In silico molecular docking of cyclooxygenase (COX-2), ADME-toxicity and in vitro evaluation of antioxidant and anti-inflammatory activities of marine macro algae

Abstract

The marine ecosystem harbors unique and diverse bioactive compounds that can offer a vast repertoire of molecules with therapeutic properties. In the present study, four different species of red marine seaweeds were analyzed for its phytoconstituents and the potent antioxidant and anti-inflammatory activity of the methanolic extracts were screened and determined. The results revealed that, among the 4 samples, G. corticata, scored a good antioxidant potential by DPPH (67.61 ± 1.23%, IC₅₀ = 577.7 µg) and metal chelation assay (29.40 ± 0.32%, IC₅₀ = 1684 µg). The anti-inflammatory analysis has shown that, H. dialata was found to exhibit maximum inhibition against the albumin denaturation (83.50 ± 0.24%), whereas G. corticata was observed to measure a maximum inhibition in heat-induced hemolysis (60.40 ± 0.46%) and proteinase inhibition assay (83.30 ± 0.18%). An extensive literature survey was carried out for the bioactive compounds in G.corticata; it was examined for drug likeliness by ADME analysis and toxicological parameters. Further, the best selected bioactive compounds were subjected to in silico molecular docking with pro-inflammatory target, cyclooxygenase (COX-2). Hexadecanal and Neophytadiene were reported to obtain the highest binding affinity (−5.3) for COX-2 enzyme. Hence, in silico molecular docking studies had shown that G. corticata was found to possess potential anti-inflammatory activity that can prevent conversion of arachidonic acid to prostaglandins by inhibiting COX-2. In addition, molecular dynamic simulation studies have shown the stability of Hexadecanal-6 COX complex. To conclude, the outcomes of the present study may shed light on the understanding of the usage of bioactive compounds for therapeutic purpose.

Introduction

Inflammation typically occurs when infectious microorganisms such as bacteria, viruses, or fungi enter the body, resides in specific tissues, and/or circulate in the blood. It also occurs as a result of cell death, tissue injury and various hypoxia related diseases (Artis et al. 2015). The innate immune system activates diverse types of cells like macrophages, mast cells, and dendritic cells that show a potential defense mechanism against invading microorganisms (Waisman et al. 2015). Various types of inflammatory mediators are secreted at the site of inflammation. Among them, prostaglandins (PG) E₂ are the most studied inflammatory mediator which is interconnected with many inflammatory diseases (Goetzl et al. 1995). It plays an important role in maintaining the temperature and integrity of the gastric mucosal lining. In contrary, any alterations in prostaglandins function will lead to various kinds of inflammatory responses (Brock et al. 2007). The synthesis of PGs begins with the production of arachidonic acid from cell membrane phospholipids by phospholipase A2 (PLA2). Further, this arachidonic acid gets converted to prostaglandins by catalyzing enzyme cyclooxygenases. Among the three known COX isoforms (COX-1, COX-2, and COX-3), the inducible enzyme COX-2 is known to be the most active during inflammatory processes (Zelová et al. 2013). The overexpression and upregulation of the pro-inflammatory enzyme cyclooxygenase (COX-2) results in the formation of prostaglandins (PGs) (Fig. 1), which in turn triggers the inflammatory responses (Seibert et al. 1994).

Fig. 1.

Schematic representation of the algal extracts in the inhibition of Cyclooxygenase pathway by preventing the conversion of arachidonic acid to prostaglandin G₂

Natural products isolated from marine origin have advanced in the discovery of potential anti-inflammatory pharmacophore agents in recent years. Discovery of phytochemical constituents and bioactive compounds from natural sources in managing various kinds of oxidative stress related diseases like cancer, diabetes, inflammatory diseases (Mitra et al. 2022). Marine seaweeds are considered to be one of the most potent organisms in the ocean that synthesizes various kinds of bioactive compounds like polyphenols, steroids, lectins and polysaccharides with wide pharmacological importance in treating various kinds of diseases. Marine natural products with anti-inflammatory activity are considered to be one of the most ongoing researched topics (Souza et al. 2020). With respect to inflammatory studies, COX-2 inhibitory agents that are specific and target-oriented have drawn numerous attentions with respect to the usage of bioactive compounds synthesized from marine seaweeds. The systemic inhibition of COX-1 results in a decrease of cyto-protective PGs required for effective mucosal defense. Both upregulation and increased expression of COX-2 are linked with various kinds of inflammatory conditions, neovascularization, repeated cell division, and angiogenesis. Moreover, COX-2 is also referred as an immuno-suppresser where the PGE₂ suppresses the natural killer cell and macrophage cell mediated cytotoxicity (Leng et al. 2003). Although several drugs, such as non-steroidal anti-inflammatory drugs (NSAIDs) and steroids, are commercially available to treat the inflammatory conditions, the side effects of these medications are harmful, including cardiovascular disease, drug dependency and gastro-intestinal ulcer as well. Thus, novel therapeutic agents of natural marine origin with no side effects are desirable as an alternative to currently available chemical therapeutics for safe, relatively inexpensive, and convenient for many patients. The knowledge about the pharmacological importance and the mode of action of the bioactive compounds from marine seaweeds are still under investigation. Hence, further evaluation, standardization and utilization of marine derived bioactive compounds for their development into a drug like candidate demands advanced computational tools. Therefore, the present study focuses on the assessment of the bioactive compounds for their anti-inflammatory properties and evaluated the drug-likeness of the compounds from various marine algal extracts using advanced computational tools and the ligand–protein interaction between the bioactive compounds with COX-2, determined by in silico molecular docking MD simulation studies.

Materials and methods

Materials

Folin–Ciocalteu (SD fine), Gallic acid (SD fine), Sodium carbonate (SD fine), Aluminium chloride (SD fine), vanillin (SD fine), sulphuric acid (thermo fisher), DPPH (2, 2-diphenyl-1-picrylhydrazyl) (SRL), sodium phosphate (SD fine), ammonium molybdate (SD fine), ferrous sulphate (SD fine), ferrozine (CDH), potassium ferric cyanide (SD fine), ferric chloride (SD fine), trichloroacetic acid (SRL), Bovine serum albumin (Sigma), trypsin (Sigma), Tris–HCL (Sigma), perchloric acid (SRL), sodium chloride (SD fine), diclofenac sodium (commercial- Novartis).

Collection and sample preparation

Red marine seaweeds were collected from Gulf of Mannar, Southeast coastal region of Tamil Nadu, India (9° 28′ N, 79° 18′ E) (Fig. 2). The seaweeds were cleaned by showing in running tap water for 2–3 times for eliminating the epiphytes, sands and salts. The cleaned algal samples were shade-dried at room temperature (25 ºC). A small part of the sample has been sent for identification and authentication to Botanical survey of India (BSI), Coimbatore. Further, the dried samples were grinded finely and stored at 4 ºC for further analysis.

Fig. 2.

Geographical location of marine seaweed collection site at Gulf of Mannar (Google Map source)

After the collection of marine seaweeds, the samples were washed 6–7 times in running tap water and dried for almost 10–15 days. After drying the sample, it is chopped and grinded using the mortar and pestle to avoid heating up of the sample during grinding. After grinding, the sample was sieved to get a fine powder of the seaweed. From this, 5 g of powdered sample was macerated with 100 ml of 5 different solvent systems (ethanol, methanol, chloroform, ethyl acetate and aqueous) and kept in shaker for 48 h. After the incubation, the samples were extracted for its phytochemical constituents using Whatman filter paper (size #1) by evaporating the solvents completely. Further, it was scrapped and stored in an amber bottle at 4 °C for further use.

