Molecular docking and DFT study of 4-difluoromethyl pyrazole derivatives as cyclooxygenase-2 inhibitor

doi:10.21203/rs.3.rs-4123172/v1

We applied molecular docking simulations and DFT to examine the binding interactions of 4-difluoromethyl pyrazole derivatives (3a-3h). We assessed the potential binding mechanisms and strengths of derivatives within the receptor's binding site. By methodical simulations, we elucidated the characteristics and interactions towards binding capacities. Proposed compounds were subjected to molecular docking with the major protease (PDB:3LN1) to assess binding affinities. In designed compounds (3a-3h), 3a and 3f show the highest docking score, leading to high affinity toward 3LN1. An energy score of -6.9765 Cal/mol of ligand 3g suggests a strong and advantageous binding affinity, with the negative number indicating stability. The reactivity parameters, FMO, and MEP of the drugs were estimated by DFT calculations. The strong affinity of 3a and 3f was attributed to the existence of three hydrogen bonds and several hydrophobic interactions between the drug and the essential amino acid residues of the receptor. Ultimately, the molecular docking findings were illustrated using the estimated molecule electrostatic potential data using DFT. All these characteristics showed varying degrees of influence on the binding affinity of these compounds with the active protein locations.

molecular docking

potential binding

pyrazole

derivatives

celecoxib

DFT

The 4-difluoromethyl pyrazole, possessing unique chemical and physical properties, holds potential applications in medicinal chemistry, agrochemicals, and materials science. The difluoromethyl group significantly influences the parent pyrazole molecule's reactivity and lipophilicity, making it a valuable building block for the synthesis of tailored derivatives [1]. These derivatives also show the potential to display several biological activities, including anti-inflammatory, antibacterial, antifungal, and anticancer properties [2]. The incorporation of the difluoromethyl group has been observed to enhance the lipophilicity and metabolic stability of the compounds, both of which are critical considerations in the field of medication design [3]. Cancer is a pathological state characterized by the uncontrolled proliferation of aberrant cells that can metastasize to different body regions [4]. Cancer is the second most common cause of death globally [5]. In addition to breast cancer, lung cancer is recognized as one of the most formidable malignancies, which exhibits the greatest fatality rate among all cancer categories globally [6]. These compounds, characterized by the incorporation of the difluoromethyl moiety, have undergone thorough investigation due to their potential pharmacological properties, positioning them as promising entities in the field of pharmaceutical research and development [7][8][9]. The derivatives have the potential to engage with distinct molecular targets within the body, including enzymes or receptors, thereby eliciting therapeutic outcomes [10]. However, the mechanisms and targets may differ based on the composition of the derivative [11]. Computational molecular docking studies estimate the preferred orientation and binding mode of a small molecule (ligand) within a target macromolecule (typically a protein). Molecular docking predicts the preferred orientation of one molecule relative to a second molecule when bonded to create a stable complex. This is carried out in drug discovery to anticipate how a tiny molecule (drug candidate) would attach to an enzyme or receptor [12]. Recognizing the promising body of research, it is essential to acknowledge that further investigations are needed to fully comprehend and harness the therapeutic capabilities of 4-difluoromethyl pyrazole derivatives [13]. The development of medications is a complex process, and scientists continue to explore a variety of chemical structures and their corresponding biological activities in order to discover innovative and effective therapeutic interventions [14]. Utilizing computational methodologies, researchers investigate the docking properties of 4-difluoromethyl pyrazole derivatives, aiming to comprehend how these compounds interact with specific targets such as proteins or enzymes in the realm of drug discovery [15]. This exploration assists in predicting binding mechanisms and estimating affinity, reflecting a keen interest among researchers in understanding the therapeutic potential of these derivatives and their interactions with specific biological targets [16][17]. The proposed study utilized virtual docking experiments to computationally dock derivatives into the binding site of the target protein [18]. This approach enabled the prediction of their binding sites and affinity [19]. The primary factors examined in docking investigations encompassed binding energy [20], hydrogen bonding [21], hydrophobic interaction [22], and electrostatic interaction [23]. The results of this investigation provide valuable insights into the potential effectiveness and specificity of these derivatives, thereby offering guidance for subsequent experimental efforts in the realm of pharmaceutical development [24].

