Synthesis of Some Oxime Derivatives as Novel Elastase Inhibitors: Molecular Dynamics Studies and Computational Insight

ABSTRACT

Oximes and oxime ethers are important compounds in organic chemistry, both structurally and in terms of applications. The biological properties of oximes are directly related to the chemical properties of their functional groups, metal‐binding capacities, and ability to interact with biological targets in a multifaceted way. This study presents the synthesis of 5‐hydroxyimino 2a‐b and 5‐methoxyimino 2c derivatives from 5‐oxo pentanoic acid methyl esters (1a‐c) containing phenyl, p‐chlorophenyl, and thiophenyl groups, elucidation of their structures through various spectroscopic analysis methods (IR, ¹H NMR, ¹³C NMR, MS, and elemental analysis), and investigation of their elastase inhibition activities. In the elastase inhibition results, compounds were found to exhibit antielastase activity. Compound 2a, containing the p‐chlorophenyl substituent, had the highest antielastase activity (IC₅₀ = 426.68 ± 46.90 µM) and was found to have a lower IC₅₀ value compared to the positive control, ursolic acid (486.19 ± 44.22 µM). Furthermore, molecular docking was used to predict binding affinities and found to be −5.8 kcal/mol for compound 2a and −6.8 kcal/mol for ursolic acid. Molecular dynamics simulations were conducted to evaluate the stability of protein–ligand interactions. These results suggest that compound 2a could be a potential elastase inhibitor candidate and scaffold for pharmaceutical or cosmetic applications.

Oxime‐based ester derivatives are investigated as potential elastase inhibitors. Compound 2a emerges as the most active analogue (IC₅₀ = 426.68 µM). Computational studies, including molecular docking and molecular dynamics simulations, reveal favorable enzyme–ligand interactions and complex stability, highlighting its potential as a promising elastase‐targeting scaffold.

1. Introduction

Oximes, known as weak organic acids, are essential compounds with versatile applications in both organic and inorganic chemistry [1]. In recent years, numerous studies have been reported showing that oxime and its derivatives have important bioactivities, such as antiprotozoan [2, 3], antimicrobial [4, 5], insecticidal [6, 7], herbicidal [8, 9], antitumor [10, 11, 12], and antioxidant activities [13] in the agricultural, cosmetic, and medical fields. The most important feature of oximes is their ability to form complexes with metals, which makes them suitable for the role of potential therapeutic agents as inhibitors of metalloenzymes [14, 15]. Additionally, some oxime derivatives have been found to have potential cholinesterase and elastase inhibitors [16, 17]. In the previous study of our working group, it was determined that oxime and oxime ether derivatives obtained from γ‐oxo esters with aryl, substituted aryl, and heteroaryl groups exhibited quite good elastase inhibitory activity [18]. In another study, DNA binding abilities and in vitro antibacterial and antifungal activities of a series of synthesized oxime derivatives were investigated [19].

Enzymes and enzyme inhibitors are used in medicine, the food industry, pesticides, the cosmetic industry, and the agriculture industry [20]. Elastases are a subgroup of serine proteases known for their ability to degrade elastin, a key component of the extracellular matrix and connective tissues. Serine proteases represent the largest family of proteolytic enzymes and are critical to numerous physiological processes, including digestion, immune response, blood coagulation, and tissue remodeling [21]. Among these, human neutrophil elastase (HNE) is a well‐studied member with significant roles in host defense due to its antimicrobial properties. HNE is predominantly secreted by activated neutrophils during inflammatory responses, where it contributes to the destruction of pathogens. However, dysregulation or excessive activity of HNE has been implicated in the pathogenesis of several chronic inflammatory and autoimmune diseases, such as inflammatory bowel disease (IBD), chronic obstructive pulmonary disease (COPD), rheumatoid arthritis (RA), cystic fibrosis, acute respiratory distress syndrome, acute lung injury, ischemia, and reperfusion injury. Moreover, recent studies have highlighted its emerging relevance in oncology, where HNE has been associated with tumor progression, immune evasion, and metastasis, making it a potential target for cancer therapy [22].

In light of all these observations and considering the continuous demand for structurally diverse and biocompatible scaffolds in cosmetic and pharmaceutical chemistry, we identified a clear gap in the literature regarding long‐chainδ‐oxime derivatives. We focused on the synthesis of novel phenyl, p‐chlorophenyl, and thiophenyl‐substituted δ‐hydroxy and δ‐methoxyiminopentanoic acid methyl ester derivatives with the aim of discovering new elastase inhibitors. The fundamental novelty of this work lies in the strategic incorporation of varied electronic features—ranging from electron‐withdrawing chlorine groups to electron‐rich heteroaryl (thiophenyl) rings—directly onto a flexible δ‐oxime core to systematically map their structure–activity relationships against elastase. In the literature, there is no data on the elastase inhibition of these specific compounds. All synthesized compounds were characterized by IR, NMR (¹H, ¹³C), MS, and elemental analysis methods. To bridge the gap between bench chemistry and mechanistic insight, comprehensive molecular docking and molecular dynamics (MD) studies were also performed to elucidate the precise binding modes and stability within the enzyme's active site.

