In Silico Assessment of Chemical Constituents of Zingiber officinale Rosc. For Anti-diabetic Activity: Molecular Docking with α-Glucosidase Receptor

: Diabetes Mellitus (DM) is a disease in which blood sugar (glucose) levels are elevated because the body cannot release or utilize insulin adequately. Rhizome of Zingiber officinale Rosc. (ginger) has been reported to possess anti-diabetic properties. This study aimed to provide information on the chemical components of ginger that have potential in silico antidiabetic activity against the α-glucosidase receptor. Twenty chemical components of ginger (quercetin, catechin, humulene, β-sesquiphellandrene, camphene, farnesene, β-sitosterol, stigmasterol, curcumin, 6-gingerol, 8-gingerol, 10-gingerol, 6-shogaol, 8-shogaol, 10-shogaol, 6-paradol, 8-paradol, 10-paradol, methyl-6-gingerol, and methyl-8-gingerol) were used as ligands. An in silico study was conducted using the molecular docking technique with the AutoDock Vina software, which was then displayed using PyMOL and Biovia Discovery Studio. The grid box settings obtained in this study were as follows:

Zingiber officinale Roscoe, also known as cultivated ginger, can thrive under various environmental conditions.
It has been grown in India and China for many generations.

Spaniards introduced this plant to the West Indies and
Mexico, and obtained it from India, Southeast Asia, and China.Over time, ginger has spread to various regions, including Africa, Fiji Islands, and Australia (Govindarajan and Connell, 1983;Kumar Poudel et al., 2022).
A previous study on the antidiabetic activity of juice and aqueous extract of Z. officinale Roscoe in streptozotocininduced type I diabetic rats indicated that this plant could reduce total blood sugar and increase the insulin response in diabetic rats (Akhani, Vishwakarma and Goyal, 2004;Al-Amin et al., 2006).In vitro evaluation of the antidiabetic effects on protein glycation and the diffusion of glucose in Z. officinale Roscoe reported that the aqueous extract has dose-dependent antidiabetic effects (Sattar et al., 2012).
The chemicals in ginger responsible for their potential anti-diabetic effects have been investigated.Gingerols, the major pungent compounds in ginger, are believed to be the primary active components.Research has shown that (S)-6-and (S)-8-gingerol significantly enhance glucose uptake in cultured rat skeletal muscle cells (L6) (Li et al., 2012).
Recently, researchers have found that unique compounds that inhibit α-glucosidase can be a highly effective way to manage high blood sugar levels after eating, especially in type 2 diabetes.These inhibitors slow down carbohydrate digestion, which delays glucose absorption in the small intestine and helps control high blood sugar levels after meals (Hossain et al., 2020).Therefore, in this study, we conducted an in silico analysis of the molecular binding of the chemical components of ginger to α-glucosidase receptors.This study aimed to provide information on the chemical components of ginger that have potential and good conformation in silico anti-diabetic activity against the α-glucosidase receptor.

METHODS
Molecular Docking was conducted in five stages: preparation of α-glucosidase, preparation of native and test ligands, Lipinski analysis, molecular docking using Autodock Vina, and analysis and visualization of docking results.

The Preparation of α-Glucosidase
The 3D Crystal Structure of (PDB ID: 2QMJ) was retrieved from the Protein Data Bank (https://www.rcsb.org/)and saved in the PDB format.The crystal structure of α-glucosidase was selected as 2QMJ because of its association with Homo sapiens and its high resolution of 1.9 Å.The α-glucosidase complex was separated from the solvent (H2O) and the ligands.
Optimization is conducted by adding hydrogen and computing charges using Gasteiger in the AutoDock Tools software and then saved in PDBQT format.

Preparation of Native Ligands and Test Ligands
The native ligand (acarbose) was used as a reference, and the test ligands consisted of chemical components from ginger rhizomes (Zingiber officinale Rosc.) obtained from PubChem using the website (https://pubchem.ncbi.nlm.nih.gov/) in the SDF format.
The MarvinSketch 20.19 software was utilized to convert the data into PDB format.Subsequently, the ligands were optimized using AutoDock Tools, with the Torsion Tree set to 'choose torsion' and the number of active torsions defined.Finally, they were saved in the PDBQT format.