Qualitative analysis of phytochemicals

Various qualitative tests were performed for the screening of phytochemicals with the standard protocol followed by (Riffat Batool et al. 2019).

Quantitative estimation of the algal extracts

Estimation of total phenol content (TPC)

The determination of total phenolic contents was studied by Folin–Ciocalteu (FC) method (Harborne et al. 1973). Using gallic acid as the standard and the values were expressed as GAE mg/ml. Variuos concentrations of the sample were prepared (100–800 μg/ml). Accordingly, 1 ml of algal extract was added to 1 ml of FC reagent and incubated for 5 min. After the peroid of incubation, 1 ml of sodium carbonate was added and further left for incubation for 30 min. As a final point, the reaction was ended up by adding 2 ml of distilled water and the absorbance was measured at 765 nm using UV–vis spectrometer (UV-1650 Shimadzu, Japan). A similar procedure was followed for the standard gallic acid. The evaluation was completed in triplicate for each step. GAE mg/g of the extract was used to express the total phenol content.

Estimation of total flavonoid content (TFC)

The estimation of total flavonoid was carried out using the method followed by (Meda et al. 2005) with few minor modifications. To 1 ml of varying concentrations (100–800 μg/ml) of algal extract, 0.5 ml of 10% aluminium chloride was added and the absorbance was noted at 430 nm using UV–vis spectrometer (UV-1650 Shimadzu, Japan). A similar protocol was followed for the standard Quercetin with varying concentrations (20–100 μg/ml) and finally the values were expressed as Quercetin equivalent (QE/g) for the extracts.

Estimation total tannin content (TTC)

The total tannin content was estimated using FC (Folin–Ciocaltaeu) (Indira CT et al. 2016) with minor modifications. Approximately 1 ml of algal extract and 1 ml of FC reagent were added to 2 ml of distilled water. To this reaction mixture, 35% sodium carbonate and 1 ml of distilled water was added and kept for incubation at room temperature for 30 min. Tannic acid was kept in a complete set of reference standards with concentrations ranging from 20 to 100 μg/ml, and the absorbance was determined at 700 nm using a UV 1650 spectrophotometer Shimidzu, Japan.

Estimation of total saponin content (TSC)

The total saponin content was examined by the protocol which was followed by Hiai et al. 1976, by vanillin sulfuric acid method. To 1 ml of algal extracts, 8% (w/v) of vanillin and 72% (w/v) of sulfuric acid was mixed and incubated at 60 ºC for 10 min. After incubation, the tubes were cooled in an ice water bath for 15–20 min and the absorbance was measured using UV 1650 spectrophotometer, Shimidzu, Japan, at 538 nm. Diosgenin was used as a reference standard and the total saponin content was expressed as Diosgenin saponin equivalent (DSE mg/ml).

In vitro antioxidant studies

DPPH radical scavenging assay (2, 2-diphenyl-1-picrylhydrazyl)

The DPPH radical scavenging test followed by (Re et al. 1999) was used to determine the algal extracts’ capacity to scavenge free radicals. The ability of the algal extracts to contribute the electrons that lead to the decolorization of DPPH as a result of the reduction process from DPPH to DPPHH was used to study the scavenging activity of the extracts. Briefly, 50 μl of algal extract ranging from 100 to 800 μg/ml was added to 150 μl of 0.1 mM DPPH. The reaction mixture was mixed properly and incubated in dark for 30 min at room temperature. The absorbance was recorded at 517 nm using ELISA reader (LISA plus). The same was followed for ascorbic acid as a standard reference and inhibition percentage was calculated using the following formula:

$$\%\text{of inhibition}=\frac{\text{Abs}C-\text{Abs}}{T}\text{Abs}C\times 100,$$

Abs T = absorbance of test sample, Abs C = absorbance of control.

Total antioxidant capacity (TAC)

The total antioxidant potential of the algal extracts was measured using phosphomolybdenum method which was followed by Prieto et al. (1999). The assay relies on the reduction of molybdenum (VI)–(V), which produces a green-colored product. Phosphomolybdenum reagent was prepared by combining 0.6 M sulphuric acid with 28 mM sodium phosphate and 4 mM ammonium molybdate. 600 μl of various concentrations (100–800 μg/ml) of algal extract was added to 1.2 ml of phosphomolybdenum reagent. The reaction mixture was thoroughly vortexed and kept in water bath for 90 min at 95 °C. The tubes were allowed to cool and the absorbance was recorded at 695 nm (UV 1650 spectrophotometer Shimidzu, Japan). Tannic acid was used as standard and the values were expressed as TAE (µM/ml).

Metal chelation assay

Metal chelation property of the algal extract was studies using the protocol followed by Dastmalchi et al. (2008). Briefly, 100 µl of 2 mM ferrous sulphate was added to 1 ml of algal extracts of various concentrations (100–800 µg/ml) and incubated at room temperature for 5 min. Further 400 µl of 5 mM ferrozine was added to the tubes and kept for incubation for 15 min. The absorbance was measure at 562 nm (UV 1650 spectrophotometer, Shimidzu, Japan). The same protocol was followed for the standard EDTA and the values were expressed by the following method:

$$\%\text{of inhibition}=\frac{\text{Abs}C-\text{Abs}}{T}\text{Abs}C\times 100,$$

Abs T = absorbance of test sample, Abs C = absorbance of control.

Reducing power asaay

The reducing potential of the algal extracts was investigated by the method followed by Landry et al. (2000). To 1 ml of algal extracts with varying concentrations (100–800 µg/ml), 2.5 ml of 1% potassium ferric cyanide and 2.5 ml of 0.2 M phosphate buffer (pH 6.6) was added and incubated for 20 min at 50 ºC. Further, 2.5 ml of 10% trichloroacetic acid was added. The reaction mixture was centrifuged for 10 min at 3000 rpm. To the supernatant, 500 µl of 0.1% ferric chloride solution was added and the absorbance was recorded at 700 nm (UV 1650 spectrophotometer, Shimidzu, Japan). Ascorbic acid was used a standard and the values were expressed as µg/ml.

In vitro anti-inflammatory assays

Inflammation is a complex biological process in response to tissue injury and damage. It is associated with pain, swelling redness, loss of function and increased temperature at the site of injury. The body’s response to irritants, invaders, and to prepare the environment for tissue healing is known as inflammation. The process is sped up by the release of chemical mediators from damaged cells and tissues as well as migratory cells. Leukocyte migration from venous networks to the site of injury and cytokine release are known to have a significant role in the inflammatory response. The treatment of inflammatory disorders frequently involves the use of non-steroidal anti-inflammatory medications (NSAID). These medications do, however, have a number of undesirable side effects, particularly gastrointestinal irritation, which can result in the development of gastric ulcers. As a result, there has been a significant surge in recent years in the quest for natural sources and phytochemicals with anti-inflammatory potential. Hence, the algal extracts have been checked for its efficiency in stabilizing the membrane of proteins by preventing it from the process of denaturation.

Erythrocytes suspension preparation

Erythrocyte suspension preparation was done according to the method followed by Shin de et al. (1999). A healthy human subject’s whole blood was taken. In a heparinized centrifuge tubes, the blood was centrifuged at 3000 rpm for 5 min and further cleaned thrice with normal saline (0.9% NaCl). Further the blood volume was measured and reconstituted (10% v/v) with 10 mM Sodium phosphate buffer at pH 7.4.

