Scrutinizing Pyrazole Derivatives as Potential Anticancer Agents: Molecular Docking Study on RET Protein Tyrosine Kinase

Gayathri H, Jefin Joby, Jomon Joy, Sibin C Babu, Jees Mariya K Babu, Adith A Amoor, Lakshminarayanan B*

Department of Pharmaceutical Chemistry, Sanjo College of Pharmaceutical Studies, Vellapara, Palakkad, Kerala

*Corresponding Author E-mail: blnrxpharma@gmail.com

ABSTRACT:

Pyrazole derivative moiety exhibits diverse pharmacological characteristics, including anticancer properties, and serves as a foundational element for synthesizing various chemical compounds. This study aims to identify novel pyrazole-based chemical entities with anticancer potential and assess their binding capabilities through molecular docking analysis. Docking simulations were conducted using the receptor tyrosine protein kinase, known for its involvement in various human cancers such as lung cancer, thyroid cancer and breast cancer. Specifically, we focused on the G810A mutant of the RET protein domain (PDB ID: 6NE7). Among the compounds studied, EH15 (hydroxyl group at the m-position), EH49 (carboxylic acid group at the p-position), and EH52 (amide group at the p-position) exhibited remarkable binding energies. Notably, Compound EH32, containing an amino group at the o-position of the pyrazole derivative, demonstrated the highest binding affinity with the receptor and displayed significant inhibitory activity. These findings suggest that EH32 and other identified compounds could serve as potent inhibitors of the receptor tyrosine protein kinase, presenting promising avenues for anticancer drug development.

KEYWORDS: Pyrazole derivatives, Protein, ADME properties, Anticancer, Ligands, Molecular Docking, and Rearranged during transfection (RET).

INTRODUCTION:

Cancer is a mass of tissue which is produced when cells divide improperly, excessively, uncontrollably, autonomously, and purposelessly, even after the growth stimulation that started the cells' proliferation has stopped. Cancer is one of the illnesses that most threatens human survival. Moreover, it is anticipated that the death rate from cancer would soon surpass the death rate from cardiovascular disease¹.

In 2020 reported more than 19 million new instances of cancer and 10 million deaths from disease globally, according to a recent WHO report. By 2040, there will likely be 30.2 million annual cancer deaths and new cases of the disease. An ICMR study estimates that one in nine Indians will develop cancer at some point in their lifetime. According to the study, which was published in the Indian Journal of Medical Research (IJMR), one in 67 males and one in 29 women (0-74 years old) are at risk of having lung cancer and breast cancer, respectively, over their lives. In 2022, 14.6 lakh Indians have been diagnosed with cancer. Lung cancer in men and breast cancer in women are the most prevalent types of cancer. Projections suggest that cancer incidence will rise by 12.8% in 2025 compared to 2020. Current cancer research highlights the severe impact of lung cancer on public health, necessitating the development of new anticancer drugs with high specificity. This can be accomplished through in-silico drug design, also known as rational drug design. This innovative process involves creating new medications based on the understanding of a biological target². Drug discovery encompasses identifying and characterizing molecules that can safely modulate disease, aiming to develop medicines that enhance patient health³.

Deep learning and computational methods are becoming more and more important in the drug discovery process. The speed at which techniques and algorithms are developing has reduced the amount of time and money needed to identify potential medication candidates. Computational biology has made contributions to drug development in the areas of ligand-binding molecular mechanisms, binding/active site identification, and structure refinement of ligand-target binding poses. The majority of these methods suggest that it's important to identify the binding and active sites on the target protein. To direct the modification and optimization of the original lead molecule and produce new ligand-target protein interactions, certain residues of these binding sites may be employed. Sometimes investigating the pathogenic activity requires more than just engaging the active spot. Docking is a technique which forecasts a molecule's preferred orientation in relation to another when a ligand and a target are bound together to form a stable complex or it refers to computational systems that look for the optimal pairing of two molecules: a ligand and a receptor^4.