To conduct molecular docking analyses on desired compounds, the Molecular Operating Environment (MOE) program was utilized [25]. The crystal structure bound to the antifungal drug was obtained from the Protein Data Bank (PDB ID: 3LNI) at a resolution of 2.00Å. The protein was created using the Protein Preparation Wizard, which involved removing water molecules and adding hydrogen atoms. The compound's energy was decreased with the OPLS3 force field. The ligands were synthesized using LigPrep software and the OPLS3 force field. The Receptor Grid Generation procedure was initiated by selecting any atom of the ligand, which automatically prepared the default grid box. The ligand was affixed to the protein grid box using conventional precision techniques. The findings were reported in terms of docking score, Glide gscore, and Glide emodel values. DFT calculations were performed using Gaussian at PBE0-D3BJ approach with a def2-TZVP basis set. We used advanced tools like Schrödinger for molecular docking and Gaussian for DFT simulations in our research. DFT calculations were employed to optimize the geometry of 4-diflouromethyl pyrazole derivatives. Analyses of the compound’s vibrational frequencies, and orbitals i.e., HOMO-LUMO [26], and MEP were conducted using the optimized molecular structure. GaussView 6 [27] was used to display the results of the FMO and MEP analyses [14]. The molecular structures and electronic properties of molecules 3a-3h were systematically characterized through theoretical calculations conducted at the DFT/PBE0-D3BJ/def2-TZVP level. This comprehensive analysis provided insights into the structural and electronic features of all examined compounds. Employing the DFT method, we derived the HOMO-LUMO energies of 3LNI, coupled with electronic parameters like ionization potential, electronegativity, electrophilic index, nucleophilic index, and chemical potential. Furthermore, we conducted MEP analysis and optimized the geometry, presenting the results through visual representations using GaussView 6 software. ChemDraw structures of 4-diflouromethyl pyrazole derivatives (3a-3h) are given in Fig. 1.

3.1. Molecular docking studies

Molecular docking was performed to investigate the interaction mechanisms and binding strengths of small compounds with the cyclooxygenase enzyme. Utilizing the crystal structure of the musculus target protein with PDB ID 3LN1 as the reference, celecoxib was employed as the ligand in the cocrystal during these investigations. The software MOE was utilized for this docking analysis [28]. A ligand library was compiled using PubChem, and ligands were chosen for the docking studies based on their structural attributes and possible pharmacological significance [29]. The docking analyses revealed the possible binding locations of all ligands to the active site of 3LN1, and the stability of the protein-ligand complexes was also assessed. These results offered a significant understanding of the molecular processes, which controlled the creation of ligand-protein complexes involving protein 3LN1. These findings can also guide additional experimental investigations, such as biochemical testing or structure elucidation, to improve the accuracy of computational predictions and aid in the development of therapeutic drugs or modulators that target protein 3LN1. This study highlights the importance of molecular docking in understanding the binding processes between small drugs and target proteins [30]. Additionally, it establishes the groundwork for the rational development of new compounds with enhanced binding capabilities [31]. Polar hydrogens were added to the macromolecules to prepare them for docking. The MOE Program was used to assign partial atomic charges. The ligand binds directly to the protein at specific positions: Arginine at position 106, Serine at position 516, Tyrosine at position 341, and Leucine at position 338. The binding pattern is influenced by the amino acids i.e., valine (Val) at position 509, phenylalanine (Phe) at position 504, alanine (Ala) at position 502, valine (Val) at position 335, and leucine (Leu) at position 517. The energy score of -7.31191 Cal/mol suggests that the ligand "3a" has a strong binding affinity to the amino acid residues, as indicated by the negative value which signifies stability. The presence of Glutamic acid (Glu) at position 510 and Arginine (Arg) at position 106 is essential for the binding interaction, indicating their importance in maintaining the stability of the ligand-protein complex. Aromatic amino acid residues, such as tyrosine at position 341 and phenylalanine at position 504, could potentially enhance the binding affinity by participating in π-π stacking or other types of interactions. The comprehensive interaction profile of ligand 3b elucidates the precise amino acid residues that facilitate its intricate attachment to the protein, including Alanine (Ala), Arginine (Arg), and Tyrosine (Tyr) at positions 513, 106, and 341 respectively. The energy score of -6.7764 Cal/mol suggests strong binding to the amino acid residues, indicating stability due to its negative value. The presence of Valine at position 509 and Arginine at position 106 is likely to play a crucial role in the process of binding and stability. The presence of aromatic residues, such as Tyrosine at position 341 and Histidine at position 75, may provide complexities in the binding process due to potential π-π stacking or hydrogen bonding interactions. The ligand 3f engages in direct binding interactions with multiple amino acid residues, specifically Arginine, Serine, and Leucine, at positions 499, 106, 516, and 338 respectively. Indirect interactions are observed between amino acids positioned at 504, 502, 509, 335, 517, and 102, along with Glutamine (Gln) at position 178. The interaction score of -7.2866 Cal/mol suggests a robust and advantageous binding affinity, with the negative value reflecting stability. The presence of polar and nonpolar amino acids indicates the participation of different chemical forces, such as hydrogen bonding and hydrophobic interactions. Positions 338, 504, and 178 are identified as crucial for the stabilization of the ligand-protein complex. The ligand 3g directly interacts with amino acids at positions 509, 516, and 106, and indirectly interacts with additional amino acids such as Methionine (Met), Alanine (Ala), Phenylalanine (Phe), Tryptophan (Trp), Leucine (Leu), and Valine (Val). The energy score of -6.9765 Cal/mol suggests a strong and advantageous binding affinity, with the negative number indicating stability. Amino acids at positions 106 and 338 exert a substantial impact on the binding strength, with the presence of aromatic residues suggesting the occurrence of hydrophobic and π-π stacking interactions. The detailed interaction profile provides crucial insights into the chemical mechanisms governing the binding of ligands 3a, 3b, 3f, and 3g to the protein. This information serves as a foundation for further experimental validation and has the potential to guide the development of molecules with enhanced binding characteristics for medication development and molecular design techniques. Figure 2 and Fig. 3 depict the interactions of compounds (3a-3h) with the active pockets of 3LNI amino acid residues in 2D and 3D designs, respectively. Additionally, the interaction of Celecoxib (cognate ligand) with the active pocket of 3LNI amino acid residues is illustrated in both 2D and 3D formats in Fig. 4.