Protein denaturation assay

Protein denaturation assay was performed according to the protocol followed by Gunathilake et al. (2018). Briefly, 1 ml of 1% BSA (Bovine serum albumin) and 1 ml of algal extracts of varying concentration (100–800 µg/ml) was added to 1 ml of PBS (Phosphate buffer saline) (pH 6.4). The reaction mixture was incubated in water bath at 70 ºC for 15 min. The mixture was allowed to cool completely and the turbidity was measured at 660 nm in UV-1800 spectrophotometer, Shimidzu, Japan. The inhibition of protein denaturation was calculated according to the following formula:

$$\%\text{inhibition of protein denaturation}=\frac{\text{Abs}C-\text{Abs}}{T}\text{Abs}C\times 100$$

Abs T = absorbance of test sample, Abs C  = Absorbance of Control.

Proteinase inhibitory assay

The inhibition of proteinase was studied using the protocol followed by Sakat et al. (2010). Briefly, the reaction contained 0.06 mg trypsin, 1 ml of 20 mM Tris–HCL buffer of pH 7.4 and 1 ml of varying concentrations (100–800 µg/ml) of the methanolic algal extracts. The reaction mixture was incubated at 37 ºC for 30 min. Further, 1 ml of 0.8% of casein (w/v) was added and incubated for 30 min at room temperature. Finally, 2 ml of 70% perchloric acid was added to the mixture to stop the reaction. Furthermore, the reaction mixture was centrifuged at 2500 rpm for 5 min and the supernatant was measured at 210 nm against the blank (UV-1800 spectrophotometer, Shimidzu, Japan). The proteinase inhibition percentage was calculated according to the following formula:

$$\text{Proteinase inhibition}\%=\frac{\text{Abs}C-\text{Abs}}{T}\text{Abs}C\times 100$$

Abs T = absorbance of test sample, Abs C = absorbance of control.

Heat-induced hemolysis

The heat-induced hemolysis assay was carried out by the protocol followed by Okoli et al. (2008). To 50 µl of blood suspension, 1 ml of algal extracts of varying concentration (100- 800 µg/ml) was added along with 2.95 ml of phosphate buffer (pH 7.4). The reaction mixture was incubated for 20 min at 54 ºC in a shaking water bath. The mixture was cooled and centrifuged at 2500 rpm for 5 min and the absorbance of the supernatant was measured at 540 nm by UV–Vis spectrophotometer (UV-1800, Shimidzu, Japan).

$$\text{\% inhibition of}\text{hemolysis}=\frac{\text{Abs}C-\text{Abs}T}{\text{Abs}C}\times 100$$

Abs T = absorbance of test sample; Abs C = absorbance of control.

Hypotonicity-induced hemolysis

Hypotonic solution-induced hemolysis was investigated by subjecting HRBC to examine the membrane stabilization of the cells by the protocol followed by Chandra et al. (2012). To 100 µl of HRBC cell suspension, 5 ml of hypotonic solution (0.9% NaCl) and 1 ml of varying concentrations (100–800 µg/ml) of algal extracts. The reaction mixture was kept for incubation for 10 min and then centrifuged at 3000 rpm for 10 min. The positive control contained 100 µl of HRBC cell suspension and 5 ml of hypotonic solution with standard diclofenac sodium (100 µg/ml). The negative control consisted of 100 µl of HRBC cell suspension and 5 ml of hypotonic solution alone. The absorbance of the supernatant was measured at 540 nm (UV-1800, Shimidzu, Japan). The percentage of inhibition of hemolysis was determined by the following formula:

$$\%\text{inhibition of hemolysis}=\frac{\text{Abs}C-\text{Abs}}{T}\text{Abs}C\times 100$$

Abs T = absorbance of test sample; Abs C  = absorbance of control.

Bioactive compounds library preparation for in silico analysis

For in silico analysis, the bioactive compounds have been obtained from the extensive literature survey taking the consideration of details of bioactive compounds through GC–MS (Ragunathan et al. 2019; Rajkumar et al. 2017; Uma Maheswari et al. 2017). The chemical compounds were examined through existing literature survey on the targeted protein Cyclooxygenase-2.

ADME analysis and pharmacokinetics toxicity analysis

The chemical structures and the canonical structures of the bioactive compounds of G.corticata and H.dialata were taken from Pubchem (www.pubchem.ncbi.nlm.nih.gov).The selected bioactive compounds were subjected for ADME analysis. In this analysis, the compounds were checked for its physicochemical parameters, pharmacokinetics analysis and drug-likeness behavior of the compounds using SWISSADME server (http://www.swissadme.ch/index.php). Further, the oral toxicity predictions were done using Protox ii (tox.charite.de), where the selected compounds were evaluated for its carcinogenicity, immunotoxicity, hepatotoxicity and toxicological pathways (Babatunde Joseph Oso et al. 2020).

Molecular docking

Protein and ligands preparation

The 3D SDF structures of the bioactive compounds of G. corticata and H. dialata were retrieved from the Pubchem database. The crystal structure of the Cyclooxygenase-2 (PDB-ID: 6 COX) protein with diclofenac as the standard drug, was taken from PDB files (www.rcsb.org). For molecular docking, the protein molecule was removed from the water molecules, heteroatoms and bounded peptide inhibitors. Further this modified protein target was used for docking studies (Babatunde Joseph Oso et al. 2020). Molecular docking was done by Pyrx software using Auto Dock Vina and docking Graphical User Interface of Pyrx 0.8 version (https://pyrx.sourceforge.io/). Further, the ligand and the protein molecules were converted into pdbqt format for docking using Autodock tools. The energy of the selected compounds was minimized using Open Babel and the blind docking was carried out. For possible ligand binding, the entire protein surface and interior compartments were made accessible. The protein and ligand interactions were visualized using Discovery studio, BIOVIA, 2020.

Molecular dynamic simulation

MD simulation was carried out to analyze the stability and the dynamics of the best hit compound of the molecular docking analysis with the 6COX in GROMACS-2019.4 followed by RMSD (Root mean square fluctuation) and RMSF (Root mean square deviation). The selected ligand (Hexadecanal) topology was retrieved from ATB server to get force field coordinates. Using the steepest descent algorithm, the system was prepared with vacuum minimization for 1500 steps. A cubic box period box of 0.5 nm with a (SPC) simple point charge water model was used to solvate the complex structures. Further it was maintained with a suitable salt concentration of 0.15 M by adding appropriate numbers of Na⁺ and Cl⁻ counter ions. The simulation run was performed for 100 ns to check the stability of the protein–ligand complex (Das et al. 2022).

Statistical analysis

All the tests were carried out in triplicates and the data were represented as mean ± SE. The experimental results were statistically analyzed using GraphPad prism 9 and Microsoft Excel 2010.

Results and discussion

Phytochemical analysis

The collected marine seaweeds were identified and authenticated from BSI, Coimbatore as Kappaphycus alverizii, Halymenia dialata, Gracilaria salicornia and Gracilaria corticata. The shade dried algal samples were finely powdered, stored (− 4 °C) and used for further analysis. In the present study, preliminary screening of 11 different phytochemicals (phenol, flavonoid, tannin, coumarins, saponin, sterols, terpenoids, proteins, quinones, steroids, glycosides) was analyzed with 5 different solvent systems (Methanol, ethanol, chloroform, ethyl acetate and aqueous) (Table 1). Among the five different solvent systems, methanol has shown to extract maximum phytochemicals from the algal extracts. The minimum extraction efficiency was observed in chloroform and ethyl acetate solvents. It is well known that methanol is a polar protic solvent that has the ability to recover the maximum phytochemicals which is due to the influencing power of the biochemical property of the algal sample, chemical configuration of the solvents and the dielectric constant of the solvent system. Hence, methanolic extract was taken for further analysis.

