INTRODUCTION:

Drug discovery is a lengthy and costly process, largely due to the high rate of drug failures that can occur at any stage of development¹. This process is multidisciplinary and involves the identification and development of new therapeutic agents for the treatment of diseases and disorders.

Over the years, efforts have been made to simplify this process and identify more cost-effective strategies. One such advancement is molecular docking². Since its introduction in the 1980s, molecular docking has become widely used in the pharmaceutical industry¹. It is a computational modeling technique that examines the interaction between a protein (often enzymes or gene products) and a ligand, which is the prospective drug molecule. Several docking software tools are available, such as AutoDock³, AutoDock Vina, Schrodinger, GOLD, and MOE⁴, which help predict binding efficiency and conformations of ligands. In silico drug design not only reduces cost but also saves time, thus accelerating the discovery process. It has now become a critical component of modern pharmaceutical research. In this study, in silico drug design was applied to identify potential BRAF inhibitors, which represent a key class of anticancer agents. The RAF gene family regulates critical cellular processes such as proliferation and apoptosis, and mutations in BRAF are strongly linked to the development of several cancers, including melanoma (50–60%), colorectal cancer (10%), thyroid carcinoma (83%), non-small cell lung cancer (3%), and hairy cell leukemia (100%)⁵. Consequently, BRAF inhibitors are recognized as an effective therapeutic class¹⁷. However, currently available drugs are associated with adverse effects such as muscle pain, photosensitivity, joint discomfort, and scaly skin⁶, and their synthesis often involves complex procedures. Therefore, the development of improved inhibitors is highly desirable. Heterocyclic scaffolds containing pyrazine, pyrazole, and anilinoquinazoline cores have been widely utilized in anticancer drug design^72,3.

Their structural resemblance to natural ligands contributes to their success as inhibitors. Over the years, various modifications of these scaffolds have been explored. In addition to anticancer activity, derivatives of pyrazine, pyrazole, and anilinoquinazoline have also demonstrated antitubercular and other pharmacological properties. The present work aims to identify such compounds and evaluate their potential to be repurposed as BRAF inhibitors. In the context of cancer biology, the BRAF gene and the MAPK pathway are of particular importance. The BRAF gene, located on chromosome 7 (region 7q34), encodes the BRAF protein, which is a member of the RAF kinase family. Other isoforms in this family include C-RAF and ARAF. RAF kinases act as key regulators in the MAPK (Mitogen-Activated Protein Kinase) signaling cascade⁸. This pathway governs essential processes such as cell proliferation, differentiation, programmed cell death, and the regulation of inflammation. It consists of a sequential activation of protein kinases, each phosphorylating the next in the cascade. The principal components of this pathway are illustrated in Fig. 1.

Fig 1: Mechanism of MAPK Pathway

Fig 2: Overview of Molecular Targets in MAPK Pathway

Alterations in RAF-MAPK pathways have been linked to various disorders like cancer, Noonan syndrome, LEOPARD syndrome, etc. Gives a step-by-step overview of MAPK pathway.

Rationale for selecting the chemical class as BRAF inhibitors:

Heterocyclic compounds are widely distributed in nature and play crucial roles in biological systems.

Nitrogen-containing aromatic rings such as pyrazine, pyrazole, and anilinoquinazoline are important structural motifs in both natural and synthetic drug molecules. These heterocycles are known for their diverse pharmacological activities. Pyrazine derivatives have been recognized as key frameworks in many pharmaceuticals. Pyrazole derivatives are reported to possess antimicrobial, anti-inflammatory, and anticancer activities^4,5. Anilinoquinazoline derivatives have also been extensively studied for their anticancer potential, particularly as inhibitors of epidermal growth factor receptor (EGFR) tyrosine kinase.

The similarity of these nitrogen-based heterocycles to nucleic acid bases enhances their therapeutic value in diseases caused by genetic mutations, such as cancer. In particular, mutations in the BRAF gene that keep the protein in a constitutively active state result in uncontrolled cell proliferation. This underscores the relevance of pyrazine, pyrazole, and anilinoquinazoline scaffolds in disease treatment and their potential as BRAF inhibitors. Therefore, the present study investigates the ability of these derivatives to act as BRAF inhibitors.