Figure 4

Interaction of Celecoxib (cognate ligand) with an active pocket of 3LNI amino acid residues in 2D and 3D illustration

We evaluated protein target interactions and ligand docking scores as displayed in Table 1. It provided the docking scores (Cal/mol) and contact types, including hydrogen bonds, π-alkyl, π-cation, C-H/π-sigma, and halogen interactions, for ligands and protein targets.

Table 1

The evaluated docking scores (Cal/mol) and contact types (hydrogen bonds, π-alkyl, π-cation, C-H/π-sigma, and halogen) for ligands and protein targets

Code	Hydrogen Bonds	$\varvec{\pi }$-alkyl	$\varvec{\pi }-\varvec{c}\varvec{a}\varvec{t}\varvec{i}\varvec{o}\varvec{n}$	$\varvec{C}-\varvec{H}/ \varvec{\pi }-\varvec{s}\varvec{i}\varvec{g}\varvec{m}\varvec{a}$	Halogen	Docking score Cal/mol
3a	Arg 106 Ser 516 Tyr 341 Leu 338	Val 509 Phe 504 Ala 502 Val 335 Ala 513 Leu 517	Arg 106	Glu 510 Tyr 341		-7.31191
3b	Ala 513 Arg 106 Tyr 341	His 75 Leu 35 Ala 513 Val 102 Leu 517	Arg 106	Val 509a		-6.7764
3c	Arg 106 Arg 106	Ala 502 Ala 513 Phe 504 Val 102 Leu 517 Tyr 341	Arg 106	Ser 339 Gln 178 Val 509		-6.8477
3d	His 106 Tyr 341	Val 102 Val 335 Val 509 Tyr 341 His 75 Ala 502			His 75	-6.4321
3e	Arg 499 Arg 106	Val 335 Val 509 Tyr 341 His 75 Phe 343 Leu 78 Leu 345 Leu 517	Arg 499 Glu 510 Arg 106		Ala 513 Val 102	-7.06335
3f	Arg 499 Arg 106 Ser 516 Leu 338	Phe 504 Ala 502 Val 509 Val 335 Leu 517 Val 102 Leu 338		Gln 178	Val 102	-7.2866
3g	Val 509 Ser 516 Arg 106	Met 508 Ala 513 Phe 504 Trp 373 Leu 370 Val 335 Leu 517 Leu 345 Val 102	Arg 106		Leu 338	-6.9765
3h	Gly 512 Ser 516	Leu 370 Phe 504 Phe 504 Val 509 Ala 513 Leu 345 Val 102		Tyr 341	Leu 338	-6.6180
Celecoxib	Arg 499 Leu 338 Ser 339	Ala 513 Val 335 Val 509 Tyr 371	Phe 504	Ser 516 Ser 339		-6.9453