2. Results and Discussion

2.1. Synthesis and Characterization

As illustrated in Scheme 1, oximes 2a–b and methoxyoxime ether 2c were synthesized in high yields from their corresponding δ‐oxo methylesters. The δ‐hydroxyimino methyl esters 2a–b were synthesized and characterized in our previous study [23]. O‐methoxyimino methyl ester (2c) was synthesized as an intermediate in another study, but spectral data of the compound are presented for the first time in this study [18].

SCHEME 1.

Synthesis of δ‐hydroxy and δ‐O‐methyl imino esters 2a‐c. Reaction conditions: (I) δ‐oxo methylester (1.0 eq), NH₂OH.HCl (2.0 eq), in EtOH, stirred at r.t., overnight. (II) δ‐oxo methylester (1.0 eq), methoxyamine hydrochloride (1.1 eq), in pyridine, stirred at r.t., 6 h.The structures of the synthesized oxime compounds 2a‐c were elucidated using spectroscopic analysis methods, including IR, ¹H NMR, ^{1 3}C NMR, and MS, as well as C, H analysis. Based on the previous studies of our group [18, 19, 23], the (E/Z)‐isomerization of the obtained oxime derivatives was analyzed by examining the ¹H NMR spectrum, and it was determined that the compounds were isolated in the E‐configuration.

2.2. Elastase Inhibitory Activity

Elastase inhibitory activity of 5‐(4‐Chlorophenyl)‐5‐hydroxyimino‐pentanoic acid methyl ester 2a, 5‐Hydroxyimino‐5‐thiophen‐2‐yl‐pentanoic acid methyl ester 2b, and 5‐methoxyimino‐5‐phenyl‐pentanoic acid methyl ester 2c was given in Table 1. According to the literature survey, the elastase inhibition ability of the compounds in question has not been previously investigated. In the elastase inhibition study, it was found that the enzyme inhibitory activities of these compounds increased in a dose‐dependent manner. Lower IC₅₀ values indicate higher enzyme inhibitory activities. The elastase inhibitory activity of the compounds and the standard decreased in the order 2a > ursolic acid > 2c > 2b. The highest antielastase activity was observed for 2a (IC₅₀ = 426.68 ± 46.90 µM) (Table 1).

TABLE 1.

Elastase inhibition values of synthesized novel oximes and oxime ether 2a‐c.

Entry	Compounds	Concentration (µM)	IC50 (µM) a
1	2a	10 100 500	426.68 ± 46.90
2	2b	250 1000 2000	1951.71 ± 109.65
3	2c	0.1 100 250	513.06 ± 25.79
4	Ursolic acid	1 10 250	486.19 ± 44.22

^a Mean ± SD.

In this study, hydroxyimino compounds containing p‐chlorophenyl and thiophenyl rings, and phenyl‐substituted methoxyimino compounds were synthesized to investigate the effects of substituents on elastase inhibition. The chlorine group is an electron‐withdrawing substituent. The chlorophenyl group showed better inhibition than the phenyl and thiophenyl groups. Electron‐withdrawing groups such as chloro (+M, −I) on phenyl increased the inhibition. The highest elastase inhibition activity was observed in compound 2a of hydroxyimino ester (IC₅₀ = 426.68 µM). Compound 2a is the best inhibitory agent when compared to standard ursolic acid and a novel and original elastase inhibitor obtained in this study. Although ursolic acid has an ester and a free hydroxyl group like 2a, it shows less inhibitory effect than 2a because it does not contain a chlorine substituent. The other two compounds synthesized in our study show less inhibitory effect than the oxime compound with a chlorophenyl group. The methoxyimino ester compound exhibited similar anti‐elastase activity to ursolic acid. Compounds 2a–b possess a free hydroxy‐oxime group that acts as a strong hydrogen bond donor. Compound 2c, however, contains a methylated oxime ether group; this group eliminates the donor property and confers steric bulk. Interestingly, compound 2c performed significantly better than 2b, suggesting that oxime tail modification may play a critical role in the inhibitory effect. Furthermore, the p‐chlorophenyl ring in compound 2a exhibits an inductive electron‐withdrawing effect, enhancing the electrophilicity of the nucleus and promoting compatibility with nucleophilic residues such as Ser195. This suggests that the active state is responsible for the in vitro results obtained between compounds 2a and 2c.

There is substantial evidence in the scientific literature indicating that oxime‐derived compounds exhibit elastase inhibitory activity. In a study conducted by Hwang et al., 23 2‐aminobenzaldehyde oxime analogs were reported to display elastase inhibitory activity. Furthermore, structure–activity relationship (SAR) analyses demonstrated that the hydroxy oxime group is a favorable functional moiety for elastase inhibition, and that hydrogen‐bonding interactions play a significant role in ligand–enzyme affinity [17]. Similarly, psammaplin A and bisaprasin, oxime‐containing compounds isolated from marine sponges, have also been reported to exhibit elastase inhibitory activity [24]. These studies suggest that the oxime group plays a crucial role in the mechanism of elastase inhibition and provide scientific support for the contribution of this functional group to the activity observed in the present study.