Table 1.

Qualitative analysis of the phytochemicals with 5 different solvent systems

Name of the algae	Solvent system	Phenol	Flavonoid	Tannin	Coumarins	Saponin	Sterols	Terpenoids	Proteins	Quinones	Steroids	Glycosides
Kappaphycus alverizii (KA)	Ethanol	+	+	+	–	+	–	–	+	–	+	–
	Methanol	+	+	+	–	–	–	–	+	+	+	+
	Aqueous	+	+	+	–	+	–	–	+	–	–	–
	Chloroform	–	–	+	–	+	–	–	+	–	–	–
	Ethyl acetate	+	–	–	–	–	–	+	+	–	–	+
Halymenia dialata (HD)	Ethanol	+	+	+	–	–	–	–	+	–	+	+
	Methanol	+	+	+	+	+	–	+	+	+	+	+
	Aqueous	+	+	+	–	–	–	–	+	+	–	–
	Chloroform	–	+	–	–	–	+	+	+	–	–	+
	Ethyl acetate	+	–	+	–	+	–	–	+	–	–	–
Gracilaria corticata (GC)	Ethanol	+	+	+	–	–	+	–	+	+	–	+
	Methanol	+	+	+	+	+	+	+	+	+	–	–
	Aqueous	+	+	+	–	–	–	–	+	–	+	–
	Chloroform	–	–	+	–	–	+	+	+	+	–	+
	Ethyl acetate	–	–	+	–	–	–	–	+	–	–	–
Gracilaria salicornia (GS)	Ethanol	+	+	+	+	–	–	–	+	+	+	+
	Methanol	+	+	+	+	+	–	+	+	–	–	+
	Aqueous	+	+	+	–	+	–	–	+	–	–	–
	Chloroform	–	+	–	–	–	+	+	+	+	+	+
	Ethyl acetate	–	–	–	–	–	–	–	+	–	–	–

The results of the total phenolic content estimation are shown in Table 2. Among the 4 algal extracts, G.corticata (33.04 ± 0.001 GAE mg/ml) has shown to have a maximum phenolic content in comparison to other algal extracts followed by G. salicornia (32.06 ± 0.004 GAE mg/ml) and H.dialata (31.61 ± 0.001 GAE mg/ml). The least phenolic content was observed in K.alverizii (11.81 ± 0.008 GAE mg/ml). (Chithra and Chandra 2013) has already reported the total phenolic content of G.corticata (7.412 GAE mg/g) and K.alverizii (very less than 5 GAE mg/g). This difference was might be due to the extraction methodology, concentrations of the phytochemicals extracted. Moreover topographical location, temperature, pH of the marine seaweeds also plays a vital role in the contributions of the phytochemicals (Moonmun et al. 2017).

Table 2.

Summary of quantitative analysis of phytochemicals of different algal extracts

Name of the algae	Total phenol GAE mg/ml	Total flavonoid QE mg/ml	Total tannin TAE mg/ml	Total saponin DSE mg/ml
K. alverizii	11.81 ± 0.008	8.22 ± 0.031	42.04 ± 0.007	25.89 ± 0.015
H. dialata	31.61 ± 0.001	5.076 ± 0.004	45.81 ± 0.007	18.56 ± 0.006
G. corticata	33.04 ± 0.001	0.0562 ± 0.005	26.32 ± 0.005	49.74 ± 0.12
G. salicornia	32.06 ± 0.004	0.835 ± 0.006	55.61 ± 0.007	29.02 ± 0.14

Flavonoids are categorized under phenolic compounds that are widely dispersed in the plant kingdom and are among all naturally occurring bioactive substances that favor the human health. In the current study, K.alverizii (8.22 ± 0.031 QE mg/ml) recorded a maximum total flavonoid content followed by H.dialata (5.076 ± 0.004 QE mg/ml). G.corticata (0.0562 ± 0.005 QE mg/ml) and G. salicornia (0.835 ± 0.006 QE mg/ml) was found to be the least recorded total flavonoid content among the 4 algal extracts. Previous studies have shown that flavonoids are considered to be a crucial factor in antioxidant property. The structural characteristics of flavonoids and the types of substitutions of hydroxy groups on rings B and C decide their antioxidant activity. The flavonoids ability to scavenge radicals was improved by a double bond between C-2 and C-3 conjugated with the 4-oxo group in ring C and by a double bond between C-2 and C-3 coupled with a 3-OH (ring C) (Pietta 2000). Hence, the flavonoid content of K.alverizii and H.dialata might contribute a moderate level of antioxidant activity, whereas G.corticata and G. salicornia might have no or very less influence on antioxidant property.

A significant interaction was observed between all the algal samples with respect to total tannin content. In the present analysis, the maximum tannin content was found in G.salicornia (55.61 ± 0.007 TAE mg/ml) followed by H.dialata (45.81 ± 0.007 TAE mg/ml) and K.alverizii (42.04 ± 0.007 TAE mg/ml). The least tannin content was found in G.corticata (26.32 ± 0.005 TAE mg/ml). These results were in agreement with the previous studies, that tannin has the capability to function as secondary antioxidants and also chelates the Fe (II) and inhibit the Fenton reaction to hinder the oxidation process (Karamac et al. 2006). Moreover, it was also reported that it inhibit the process of lipid peroxidation by inhibiting the cyclooxygenase enzyme that plays a very important role in the arachidonic acid pathway of inflammation (Zhang et al. 2004).

Plant saponin had been long recorded for its defense mechanism against pathogens. In the current study, G. corticata (49.74 ± 0.12 DSE mg/ml) has recorded maximum total saponin content followed by G. salicornia (29.02 ± 0.14 DSE mg/ml) and K. alverizii (25.89 ± 0.015 DSE mg/ml). The least saponin content was found to be recorded in H. dialata (18.56 ± 0.006 DSE mg/ml). Earlier reports had also proved the role of saponin in management of various human diseases like anticancer, antioxidant, hypoglycemic activities (Hostettmann et al. 1995). Hence, it is expected that algal saponin might have some vital role in exhibiting antioxidant activity.

In vitro antioxidant studies

In the current study, the antioxidant activity of the extracts was assessed using several free scavenging assays. DPPH scavenging activity of the algal extracts is shown in Table 3. Among the four extractives, at a concentration of 800 µg/ml, G.corticata (67.61 ± 1.23%, IC₅₀ = 577.71 µg/ml), G.salicornia (66.66 ± 1.73%, IC₅₀ = 598.0 µg/ml) and H.dialata (65.93 ± 0.74%, IC₅₀ = 609.8 µg/ml) was shown to have similar values of free radical scavenging property. At the same concentration K.alverizii (43.80 ± 0.48%, IC₅₀ = 1194.1 µg/ml), has shown the least level of scavenging activity.

Table 3.