Fig 3: Hypothetical model to predict the interaction of the ligand AQ13 with ATP binding site of the enzyme kinase

MATERIAL AND METHODS:

Selection and Preparation of Target Protein:

BRAF kinase (PDB ID: 4XV9) was chosen as the molecular target because of its key involvement in the MAPK/ERK signaling pathway and the high frequency of oncogenic mutations (notably V600E) in melanoma, colorectal, and thyroid cancers¹⁸. The crystal structure at 1.90 Å resolution was obtained from the RCSB Protein Data Bank. This structure was co-crystallized with the reference inhibitor PLX5568, which occupies the ATP-binding pocket and serves as a validated template for docking studies. Preparation of the structure was performed in the Molecular Operating Environment (MOE v2024.09)⁹. Water molecules, ions, and other non-essential groups were removed, and missing loops or side chains were refined using the QuickPrep module. Hydrogen atoms were introduced to satisfy valences, and ionizable residues (Asp, Glu, His, Lys) were assigned appropriate protonation states for physiological pH (7.4) using Protonate 3D. The protein was further energy-minimized with the Amber99 forcefield (RMSD gradient 0.1 kcal/mol·Å; 500 iterations) to remove steric clashes while maintaining the native fold. The binding pocket was defined using MOE’s Site Finder, centered on PLX5568, with a 12-Å radius that included key catalytic residues such as Gly593, Leu415, and Lys483.

Fig 4: Receptor (4XV9- Braf kinase) Visualization on MOE software

Ligand Selection and Preparation:

A library of 67 heterocyclic derivatives was compiled from five structural classes with reported pharmacological activities:

a. Pyrazine-1,2,3-triazoles (PY; 15 compounds): antitubercular agents

b. Pyridinyl-thio-oxadiazolyl-triazoles (PT; 11 compounds): antimicrobial leads

c. Pyrazole derivatives (PZ; 24 compounds): anti-inflammatory scaffolds

d. Anilinoquinazolines (AQ; 13 compounds): EGFR inhibitors

e. Pyrazole-4-carbaldehydes (PD; 5 compounds): antioxidant motifs

The compounds were first drawn in two-dimensional form using ChemSketch (v2024)¹⁰, and their stereochemistry and tautomeric states were verified. Three-dimensional conformations were then generated in MOE, with protonation adjusted to physiological pH (7.4). Energy minimization was performed using the MMFF94x forcefield (convergence gradient 0.01 kcal/mol·Å, 300 iterations) to obtain stable low-energy structures. The final ligand set was exported in. mol format for subsequent docking.

Fig 5: Structure of pyrazine derivative (PZ17) on Chemsketch software

Molecular Docking Protocol:

Docking studies were conducted in MOE using the Triangle Matcher algorithm, generating up to 100 poses per ligand with a rigid-receptor and flexible-ligand setup. The initial scoring function applied was London dG to estimate binding affinities, and the resulting complexes were subsequently refined through forcefield-based methods to better account for enthalpic and entropic contributions. The binding pocket was defined as a 12 Å sphere centered on the reference ligand PLX5568. Protonation states were adjusted to reflect physiological pH. Validation of the docking procedure was performed by re-docking PLX5568 into the BRAF active site, which produced an RMSD value below 2.0 Å when compared with the crystallographic orientation. A representative docked pose demonstrated:

Fig 6: Redocking of the Receptor with Internal Ligand during validation of docking protocol

1. Favorable binding energy (ΔG < -9.0kcal/mol)

2. Hydrogen bonding with residues Cys599, Asp594, and Lys483

3. π–π stacking interactions with Phe595

4. van der Waals contacts with Leu514 and Ile463

In Silico Pharmacokinetic Evaluation:

Pharmacokinetic characteristics of the heterocyclic derivatives were assessed using the SwissADME online tool¹¹(6). Evaluation of drug-likeness was carried out according to Lipinski’s Rule of Five, together with additional medicinal chemistry filters including those proposed by Veber, Ghose, Egan, and Muegge. These guidelines consider parameters such as molecular weight, lipophilicity (log P), hydrogen bond donors and acceptors, and topological polar surface area (PSA). Compounds predicted to have high gastrointestinal absorption were considered suitable for further analysis, whereas their ability to cross the blood–brain barrier (BBB) was examined to assess potential CNS activity. The bioavailability score, which ranges from 0 to 1, was also calculated; compounds with values of 0.55 or higher were regarded as having favorable oral bioavailability. This computational strategy offered an overview of the drug-likeness and pharmacokinetic profiles of the evaluated compounds, reinforcing their potential applicability as BRAF inhibitors.