2.3. Molecular Docking

As a result of the docking studies, the results obtained for 2a‐c were in parallel with in vitro studies, and the docking scores were −5.8, −4.4, and −5.0 kcal/mol, respectively (Table 2). Also, the RMSD value between the co‐crystallized ligand and the redocked 0Z2 ligand in the target protein structure was determined to be 0.938 Å. UA, used as a positive control, showed higher binding relevance than all other compounds. It should be noted that there is a slight discrepancy between the initial molecular docking scores of the compounds and the experimental IC₅₀ values. Although compound 2a showed the highest efficacy in in vitro elastase inhibition, its static docking score did not linearly outperform the other derivatives. This lack of perfect correlation reveals the well‐known inherent limitations of standard molecular docking protocols. This may stem from treating the protein receptor as a rigid or semi‐rigid structure and thus neglecting the induced conformational adjustments that the elastase enzyme undergoes in response to ligand binding. To overcome these limitations and decipher the actual binding behavior, molecular dynamics (MD) simulations were performed.

TABLE 2.

IC₅₀ and docking scores of the ligands and standards.

Compounds	IC50 (µM)	Docking scores (kcal/mol)
2a	426.68 ± 46.90	−5.8
2b	1951.71 ± 109.65	−4.4
2c	513.06 ± 25.79	−5.0
Ursolic acid	486.19 ± 44.22	−6.8
N‐(trifluoroacetyl)‐L‐leucyl‐N‐[4‐(trifluoromethyl)phenyl]‐L‐alaninamide (0Z2)	—	−6.9

2.4. Molecular Dynamics Simulations

MD simulations were performed for 100 ns to analyze the interaction behavior between the target protein and ligands. Graphs were drawn for the RMSD, RMSF, and Rg results obtained after MD simulation. RMSD provides an understanding of how the structural stability between the target protein and the ligand changes over time. When the values obtained throughout the simulation were averaged, they were found to be 1.581 ± 0.205, 1.680 ± 0.150, 1.354 ± 0.126, and 1.591 ± 0.128 Å for 2b, 2a, 2c, and UA, respectively (Figure 1). The overall average results reveal that the most stable structures are 2c, 2b, UA, and 2a, respectively, but the fact that the values are close to each other, and especially after 40 ns, all ligands except 2b reach constant RMSD values with the protein, means that the structures are stable. The fluctuations for 2b reveal that the stability of the complex is lower compared to other complexes.

FIGURE 1.

The RMSD plots of the protein–ligand complexes.

RMSF is one of the MD simulation results that provides an understanding of the mobility of protein residues. While the decrease in RMSF values with ligand binding indicates that the protein stabilizes, increasing RMSF values indicate that the flexibility of the protein increases. When RMSF values were averaged from the simulation results, they were found to be 0.874 ± 0.542, 0.7301 ± 0.358, 0.708 ± 0.374, and 0.766 ± 0.363 Å for 2b, 2a, 2c, and UA, respectively (Figure 2A). In terms of overall structure stability, it is seen that the most stable structure is realized for 2c. However, evaluation of RMSF values for residues located in the active center of the enzyme may provide better information about structure stability. Ser195, His57, and Asp102 residues in the active center of the target protein play an active role in the reaction. Ser195 makes a nucleophilic attack on the carbonyl carbon of the substrate, His57 accepts the proton of Ser195, and Asp102 stabilizes the protonation state of His57 to carry out the reaction. It can be suggested that 2a, the molecule with the lowest IC₅₀ value in vitro studies, may have an inhibition effect due to the fact that this residue forms a more stable structure, especially since the RMSF value with Asp102 residue in the active center is very low and there is not a high difference between UA and other residues (Figure 2B). Asp102 appears to structurally preserve the enzyme's active site architecture. The dynamic stability of the complex indirectly stabilizes the catalytic network. This behavior is well supported by RMSF profiles and points to a highly stabilized local conformation during ligand docking.

FIGURE 2.

(A) The overall RMSF plots and (B) active center residues RMSF of the protein–ligand complexes.

Rg plots obtained from MD simulations provide an understanding of how protein–ligand compactness changes with time. The fact that Rg values remain constant throughout the simulation means that the protein structure is compact and stable. The Rg plots obtained from MD simulations for the target protein with 2b, 2a, 2c, and UA are presented in Figure 3. The Rg plots show that all ligand and protein complexes are compact and stable.

FIGURE 3.

The Rg plots of the protein–ligand complexes.

