INTRODUCTION:

Abnormalities in insulin is the hallmarks of diabetes mellitus, a group of metabolic disorders that lead to aberrantly high blood sugar levels. Insulin's dysfunction causes irregularities in the metabolism of fats, proteins, and carbohydrates. The root causes of these metabolic disorders include insulin resistance in target tissues such as the liver, adipose tissue, and skeletal muscles. This resistance can occur at the level of insulin receptors. The severity of symptoms varies based on the type and duration of the diagnosis.

Some individuals, especially young patients with early-stage type 2 diabetes, may experience significant hyperglycemia, while others may show no symptoms at all.¹The global cost of diabetes-related healthcare was projected to be 966 billion USD in 2021, increasing to 1, 054 billion USD by 2045.² The development of new drugs is an expensive, precarious, and long process. Typically, it takes around 14 years and costs between 0.8 and 1.0 billion USD to move a drug from concept to commercialization. Recent advancements methods and combinatorial chemistry have speeded this process. Computer-aided drug design (CADD) encompasses computational tools and techniques used for organizing, storing, analysing, and modeling materials. CADD includes tools for evaluating potential lead candidates, algorithms for compound creation, and digital repositories for studying chemical interactions.^3,4.

Molecular docking has become increasingly significant in the drug development process. It predicts the optimal shape, alignment, and point of a small molecule (drug candidate) when it drags to a protein, aiding in lead optimization. Understanding the precise location and binding mechanism of a ligand allows for the rational design of modifications to enhance protein-ligand interaction, increase activity, and avoid conflicts that could arise from changes.⁵ Certain compounds have shown potential in treating diabetes, including chalcone and many heterocyclic derivatives.^6,7,8 Thiazole and its derivatives have demonstrated various activities, such as antidiabetic, antitubercular, and anti-inflammatory properties.^9,10,11,12Human pancreatic alpha-amylase, a member of the Homo sapiens family, is complexed with myricetin, also known as protein 4GQR. Thiazole compounds are anticipated to have anti-diabetic effects by inhibiting this target protein.¹³

MATERIALS AND METHODS:

Using the docking program iGEMDOCKv2.1, the binding relationships between the produced chemicals and proteins were ascertained. The computer work was done using a DELL Laptop with an Intel Core i3 processor (OKTP5DJ inspiron 3593).

Selection of protein structure¹⁴:

For biological macromolecule, the Protein Data Bank (PDB; http://www.rcsb.org/pdb/) serves as the sole global repository. The PDB contains three-dimensional structural information for large biological entities such as proteins and nucleic acids. The protein 4GQR, as previously mentioned, provides high-doggedness structures of representative inhibitors when interacting with pancreatic α-amylase. Myricetin, in particular, demonstrates an antidiabetic effect by binding to sites far from the active site—an attribute unique among studied human α-amylase inhibitors. In this docking study, the binding site of pancreatic alpha-amylase (4GQR) was selected as the receptor for the synthesized thiazole compounds. To proceed, select the protein "Human Pancreatic Alpha-Amylase in Complex with Myricetin from the website and download it in "PDB format". Save the file in the appropriate folder for further analysis.

Preparation and purification of the protein¹⁵:

The "BIOVIA –Discovery Studio Visualizer" computer program was then launched after the protein had been cloned. When you open it from the file, the necessary protein will show up on the screen. Select all of the water molecules by selecting hierarchy in view, and then use the right-click menu to select "cut" to get rid of all of the water molecules. In a similar way, the ligand was also removed. After that, store the refined protein in the relevant folder. Structure of protein were given in Figure 1 and 2.

Fig 1. Structure of 4GQR Fig 2. 3D Structure of protein 4GQR

Preparation of ligands¹⁶:

Using the Chemsketch program, sketch the ligand's structure. Once your tool selections are complete, select Generate and SMILES Notation. Copy and paste it into Google's online Smiles translator.Click Translate, download, and save the file after choosing PDB, Aromatic, 3D as the Unique SMILES Output Format. Compounds structures and IUPAC names were given in Table 1.