RESULT:

1) Ligand series 1: Pyrazine-1,2,3-triazole derivatives [PY]

Table no 1: Binding Energy of Docked Pyrazine-1,2,3-triazole derivatives

Serial no	Ligand ID	R1	R2	R	Binding Energy
1.	PY14	CH	CH	4-Trifluromthyl benzyl	-8.9232
2.	PY12	CH	CH	4-Nitrobenzyl	-8.9142
3.	PY4	N	N	4-Trifluromethyl benzyl	-8.8827
4.	PY2	N	N	4-Nitrobenzyl	-8.8437
5.	PY9	N	CH	4-Trifluromethyl benzyl	-8.8427
6.	PY7	N	CH	4-Nitrobenzyl	-8.8334
7.	PY11	CH	CH	4-Cyanobenzyl	-8.7965
8.	PY1	N	N	4-Cyanobenzyl	-8.7565
9.	PY6	N	CH	4-Cyanobenzyl	-8.6224
10.	PY3	N	N	4-Fluorobenzyl	-8.4667
11.	PY13	CH	CH	4-Fluorobenzyl	-8.3969
12.	PY8	N	CH	4-Fluorobenzyl	-8.2831
13.	PY15	CH	CH	4-Fluorobenzyl	-8.1023
14.	PY5	N	N	4-Fluorobenzyl	-8.0750
15.	PY10	N	CH	4-Fluorobenzyl	-7.8250

Fig 7: General structure of pyrazine derivatives

The pyrazine-1,2,3-triazole derivatives (PY1–PY15) demonstrated favourable physicochemical¹³, drug-likeness, and pharmacokinetic profiles. Their molecular weights ranged between 297.29 and 367.35g/mol, with 5–7 rotatable bonds, 4–8 hydrogen bond acceptors, and a consistent presence of one hydrogen bond donor. Molar refractivity values were within the range of 76.6 to 91.91. All compounds complied with Lipinski’s Rule of Five, Ghose, Veber, Egan, and Muegge filters, without any violations, and showed a uniform bioavailability score of 0.55. In-silico ADME predictions revealed high gastrointestinal absorption for all derivatives. Additionally, compounds such as PY13, PY8, PY15, PY10, PY14, PY4, PY2, and PY9 exhibited potential blood–brain barrier (BBB) permeability, suggesting central nervous system (CNS) applicability. The remaining compounds lacked BBB penetration, indicating their suitability for peripheral targets. These findings collectively support the PY series as promising candidates for further development as BRAF kinase inhibitors.

2) Ligand series 2: Pyridinyl-thio-oxadiazolyl-triazole derivative [PT]

Fig 8: General structure of Pyridinyl-thio-oxadiazolyl-triazole derivative

The pyridinyl-thio-oxadiazolyl-triazole derivatives (PT1–PT11) showed acceptable physicochemical and drug-likeness profiles. Their molecular weights ranged from 353.4 to 419.38g/mol, with 5–7 rotatable bonds and 6–10 hydrogen bond acceptors; all lacked hydrogen bond donors. Molar refractivity values fell within 91.16 to 101.72, indicating moderate polarizability. Most compounds adhered to Lipinski, Ghose, Veber, Egan, and Muegge rules, with a consistent bioavailability score of 0.55, except PT2, PT7, and PT8, which showed slight violations due to elevated TPSA values. Pharmacokinetic analysis predicted high gastrointestinal absorption across all compounds. BBB permeability was observed in PT10, PT3, PT4, PT2, PT7, and PT5, suggesting potential CNS activity, whereas PT1, PT6, PT11, PT8, and PT9 lacked BBB penetration, supporting their suitability for peripheral applications. These results support the PT series as drug-like molecules with promising oral bioavailability and target selectivity.