The naturally occurring cellular or molecular structure implicated in the pathology of interest; this is the "target" where the drug-in-development is intended to act⁵. RET functions as a transmembrane growth factor receptor, and several clinically significant protein-tyrosine kinase inhibitors (TKIs) targeting RET have been discovered. In this study, we focus on the G810A mutant of the RET protein tyrosine kinase domain (PDB ID: 6NE7).

Fig. 1. Graphical abstract of the study

Aberrant activation of RET is implicated in various human cancers, making it a critical target for therapies aimed at cancers associated with RET abnormalities. Graphical abstract of the study is given in Figure 1. Compounds containing moieties like pyrazole, thiazole, quinoxaline, oxadiazole and chalcone have showed greater affinity against target protein for cancer and possess anticancer activity.^6-13

MATERIALS AND METHODS:

To find out the binding interactions of the synthesized compounds with protein, docking was performed by using iGEMDOCKv2.1 software. The computational work was performed on a HP Laptop15s AMD RYZEN 5.

Selection of protein structure¹⁴:

The RET protein tyrosine kinase is a receptor tyrosine kinase that plays a critical role in cell signalling. It is encoded by the RET gene and is involved in the regulation of cell proliferation, differentiation, migration, and survival. RET stands for "Rearranged during Transfection" and mutations in this gene are associated with several diseases, including multiple endocrine neoplasia type 2 (MEN2), familial medullary thyroid carcinoma (FMTC), and Hirschsprung's disease. RET is activated by binding to its ligands, which are members of the glial cell line-derived neurotrophic factor (GDNF) family. Upon ligand binding, RET undergoes dimerization and auto phosphorylation, leading to the activation of downstream signalling pathways, such as the MAPK, PI3K/AKT, and JAK/STAT pathways. These pathways are crucial for the normal development of the nervous system and kidneys. In cancer, activating mutations in RET can lead to uncontrolled cell growth and tumor development. As a result, RET is a target for cancer therapies, and several RET inhibitors have been developed and approved for the treatment of RET-mutant cancers.

Download the protein structure as follows from www.rcsb.org. First, go to www.rcsb.org and search for the protein with the PDB ID "6NE7". Download the protein file in PDB format. Once downloaded, copy the protein file from your downloads folder. Open MOE (Molecular Operating Environment) and paste the downloaded protein file (e.g., 6NE7) into MOE for further analysis.

Preparation and purification of the protein¹⁵:

Select 'moe.exe' from Windows, then open the required protein file. The protein structure will be displayed on the screen. Next, press 'Ctrl+Q' and select all water molecules. Click on the 'Edit' option and choose 'Delete Selected Residues' to remove the water molecules. The amino acid chains will then be visible. Identify the longest chain from the amino acid chains and delete the remaining chains. Then, select the 'Edit' option, click on 'Hydrogens', and choose 'Add Polar Hydrogens'. Finally, save the modified protein structure in PDB format (e.g., 6NE7.pdb). The structure of the protein and its 3D view are shown in Figures 2 and 3.

Preparation of ligands¹⁶:

Structures of pyrazole and its derivatives were drawn in ChemDraw Pro 8.0 and converted into ligand structures in ChemDraw 3D Pro 8.0. Select 'MM2' and click on 'Minimize Energy', then select the 'Run' button. Go to 'File' and 'Save As' in PDB format. The structures with their codes are given in Table 1.