3.2. Frontier molecular orbitals (FMOs)

Frontier molecular orbitals (FMOs) consist of the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO). The HOMO, encompassing the highest energy level occupied by electrons, signifies an entity with the capacity to donate electrons. In contrast, the LUMO, representing the lowest energy orbital capable of receiving electrons, characterizes a species prepared to accept electrons [32]. These orbitals play a crucial role in dictating how pharmaceuticals engage with other molecules, influencing interactions between these medications and their respective receptors. The frontier molecular orbitals (FMOs) of compounds (3a-3h) provide reliable qualitative insights into the electron transfer susceptibility from HOMO to LUMO, as depicted in Fig. 5. Furthermore, the HOMO and LUMO play a crucial role as quantum chemical parameters in assessing the reactivity of molecules. They are utilized in the computation of several significant characteristics, including chemical reactivity parameters. The HOMO and LUMO energies of the compounds under investigation were determined using Gaussian at PBE0-D3BJ approach with a def2-TZVP basis set. The calculated electronic properties of the compounds (3a-3h), such as E_HOMO, E_LUMO, and energy gap (∆E) between E_LUMO and E_HOMO values are displayed in Table 2.

Table 2

Calculated electronic properties of the compounds (**3a-3h**), such as E_HOMO, E_LUMO, and energy gap (∆E)
Compounds	E_HOMO (eV)	E_LUMO (eV)	∆E = E_LUMO - E_HOMO (eV)
3a	-7.12	-1.83	5.28
3b	-6.52	-1.92	4.59
3c	-6.63	-1.79	4.83
3d	-6.74	-1.82	4.92
3e	-7.76	-2.44	5.32
3f	-7.74	-2.30	5.44
3g	-7.28	-2.13	5.14
3h	-7.21	-2.17	5.04

HOMO and LUMO are influential in determining various molecular properties, including optical and electrical properties, chemical reactivity and stability, biological activity arising from intermolecular charge transfer, chemical hardness, and chemical softness. HOMO energy refers to the molecule's capacity to donate electrons, while LUMO energy refers to the molecule's capacity to accept electrons. The energy difference between HOMO and LUMO provides insights into the molecule's stability [33]. A substantial energy gap between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO) signifies diminished reactivity, indicating the stability of the molecule [34].

3.3. Molecular electrostatic potential evaluation

The MEP graph of a molecule depicts how the positive point charge interacts with the charges scattered among its atoms. Although the areas highlighted in red on both maps represent the region vulnerable to chemical reactions, where the electron density is larger than the nucleus throughout the entire molecule, it signifies the negative region of the electrostatic potential. The partial positive charge and unstable reaction zones are indicated by the blue areas on the potential surface. Yellow color indicates lesser electron density, whereas green color denotes nearly neutral areas [35]. The MEP map of 3a-3h compounds showed that the perimeter of the carbon and hydrogen atoms seemed more positively charged, but the red zones were primarily concentrated on the oxygen atoms, which are more negatively charged.

Molecular Electrostatic Potential (MEP) is employed to predict the locations of nucleophilic and electrophilic attacking sites within a molecule, providing insights into their relative reactivity. The MEP analysis was conducted on the optimized structures of all compounds. The molecular electrostatic potential (MEP) can be a useful method for verifying data, indicating that these compounds interact as inhibitors. MEP uses color categorization to define a molecule’s size, shape, positive, negative, and neutral areas. Red, orange, yellow, green, and blue are the colors in ascending order of potential [36]. By following the ring arrangement, it is quite simple to locate places that are suitable for nucleophile and electrophile attack. In contrast to the red color representing regions of low electrostatic potential, indicating an abundance of electrons, the blue color denotes regions of extreme electrostatic potential. This designation signifies the non-existence of electrons in this region, making it a preferred site for nucleophilic attack [37]. The oxygen atoms of the nitro group (red coded area) in each system are assigned regions of minimal potential following the MEP analysis, as illustrated in Fig. 6.

3.4. Conceptual DFT reactivity parameters

The reactivity parameters of the molecules are calculated from the total energies and the Koopmans’ theorem. The ionization potential i.e., ${IP}_{TE}$ and ${IP}_{KE}$ are determined from the energy difference between the energy of the compound derived from electron transfer (radical caution) and the respective neutral compound and negative of E_HOMO respectively, as provided by Eqs. (1) and (2)

${IP}_{TE}={E}_{cation}-{E}_{n}$	(1)
${IP}_{KE}=-{E}_{HOMO}$	(2)

The electron affinity i.e., ${EA}_{TE}$ and ${EA}_{KE}$ are computed from the energy difference between the neutral molecule and the anion molecule and negative of LUMO energy, as given in Eqs. (3) and (4) respectively [38].

$${EA}_{TE}={E}_{n}-{E}_{anion}$$

3

$${EA}_{KE}=-{E}_{LUMO}$$

4

The other important quantities such as chemical potential (µ), hardness (ƞ), and electrophilicity index (ω) were calculated from the following Eq. (5)(6)(7) [39].

