Arg365, Thr361, Arg72, Arg112, Ser114, Val74, Thr115 Pi-Alkyl: Val116
SOD1	Medicarpin	Conventional Hydrogen: Gly130, Leu84, Asn86 Carbon Hydrogen: Ser98, Glu78 van der Waals: Gly85, Lys128, Thr135, Ser98, Gly127, His71, Asp76, Lys75, Glu100 Pi-Cation: Lys70 Pi-Sigma: Ile99 Pi-Alkyl: Pro74
	Homopterocarpin	Carbon Hydrogen: Lys128, Glu100 van der Waals: Pro74, Leu84, Asn86, Gly85, Gly130, Gly127, Thr135, His71, Gly72, Glu78, Asp76, Lys75 Pi-Cation: Lys70 Alkyl/Pi-Alkyl: Ile99
EGFR	Medicarpin	Conventional Hydrogen: Met1002 Carbon Hydrogen: Pro741 van der Waals: Leu792, Glu1004, Lys846, Glu1004, Asp1003, Gln791, Leu1001, Pro794 Alkyl/Pi-Alkyl: Leu1017, Met1002, Pro794, Pro1019, Pro741
	Homopterocarpin	Carbon Hydrogen: Leu1001, Pro741 van der Waals: Pro794, 2(Leu792), 2(Gln791), Val742, Met1002, Met793, Lys846, Leu1001 Alkyl/Pi-Alkyl: Pro741, Leu1017, Pro794
PDGFR	Medicarpin	Conventional Hydrogen: Arg558 van der Waals: Arg817, Glu556, Tyr555, Arg554, Phe604, Gly838, Phe856, Thr855, Leu857 Pi-Cation: Arg558 Pi-Alkyl: Ile843
	Homopterocarpin	Coventional Hydrogen: Arg558 Carbon Hydrogen: Glys838, Arg817 van der Waals: Leu839, Phe604, Tyr555, Glu556, Phe856, Thr855, Leu857 Pi-Cation: Arg558 Pi-Alkyl: Ile843
VEGFR	Medicarpin	Conventional Hydrogen: Asp1040 Carbon Hydrogen: Glu878, His1020 van der Waals: Val891, Leu1013, Cys1018, Ile1019, Arg1021, Val909, Lys861, Cys1039, Ile1038, Ile885 Pi-Anion: Asp1040 Pi-Sigma: Leu882 Pi-Pi T-shaped: His1020 Alkyl/Pi-Alkyl: Val892, Ile881
	Homopterocarpin	Conventional Hydrogen Bond: Asp1040 van der Waals: Ile1038, Val891, Cys1018, Leu1013, Ile885, Cys1039, Val892, Val909, Lys861, Glu878, Lys861, Arg1021 Pi-Anion: Asp1040 Pi-Sigma: Leu882 Pi-Pi T-shaped: His1020 Alkyl/Pi-Alkyl: Ile881, Leu882
HER2	Medicarpin	van der Waals: Asp863, Thr862, Leu796, Thr798, Leu726, Ser728, Gly727 Pi-Sigma: Val734 Alkyl/Pi-Alkyl: Lys753, Ala751, Leu852, Val734
	Homopterocarpin	Carbon hydrogen: Gly727 van der Waals: Ser728, Leu726, Thr798, Leu796, Asp863, Thr862 Pi-Sigma: Val734 Alkyl/Pi-Alkyl: Val734, Leu852, Ala751, Lys753
PfPMV	Medicarpin	van der Waals: Phe180, Tyr61, Leu179, Phe318, His320, Thr317, Ser316, Gly315, Asp80, Ala60 Pi-Donor Hydrogen: Tyr139 Pi-Sigma: Ile78 Pi-Alkyl: Val188
	Homopterocarpin	Carbon Hydrogen: Lys214 van der Waals: Leu213, Gln215, Phe207, Pro211, Asp208, Ser151, Leu169, Lys168, Asn209, Leu205, Gln455 Alkyl/Pi-Alkyl: Lys214, Pro200, Arg167
PfLDH	Medicarpin	Conventional Hydrogen: Arg171 Carbon Hydrogen: Ser245 van der Waals: Pro250, Pro246, Tyr247, Val248, Thr235, Ser170 Pi-Sigma: Ile239 Pi-Pi Stacked: Tyr174 Alkyl/Pi-Alkyl: Ala249, Arg171
	Homopterocrapin	Conventional Hydrogen: Arg171 Carbon Hydrogen: Ser170, Ser245 van der Waals: Thr235, Pro246, Pro250, Val248, Tyr247 Pi-Sigma: Ile239 Pi-Pi Stacked: Tyr174 Alkyl/Pi-Alkyl: Ala249, Arg171, Ile239