Analysis of Lipinski
In order to ensure that the ligands possess characteristics conducive to effective oral administration based on Lipinski's guidelines, Lipinski's analysis was conducted on the SCFBio (http://scfbioitd.res.in/software/drugdesign/lipinski.jsp#anchortag)

Molecular Docking Process
Before the docking simulation, the ligand's active site (grid box) was determined using AutoDock Tools software and saved in a (grid.txt)format.In the docking process, the receptors and ligands were saved in (*.pdbqt) format were copied into a file used to run AutoDock Vina through the command prompt (CMD).

Analysis and Visualization of Docking Results
The analysis used the binding energy parameters, root mean square deviation (RMSD) with PyMOL software, and interactions between α-glucosidase and ligands.
Docking visualization was performed using the Biovia Discovery Studio Visualizer 2019 software.

RESULT AND DISCUSSION
Initially, the structures of the chemical components of ginger were subjected to physicochemical analysis to validate their suitability as potential drug candidates following Lipinski's rule of five.According to Lipinski's criteria, a compound qualifies as a drug candidate if it meets the following specifications: a molecular weight (MW) of ≤ 500 daltons, a maximum of 10 hydrogen acceptors (HA), no more than 5 hydrogen donors (HD), and lipophilicity (LogP) not exceeding 5 (Lipinski, 2004).
The Lipinski analysis results revealed that 13 of 20 chemical compounds from ginger met all five Lipinski rule criteria, as shown in Table 1.
Visualization of the interactions between quercetin, catechin, curcumin, and 6-gingerol and the amino acid residues of α-glucosidase is shown in Figure 1.The larger the bond distance, the easier it is to break.
Furthermore, the presence of compounds such as βsesquiphellandrene, farnesene, 6shogaol,10paradol, enhances the anti-diabetic potential of ginger rhizomes.
by a continuous increase in blood glucose levels.The increasing incidence of diabetes has become a significant public health concern worldwide.Rapid economic development, which has led to urbanization and the adoption of modern living patterns, correlates with an increase in the prevalence of diabetes in most countries worldwide.According to IDF data, an estimated 537 million people aged 20-79 years are living with diabetes.This represents 10.5% of the global population of this age group.The population is projected to increase to 643 million (11.3%) by 2030 and 783 million (12.2%) by 2045 (International Diabetes Federation, 2021) Hyperglycemia, the leading cause of diabetic complications, arises from abnormalities in insulin secretion, insulin action, or both and chronically and heterogeneously presents as glucose, lipid, and protein metabolic dysfunction.Based on its etiology and pathogenesis, diabetes can be divided into four types: type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM), gestational diabetes mellitus (GDM), and diabetes-induced or related to certain diseases, pathologies, and syndromes.T1DM is also known as insulin-dependent diabetes mellitus (IDDM) or juvenileonset diabetes.It is an autoimmune disease characterized by T cell-mediated destruction of pancreatic β-cells, leading to insulin insufficiency and, ultimately, hyperglycemia.T2DM is known as non-insulin-dependent diabetes mellitus (NIDDM) or adult-onset diabetes, accounting for approximately 90-95% of all cases of diabetes.(Banday, Sameer and Nissar, 2020; International Diabetes Federation, 2021).Several pharmacological strategies have been used to manage hyperglycemia in patients with diabetes.Patients with type I diabetes are frequently treated with insulin injections, whereas those with type 2 diabetes are treated with oral medicines and lifestyle modifications.Major classes of oral antidiabetic medications include biguanides, sulfonylureas, meglitinide, thiazolidinedione (TZD), dipeptidyl peptidase 4 (DPP-4) inhibitors, sodiumglucose cotransporter (SGLT2) inhibitors, and αglucosidase inhibitors the α-glucosidase and ligand.The grid box settings obtained in this study are as follows: center_x = -20.209,center_y = -6.763,center_zs = 9.393, size_x = 12, size_y = 10, size_z = 12, and spacing (angstrom) = 1.The docking result analysis in this study included the values of ΔGbind (binding energy), RMSD (root mean square deviation), and the interaction between αglucosidase and the ligands.The ΔGbind values (binding energies) were examined based on the conformations of each test ligand and the native ligand obtained from docking and sorted from the smallest to the largest values.The data for ΔGbind values of ligands against the αglucosidase in

Figure 1 .
Figure 1.Molecular docking of protein (PDB ID: 2QMJ) -ligands.The amino acid residues show the specific interaction to ligand

Table 1 .
The Results of Lipinski Analysis

Table 2 .
Interaction results of α-glucosidase with ligands *Values of ΔGbind compounds are lower than acarbose.

Table 2 Continue
*Values of ΔGbind compounds lower than acarbose.