The 2D protein–ligand interactions and bond lengths were analyzed to understand the structure–activity relationship of the results obtained from molecular docking and MD simulations (Figure 4). It is observed that 2b, 2a, 2c ligands interact with His57 residue in the active center of the enzyme unlike UA. The fact that His57 acts as a proton carrier and the interactions of the ligands with this residue may mean that it may be effective in the inhibition mechanism. Especially for 2a and 2c (which have lower IC₅₀ values than 2b), the number of interactions with the His57 residue is higher. The lengths of the hydrophobic interactions between 2b, 2a, and 2c and the His57 residue were 4.47, 3.55/3.88/4.70, and 4.72/5.03 Å, respectively, with 2a being the closest. The interaction with His57 may have caused the stability change in Asp102 and caused 2a to have a better inhibition value. Another residue that interacts with UA and all other ligands is Val216. The interaction distances for 2b, 2a, 2c, and UA were 5.07, 3.61, 3.84, and 5.17 Å, respectively. This suggests that the Val216 residue plays an active role in the inhibition of the reaction at the enzyme active center. Because both the inhibitory effects of all compounds and the fact that the molecules with the lowest IC₅₀ values interacted closely with Val216 indicate the importance of its role in this inhibition effect.

FIGURE 4.

The 2D protein–ligand interactions of (A) 2a, (B) 2b, (C) 2c, and (D) UA with the target protein.

2.5. HOMO–LUMO and Molecular Electrostatic Potential (MEP) Maps of the Compounds

Calculations obtained from the 2a molecule resulted in HOMO (highest occupied molecular orbital) and LUMO (lowest unoccupied molecular orbital) energy values of −0.25849 and −0.05772 eV, respectively (Figure 5). The distribution of the HOMO orbital is seen to be concentrated predominantly in regions containing aromatic rings and heteroatoms. This indicates that these regions are electron‐rich and may behave as potential electron‐donating regions. In contrast, the distribution of the LUMO orbital is more concentrated on the different functional groups of the molecule, suggesting that these regions may be electrophilic centers more prone to accept electrons. MEP analysis was performed to determine the electrostatic potential distribution of the molecule. In the obtained MEP surface map, red regions represent high electron density and negative electrostatic potential, while blue regions indicate low electron density and positive electrostatic potential areas. Green regions represent neutral or moderate electrostatic potential. The analysis revealed distinct red regions around the functional groups containing carbonyl and heteroatoms, particularly oxygen atoms. This indicates that these regions have high electron density and may serve as suitable nucleophilic centers for potential electrophilic attacks. In contrast, blue‐toned areas were observed in regions adjacent to some hydrogen atoms and heterocyclic structures of the molecule. These regions can be considered electrophilic centers that could interact with nucleophilic agents due to their low electron density.

FIGURE 5.

(A) HOMO (highest occupied molecular orbital)—(B) LUMO (lowest unoccupied molecular orbital) and (C) Molecular electrostatic potential (MEP) surface analysis for compound 2a.

The overlap between the π‐based interactions observed in the docking results and the regions identified as electron‐rich in the MEP analysis, which contain aromatic and heteroatoms, indicates that the ligand's electrostatic properties directly influence the binding mode. In particular, the interaction of regions with high negative electrostatic potential with aromatic amino acid residues contributes to the stabilization of the ligand in the binding pocket. Furthermore, the formation of hydrophobic interactions between the hydrocarbon chain portion of the molecule and Val216 indicates that the ligand is appropriately positioned in the binding pocket. In conclusion, there is a strong correlation between the electrostatic potential distribution determined in the MEP analysis and the protein–ligand interactions observed in the docking analysis.

Results regarding quantum chemical parameters were calculated to understand the chemical selectivity and reactivity of the identified compounds. The calculated electronegativity (χ), spherical hardness (η), chemical potential (μ), spherical softness (σ), electrophilic index (ω), and maximum electronic charge transfer (ΔNmax) values ​​for compound 2a in Table 3.

TABLE 3.

Quantum chemical parameters of the compound 2a.

Quantum chemical parameters
Χ	0.158
Η	0.100
μ	−0.158
Σ	10.000
Ω	0.125
ΔNmax	1.580

The calculated quantum chemical descriptors indicate a chemically reactive molecular framework. The low chemical hardness (η = 0.100) together with the high global softness (σ = 10.000) suggest that the molecule can readily undergo electronic polarization upon interaction with biological targets. In the framework of conceptual DFT, such characteristics are generally associated with enhanced chemical reactivity and charge‐transfer capability. Furthermore, the electrophilicity index (ω = 0.125) and maximum electronic charge acceptance (ΔNmax = 1.580) indicate a moderate tendency to accept electron density and participate in intermolecular electronic interactions. These electronic properties may contribute to the favorable protein–ligand interactions observed in the docking study, particularly considering the presence of the oxime moiety, which can facilitate hydrogen‐bonding and charge‐transfer interactions within the elastase active site.