Table no 3: Binding energy 4-(3-benzoylamino-6-methyl-anilino) quinazolines

Serial no,	Ligand Id	R1	R2	R3	R	Binding energy
1.	AQ13	H	Me	H	N-morpholino	-10.9945
2.	AQ11	H	Me	H	NMe2	-10.1846
3.	AQ10	H	Cl	H	NMe2	-10.1206
4.	AQ12	H	Cl	H	NMe2	-9.5820
5.	AQ9	H	H	Cl	NMe2	-9.5643
6.	AQ3	H	Cl	H	H	-9.5009
7.	AQ7	F	H	H	H	-9.0252
8.	AQ2	H	F	F	H	-8.9945
9.	AQ6	H	H	Me	H	-8.9333
10.	AQ4	H	Me	H	H	-8.6800
11.	AQ5	H	F	Cl	H	-8.6465
12.	AQ1	H	H	H	H	-8.6448
13.	AQ8	H	Cl	H	H	-8.6079

Fig 9: General structure of Anilinoquinozoline

3) Ligand series 3: Anilinoquinozoline (AQ):

The anilinoquinazoline derivatives (AQ1–AQ13) exhibited favourable physicochemical and drug-likeness characteristics. Molecular weights ranged from 400.43 to 499.56 g/mol, with each compound containing 5–7 hydrogen bond acceptors, 2 hydrogen bond donors, and 7–8 rotatable bonds. Molar refractivity values were between 116.2 and 146.97, indicating substantial polarizability suitable for biological interaction. All derivatives satisfied Lipinski’s Rule of Five along with Ghose, Veber, Egan, and Muegge filters, and shared a uniform bioavailability score of 0.55. In-silico pharmacokinetic analysis showed high gastrointestinal absorption for all compounds, while none exhibited blood–brain barrier (BBB) permeability, suggesting their selective suitability for peripheral therapeutic targets. These findings highlight the AQ series as strong oral drug candidates for BRAF inhibition with minimal CNS-related concerns.

4) Ligand series 4: Pyrazole derivatives (PZ):

Table no 4: Binding energy of the docked pyrazole derivatives

Serial No.	Ligand ID	R	Binding energy
1.	PZ17	-N=N	-10.1399
2.	PZ21	SO2-cyclopropane	-9.6284
3.	PZ22	SO2Ar	-9.2679
4.	PZ9	SO3H	-9.1969
5.	PZ24	OCF3	-9.1429
6.	PZ3	CF3	-9.0873
7.	PZ19	PO3H	-9.0591
8.	PZ12	CHO	-8.9091
9.	PZ13	COCH3	-8.9867
10.	PZ23	CF2H	-8.9665
11.	PZ18	SO2NH	-8.9035
12.	PZ10	CN	-8.8539
13.	PZ1	CH3	-8.8080
14.	PZ16	COOH	-8.7828
15.	PZ2	NO2	-8.7577
16.	PZ6	Br	-8.7323
17.	PZ7	OH	-8.6881
18.	PZ15	PO3	-8.6682
19.	PZ11	CO	-8.5600
20.	PZ5	Cl	-8.5502
21.	PZ4	F	-8.4179
22.	PZ8	NH2	-8.3966
23.	PZ20	SH	-8.3964
24.	PZ14	SO2	-8.1972

Fig 10: General structure of pyrazole derivative

The pyrazole derivatives (PZ1–PZ24) displayed favorable physicochemical and pharmacokinetic profiles for oral drug development. The molecular weights ranged from 353.41 to 479.55g/mol, with 4–6 rotatable bonds, 4–8 hydrogen bond acceptors, and 0–1 hydrogen bond donor. Molar refractivity values were within 104.98 to 136.96, indicating adequate molecular polarizability. All compounds complied with Lipinski’s rule and Veber, Egan, and Muegge filters, while most also passed the Ghose rule; bioavailability scores were consistently between 0.55 and 0.56. In-silico ADME predictions showed high gastrointestinal absorption across the series. Notably, only a subset of compounds—such as PZ3, PZ5, PZ6, PZ23, and PZ24—were predicted to cross the blood–brain barrier, indicating potential CNS activity, whereas the majority were confined to peripheral distribution. These findings support the PZ series as promising scaffolds for further development as orally active BRAF inhibitors.