Fig. 2: Structure of 6NE7               Fig. 3: 3D View of 6NE7

Table 1: Molecular structures of pyrazole derivatives and standard

Compound Code	R	Corresponding derivatives and IUPAC name	Compound Code	R	Corresponding derivatives and IUPAC name
EH1	-H	3-(4-ethoxyphenyl)-5-phenyl-1H-pyrazole	EH11	-Cl	5-(2-chlorophenyl)-3-(4-ethoxyphenyl)-1H-pyrazole
EH2	-OCH3	3-(4-ethoxyphenyl)-5-(2-methoxyphenyl)-1H-pyrazole	EH12	-Cl	5-(3-chlorophenyl)-3-(4-ethoxyphenyl)-1H-pyrazole
EH3	-OCH3	3-(4-ethoxyphenyl)-5-(3-methoxyphenyl)-1H-pyrazole	EH13	-Cl	5-(4-chlorophenyl)-3-(4-ethoxyphenyl)-1H-pyrazole
EH4	-OCH3	3-(4-ethoxyphenyl)-5-(4-methoxyphenyl)-1H-pyrazole	EH14	-OH	4-[3-(2-ethoxyphenyl)-1H-pyrazol-5-yl]phenol
EH5	-OCH2CH3	5-(2-ethoxyphenyl)-3-(4-ethoxyphenyl)-1H-pyrazole	EH15	-OH	4-[3-(3-ethoxyphenyl)-1H-pyrazol-5-yl]phenol
EH6	-OCH2CH3	5-(3-ethoxyphenyl)-3-(4-ethoxyphenyl)-1H-pyrazole	EH16	-OH	4-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]phenol
EH7	-OCH2CH3	3,5-bis(4-ethoxyphenyl)-1H-pyrazole	EH17	-F	3-(4-ethoxyphenyl)-5-(2-fluorophenyl)-1H-pyrazole
EH8	-CH3	3-(4-ethoxyphenyl)-5-(2-methylphenyl)-1H-pyrazole	EH18	-F	3-(4-ethoxyphenyl)-5-(3-fluorophenyl)-1H-pyrazole
EH9	-CH3	3-(4-ethoxyphenyl)-5-(3-methylphenyl)-1H-pyrazole	EH19	-F	3-(4-ethoxyphenyl)-5-(4-fluorophenyl)-1H-pyrazole
EH10	-CH3	3-(4-ethoxyphenyl)-5-(4-methylphenyl)-1H-pyrazole	EH20	-Br	5-(2-bromophenyl)-3-(4-ethoxyphenyl)-1H-pyrazole
EH21	-Br	5-(3-bromophenyl)-3-(4-ethoxyphenyl)-1H-pyrazole	EH31	-N(CH3)2	4-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]-N,N-dimethylaniline
EH22	-Br	5-(4-bromophenyl)-3-(4-ethoxyphenyl)-1H-pyrazole	EH32	-NH2	2-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]aniline
EH23	-NO2	3-(4-ethoxyphenyl)-5-(2-nitrophenyl)-1H-pyrazole	EH33	-NH2	3-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]aniline
EH24	-NO2	3-(4-ethoxyphenyl)-5-(3-nitrophenyl)-1H-pyrazole	EH34	-NH2	4-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]aniline
EH25	-NO2	3-(4-ethoxyphenyl)-5-(4-nitrophenyl)-1H-pyrazole	EH35	-COCH3	1-{2-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]phenyl}ethan-1-one
EH26	-CH2CH3	3-(4-ethoxyphenyl)-5-(2-ethylphenyl)-1H-pyrazole	EH36	-COCH3	1-{3-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]phenyl}ethan-1-one
EH27	-CH2CH3	3-(4-ethoxyphenyl)-5-(3-ethylphenyl)-1H-pyrazole	EH37	-COCH3	1-{4-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]phenyl}ethan-1-one
EH28	-CH2CH3	3-(4-ethoxyphenyl)-5-(4-ethylphenyl)-1H-pyrazole	EH38	-CCl3	3-(4-ethoxyphenyl)-5-(2-trichlorophenyl)-1H-pyrazole
EH29	-N(CH3)2	2-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]-N,N-dimethylaniline	3H39	- CCl3	3-(4-ethoxyphenyl)-5-(3-trichlorophenyl)-1H-pyrazole
EH30	-N(CH3)2	3-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]-N,N-dimethylaniline	EH40	- CCl3	3-(4-ethoxyphenyl)-5-(4-trichlorophenyl)-1H-pyrazole
EH41	-N(C2H5)2	3-(4-ethoxyphenyl)-5-(2-methylphenyl)-1H-pyrazole	EH47	-COOH	2-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]benzoic acid
EH42	-N(C2H5)2	3-(4-ethoxyphenyl)-5-(3-methylphenyl)-1H-pyrazole	EH48	-COOH	3-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]benzoic acid
EH43	-N(C2H5)2	3-(4-ethoxyphenyl)-5-(4-methylphenyl)-1H-pyrazole	EH49	-COOH	4-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]benzoic acid
EH44	-CF3	3-(4-ethoxyphenyl)-5-[2-(trifluoromethyl)phenyl]-1H-pyrazole	EH50	-CONH2	2-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]benzamide
EH45	-CF3	3-(4-ethoxyphenyl)-5-[3-(trifluoromethyl)phenyl]-1H-pyrazole	EH51	-CONH2	3-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]benzamide
EH46	-CF3	3-(4-ethoxyphenyl)-5-[4-(trifluoromethyl)phenyl]-1H-pyrazole	EH52	-CONH2	4-[3-(4-ethoxyphenyl)-1H-pyrazol-5-yl]benzamide
STD (Doxorubicin)