Conceptually, the combination of low chemical hardness (η = 0.100) and very high overall softness (σ = 10 000) indicates that the molecule possesses an extremely flexible, polarizable, and reactive electron cloud. This soft electronic structure minimizes the kinetic energy barrier required for structural adaptation when entering the restrictive enzyme environment. Experimentally, compound 2a exhibited the strongest elastase inhibiton, outperforming both other derivatives and standard ursolic acid. This superior biological activity is in excellent agreement with the overall electrophilic index (ω = 0.125) and high maximum charge transfer capacity (ΔN_max = 1.580).

2.6. Cytotoxicity Prediction of the Compounds to Tumor Cell Lines

Developing databases and computer technologies contributes to our understanding and prediction of possible biological activities of chemical compounds. One of these is cancer predictions. Predictions obtained for the types of cancer that the synthesized compounds may affect are presented in Table 4. While the Pa value obtained from the prediction results indicates the possibility of being active, Pi indicates the prediction of not being active. Pa>Pi means that it may be more effective for that type of cancer. For the synthesized compounds, the results with Pa>0.3 were taken into consideration. The obtained results reveal that compound 2a may be related to more types of cancer than other compounds.

TABLE 4.

The cytotoxicity prediction to tumor cell lines of the synthesized compounds.

Compounds	Pa	Pi	Cell‐line	Cell‐line name	Tissue/organ
2a	0.517	0.017	UO‐31	Renal carcinoma	Kidney
	0.339	0.062	CAKI‐1	Kidney carcinoma	Kidney
	0.368	0.103	NCI‐H187	Small cell lung carcinoma	Lung
	0.34	0.078	UACC‐257	Melanoma	Skin
	0.309	0.048	EKVX	Non‐small cell lung carcinoma	Lung
	0.326	0.07	NCI‐H226	Non‐small cell lung carcinoma	Lung
	0.394	0.138	NCI‐H838	Non‐small cell lung cancer. 3 stage	Lung
	0.328	0.083	NCI‐H322M	Non‐small cell lung carcinoma	Lung
	0.312	0.095	NCI‐H23	Non‐small cell lung carcinoma	Lung
	0.301	0.101	OVCAR‐5	Ovarian adenocarcinoma	Ovarium
	0.346	0.166	Hs 683	Oligodendroglioma	Brain

	Pa	Pi	Cell‐line	Cell‐line name	Tissue/organ
2b	0.374	0.096	MCF7	Breast carcinoma	Breast
	0.399	0.133	NCI‐H838	Non‐small cell lung cancer. 3 stage	Lung
	0.307	0.069	UO‐31	Renal carcinoma	Kidney
	0.326	0.09	UACC‐257	Melanoma	Skin
	0.301	0.068	5637	Urothelial bladder carcinoma	Urinary tract
	0.326	0.165	NCI‐H187	Small cell lung carcinoma	Lung
	0.343	0.193	YAPC	Pancreatic carcinoma	Pancreas

	Pa	Pi	Cell‐line	Cell‐line name	Tissue/organ
2c	0.559	0.013	SF‐268	Glioblastoma	Brain
	0.5	0.05	NCI‐H838	Non‐small cell lung cancer. 3 stage	Lung
	0.34	0.204	SK‐MEL‐1	Metastatic melanoma	Skin

2.7. ADME Prediction of the Compounds

The detailed ADME prediction results for compounds 2a, 2b, and 2c are presented in Table 5. All three compounds comply with established drug‐likeness criteria, indicating that their molecular weight, lipophilicity (LogP), hydrogen bond donor/acceptor counts, and polar surface area fall within the acceptable range for oral bioavailability. High gastrointestinal absorption was predicted for all compounds, suggesting that the synthesized oxime derivatives may serve as potential candidates for oral administration. In addition, compounds 2a and 2c were predicted to be capable of crossing the blood–brain barrier (BBB). Considering the involvement of elastase in neuroinflammatory processes, this property may provide a potential advantage. Compound 2a was predicted to exhibit inhibitory activity against CYP1A2 and CYP2C19 enzymes, indicating a possible risk of drug–drug interactions that should be carefully evaluated in further studies. In contrast, the more limited interaction of compound 2c with CYP enzymes suggests a more favorable pharmacokinetic profile.

TABLE 5.

ADMET prediction of the compounds 2a, 2b, and 2c.