Anticancer activity

The molecular interactions of candidate anticancer ligands formed on the EGFR domain included van der Waals, conventional hydrogen, and alkyl/pi-alkyl bond types, with similar interaction positions at Leu100, Pro1019, Pro741, and Met1002. Pro794, Leu792, and Leu1017. Ligand interactions in the PDGFR domain included van der Waals, conventional hydrogen, carbon-hydrogen, pi-cation, and acyl/pi-alkyl bonds, with similar interaction positions at Thr855, Leu857, Arg558, Glu556, Tyr555, Gly838, Phe604, Phe856, Ile843, and Arg554. Ligand interactions in the VEGFR domain included van der Waals, conventional hydrogen, carbon-hydrogen, pi-anion, pi-sigma, pi-pi T-shaped, and alkyl/pi-alkyl bonds, with similar interaction positions at Lys861, Val891, Ile885, Leu1013, Lys861, Asp1040, Glu878, Cys1018, Ile881, Leu882, Cys1039, Val909, Ile1038, and His1020. The ligand interactions in the HER2 domain included van der Waals, conventional hydrogen, carbon-hydrogen, pi-anion, alkyl/pi-alkyl, pi-sigma, and unfavorable bond types, with similar interaction positions at Asp863, Asn850, Lys753, Thr862, Gly727, Gly804, Leu852, Val734, Leu726, Leu800, Phe1004, Met801, and Ala751 (Table 7). The molecular interactions between the ligand and target domains are shown in a two-dimensional plot (Fig. 6).

[See PDF for image]

Fig. 6

Visualization of ligand-protein complexes from docking simulations and molecular interaction as antiplasmodial candidate (A1) Medicarpin-PfPMV, (A2) Homopterocarpin-PfPMV, (B1) Medicarpin-PfLDH, (B2) Homopterocarpin-PfLDH.

Anti-plasmodium candidates

Molecular interactions of the anti-plasmodial candidate ligands formed on the PfPMV domain included van der Waals, conventional hydrogen, alkyl/pi-alkyl, pi-donor hydrogen, and pi-sigma bond types, with interaction positions at Ser151, Lys168, Gln215, Pro200, Arg167, Leu169, Leu205, Pro211, and Lys214. Ligand interactions in the PfLDH domains included van der Waals, conventional hydrogen, carbon-hydrogen, pi-cation, pi-sigma, pi-pi stacked, unfavorable acceptor-acceptor, and alkyl/pi-alkyl bond types, with similar interaction positions at Glu310, Glu311, Lys203, Val233, Met199, Phe229, Leu202, Lys314, Val200, Leu201, and Phe229 (Table 7). The ligand-molecule interactions in the target domain are displayed using a two-dimensional plot (Fig. 7).