Molecular docking study on receptor tyrosine protein kinase RET¹⁷:

Install and open ‘iGEMDOCKv2.1.zip’. Click ‘iGEMDOCKv.2.1’ and select ‘bin’. Click ‘Prepare Binding Site’, then select the ‘Browse’ option, choose the required protein, and click ‘OK’. Next, click on ‘Prepare Compounds’, select ‘Ligand’, choose the required ligand, and click ‘OK’. Adjust the population size to 50, generations to 20, number of solutions to 1, and select ‘Custom’. Then click on ‘Start Docking’ and click ‘OK’. After the docking process is complete, click ‘View Docked Poses and Post Analyse’. Results can be interpreted by clicking on ‘Interaction Profile’ and ‘Interaction Analysis’. Repeat the same procedure with the standard drug.

RESULTS AND DISCUSSION¹⁷:

The software iGEMDOCK is a useful tool that can offer a more advantageous starting point for pharmacological interactions. This software facilitates results in identifying extra novel and potentially active compounds for a specific protein that causes disorders. The binding energy with the highest value supports the drug's ability to fit to the target molecules. The likelihood that a chemical will be approved as a medication increases with the amount of negative binding energy. The docking of pyrazole derivatives with the target protein was performed using iGEMDOCK, utilizing genetic algorithm parameters set to a population size of 50, with 20 generations and a single solution. This docking technique identifies various bond energies, such as hydrogen bonds (H-bonds), Van der Waals (VDW) interactions, and electrostatic interactions occurring between the compounds and the protein. Results were given in Table 2. 

The docking results for the given compounds indicate varying binding energies, with compound EH32 exhibiting the most significant binding energy at -74.58 kcal/mol. Binding energy is a crucial parameter in molecular docking, as it reflects the stability and affinity of the ligand-protein complex; lower energy values denote stronger interactions and more stable complexes.