	2a	2b	2c
Druglikeness
Lipinski	Yes	Yes	Yes
Ghose	Yes	Yes	Yes
Veber	Yes	Yes	Yes
Egan	Yes	Yes	Yes
Muegge	Yes	Yes	Yes
Bioavailability Score	0.55	0.55	0.55
Pharmacokinetics
GI absorption	High	High	High
BBB permeant	Yes	No	Yes
P‐gp substrate	No	No	No
CYP1A2 inhibitor	Yes	Yes	Yes
CYP2C19 inhibitor	Yes	No	Yes
CYP2C9 inhibitor	No	No	No
CYP2D6 inhibitor	No	No	No
CYP3A4 inhibitor	No	No	No
Log K p (skin permeation)	−6.01 cm/s	−6.27 cm/s	−6.10 cm/s
Water solubility
Log S (ESOL)	−2.93 (Soluble)	−2.35 (Soluble)	−2.55 (Soluble)
Log S (Ali)	−3.50 (Soluble)	−3.45 (Soluble)	−2.94 (Soluble)
Log S (SILICOS‐IT)	−3.83 (Soluble)	−2.48 (Soluble)	−3.92 (Soluble)
Medicinal chemistry
PAINS	0 alert	0 alert	0 alert
Brenk	3 alerts	3 alerts	2 alerts
Leadlikeness	Yes	No	No
Synthetic accessibility	2.27	2.64	2.47

No PAINS alerts (0 alerts) were identified for any of the compounds, indicating a low likelihood of false‐positive biological activity. From a pharmacokinetic perspective, Compounds 2a and 2c demonstrated the highest elastase inhibitory activity. Nevertheless, the potential inhibition of CYP1A2 and CYP2C19 by compounds 2a and 2c warrants further investigation regarding possible drug–drug interactions. Overall, compound 2a can be considered a promising candidate for further optimization studies, as it satisfies drug‐likeness criteria while exhibiting the most potent biological activity among the tested compounds.

The obtained results indicate that compound 2a exhibited superior performance compared to the other compounds in both in vitro and in silico studies. This difference appears to be associated with variations in the chemical structures of the compounds. In particular, unlike compound 2c, compound 2a contains a chlorine substituent, which may have influenced the in vitro results by altering the types of interactions with amino acid residues within the binding site. According to the 2D protein–ligand interaction analyses obtained from docking studies, compounds 2a, 2b, and 2c, unlike UA, interact with His57. Considering that histidine functions as a proton carrier, this interaction may play a critical role in the inhibition mechanism. Furthermore, the types and interaction distances of the contacts between all compounds and UA with Val216 may also contribute to the observed differences in biological activity. Therefore, these findings may not only be relevant to the compounds evaluated within the scope of this study, but may also contribute to the assessment of key active‐site residues in the design of future inhibitors.

3. Conclusions

In the present study, the synthesis of the corresponding oxime derivatives 2a‐c from phenyl, p‐chlorophenyl and thiophenyl substituted 5‐oxo pentanoic acid methyl esters 1a‐c, the elucidation of their structures using various spectroscopic analysis methods (IR, ¹H NMR, ¹³C NMR, MS and elemental analysis) and the investigation of their elastase inhibition activities were presented. Compound 2a was found to have the highest elastase inhibition effect (IC₅₀ = 426.68 µM). Molecular docking and molecular dynamics (MD) simulations were performed to analyze protein–ligand interactions and predict binding affinities. However, it must be emphasized that while computational approaches like molecular docking and MD simulations provide essential insights into the potential binding modes and structural stability of the complexes, they do not substitute for experimental enzyme kinetics. The lack of experimental kinetic validation and inhibition mechanism analysis represents a limitation of the present study, which we aim to address in future investigations alongside the expansion of the compound library. As a result of these studies, the results obtained for 2a‐c were parallel to those of in vitro studies. It was determined that compound 2a, which had the lowest IC₅₀ value in vitro studies, formed a more stable structure. Therefore, it can be suggested that the compound has an inhibitory effect. Based on these results, the oxime derivatives 2a‐c synthesized, especially 2a, in this study can be considered a scaffold in elastase inhibitor design and potential resource for the pharmaceutical and cosmetic industries due to their elastase inhibition activities.

4. Experimental Section

All reagents used in this study were commercially available from commercial suppliers. δ‐oxo methyl esters as starting materials were synthesized by Friedel–Crafts acylation [23]. The reaction products were purified by column chromatography on silica gel (mesh 0.063–0.200 mm) using a hexane‐ethyl acetate mixture [1]. H NMR and ¹³C NMR spectra were recorded at 500 and 150 MHz, respectively. CDCl₃ was used as a solvent, and Me₄Si was used as the internal standard. GC‐MS spectra were recorded on a Shimadzu QP2010 Plus. IR spectra were recorded on a Bruker Vertex 70. Melting points were determined with a Buchi melting point apparatus B‐540. p‐Chloro phenyl‐ and thiophenyl‐δ‐hydroxyimino pentanoic acid methyl esters 2a‐b were synthesized in our previous study, and their structures were elucidated by spectroscopic and chromatographic methods [25].

4.1. General Procedure for the Synthesis of O‐methoxyiminopentanoic Acid Methyl Ester 2c [18, 19]

To a solution of δ‐oxo ester (1.0 eq.) 1c in pyridine was added a solution of methoxyamine hydrochloride (1.1 eq.) in pyridine at room temperature. The resulting solution was stirred for 6 h. After the consumption of the starting material, the reaction mixture was diluted with water and then extracted with ethyl acetate. The organic phase was combined, dried over anhydrous Na₂SO_4, and concentrated under reduced pressure. The residue was purified by column chromatography on silica gel (n‐hexane/ethyl acetate = 7:3).