Table No.1. Structure of compounds with IUPAC names

Compound code	R	Compounds Derivatives and IUPAC Name	Compound code	R	Compounds Derivatives and IUPAC Name
T1	-H	(1E)-1-phenyl-N-(4-phenyl-1, 3-thiazol-2-yl)ethan-1-imine	T27	-N(CH₃)₂	N, N-dimethyl-3-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}aniline
T2	-CH₃	(1E)-N-[4-(2-methylphenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T28	-N(CH₃)₂	N, N-dimethyl-4-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}aniline
T3	-CH₃	(1E)-N-[4-(3-methylphenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T29	-C₂H₅	(1E)-N-[4-(2-ethylphenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine
T4	-CH₃	(1E)-N-[4-(4-methylphenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T30	-C₂H₅	(1E)-N-[4-(3-ethylphenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine
T5	-OCH₃	(1E)-N-[4-(2-methoxyphenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T31	-C₂H₅	(1E)-N-[4-(4-ethylphenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine
T6	-OCH₃	(1E)-N-[4-(3-methoxyphenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T32	-OC₂H₅	(1E)-N-[4-(2-ethoxyphenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine
T7	-OCH₃	(1E)-N-[4-(4-methoxyphenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T33	-OC₂H₅	(1E)-N-[4-(3-ethoxyphenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine
T8	-Cl	(1E)-N-[4-(2-chlorophenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T34	-OC₂H₅	(1E)-N-[4-(4-ethoxyphenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine
T9	-Cl	(1E)-N-[4-(3-chlorophenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T35	-COOH	2-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}benzoic acid
T10	-Cl	(1E)-N-[4-(4-chlorophenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T36	-COOH	3-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}benzoic acid
T11	-NO₂	(1E)-N-[4-(2-nitrophenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T37	-COOH	4-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}benzoic acid
T12	-NO₂	(1E)-N-[4-(3-nitrophenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T38	-CONH₂	2-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}benzamide
T13	-NO₂	(1E)-N-[4-(4-nitrophenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T39	-CONH₂	3-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}benzamide
T14	-OH	2-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}phenol	T40	-CONH₂	4-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}benzamide
T15	-OH	3-{2-[(E)-(1-phenylethylidene) amino]-1, 3-thiazol-4-yl} phenol	T41	-COCH₃	1-(2-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}phenyl)ethan-1-one
T16	-OH	4-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}phenol	T42	-COCH₃	1-(3-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}phenyl)ethan-1-one
T17	-NH₂	2-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}aniline	T43	-COCH₃	1-(4-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}phenyl)ethan-1-one
T18	-NH₂	3-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}aniline	T44	-CHO	2-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}benzaldehyde
T19	-NH₂	4-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}aniline	T45	-CHO	3-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}benzaldehyde
T20	-F	(1E)-N-[4-(2-fluorophenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T46	-CHO	4-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}benzaldehyde
T21	-F	(1E)-N-[4-(3-fluorophenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T47	-CF₃	(1E)-1-phenyl-N-{4-[2-(trifluoromethyl)phenyl]-1, 3-thiazol-2-yl}ethan-1-imine
T22	-F	(1E)-N-[4-(4-fluorophenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T48	-CF₃	(1E)-1-phenyl-N-{4-[3-(trifluoromethyl)phenyl]-1, 3-thiazol-2-yl}ethan-1-imine
T23	-Br	(1E)-N-[4-(2-bromophenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T49	-CF₃	(1E)-1-phenyl-N-{4-[4-(trifluoromethyl)phenyl]-1, 3-thiazol-2-yl}ethan-1-imine
T24	-Br	(1E)-N-[4-(3-bromophenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T50	-COCl	2-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}benzoyl chloride
T25	-Br	(1E)-N-[4-(4-bromophenyl)-1, 3-thiazol-2-yl]-1-phenylethan-1-imine	T51	-COCl	3-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}benzoyl chloride
T26	-N(CH₃)₂	N, N-dimethyl-2-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}aniline	T52	-COCl	4-{2-[(E)-(1-phenylethylidene)amino]-1, 3-thiazol-4-yl}benzoyl chloride
STD (ACARBOSE)

Table No. 2: Binding energy and interactions of ligand

S.No	Compound	Energy	VDW	H-Bond
1.	T1	-44.9615	-41.2627	-3.6988
2.	T2	-61.6865	-58.1865	-3.5
3.	T3	-55.8516	-55.8516	0
4.	T4	-55.6671	-45.9504	-9.71669
5.	T5	-56.755	-56.755	0
6.	T6	-44.2543	-44.0308	-0.22347
7.	T7	-47.1398	-47.1398	0
8.	T8	-55.1873	-52.8246	-2.36273
9.	T9	-57.3212	-50.7952	-6.52596
10.	T10	-55.0827	-53.57	-1.51269
11.	T11	-59.8883	-59.8883	0
12.	T12	-61.9848	-58.4848	-3.5
13.	T13	-65.4933	-61.4762	-4.01708
14.	T14	-52.6316	-52.6316	0
15.	T15	-51.0103	-47.5103	-3.5
16.	T16	-58.0903	-55.032	-3.05828
17.	T17	-47.7041	-29.6015	-18.1026
18.	T18	-48.2604	-44.9737	-3.28666
19.	T19	-55.3624	-48.8777	-6.48469
20.	T20	-46.9204	-46.9204	0
21.	T21	-49.6574	-49.6574	0
22.	T22	-56.9425	-56.9425	0
23.	T23	-47.635	-42.6131	-5.02192
24.	T24	-49.7777	-46.2777	-3.5
25.	T25	-49.0207	-46.6108	-2.40992
26.	T26	-46.5393	-43.7267	-2.81258
27.	T27	-52.9231	-46.6702	-6.25288
28.	T28	-49.9638	-49.9638	0
29.	T29	-55.4256	-55.4256	0
30.	T30	-57.8552	-57.8552	0
31.	T31	-59.1559	-59.1559	0
32.	T32	-43.5814	-43.3129	-0.26853
33.	T33	-59.3081	-52.766	-6.54214
34.	T34	-57.1733	-57.1733	0
35.	T35	-64.832	-58.5723	-6.25973
36.	T36	-55.4105	-48.4105	-7
37.	T37	-55.1765	-45.2871	-9.88941
38.	T38	-51.2782	-49.5884	-1.68982
39.	T39	-50.0679	-36.1011	-13.9668
40.	T40	-59.1347	-55.6839	-3.45082
41.	T41	-53.2716	-53.2716	0
42.	T42	-55.6527	-44.276	-11.3767
43.	T43	-54.0711	-54.0711	0
44.	T44	-50.756	-47.8273	-2.92871
45.	T45	-52.729	-49.014	-3.71498
46.	T46	-46.2491	-45.0887	-1.16035
47.	T47	-55.2605	-55.2605	0
48.	T48	-48.9901	-48.9901	0
49.	T49	-54.2604	-50.7604	-3.5
50.	T50	-56.2506	-56.2506	0
51.	T51	-48.6388	-48.6388	0
52.	T52	-47.3004	-39.2109	-8.08947
53.	STD(ACARBOSE)	-47.2126	-37.4695	-9.74314