Table 2: Docking Results

Code	Energy	VDW	H-bond	Code	Energy	VDW	H-bond
EH1	-52.69	-52.69	0	EH27	-65.82	-50.82	-15
EH2	-53.48	-43.54	-9.94	EH28	-65.25	-59.95	-5.3
EH3	-57.93	-55.74	-2.19	EH29	-48.25	-44.66	-3.59
EH4	-54.56	-53.65	-0.91	EH30	-55.93	-48.93	-7
EH5	-61.67	-56.55	-5.12	EH31	-47.11	-44	-3.11
EH6	-53.04	-53.04	0	EH32	-74.58	-56.54	-18.03
EH7	-57.72	-57.72	0	EH33	-56.54	-55.12	-1.51
EH8	-62.78	-54.51	-8.27	EH34	-59.68	-42.83	-16.86
EH9	-54.35	-44.11	-10.24	EH35	-56.12	-54	-2.12
EH10	-52.35	-45.58	-6.77	EH36	-61.74	-55.13	-6.61
EH11	-54.73	-53.3	-1.44	EH37	-54.3	-50.67	-3.63
EH12	-58.45	-54.95	-3.5	EH38	-49.99	-49.99	0
EH13	-55.64	-48.34	-7.3	EH39	-54.87	-54.87	0
EH14	-61.92	-57.15	-4.77	EH40	-55.9	-52.4	-3.5
EH15	-67.97	-52.11	-15.86	EH41	-52.81	-45.51	-7.66
EH16	-59.68	-55.53	-4.15	EH42	-63.51	-54	-9.42
EH17	-54.57	-49.97	-4.6	EH43	-52.1	-50.56	-1.54
EH18	-66.07	-65.52	-0.55	EH44	-52	-46.3	-5.7
EH19	-50.37	-50.37	0	EH45	-62.24	-60.3	-1.94
EH20	-57.42	-47.48	-9.93	EH46	-54.96	-54.96	0
EH21	-53.73	-53.73	0	EH47	-55.44	-42.29	-13.14
EH22	-52.39	-52.39	0	EH48	-61.9	-56.87	-5.03
EH23	-51.18	-51.18	0	EH49	-70.34	-54.13	-16.21
EH24	-54.66	-51.16	-3.5	EH50	-50.41	-50.41	0
EH25	-56.12	-37.93	-18.19	EH51	-62.98	-51.47	-11.51
EH26	-64.59	-53.21	-11.38	EH52	-66.54	-55.11	-11.43
STD (Doxorubicin)					-57.86	-43.04	-14.81

EH32, with the highest binding energy, demonstrates a strong interaction primarily through Van der Waals forces (-56.54kcal/mol) and significant hydrogen bonding (-18.03kcal/mol). This suggests a substantial interaction at both the hydrophobic and hydrophilic sites of the protein.

Other notable compounds include EH49 (-70.34 kcal/mol) and EH15 (-67.97kcal/mol), both of which also show considerable binding energies, indicating strong and stable binding to the protein target. In contrast, the standard drug Doxorubicin (DOX) has a binding energy of -57.86kcal/mol, with significant contributions from both Van der Waals forces (-43.04 kcal/mol) and hydrogen bonding (-14.81kcal/mol). In comparison, compounds like EH32, EH49, and EH15 surpass Doxorubicin in terms of binding energy, suggesting these compounds could potentially offer more effective interactions with the target protein. Notably, EH32's substantial hydrogen bonding indicates a strong potential for specific and targeted interactions, which may translate to higher efficacy in a biological context.

CONCLUSION:

In this study, we have designed pyrazole derivatives as inhibitors of RET. Abnormal activation of RET is present in various human cancers, including lung cancer, making it a key target for treatments addressing RET-related cancer abnormalities. Docking studies were performed on the designed compounds. The drug's capacity to fit the target molecules is supported by the binding energy, with more negative binding energies indicating a higher likelihood of a chemical being approved as a drug. Most of the compounds showed high binding affinity towards the receptor. The compounds EH15 (hydroxyl group at the m-position in ring C), EH49 (carboxylic acid group at the p-position in ring C), and EH52 (amide group at the p-position in ring C) demonstrated more binding energy than the standard drug. Overall, these findings highlight EH32 (amino group at the o-position in ring C) as the compound with the most promising binding energy, indicating a potentially more effective interaction with the target protein compared to the standard drug Doxorubicin. Further experimental validation is required to confirm these in silico predictions and to evaluate the therapeutic potential of EH32 and other high-binding energy compounds. Such validation would include in vitro and in vivo studies to assess the efficacy, specificity, and safety of these compounds. Additionally, understanding the pharmacokinetics and Pharmacodynamics of these potential inhibitors will be crucial for their development as therapeutic agents.

CONFLICT OF INTEREST:

Authors declared that there is no conflict of interest.

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Received on 19.06.2024      Revised on 18.10.2024

Accepted on 27.01.2025 Published on 03.05.2025

Available online from May 05, 2025

Asian J. Pharm. Res. 2025; 15(2):134-140.

DOI: 10.52711/2231-5691.2025.00022

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