4.1.1. 5‐(4‐Chlorophenyl)‐5‐hydroxyimino‐pentanoic Acid Methyl Ester 2a

Yield: 80%. ¹H NMR (500 MHz, CDCl₃) δ 7.49 (d, J = 5.0 Hz, 2H), 7.27 (d, J = 10.0 Hz, 2H), 3.59 (s, 3H, COOCH₃), 2.76 (t, J = 7.5 Hz, 2H), 2.32 (t, J = 7.5 Hz, 2H), 1.81 (q, J = 7.5 Hz, 2H). ¹³C NMR (150 MHz, CDCl₃) δ 173.9, 158.1, 135.5, 134.0, 129.0, 127.7, 51.8, 33.7, 25.4, 21.6. Anal. Calcd. for C₁₂H₁₄ClNO₃ C, 56.37; H, 5.52; Cl, 13.86; N, 5.48. Found: C, 56.20; H, 5.55; Cl, 13.80; N, 5.52. MS (m/z): 55, 75, 88, 102, 138, 164, 192, 224, 256(M⁺).

4.1.2. 5‐Hydroxyimino‐5‐thiophen‐2‐yl‐pentanoic Acid Methyl Ester 2b

Yield: 65%. ¹H NMR (500 MHz, CDCl₃) δ 7.50–7.47 (m, 2H), 7.03 (t, J = 5.0 Hz, 1H), 3.59 (s, 3H, COOCH₃), 2.72 (t, J = 7.5 Hz, 2H), 2.37 (t, J = 7.5 Hz, 2H), 1.97 (q, J = 7.5 Hz, 2H). ¹³C NMR (150 MHz, CDCl₃) δ 172.1, 152.7, 137.8, 129.9, 126.3, 124.6, 50.8, 29.5, 21.6. Anal. Calcd. for C₁₀H₁₃NO₃S C, 52.85; H, 5.77; N, 6.16; S,14.11. Found: C, 52.95; H, 5.55; N, 6.20; S, 14.20. MS (m/z): 55, 84, 97, 110, 123, 136, 150, 178, 210, 227(M⁺).

4.1.3. 5‐Methoxyimino‐5‐phenyl‐pentanoic Acid Methyl Ester 2c

Yield: 90%. ¹H NMR (500 MHz, CDCl₃) δ 7.57–7.55 (m, 2H), 7.30–7.25 (m, 3H), 3.88 (s, 3H, NOCH₃), 3.57 (s, 3H, COOCH₃), 2.71 (t, J = 7.5 Hz, 2H), 2.27 (t, J = 7.5 Hz, 2H), 1.78 (q, J = 8.5 Hz, 2H).¹³C NMR (150 MHz, CDCl₃) δ 173.7 (C═O), 157.7 (C═N), 135.6, 129.3, 128.7, 126.4, 62.0 (═N‒OCH₃), 51.7 (COOCH₃), 33.7 (CH₂), 25.8 (CH₂), 21.9 (CH₂). Anal. Calcd. for C₁₃H₁₇NO₃ C, 66.36; H, 7.28; N, 5.95. Found: C, 66.42; H, 7.37; N, 5.90. MS (m/z) = 31, 55, 74, 92, 148, 178, 207, 221, 235 (M⁺).

4.2. Elastase Inhibitory Activities

Elastase activity was examined by using N‐succinyl‐Ala‐Ala‐Ala‐p‐anilide (STANA) as a substrate and by measuring the release of p‐nitroanilide at 410 nm [26]. Ursolic acid (UA)was used as a standard compound. The percent inhibition of elastase was calculated as follows:

$$\mathrm{Inhi}\mathrm{biti}\mathrm{on}\left(\%\right)=\frac{A-B}{A}\times 100$$

where A represents the activity of the enzyme without the sample, and B is the elastase activity in the presence of the sample. Ursolic acid was used as a standard compound. The results are given as half maximal inhibitory concentrations (IC₅₀) values, calculated from the regression equations prepared from the concentrations of samples. All experiments were performed in at least triplicate, and the obtained data were expressed as mean ± standard deviation (SD).

4.3. Molecular Docking

After the three‐dimensional structures of the synthesized compounds were drawn in the Avagadro program, energy minimizations were performed by the Universal Force Field (UFF) method [27]. N‐(trifluoroacetyl)‐L‐leucyl‐N‐[4‐(trifluoromethyl)phenyl]‐L‐alaninamide molecule (PubChem CID: 5496995, 0Z2), which is in the three‐dimensional structure of the elastase target protein, and ursolic acid (PubChem CID: 64945) used as a positive control in in vitro experiments, was downloaded from PubChem in sdf format. Energy minimizations were also performed with UFF for UA and 0Z2, and all ligands and standards were saved in mol2 format. The target protein, elastase (PDB ID: 7EST) [28], was downloaded from the Protein Data Bank in pdb format and molecules other than amino acids and water were deleted. Polar hydrogens were then added and saved in pdb format.