${\eta } = (\text{I}–\text{A})/2$	(5)
${\mu } = - (\text{I}+\text{A})/2$	(6)
${\omega } = {\mu }2/2{\eta }$	(7)

The Table 3 presents the values of reactivity parameters i.e., IP (ionization potential), EA (electron affinity), ƞ (chemical hardness), µ (chemical potential), and ω (electrophilicity) in eV of the selected compounds (3a-3h).

Table 3

The table presents the calculated chemical parameters of the selected compounds (**3a-3h**)
Compounds	IP (eV)	EA (eV)	ƞ (eV)	µ (eV)	ω (eV)
3a	7.12	1.83	2.64	-4.47	3.79
3b	6.52	1.92	2.29	-4.22	3.88
3c	6.63	1.79	2.41	-4.21	3.67
3d	6.74	1.82	2.46	-4.28	3.72
3e	7.76	2.44	2.66	-5.10	4.89
3f	7.74	2.30	2.72	-5.02	4.63
3g	7.28	2.13	2.57	-4.70	4.30
3h	7.21	2.17	2.52	-4.69	4.36

A detailed analysis was conducted to examine the electronic characteristics of a set of 4-difluoromethyl pyrazole derivatives (3a-3h), which revealed clear distinctions in energy-related metrics. The compounds displayed a range of ionization potentials (IP) from 6.52 eV to 7.76 eV, indicating their tendency to donate electrons [40]. Additionally, the electron affinities (EA) exhibited a range from 1.79 eV to 2.44 eV, providing valuable insights into the compounds' ability to accept electrons. The variations in the HOMO-LUMO energy gaps (ƞ) within the range of 2.29 eV to 2.72 eV indicated electronic stability and reactivity among the compounds. Moreover, the dipole moments (µ) ranged from − 4.47 eV to -5.10 eV, implying the polarity of the compounds and their potential for interactions with other molecules [41]. Finally, the electronegativities (ω) ranged from 3.67 eV to 4.89 eV, indicating the compounds' varying capacities to attract electrons [42]. The detailed electronic characterizations significantly contribute to our understanding of the distinct attributes of each derivative. This enhanced knowledge not only facilitates further exploration of their potential biological activities but also plays a crucial role in strategically developing new compounds tailored for specific medicinal purposes.

In this study, we combined molecular docking simulations with DFT studies to thoroughly investigate the binding interactions displayed by a wide range of 4-difluoromethyl pyrazole derivatives. We aimed to analyze the complex structural features and molecular interactions that explain the strong binding affinity of these derivatives in the receptor's binding region. Our goal was to decode the precise characteristics and interactions that contribute to their ability to bond. The results provided an understanding of the structural and molecular complexities of 4-difluoromethyl pyrazole derivatives, revealing information about their possible biological characteristics. Notably, ligand 3f showed a robust and favorable binding affinity for the target protein, evidenced by a computed interaction score of -7.2866 Cal/mol. Negative interaction scores indicate thermodynamic favorability and binding strength, indicative of stable complex formation. The complex interaction profile revealed interactions involving both polar and nonpolar amino acids, suggesting the presence of hydrogen bonding and hydrophobic interactions. The findings provide a foundational understanding of how these compounds bind, offering insights for improving them in specific medical applications. The study's roadmap for future research contributes to our knowledge, creating opportunities for further exploration and application of the healing properties in 4-difluoromethyl pyrazole derivatives. Beyond this study, it establishes a base for ongoing progress in pharmaceutical research and the development of therapeutic drugs. Consequently, this study guides the effective use of the therapeutic potential inherent in 4-difluoromethyl pyrazole derivatives in the medical and pharmaceutical fields.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Author Contributions

The project was a collaborative effort led by M. T. N. K., with R. H. conceptualizing and A. M. visualizing the data. M. D. S. H. conducted a formal analysis and reviewed the content, while M. I. curated the data. A. A. contributed to formal analysis, M. F. N. to methodology, E. H. to resources and software, and K. A. to validation. All authors reviewed the manuscript.

Data Availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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No competing interests reported.

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Graphical Abstract

Molecular docking and DFT study of 4-difluoromethyl pyrazole derivatives as cyclooxygenase-2 inhibitor

Status:

Version 1

Abstract

Figures

1. Introduction

2. Methodology

3. Result and discussion

3.1. Molecular docking studies

3.2. Frontier molecular orbitals (FMOs)

3.3. Molecular electrostatic potential evaluation

3.4. Conceptual DFT reactivity parameters

4. Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1

\({\eta } = (\text{I}–\text{A})/2\)	(5)
\({\mu } = - (\text{I}+\text{A})/2\)	(6)
\({\omega } = {\mu }2/2{\eta }\)	(7)