[See PDF for image]

Fig. 7

Graph of RMSF values ​​from the molecular dynamic simulation results. (A1) Medicarpin-Cat, (A2) Homopterocarpin-Cat, (B1) Medicarpin-SOD1, (B2) Homopterocarpin-SOD1, (C1) Medicarpin-EGFR, (C2) Homopterocarpin-EGFR, (D1) Medicarpin-VEGFR, (D2) Homopterocarpin-VEGFR, (E1) Medicarpin-PDGFR, (E2) Homopterocarpin-PDGFR, (F1) Medicarpin-HER2, (F2) Homopterocarpin-HER2, (G1) Medicarpin-PfPMV, (G2) Homopterocarpin-PfPMV, (H1) Medicarpin-PfLDH, (H2) Homopterocarpin-PfLDH, Cat = Catalase, SOD1 = Superoxide dismutase 1, PDGFR = Platelet-derived growth factor receptor, VEGFR = Vascular Endothelial Growth Factor Receptor, HER2 = human epidermal growth factor receptor 2, PfPMV = P. falciparum plasmepsin V, and PfLDH = P. falciparum lactate dehydrogenase.

The stability of molecular complexes consisting of ligands and proteins from the molecular docking simulation results was determined via molecular dynamics analysis using CABS-flex v2.0. Molecular complexes with anticancer activity, namely medicarpin and homopterocarpin, showed average RMSF values of 0.954 and 0.878 Å at EGFR, 1.007 and 1.072 Å at PDGFR, 0.917 and 1.012 Å at VEGFR, and 0.860 and 0.942 Å at HER2, respectively. Molecular complexes with antioxidant activity, i.e., medicarpin and homopterocarpin, showed average RMSF values of 1.205 and 1.172 Å at Cat and 1.269 and 1.381 Å at SOD1, respectively. Molecular complexes anti-plasmodial activity, namely medicarpin and homopterocarpin, showed average RMSF values of 0.859 and 0.848 Å in PfPMV and 0.702 and 0.870 Å in PfLDH (Fig. 7), respectively. The RMSF parameter was used on the server to identify the stability of bond interactions with values < 3 Å⁷⁶. All molecular complexes had an average RMSF value > 3 Å, indicating stable fluctuations formed in the interaction of the ligand with the target. The molecular dynamics simulation results for medicarpin with various targets are provided at the following links (Supplementary Data III).

In summary, in silico studies showed that drug-likeness analyses for medicarpin and homopterocarpin had the same values in some categories, excluding molecular weight (Table 4). The bioactivity prediction of medicarpin showed higher values than that of homopterocarpin for some criteria, based on the Molinspiration and PASSonline software (Table 5). Furthermore, the binding affinities of medicarpin and homopterocarpin with some protein targets were lower than those of ascorbic acid and trolox for antioxidant activity, vinblastine for anticancer activity, and chloroquine for antiplasmodial activity (Table 6).

Moreover, the molecular interactions between the ligand and protein showed that medicarpin is more stable than homopterocarpin. The docking scores of medicarpin with antioxidant, anticancer, and antiplasmodial proteins were lower than those of homopterocarpin based on the binding affinity energy and molecular interaction. Thus, in silico studies corroborated the findings of in vitro assays for medicarpin and homopterocarpin activities.

Conclusion

To our knowledge, this is the first report demonstrating the biotransformation of homopterocarpin to medicarpin using A. niger, suggesting an alternative biotechnological source for the green production of valuable bioactive compounds from traditional Thai medicine. Overall, the study findings characterize the anti-liver cancer and antiplasmodial of of A. niger-produced medicarpin based on in vitro and computational studies for development as a drug candidate. However, optimization methods must be further improved for the efficient production of valuable compounds and enzymes. Then, further studies on medicarpin for disease control are essential including in vivo and clinical studies.

Acknowledgements

We thank Mr. Sujarwo for his help with plant extraction and Mr. Viol for his help with in-silico analysis.

Author contributions

DKW, SW, WB, SPP, and SP designed the study. DWK performed experiments and analysed data. DKW, SW, WB, SPP, and SP wrote and edited the manuscript. DKW, SW, WB, SPP, and SP confirmed the authenticity of all the raw data and reviewed the manuscript. All authors have read and approved the final manuscript.

Funding

This study was financially supported by the Second Century Fund (C2F) of Chulalongkorn University.

Data availability

The data generated in the present study are included in the figures and/or tables of this article.

Declarations

Competing interests

The authors declare no competing interests.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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