The AMDock program was used to understand the interactions between the target protein and ligands using the Autodock Vina algorithm [29, 30]. The grid coordinates for the target protein were set as x: 11.82, y: 49.93, z: −5.24, and the grid box was set to 25 × 25 × 25 Å³. The results are presented in kcal/mol. The 2D interaction of ligands and protein was monitored using DassaultSystèmes Discovery Studio, 2021. To validate the docking results, the ligand present in the target protein's structure was redocked, and the RMSD values of the binding positions obtained from the redocking were calculated. This process was performed using DockRMSD (https://zhanggroup.org/DockRMSD/) [31].

4.4. Molecular Dynamics Simulation

Protein–ligand complexes obtained from docking results were used to perform molecular dynamics (MD) simulations. AMBER was used to generate topology in MD simulations. Protein topologies were generated using the ff19SB force field, while ligand parameters were assigned using the GAFF2 force field. All systems were immersed in a 12 × 12 × 12 × 12 Å cubic box containing TIP3P water molecules, and Na⁺ ions were used to neutralize the solution (0.15 M). Each system was energy minimized to remove unfavorable contacts, followed by gradual heating from 0 to 300 K under the NVT ensemble. Subsequently, equilibration was performed under the NPT ensemble at 1 atm pressure and 300 K temperature. MD simulations were performed for 100 ns, and coordinates were recorded every 10 ps for subsequent analysis. At the end of the simulation, protein–ligand interactions were investigated by plotting RMSD, RMSF, and Rg plots [32, 33, 34].

4.5. HOMO–LUMO and Molecular Electrostatic Potential (MEP) Maps of the Compounds

Density functional theory (DFT) calculations were performed to investigate the electronic properties of the synthesized compounds. Full geometry optimizations were carried out using the Becke three‐parameter hybrid functional combined with the Lee–Yang–Parr correlation functional (B3LYP) [35] together with the 6–31G+(d,p) [36] basis set. All optimized structures were confirmed to be true minima on the potential energy surface by the absence of imaginary frequencies. Subsequently, HOMO (highest occupied molecular orbital)–LUMO (lowest unoccupied molecular orbital) and molecular electrostatic potential (MEP) maps were generated at the same level of theory (B3LYP/6‐31G+(d,p)) to analyze the charge distribution and identify potential electrophilic and nucleophilic regions. The HOMO–LUMO and MEP surfaces were mapped onto the electron density surface to visualize the electrostatic potential distribution across the molecular framework [37, 38]. All quantum chemical calculations were performed using the Gaussian software package, and the resulting molecular orbitals and electrostatic potential surfaces were visualized using GaussView 09.

Quantum chemical reactivity descriptors were used to predict molecular stability, reactivity patterns, and interaction tendencies. These parameters, derived from leading molecular orbital energies, χ, η, μ, σ, ω, ΔN_max, and these parameters were calculated in our study. These parameters were calculated using equations (1), (2), (3), (4), (5) and (6) [39, 40].

$$\chi =-\left(E_{HOMO}+E_{LUMO}\right)/2$$ (1)

$$\eta =(E_{LUMO}-E_{HOMO})/2$$ (2)

$$\mu =-\chi$$ (3)

$$\sigma =\frac{1}{\eta }$$ (4)

$$\omega =\frac{{\mu }^2}{2\eta }$$ (5)

$$\mathrm{\Delta }{N}_{\max }=\frac{-\mu }{\eta }$$ (6)

4.6. Cytotoxicity Prediction of the Compounds to Tumor Cell Lines

The prediction of interaction with tumor cell lines of the synthesized compounds was performed via CLC‐Pred (Cell Line Cytotoxicity Predictor) web service [41]. This step provides an estimate of which types of cancer synthesized compounds may be effective against.

4.7. ADME Prediction of the Compounds

The pharmacokinetic properties and drug‐likeness parameters of the synthesized compounds were evaluated in silico. ADME (absorption, distribution, metabolism, and excretion) predictions were performed using the web‐based SwissADME platform [42]. In addition, the drug‐likeness of the compounds was assessed primarily according to Lipinski's “Rule of Five,” along with the Veber, Ghose, Egan, and Muegge criteria. All calculated parameters were comparatively analyzed and interpreted in terms of their potential oral bioavailability.

Author Contributions

Hasniye Yaşa: data curation, writing – original draft, writing – review and editing. Onur Ertik: writing – original draft, writing – review and editing, molecular docking. Ozlem Sacan: inhibition study, writing –original draft. Belma Hasdemir: visualization, data curation, writing – original draft, writing – review and editing. Hatice Baspınar Küçük: visualization, writing – review and editing. Ayşe Serguzel Yusufoglu: writing – original draft. Refiye Yanardag: writing – original draft, writing – review and editing.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.