Summary of antioxidant assays of algal extracts with different concentrations

Name of the algal sample	DPPH (%) and IC50 (µg)			TAC (µM)	Metal chelation assay and IC50 (µg)			Reducing power assay absorbance at 700 nm
K. alverizii	43.80 ± 0.48	1194.1		1103.48	17.78 ± 0.39		2440	68.49 ± 0.22
H. dialata	65.93 ± 0.74	609.8		1881.24	28.96 ± 0.20		1854.5	56.53 ± 0.22
G. corticata	67.61 ± 1.23	577.71		1077.91	29.40 ± 0.32		1684.7	68.80 ± 0.20
G. salicornia	66.66 ± 1.73	598.0		1543.35	27.22 ± 0.30		1674.0	68.90 ± 0.23
Standards
Ascorbic acid (AA)	81.0 ± 0.44			–	–
Tannic acid	–			1465 ± 0.003	–
EDTA	–			–	85.09 ± 0.88

Results are expressed as mean ± SE of three replicates (n = 3), the data was statistically analyzed by two-way ANOVA using Graph pad Prism. The difference was considered significant when p < 0.05

The radical scavenging activity of the algal extracts in comparison to standard can be given in the following order: AA > GC > GS > HD > KA. In the DPPH assay, the algal extracts had reduced the violet-colored DPPH solution to diphenylpicryl hydrazine which is yellow-colored product. Our results have shown a positive correlation between the phytochemicals and the scavenging property. The results obtained suggest that the radical scavenging activity of the algal extracts was due to either hydrogen donating factor or by electron transfer system (Huang et al. 2005).

The total antioxidant capacity of the methanolic extracts was estimated by measuring the ability of the algal extracts to reduce Mo (VI) to Mo (V), a green-colored molybdenum complex was formed at an acidic pH due to the addition of the antioxidant enriched algal extracts. A summary of the total antioxidant capacity of the extracts is shown in the Table 2. At the maximum concentration of 800 µg/ml, H.dialata (1881.24 µM/ml) was found to measure the maximum antioxidant activity followed by G. salicornia (1543.3 µM/ml) and K. alverizii (1103.4 µM/ml). The minimum antioxidant activity was found to be measured in G. corticata (1077.7 µM/ml). The results revealed that the antioxidant activity has increased by increasing concentration in a dose dependent manner. Our findings proved that, the concentration of the phytochemicals in the algal extracts plays a potential role in the antioxidant activity (Oktay et al. 2003).

Reducing power assay is widely used method for evaluating the antioxidant potential of the sample. The reducing power of the methanolic extracts is shown in the Table 3. At a maximum concentration of 800 µg/ml, all the algal samples had shown good reducing power. G. salicornia (68.90 ± 0.23), G. corticata (68.80 ± 0.20) and K. alverizii (68.49 ± 0.22) was recorded almost similar reducing power at a maximum concentration of 800 µg/ml by measuring the development of Perl’s Prussian blue at the absorbance of 700 nm. The results showed that the presence of reductants in the algal extracts might be the reason for the reduction of Fe³⁺ to Fe²⁺ (ferricyanide complex to ferrous form) by donating electrons. Here, we presume that the presence of polyphenols might be the reason to scavenge free radicals by donating an electron or hydrogen, which was influenced in its antioxidant activity and reducing power capacity (Oktay et al. 2003).

Metal chelation activity of the methanolic extracts was determined by measuring the reduction of ferrozine at 562 nm. In the present study, G. corticata (29.40 ± 0.32%, IC₅₀ = 1684.7 µg/ml), H. dialata (28.96 ± 0.20%, IC₅₀ = 1854.5 µg/ml) and G. salicornia (27.22 ± 0.30%, IC₅₀ = 1674 µg/ml) has measured a similar metal chelation activity followed by K.alverizii (17.78 ± 0.39%, IC₅₀ = 2440 µg/ml). The results proved that the antioxidant molecules present in the algal extracts has the potential for Fe-binding capability to their functional groups and enhance its biological functions (Ghosh et al. 2015). This chelating ability of the extracts is important so that it reduced the metals which have a catalytic influence in lipid peroxidation process. In addition to it, these extracts might act as secondary antioxidants to stabilize the metal ion that are oxidized (Kalin et al. 2015). Hence these extracts might have a vital role in protection of oxidative stress that is induced by metals.

In vitro anti-inflammatory studies

Inflammation is inter-connected with protein denaturation which was well studied and reported (Sakat et al. 2010). The ability of the algal extracts to inhibit the protein denaturation was studied as a part of anti-inflammatory activity. Table 4 represents the effect of the algal extracts in inhibiting the denaturation of protein. H. dialata (83.50 ± 0.24%, IC₅₀ = 247.75 µg/ml) has showed an increased albumin denaturation when compared with the standard drug diclofenac sodium (96.48 ± 0.25%). K. alverizii (68.78 ± 0.15%, IC₅₀ = 469.48 µg/ml) and G. salicornia (57.74 ± 0.20%, IC₅₀ = 648.25 µg/ml) resulted in a moderate level of inhibition. G. corticata (48.69 ± 0.15%, IC₅₀ = 978.88 µg/ml) showed a lower protein denaturation inhibition when compared with the other algal extracts. Nevertheless, the exact mechanism of stabilization of membrane was not explained completely. Previous studies suggested that the algal extracts might have the property of hindering the release of the lysosomal contents of neutrophils at the site of inflammation (Govindappaaga et al. 2011). Since lysosome contains bactericidal enzyme and proteinases, upon release into the extracellular spaces, causes secondary tissue damage. The results had proved that the algal extracts had shown a significant effect in stabilizing the protein membrane. Hence the lysosomal contents present in the neutrophils might have repressed at the site of inflammation (Chou et al. 1997).

Table 4.

Summary of anti-inflammatory assays with different concentrations of algal extract

Name of the sample	In vitro anti-inflammatory assays
	Protein denaturation assay (%)		IC50 values		Heat-induced hemolysis (%)	IC50 values		Hypotonicity-induced hemolysis (%)	IC50 values		Proteinase inhibition assay (%)	IC50 values
K. alverizii	68.78 ± 0.15		469.48		60.71 ± 0.43	22.3		95.77 ± 0.46	NA		79.09 ± 0.24	251.25
H. dialata	83.50 ± 0.24		247.75		59.02 ± 0.07	245.78		87.94 ± 1.24	NA		80.14 ± 0.32	NA
G. corticata	48.69 ± 0.15		978.88		60.40 ± 0.46	77.85		90.65 ± 2.74	199.39		83.30 ± 0.18	251.23
G. salicornia	57.74 ± 0.20		648.25		60.29 ± 0.58	106.42		81.36 ± 0.74	193.33		71.59 ± 0.11	256.06
Standards
Diclofenac sodium (100 µg/ml)	96.48 ± 0.25				–			–			–
Aspirin(100 µg/ml)	–				86.65 ± 1.21			87.07 ± 0.59			94.35 ± 0.22

Results are expressed as mean ± SE of three replicates (n = 3), the data was statistically analyzed by One-way ANOVA using Graph pad Prism. The difference was considered significant when p < 0.05

The property of inhibition of proteinase with the algal extracts was assessed by proteinase inhibitory assay. Proteinase inhibition by algal extracts is shown in Table 4. The results had shown that a significantly increased inhibition of proteinases was observed in G. corticata (83.30 ± 0.18%, IC₅₀ = 251.23 µg/ml) in comparison to the standard drug aspirin (94.35 ± 0.22%). On the other hand, K. alverizii (79.09 ± 0.24%, IC₅₀ = 251.25 µg/ml), H. dialata (80.14 ± 0.32%) and G. salicornia (71.59 ± 0.11%, IC₅₀ = 256.06 µg/ml) has also proved to possess good inhibition of proteinase in comparison to the standard. The results revealed that the bioactives present in the algal extracts, might have the property of inhibiting proteinase in addition to the anti-inflammatory activity. Previous studies had also linked proteinase with many other inflammatory diseases (Das et al. 1995). Since, proteinase plays a vital role in secondary damage during the inflammatory process. The quantitative estimations of the bioactives of H. dialata have reflected on its antioxidant activity. Since earlier reports suggest that bioactive rich extracts could display efficient response in scavenging the radicals which show confirms its role in anti-inflammatory property (Islam et al. 2020).

The effect of heat-induced hemolysis inhibition by the algal extracts was investigated. All the algal extracts had shown almost similar level of inhibition in a dose dependent manner. The inhibition ranges between 59.02 ± 0.07 to 60.71 ± 0.43% in comparison to the standard drug aspirin (86.65 ± 1.21%). The results had revealed that there was a strong interaction between the algal extracts and the membrane proteins. This shows that the algal extracts might have the capability to interfere with the early phase of inflammatory mediator’s release by inhibiting the release of phospholipases which leads to the conversion of arachidonic acid to prostaglandins catalyzed by cyclooxygenase enzyme (COX-2) (Shinde et al. 1999). Hence, the membrane stabilization by algal extracts had prevented the leakage of lysosomal membrane and release of the neutrophil contents into the extracellular space was avoided (Rosales et al. 2018).

The effect of hypotonicity-induced hemolysis at different concentrations was examined. In the present study the methanolic extract of K. alverizii (95.77 ± 0.46%) and G. corticata (90.65 ± 2.74%, IC₅₀ = 199.39 µg/ml) had shown a notable and a significant level (p < 0.0001) of hypotonicity-induced hemolysis in comparison to the standard aspirin (87.07 ± 0.59%). H. dialata (87.94 ± 1.24%) and G. salicornia (81.36 ± 0.74%) had also shown a similar kind of inhibition. Excessive fluid buildup inside red blood cells induces rupture of their membrane, which results in hypotonicity-induced hemolysis and subsequent damage from lipid peroxidation caused by free radicals. As it is clear that, the red blood cell membrane on exposure to hypotonic solution leads to hemoglobin oxidation in addition to hemolysis (Ferrali et al. 1992). Hence the algal extracts had mimicked the property of non-steroidal anti-inflammatory drug (NSAIDS) by either protecting the lysosomal membrane or by inhibiting the release of lysosomal constituents from the neutrophils. This effect was may be due to the selected algal extracts would have stabilized the red blood cell membrane by inhibiting the inflammatory mediators. Hence, many algal sources have been included in dietary form to overcome various kinds of diseases. Recent studies have also proved that lipids, proteins, PUFA’s in the form of dietary recommendations have improved the health condition (Ağagündüz et al. 2023).

ADME, pharmacochemical and toxicological analysis (SWISSADME)

Computational therapeutics have made it possible to attempt the predictions in the field of Medical therapeutics. To evaluate the effectiveness and affinity of a new drug, various screening methods had been followed. In this context, reviewing the pharmacokinetic features of the drug component is very crucial. Therefore it is important to evaluate and forecast the pharmacokinetic and the toxicological parameters like (ADME—Absorption, Distribution, Metabolism, and Excretion). This has been achieved by performing SWISSADME and PROTOX II analysis.

Intensive literature survey has been done for G. corticata and H. dialata in search of the bioactive compounds through GC MS analysis. Ragunathan et al. (2019) and Rajkumar et al. (2017) has reported 7 bioactive compounds of methanolic extracts of and 10 compounds of both acetone and hexane extracts of G. corticata. Jainab et al. (2019) and Uma Maheswari et al. (2017) have reported nine compounds of methanolic extracts of H. dialata. Among those 12 compounds of G. corticata, only 9 compounds have been taken forward (Table 5). Similarly, out of nine compounds from H. dialata, only seven compounds have been taken forward based on their pharmacokinetic properties, physicochemical properties as well as their ADME limitations (Table 6). Thorough examination of the physico-chemical bioactive compounds is mandatory in addition to their bioavailability and pharmacokinetics parameters based on their anti-inflammatory properties.

Table 5.

ADME analyses of bioactive compounds of G.corticata

Name of the bioactive compound	Mole formula	Mole weight	H donor	R bonds	H acceptor	Solubility	Logp 0/w	Bioavailability score	GI	BBB	Lipinski
Oxirane, decyl-	C12H24O	184.3	0	9	1	S	4.02	0.55	High	yes	Yes
n-Hexadeconoic acid	C16H32O2	256.4	1	14	2	MS	5.20	0.85	High	Yes	Yes
Eicosanoid acid	C20H40O2	312.5	1	18	2	PS	6.62	0.85	Low	No	Yes
Nonanoic acid	C9 H18O2	158.2	1	7	2	S	2.60	0.85	High	Yes	Yes
Oleic acid	C18H34O2	282.4	1	15	2	MS	5.71	0.85	High	No	Yes
Pentadecanoic acid	C15H30O2	242.3	1	13	2	MS	4.84	0.85	High	Yes	Yes
Hexadecanal	C16H32O	240	0	14	1	MS	5.43	0.55	High	No	Yes
O-Toluic acid	C8H8O2	136.1	1	1	2	S	1.83	0.85	High	Yes	Yes
Tridec-2-ynyl ester	C21H30O2	314.5	0	11	2	PS	6.00	0.55	High	Yes	Yes
3-methylhexyl isothiocyanate	C8H15NS	157.2	0	5	1	S	3.52	0.55	High	yes	Yes
cholesterol	C27H46O	386.7	1	5	1	PS	6.76	0.55	Low	No	Yes
13-Docosenamide (Z)	C30H51NO3	473.7	2	23	3	PS	7.89	0.55	Low	No	Yes
2-[5- (2-Hydroxy-propyl)-tetrahydro furan-2-yl]-propionic acid, t-butyl ester]	C14H26O4	258.3	1	6	4	S	2.33	0.55	High	Yes	Yes
Heptadecane	C17H36	240.5	0	14	0	MS	6.79	0.55	Low	No	Yes
Neophytadiene	C20H38	278.5	0	13	0	PS	7.07	0.55	Low	No	Yes
2-Hexadecen-1-ol 3,7,11,15-tetramethyl-,[R-[R,R-(E)]	C16H32O2	256.4	1	13	1	MS	6.22	0.55	Low	No	Yes
13-Docosenamide (Z)	C22H43NO	337.6	1	19	1	PS	6.77	0.55	Low	No	Yes

H donor hydrogen donor, H acceptor hydrogen acceptor, GI gastrointestinal absorption, BBB blood–brain barrier, S soluble, MS moderately soluble, PS poorly soluble, VS very soluble, R bonds rotatable bonds, B.A score Bioavailability score

Table 6.

ADME analyses of bioactive compounds of H. dialata

Name of the bioactive compound	Mole formula	Mole. Weight	H donor	R bonds	H acceptor	Solubility	Logp 0/w	BA score	GI	BBB	Lipinski
9-Hexadecenoic acid, methyl ester (Z)	C 17 H 32 O2	268.44	0	14	2	MS	5.26	0.55	High	Yes	Yes
Hexa decanoic acid, methyl ester	C17H34O2	270.46	0	14	2	MS	5.47	0.55	High	Yes	Yes
n-Hexa decanoic acid	C 16 H 32 O2	256.43	1	14	2	MS	5.20	0.85	High	Yes	Yes
Oleic Acid	C 18 H 34 O2	326.57	2	18	2	MS	5.28	0.55	High	Yes	Yes
9-Octadecenoic acid (Z)-,methyl ester	C 19 H 36 O2	296.50	0	16	2	MS	5.95	0.55	High	No	Yes
Hydro peroxide, 1-methylbutyl	C5H12O2	104.14	1	3	2	VS	1.23	0.55	High	Yes	Yes
Nonyl trifluoroacetate	C11H19F3O2	240.26	0	10	5	S	4.15	0.55	High	Yes	Yes
Acetyl valeryl	C7H12O2	128.16	0	4	2	VS	1.29	0.55	High	Yes	Yes
Dodecyl trifluoroacetate	C14H25F3O2	283.34	0	13	5	MS	5.26	0.55	High	No	Yes