Molecular docking study on receptor Pancreatic alpha-amylase in complex with myricetin¹⁷:

The iGEMDOCK V.2 software is utilized to dock 52 compounds and a standard to the target protein 4GQR. This software also calculates the binding energies of all compounds. To begin, open the application and select "Prepare binding site," then locate the protein in the appropriate folder. Similarly, choose "Prepare Compound," click on "Ligand," and select the ligand from the respective folder. Adjust the docking accuracy settings to a Population size of 50, Generations to 20, and Number of solutions to 1, then initiate the docking process by clicking "Start Docking." After the docking is complete, select "View Docked Pose" and "Post-Analyse." Next, choose the interaction profile, select a docked position, click "Display," and capture a screenshot using the Print Screen key. Save the image and repeat this process for the remaining compounds. Use Microsoft Word to create a table, and then copy and paste the interaction results for each docked compound into the appropriate table. Finally, save the file in the relevant directory.

RESULTS AND DISCUSSION^18,19:

The protein of choice for the docking investigation was Pancreatic Alpha-Amylase in Complex with Myricetin. A review of the literature led to the selection of the target enzymes. The ligands were docked using the program iGEMDOCK V.2. Following acarbose, 52 molecules were docked to interact with the human pancreatic alpha-amylase protein 4GQR. The majority of drug ligand interactions with the protein exhibited an effective binding energy, indicating strong stability between the protein and ligand. Docking analysis results were given in Table 2.

The overall binding energy is a critical indicator of the compound's affinity for the protein. Compounds with lower binding energies are generally more effective. Compound T13 has the lowest energy (-65.4933), suggesting the strongest binding affinity. Van der Waals forces are important for stabilizing the collaboration between the ligand and the protein. Compound T13 also has a significantly low VDW energy (-61.4762), which supports its strong binding affinity. Hydrogen bonds are specific interactions that contribute to the binding specificity and stability. While Compound T13 has a moderately low H-bond energy (-4.01708), compounds such as T4 (-9.71669) and T17 (-18.1026) show significantly lower H-bond energies. However, their overall binding energies are higher than T13, making them less favourable overall. The standard compound acarbose has an overall energy of -47.2126. Compound T13 outperforms acarbose significantly in terms of binding energy (-65.4933 vs. -47.2126), VDW interactions (-61.4762 vs. -37.4695), and slightly better H-bond interactions (-4.01708 vs. -9.74314). Based on the provided data, Compound T13 stands out as the best candidate due to its Lowest overall binding energy (-65.4933), Strong VDW interaction energy (-61.4762) and Adequate H-bond interaction energy (-4.01708).

CONCLUSION:

The application of CADD facilitates the process of discovering novel medications. The protein 4GQR served as the study's instrument. BIOVIA helped to improve the protein molecule's fineness. The iGEMDOCK V.2 software was used to carry out the docking studies. Investigating the usefulness of computer-aided drug design in figuring out the binding energy between medications and proteins was the aim of this investigation. The molecules with the methyl group at o-position (T2), nitro group at m-position (T12), nitro group at p-position (T13), and carboxylic group at o-position (T35) show better binding energy than ordinary acarbose based on the docked result. Compound T13 in which nitro group at p-position exhibited the highest binding affinity among them, leading to its consideration as a possible lead chemical that lowers blood sugar level in diabetes mellitus. Also, the study indicates that compound T13 is the most promising thiazole derivative for potential antidiabetic activity due to its superior binding energy and strong VDW interactions compared to both other derivatives and the standard acarbose. Further studies would be necessary to ratify its efficacy and safety as an antidiabetic medication.

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Received on 26.06.2024 Revised on 02.09.2024

Accepted on 27.10.2024 Published on 10.12.2024

Available online on December 17, 2024

Asian J. Res. Pharm. Sci. 2024; 14(4):345-352.

DOI: 10.52711/2231-5659.2024.00055

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