5) Ligand series 5: Pyrazole Carbaldehyde Derivative (PD):

Table no 5: Binding Energy of the docked pyrazole Carbaldehyde derivatives

Serial No.	Ligand ID	R	Binding energy
1.	PD1	OCH3	-8.4044
2.	PD5	Br	-8.0366
3.	PD2	CH3	-7.8671
4.	PD3	Cl	-7.6420
5.	PD4	F	-7.5703

Fig 11: General structure of Pyrazole Carbaldehyde Derivative

The pyrazole carbaldehyde derivatives (PD1–PD5) demonstrated consistent physicochemical and drug-like characteristics. Molecular weights ranged from 326.78 to 391.65g/mol, with all compounds possessing 4–5 rotatable bonds, 3–4 hydrogen bond acceptors, and one hydrogen bond donor. Molar refractivity values were between 84.93 and 92.67. All derivatives complied with Lipinski’s, Ghose, Veber, Egan, and Muegge rules without violations, and each showed a bioavailability score of 0.55. Pharmacokinetic predictions indicated high gastrointestinal absorption and positive blood–brain barrier (BBB) permeability for all five compounds, suggesting potential applicability for central nervous system targets. Among them, PD1 showed the highest binding affinity and stands out as a lead candidate. These findings suggest that the PD series possesses promising oral bioavailability and CNS activity potential.

DISCUSSION:

This work combined molecular docking with pharmacokinetic profiling to examine five classes of heterocyclic derivatives—anilinoquinazolines, pyrazoles, pyrazine-triazoles, pyridinyl-thio-oxadiazolyl-triazoles, and pyrazole-carbaldehydes—as candidate BRAF inhibitors. Among the tested molecules, AQ13 displayed the most favorable binding affinity (−10.99kcal/mol), followed by PT10 (−9.66 kcal/mol) and PZ17 (−10.13 kcal/mol). All three compounds complied with major drug-likeness guidelines and had acceptable predicted bioavailability scores (≥0.55). The ADME results further indicated that most derivatives possessed satisfactory pharmacokinetic properties without major violations. Notably, AQ derivatives appeared more suitable for peripheral applications, whereas PT and PZ derivatives exhibited potential for CNS activity. Collectively, these findings suggest AQ13, PT10, and PZ17 as strong lead candidates that warrant further biological investigation²⁵.

CONCLUSION:

This study applied molecular docking and pharmacokinetic modeling to evaluate a library of heterocyclic compounds as prospective BRAF inhibitors. Several derivatives exhibited favorable binding affinities and satisfactory drug-likeness. In particular, AQ13, PT10, and PZ17 emerged as the most promising scaffolds, combining strong binding with acceptable ADME characteristics. The predicted ability of some compounds to cross the blood–brain barrier highlights their potential for CNS-directed therapies, while others may be more appropriate for peripheral targets. Overall, these results emphasize the potential of heterocyclic derivatives as leads for BRAF inhibition, meriting additional synthesis and experimental validation.

CONFLICT OF INTEREST:

The authors declare that there are no competing interests related to this study.

ACKNOWLEDGMENTS:

The authors gratefully acknowledge their research supervisor for valuable guidance and the institution for providing essential facilities. The availability of open-access databases and computational tools is also duly recognized.

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Received on 21.08.2025 Revised on 23.09.2025

Accepted on 13.10.2025 Published on 06.11.2025

Available online from November 11, 2025

Asian J. Research Chem.2025; 18(6):371-377.

DOI: 10.52711/0974-4150.2025.00057

This work is licensed under a Creative Commons Attribution-Non Commercial-Share Alike 4.0 International License. Creative Commons License.

Serial no.	Ligand ID	R1	R	Binding energy
1.	PT10	CH	4-trifluoromethyl benzyl	-9.6656
2.	PT3	N	4-trifluoromethyl benzyl	-9.6250
3.	PT4	N	4-nitro benzyl	-9.6173
4.	PT2	CH	4-cyano benzyl	-9.5288
5.	PT7	N	4-methyl benzyl	-9.4426
6.	PT1	CH	4-nitro benzyl	-94168
7.	PT6	N	4-cyano benzyl	-9.5288
8.	PT11	CH	4-methyl benzyl	-9.4426
9.	PT8	N	2-fluoro benzyl	-8.8862
10.	PT9	N	2-fluoro benzyl	-9.6656
11,	PT5	CH	2-fluoro benzyl	-9.4168

Molecular Docking Studies of selected Heterocyclic derivatives as Potential BRAF Inhibitors using MOE

INTRODUCTION:

Rationale for selecting the chemical class as BRAF inhibitors: