A Computational Modelling Study of Phytoconstituents of Curcuma longa Rhizome with IGF-1R Protein in Ovarian Cancer

doi:10.21203/rs.3.rs-5091347/v1

Background: Ovarian cance,r is a huge concern due to its high mortality rate and resis,tance tothe conventional therapies. Recent studies have focused on the insulin-like growth factor 1 receptor (IGF-1R) as a therapeutic tphytochemicalsits ron the prolifa eration of cancer cells. Phytoco tituents from Curcuma longa ar known for their anti-cancer propertisignallingg them potential candidates for ovarian cancer treatment. This computational study aims to evaluate the molecular docking and pharmacokinetic profiles of ,phytochemicals in Curcuma longa against IGF-1R to explore their potential to inhicer ,progression.

Results: Molecular docking analysis showed that digalloyl-hexoside had the highest binding affinity with IGF-1R, with a docking score of -8.849 kcal/mol. Hyperoside and valoneic acid dilactone followed closely, showing strong interactions as well. All three compounds exhibited six hydrogen bonds with key residues like ASP 1056 and LYS 1003, contributing to their strong binding potential. Caffeic acid showed the lowest affinity with a docking score of -7.985 kcal/mol. ADMET analysis reveal ed that caffeic acid had the highest gastrointestinal absorption and skin permeability, adhering to Lipinski’s rule of five. In contrast, digalloyl-hexoside, hyperoside, and valoneic acid dilactone had lower bioavailability and gastrointestinal absorption but exhibited acceptable pharmacokinetic properties.

Conclusion: Digalloyl-hexoside exhibited the highest binding affinity, followed by hyperoside and valoneic acid dilactone, though all compounds had lower docking scores than the reference ligand. ADMET analysis revealed that while caffeic acid had the highest absorption, the other compounds showed better overall pharmacokinetic profiles. However, low gastrointestinal absorption limits their bioavailability. Further research, including structural modifications and additional validation, is recommended.

Curcuma longa

ovarian cancer

IGF-1R

phytochemical compounds

drug candidates and inhibitors

computer-aided drug design.

Ovarian cancer (OC) is one of the deadliest gynecological cancers in recent years. According to the Global Cancer Observatory (GLOBOCAN), ovarian cancer occupied the eighteenth ranking among cancer-related deaths worldwide with an expected 200,000 incident cases annually [1]. Moreover, life expectancy was estimated around 5 years as most cases detected at the advanced stages with complications. Because the early detection can be difficult due to misdiagnosis with gastrointestinal and urogenital health disorders as all show intercorrelation in signs and symptoms [2]. Alongside, OC showed distinct genetics and environmental etiology that are associated with various histologic types and behaviors patterns [2].

Therefore, tthe here is a continuous demand to develop a treatable drug for ovarian cancer. One of the successful approaches was inhibition of an insulin like growth factor (IGF) pathway through targeted antibodies and small-molecule tyrosine kinase inhibitors (Figure 1) [3]. In healthy ovarian tissues, this pathway is highly active to maintain follicular health development and cell proliferation during the menstrual cycle [4]. Meanwhile, any dysregulation of the IGF pathway leads to overexpress of growth proteins and eventually cancer development [5]. Nevertheless, the outcomes showed limitations in confined ovarian cancer growth, especially in phase III clinical trials. This could be explained by a lower specification of the kinase’s inhibitor therapies along with the ability of cancer cells to develop a resistance mechanism against IGF-IR receptor [6]. Nowadays, herbal medicine has emerged as a potential and supported treatment for cancer and various chronic diseases. One Turmeric (Curcuma longa; C. longa) possesses the richest phytochemicals, which are bioactive substances extracted from plants. The extracted phytochemical is characterized with modulation of anticancer, antioxidant, modulate autophagy and apoptosis, reduce cell proliferation, delay metastasis, boost the immune system during chemotherapy, and inhibit angiogenesis [7,8,9]. Thus, C. longa substances could have an inhibitory effect on the IGF-IR signaling pathway [10]. Nevertheless, further investigation is required to determine the bioactivity and safety for these compounds.

In our study, we aimed to evaluate the efficiency of a four extracted phytochemical from the C. longa as potential herbal drug to inactivate the IGF signaling pathway which may affect significantly on ovarian cancer cell growth. Drug bioavailability is a crucial factor in determining the effectiveness of the drug by determining the rate absorbed into the bloodstream after the drug administration. This could be influenced by pharmacokinetic properties which are governed by physicochemical properties (binding affinity, polarity), and drug-likeness, and toxicity. For this reason, a drug bioavailability has a value effect on designing a therapy and dosage [11]. This was achieved through applying a molecular docking to position the computer-generated 3D structure of small ligands into a receptor structure in a variety of orientations, conformations and positions [12]. Oladapo et al. (2024) carried out molecular docking of compounds of Nigella sativa with anti-apoptotic proteins to identify drug candidates that can effectively bind to Mcl-1 and Bcl-Xl in cancer treatment. Their study predicted compounds of Nigella sativa that could serve as good drug candidates in Ovarian cancer treatment [13]. After that, they filtered the appropriate compounds according to the ADMET profile [14]. This approach was successful in screening over 1100 phytochemical compounds of natural plants and the molecular docking of these compounds was carried out with the main protease of the SARS-CoV-2 to identify drug candidates that could be used in coronavirus treatment.

This study aimed to investigate the safe and sufficient drug bioavailability for the extracted phytochemical from the C. longa as potential anticancer herbal drug to limit the incidence rate of ovarian cancer.

2.1 Protein Ligands and Their Target

We retrieved C. longa's bioactive components from the PubChem database and used the Lig Prep tool to extract them.Their ionization states and tautomers were then generated at pH 7.2 + 0.2 for optimization (planned for 2017 Schrödinger's Cat release) using the Orthogonal Partial Least-Square (OPLS) 2005 force field. After importing the protein structures from the Protein Data Bank (PDB) into Maestro, the protein production wizard was used to produce the IGF-1R protein 3D structure. This structure gave a unique PDB identification code with 1K3A, which represents the structure of the Insulin-like Growth Factor 1 Receptor Kinase (IGF-1R). The bound ligands and other bound moieties were then removed from the protein, and the binding energies were reduced by adding hydrogen. Prime and water were employed to replace the absent side chains to support any structural dysregulation. To guide the automated docking process and pinpoint the protein binding sites, the grid boxes were constructed based on the positions of the co-crystallised ligands. The IGF-1R protein's grid box coordinates were x = 26, y = 26, and z = 26.

2.2 Docking of Molecules

The Glide docking tool in Maestro 11.1 was used for the molecular docking process. After preparing the compounds, they were docked into an established grid of protein targets to look for strong inhibitory interactions. We retrieved the most thorough screening (XP) results for further analysis.

2.3 ADME/Tox Screening

The pharmacokinetics, drug likeness, and toxicity of the lead compounds were investigated using the Swiss ADME online server [16].

3.1 Molecular Docking of C. longa with IGF-1R Protein

Molecular docking studies revealed C. longa molecules and four molecules from C. longa having high binding affinity were digalloyl-hexoside, hyperoside, valoneic acid dilactone, and caffeic acid. Figure 1 below shows the molecular interaction between the target protein IGF-1R and these hit compounds. Table 1 below also provides the docking scores, hydrogen bond and amino acid residues in these ligand-protein interactions.

Table 1: Molecular Docking of C. longa with IGF-1R Protein

Compounds	Docking score (Kcal/mol)	No. of H-bond	Residue involved
CHEMBL133463 (IGF-1R Ligand)	-11.31	7	GLU 1050,ARG 1109, MET 1052
Digalloyl-hexoside	-8.849	6	ARG 1109, ASP 1056, LYS 1003
Hyperoside	-8.843	6	GLN 977, ASP 1056, LYS 1003, MET 1052, GLU 1050
Valoneic acid dilactone	-8.472	6	SER 979, LYS 1003, LYS 1058, ASP 1056, MET 1052, GLU 1050
Caffeic Acid	-7.985	3	GLU 1050

3.2 Drug likeness and ADMET Profile Assessment of The Lead Compounds

This was estimated by evaluating the absorption, distribution, metabolism, excretion, and toxicity properties as an ADMET profiling. For the chemical absorption and transport properties, Lipinski's ‘rule of five.’ helps to screen out compounds with probable absorption problems. The results of the ADMET profiling including the Lipinski rule of five are shown in table 2 below.

Table 2: ADMET profile of the lead compounds of C. longa with IGF-1R ligands

MODELS	Digalloyl-hexoside	Hyperoside	Valoneic acid dilactone	Caffeic acid
CYP1A2 inhibition	-	-	-	-
CYP2C19 inhibition	-	-	-	-
CYP2C9 inhibition	-	-	-	-
CYP2D6 inhibition	-	-	-	-
CYP3A4 inhibition	-	-	-	-
Gastrointestinal absorption	Low	Low	Low	High
Blood Brain Barrier Permeation	-	-	-	-
P-glycoprotein substrate	-	-	-	-
Log K_pcm/s (skin permeability)	-9.83	-7.05	-8.14	-6.58
Lipinski’s rule	2	2	2	0
Log P value	0.93	2.11	0.78	0.97
Log S value	-3.83	-4.35	-5.85	-2.38
TPSA	243.90	210.51	228.33	77.76
Molar mass	484.36	464.38	470.30	180.16
Hydrogen bond donors	9	8	7	3
Oral Bioavailability	0.16	0.17	0.11	0.56

(CYP1A2=Cytochrome P450 1A2; CYP2C19= Cytochrome P450 2C19; CYP2C9= cytochrome P450 2C9; CYP2D6= Cytochrome P450 2D6; CYP3A4= Cytochrome P450 3A4; TPSA= Topological Polar Surface Area).

Molecular docking simulations provide us abilities to study protein-protein interactions as well as protein-ligand interactions with varieties of computational softwares available for these docking studies in drug discovery. These interactions are studied by predictions of binding sites which are determined by using the shape, electrostatic interactions, van der Waals interactions, hydrogen bond formation and coulombic interactions to study the ligand and protein receptors or enzyme interactions[17]. Over 60 available programs are used for docking studies, AutoDock Vina, GOLD, FlexX and MoE-Dock are just a few examples[18]. Our study used the Glide docking tool in Maestro 11.1 to predict binding affinities of C. Longa compounds with the IGF-1R protein receptor. We screened twenty-four phytochemical compounds virtually from the phenolic extracts of C. Longa rhizome and identified four lead compounds based on their docking scores. Ligands are ranked lead compounds based on their binding affinity scores, the higher the binding affinity scores, the more potential it has to bind to the target protein and this score is retrieved in the process of post docking analysis[17]. The lead compounds identified in this study were digalloyl-hexoside, hyperoside, valoneic acid dilactone, andcaffeic acid. Digalloyl-hexoside exhibited the highest negative docking score (-8.849 kcal/mol; Table 1) followed by close number of score for hyperoside and valoneic acid dilactone (-8.843 kcal/mol, -8.472 kcal/mol, respectively). Hyperoside and valoneic acid dilactone were also predicted to be candidates to inhibit the IGF pathway with docking scores. Caffeic acid showed the lowest docking score with -7.985 kcal/mol indicating a least binding affinity with IGF-1R. The three ligands’ molecules digalloyl-hexoside, hyperoside and valoneic acid dilactone showed ability to interact with the target receptor and form both hydrogen and other electrostatic/hydrophobic interactions with several amino residues. Digalloyl-hexoside, hyperoside, and valoneic acid bilactone showed six hydrogens bonds while caffeic acid had three hydrogen bonds (Table 1). Valoneic acid dilactone compound exhibited the highest active site with 7 residues followed by Hyperoside with 5 residues, Digalloyl-hexoside with 3 residues, and at the last Caffeic Acid with 1 residue (Table 1; Figure 1). The active site was ASP 1056, LYS 1003, and GLU 1050. Among the active residues involved, polar amino acids were highly dominant, which can significantly influence key structural parameters such as hydrophobicity, solvent accessibility, and secondary structure. This indicates that digalloyl-hexoside has a great affinity with a favorable interaction with IGF-1R. Previous studies have highlighted the anticancer properties of identified C. longa compounds, particularly in the context of inhibiting cancer cell proliferation. Prominently, digalloyl-hexoside, from gallic acid demonstrated considerable anticancer activity through multiple pathways [19]. Methanolic extract from the compounds of C. Longa rhizomes have been shown to inhibit the growth of the human hepatoma cell line (HepG2), this study identified lead compounds that include ar-turmerone (20.50 %), β-sesquiphellandrene (5.20 %) and curcumenol (5.11 %), and Curcumin[20]. Consequently, these lead compounds provide insight to building a strong folding and stable configuration during binding with target proteins and in the case of our study, IGF-1R [21,22,23].

Pharmacokinetics profile of drugs include studying the Absorption, Distribution, Metabolism and Excretion (ADME) properties of drug candidates. This is a very important stage in drug discovery and development as it helps to look into cost, efficacy, toxicity and treatment strategies for patients as drugs that do not meet up to a standard pharmacokinetic profile, have a higher tendency to result in failures in clinical trials[24]. Toxicity of the drug was estimated by the degree of drug-drug interactions[25]. Digalloyl-hexoside, Hyperoside, Valoneic acid bilactone compounds showed low gastrointestinal absorption while caffeic acid had the highest absorption rate. While the first three compounds exhibited low metabolic rates, negatively affecting their bioavailability and limiting their ability to reach the target site through the bloodstream, caffeic acid displayed significantly improved pharmacokinetic properties. Specifically, caffeic acid demonstrated a high absorption rate and efficient metabolism, indicating its superior capacity to reach and act upon the target site. Moreover, its remarkable skin permeability (with a value of -6.58) suggests that caffeic acid is particularly well-suited for topical or transdermal delivery, offering an effective method of permeating the skin. Ideally, none of the molecules showed any penetration through the blood-brain barrier. Digalloyl-hexoside, Hyperoside, Valoneic acid bilactone, and caffeic acid all showed low oral bioavailability within the range of 0.11-0.56, making them ineffective via oral use (table 2). Results from the interactions of our lead compounds with the five cytochrome P450 families of enzymes (CYP1A2, CYP2C19, CYP2C9, CYP2D6, and CYP3A4) showed that extracted compounds have no inhibitory properties on these enzymes which indicates that there is no impact or alteration on the normal metabolic processing of other drugs.

The Lipinski rule of five is one of the rules providing standards for compounds to be identified as drug candidates.The Lipinski rule of five considers five parameters which includes the molecular weight, polar surface area, lipophilicity (Log P), hydrogen bonding, and charge[26]. Our study also evaluated the lead compounds based on the Lipinski rule of five to screen out compounds with probable absorption problems. Caffeic acid showed no violation of the Lipinski rule of five, indicating that it is suitable for oral administration. According to the rule, poor absorption or permeation of a drug is more probable when the chemical structure fulfills two or more of the following criteria: the Molecular weight (MW) is greater than 500, the calculated log P value is above five, there are more than five hydrogen bond donors (–NH–, –OH), the number of hydrogen bond acceptors (–N=, –O–) is greater than ten [23]. Lipinski’s rule was tested, caffeic acid complied with the Lipinski rule of five while the other compounds had two violations. It has been demonstrated that heavier molecules have a lower probability of absorption and site-specific localization [24]. All lead compounds showed molecular weights below 500g/mol, this is significant in that it increases the likelihood that they will be easily absorbed by the body since smaller molecules penetrates the cell membranes more easily and are less likely to be substrates for efflux pumps and metabolic enzymes that can reduce a drug's bioavailability. For Oral absorption and water solubility Log P and LogS were evaluated. Molecules showed acceptable results for the former test with Hyperoside as the highest with 2.11, while less water solubility was indicated by the latter test as all results were than -3.0. Furthermore, membrane permeability and the movement of molecules were measured as Caffeic acid showed the lowest number among them. The Hyperoside, Digalloyl-hexoside, and Valoneic acid bilactone molecules showed higher values, while caffeic acid had 77.76 polar surface area (PSA) value was the highest efficient membrane permeability, and this was predicted to be directly linked with the molar mass of the modules.

LIMITATIONS

Our study focused on only the bioactive compounds in the C. Longa rhizome which limits us to just twenty-four phytochemical compounds present in C. longa rhizome to be screened for identification of the ligands and this represents a small portion of the copious bioactive compounds present in the entire plant. Additionally, Molecular Mechanics Generalized Born Surface Area (MMGBSA) which serves to estimate the binding free energy of the ligands and predict the strength of non-covalent interactions between ligands and protein (receptor) was not determined for the ligands in our study, also, wet lab experiments were not carried out to validate the finding of our studies due to funding issues.

Ovarian cancer remains one of the challenging treatable cancers with a high mortality rate. Taken together, our results indicate that three phytochemical compounds of C. longa have a good score of drug bioavailability and safety includes Digalloyl-hexoside, Hyperoside, and Valoneic acid bilactone. However, their gestational absorption affects their bioavailability effectiveness, their structures could be modified to improve their absorption for high potency. Also, none of the compounds evaluated had high docking scores when compared with the IGF-1R ligand, the caffeic acid showed the least favorable drug in fighting ovarian cancer according to the pharmacokinetic properties. However, we suggest that other in-depth work in Silico, and wet lab experiments should be carried out to further validate these findings.

CA125: Cancer antigen 125

Akt / PI3K pathway: PI3K (phosphatidylinositol 3-kinase) and Akt (protein kinase drug-likenesshe extracellular signal-regulated kinase 1/2

COX-2: Cyclooxygenase-2 inhibitors

MAPK: Mitogen-activated protein kinase

PKC: Protein kinase C

uPA: Urokinase-type pThe toxicityen activator

GLU – Glutamic Acid

ARG – Arginine

MET – Methionine

ASP – Aspa ic Acid

LYS – Lysine

GLN – Glutamine

SER – Serine

MMGBSA – Molecular Mechanics Generalized Born Surface Area

Ethics approval and consent to participate

Not applicable.

Funding

Not applicable.

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No competing interests reported.

GraphicalAbstract.png

A Computational Modelling Study of Phytoconstituents of Curcuma longa Rhizome with IGF-1R Protein in Ovarian Cancer

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Abstract

Figures

1. INTRODUCTION

2. Materials and Methods

3. RESULTS

DISCUSSION

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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