H donor hydrogen donor, H acceptor hydrogen acceptor, GI gastrointestinal absorption, BBB blood–brain barrier, S soluble, MS moderately soluble, PS poorly soluble, VS very soluble, R bonds rotatable bonds, B.A score bioavailability score

BOILED EGG analysis for BBB and HIA (SWISSADME)

BOILED EGG analysis was done to yield a fast, spontaneous, efficient technique to predict the passive gastrointestinal absorption (HIA) and to analyze the probability of a compound to permeate into the blood–brain barrier (BBB). BBB was considered to act as protecting shield by the brain and also performs the function of active effluxes from central nervous system (Artursson et al. 2012). Figure 3a presents the HIA and BBB properties of the bioactive molecules of G. corticata under investigation. The results had shown that, among 12 compounds of G. corticata, 8 compounds (Oxarine decyl-, n-hexa decanoic acid, Nonanoic acid, Pentadecanoic acid, O-Toluic acid, Tridec-2-ynyl ester, 3-methylhexyl isothiocyanate, 2-[5- (2-Hydroxy-propyl)-tetrahydro furan-2-yl]-propionic acid, t-butyl ester]) had shown a high probability to cross BBB (Yolk) and rest of the seven compounds of G.corticata had shown its physicochemical space in white region where it shows the probability of high absorption of the compound (White). Hence, Eicosanoid acid, Oleic acid and Hexadecanal had predicted to be well absorbed compounds but not has the access to BBB. In the same way, among nine compounds of H. dialata, only two compounds have shown least probability to cross the BBB and rest of the seven compounds were not considered for further analysis.

Fig. 3.

Overview of the selected bioactive compounds of G. corticata and H. dialata by BOILED EGG analysis for its blood–brain barrier diffusion and gastrointestinal absorption (HIA- Human intestinal absorption; BBB- blood–brain barrier). a BOILED EGG analysis of G. corticata. b BOILED EGG analysis of H. dialata. The white-colored region of the BOILED EGG represents the molecules which can be absorbed easily by the GI tract. The yellow-colored region represents the molecules that penetrate the BBB

Moreover, the bioavailability parameters give a glimpse of drug-likeness of the nine selected molecules in G. corticata and H. dialata. In this analysis, six parameters were considered: Size, polarity, flexibility, saturation, lipophilicity and solubility. Taken these parameters into consideration, if the molecules fall under drug-like molecule, the selected compounds will be placed within the pink region in the radar chart. Our results showed that all the bioactive compounds had almost followed the physicochemical and pharmacochemical parameters (molecular size (150–500 D), polarity (20 and 130 Å2), solubility (log S > 6) and saturation (Csp3 < 0.25). All the compounds did not fall under the optimum flexibility and Lipophilicity category for both H. dialata and G. corticata, but overall the compounds showed good drug likeliness. Additionally, various studies have proved that gut micro biota has a vital role in the drug metabolism that helps in the activation of certain drug like compounds by the exudation of potent metabolizing enzymes. Hence, metabolizing the bioactive compounds by micro biota results in better absorption that increases the bioavailability of the drug (Ağagündüz et al. 2022).

To predict the toxicity, the chemical structure of the compounds was tested using Protox ii software. Summary of the lethality dose (LD₅₀), toxicity class of the chemical compound, carcinogenicity, immunotoxicity, TPSA value and log p values were given. The prediction clearly showed that Oleic acid and Heptadecane of G. corticata falls under toxicity class 2 and 3, where the compounds are toxic on consumption, thus those compounds were not taken further for analysis. From the results it is clear that, Cholesterol reports to be active towards immunogenicity (Table 7). Except, Dodecyl trifluoroacetate of H. dialata, all other compounds had shown inactiveness towards carcinogenicity and immunotoxicity (Table 8). The present study results reveal that the selected compounds neither increase the incidence of cancer nor show any immunotoxicity on the immune cells. Since the selected compound of H. dialata has shown carcinogenicity, Dodecyl trifluoroacetate was not taken forward for analysis. The compound that does not have proper computational data was excluded from the study. Hence the present study consider only the chemical compounds of G. corticata (Eicosanoid acid, Hexadecanal, Neophytadiene and 2-Hexadecen-1-ol, 3,7,11,15-tetramethyl-,[R-[R,R-(E)]) for further in silico molecular docking with the inflammatory target.

Table 7.

Toxicological prediction of G.corticata using Protox ii

Name of the compound	Predicted LD50 (mg/kg)	Predicted toxicity class	Carcinogenicity	Immunotoxicity	(TPSA)	Octanol/water partition (log P)
Eicosanoid acid	900	4	Inactive	Inactive	37.3	7.11
Oleic acid	48	2	Inactive	Inactive	37.3	6.11
Hexadecanal	5000	5	Inactive	Inactive	17.07	5.67
Cholesterol	890	4	Inactive	Active	20.23	7.39
Heptadecane	750	3	Inactive	Inactive	0	6.88
Neophytadiene	5050	6	Inactive	Inactive	0	7.17
2-Hexadecen-1-ol, 3,7,11,15-tetramethyl-[R-[R,R-(E)]	5000	5	Inactive	Inactive	20.23	6.26

Table 8.

Toxicological prediction of H.dialata using Protox ii

Name of the compound	Predicted LD50 (mg/kg)	Predicted Toxicity class	Carcinogenicity	Immuno toxicity	TPSA	Octanol/water partition (log P)
9-Octadecenoic acid (Z)-methyl ester	–	–	–	–	–	–
Dodecyl trifluoroacetate	5000	5	Active	Inactive	26.3	5.01

In silico molecular docking studies

Arachidonic acid is ω-polyunsaturated fatty acid (PUFA), which has attracted lot of attention related to various kind of inflammatory disease. This fatty acid can be metabolized by three different enzyme systems namely, cyclooxygenase (COX), Lipoxygenase (LOX) and cytochrome P450 (CYP) enzymes that leads to the synthesis of various biologically active fatty acid mediators. Among the three enzymes, cyclooxygenase (COX) are the first enzyme system to metabolize the arachidonic acids to prostaglandins (PG) that contribute majorly to various inflammatory responses. Cyclooxygenase enzyme has two isoforms, where COX-1 is constitutively expressed in almost all the cells, whereas, COX-2 is known to be produced by various inflammatory stimuli. Previous studies have reported that aspirin and non-steroidal anti-inflammatory drugs (NSAIDs) are widely used in inhibiting COX-2 for treating pain and inflammation (Sharma et al. 2019).

Even though, the NSAIDs are effective in treating the inflammatory responses, natural replacements are required for safer and effective alternative for treating the inflammatory conditions. Hence, the present study focused on the in silico investigation of the marine algal bioactive compounds for anti-inflammatory activity by the inhibition of COX-2 enzyme. The results of the in silico molecular docking by Auto Dock Vina has shown that out of 26 compounds of both H. dialata and G. corticata, 16 compounds have taken forward for pharmacokinetics and toxicity prediction analysis. Based on the results, only five compounds of G. corticata have been considered for COX-2 inhibition by in silico molecular docking. The results had shown that Hexadecanal and Neophytadiene were reported to obtain almost same effective binding to COX-2 enzyme with the highest binding affinity of (− 5.3), followed by Heptadecane (− 5.0), 2-Hexadecen-1-ol 3, 7, 11, 15-tetramethyl-, [R-[R, R-(E)] (− 4.9) and Eicosanoid (− 4.7) with respect to the standard drug diclofenac (− 7.3 kcal/mol (Uzzaman et al. 2021). The binding complex’s strength and catalytic activity are predicted by the hydrogen bonds that connect them (Table 9).

Table 9.

Binding affinity of the selected compounds of G.corticata docked with cyclooxygenase (COX-2)

Name of the bioactive compound	Binding affinity (Kcal/moles)
Eicosanoid acid	− 4.7
Hexadecanal	− 5.3
Neophytadiene	− 5.3
Heptadecane	− 5.0
2-Hexadecen-1-ol, 3,7,11, 15-tetramethyl-{(R-R,R-(E)]	− 4.9
Ibuprofen (Standard drug)	− 6.5

Docking parameters were measured between the binding sites of COX-2 and the ligands. The hydrogen bonds that hold a binding complex together predict its strength and catalytic activity. The grid box for the efficient binding was, x = 27.77, y = 24.33, z = 39.76. Among the 5 bioactive compounds, Hexadecanal interacted with ARG44, ASN43 through conventional hydrogen bonds and LEU152, PRO153, CYS47, CYS36, TYR130 through Pi-Alkyl bonds with the highest binding affinity of (− 5.3) Fig. 4a. These residues are located in the COX-2 enzyme’s active site area (Kiefer et al. 2000). Similarly, Neophytadiene showed an interaction with VAL89, VAL103, ILE112 through Van der Waals forces with a binding affinity of (− 5.3) Fig. 4b. Previous reports suggest that the catalytic residue TYR385 amino acid plays an important role in the conversion of arachidonic acid to prostaglandin G2 by transferring an electron from TYR to the cyclooxygenase active site (Rowlinson et al. 2003). The same has been reflected in our present study, that the compounds had shown the interaction with TYR through Pi-Alkyl bonds. Eicosanoid acid (− 4.7) and 2-Hexadecen-1-ol, 3, 7, 11, 15-tetramethyl-(R-R, R-(E)] (− 4.9) was observed to exhibit almost similar binding features with the cyclooxygenase enzyme (Fig. 4c, d and e). The computational results clearly indicate that Hexadecanal and Neophytadiene from G. corticata have proved its possible role in inhibiting the cyclooxygenase pathway. Our present study may shed light on the discovery of novel drug like compounds from marine environment for inflammation associated disease management.

Fig. 4.

Docking pose of COX-2 with selected ligand molecules of G. corticata. a Hexadecanal. b Neophytadiene. c Eicosanoic acid. d Heptadecane. e 2-Hexadecen-1-ol, 3, 7, 11, 15-tetramethyl-(R-R, R-(E). f Ibuprofen (Standard drug). Conformational poses of ligand and protein markers are represented according to its hydrophobicity of the residues. 2D representation of the protein ligand interaction is shown

Recent reports had proved that Neophytadiene significantly lowers iNOS activity to reduce NO generation both in vitro and in vivo. Moreover, it was also evidenced that it reduces the level of Malondialdehyde that helps in reducing the oxidative stress. It was shown that Neophytadiene has considerably lowered the production of pro-inflammatory cytokines by inhibiting the NF-κB pathway in RAW 264.7 murine macrophage cell lines and in rat heart tissues. Moreover, the study has proved that to reduce the inflammatory response by downregulating the production of NO, TNF-α, IL-10, IL-6 and iNOS (Meenakshi Bhardwaj et al. 2020). Previous reports had proved that Hexadecanal (n-hexadecanoic acid), can be used as an anti-inflammatory agent. It is already shown that Hexadecanal has the potential of binding with PLA₂ (Phospholipase A2). Inhibition of PLA₂ by hexadecanoic acid plays a vital role in varied cellular functions, immune modulation and signal transduction. (Vasudevan Aparna et al. 2012). To compare the efficacy of the selected bioactive compound, in silico molecular docking analysis was performed with standard NSAID ibuprofen (Table 9). The docking score of ibuprofen with cyclooxygenase (− 6.5 kcal/moles) revealed a strong hydrogen bond interactions (LYS B: 83), Pi-cation (ARG B:120), various Vander walls interaction (TYR B:122, SER B:119, LEU B:123, SER B:471, GLU B:524, PRO B:86, TYR B:355) followed by alkyl (VAL B:116 and LEU B:93) and Pi-alkyl (VAL B:89 and TYR B:115). The results are interesting that the selected compound (Hexadecanal) has shown almost a similar docking score (− 5.3 kcal/moles) when compared with ibuprofen (− 6.5 kcal/moles) (Fig. 4f).

Molecular dynamic simulation (MD)

The binding geometries of the selected compound were predicted using molecular docking analysis, however the flexibility of the compound is analyzed by performing MD simulation. In silico molecular docking results have clearly showed that Hexadecanal (− 5.3 kcal/mol) and Neophytadiene (− 5.3 kcal/mol) was observed to have a maximum binding affinity with the inflammatory marker (6COX). Though Hexadecanal and Neophytadiene had shown a similar binding affinity towards the marker, considering other parameters (Tables 5 and 7), Hexadecanal was further taken forward to assess its structural stability. Henceforth, molecular dynamic simulation was performed for 100 ns to check the RMSD and RMSF too. For ligand–protein interaction, it was observed to show an average RMSD of 0.31 ± 0.01 nm from 0 to 100 ns (Fig. 5a). The results clearly showed that the protein and ligand complex was stable throughout the simulation. In addition, RMSF analysis against the timescale of 0 to 100 ns showed an average RMSF of 0.29 ± 0.05 nm (Fig. 5b). This clearly indicates that there are no substantial structural changes occurred during the simulation time period (0–100 ns). Compactness of hydrophobic core was examined by measuring the changes in SASA (solvent accessible surface area) for 0–100 ns. The protein complex’s average SASA value from 0 to 100 ns was 254.66 ± 2.12 nm (Fig. 5c). The results indicate that there are no structural changes observed throughout the simulation of the protein. Also, it was observed that the ligand–protein complex was stylized by the formation of hydrogen bonds (Fig. 5d).

Fig. 5.

Molecular dynamic simulation of Hexadecanal with 6COX. a Ligand–protein RMSD, b RMSF of protein–ligand complex, c SASA of the backbone atoms of protein–ligand complex, d hydrogen bond formation between protein and ligand during docking process

Similarly, a complete literature survey was done to confirm and get deeper insight to know about the stability of the protein (6COX) and ligand (Ibuprofen) complex by MD simulation. Previous studies had reported that the RMSD values of ibuprofen has recorded a stable structural configuration for 10 ns (3.23Å) with cyclooxygenase (6COX). Similarly, the RMSF value of the binding site showed a minimized residual fluctuation of 1.43 Å (Bittencourt et al. 2019). Based on the in silico predictions, the proposed compound has shown a potential mechanism of inhibiting cyclooxygenase in comparison with the control standard drug. Hence, further in vivo studies are required for validating the efficient inhibition of COX-2 by Hexadecanal.

Conclusion

In silico computational analysis on these bioactive compounds has made it possible to understand the efficient binding affinity of the chemical compound Hexadecanal of G. corticata with the protein target enzymes (COX-2). Hence the selected compound might be good choice of medication for treating inflammatory conditions as predicted by the docking scores and MD simulation. The knowledge gathered from this research can be employed to build anti-inflammatory medications with new targets and mechanisms of action in experimental investigations.

Author contributions

DES conceptualization, investigation, formal analysis. AM original draft writing—review and editing.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Data availability

Data will be made available on request.

Declarations

Conflict of interest

The authors declare that they have no conflict of interest in the publication.

Ethical statement

Not applicable.