Multifaceted analysis of 3β-chloro-5α-cholestane-6-one cyanoacetic acid hydrazone: From green solid-state synthesis and structural elucidation to computational modeling and human serum albumin interactions

2.1. Solid-State Synthesis of 3β-chloro-5α-cholestane-6-one cyanoacetic acid hydrazone (or 3β-Chloro-6-[2-(2-cyanoacetyl)hydrazin-1-ylidene]-5α-Cholestane (CCHC) or 3β-chloro-cholestane-6-one 2-cyanoacetylhydrazone)

Equimolar amounts of 3β-chloro-5α-cholestane-6-one and cyanoacetic hydrazide were weighed. Activated basic alumina was in a 1:1 weight ratio to the total weight of the reactants (i.e., the total weight of the two reactants). The mixture was thoroughly ground with a mortar and pestle until a uniform powder was obtained. Thee ground mixture was transferred to a clean, dry round-bottom flask, which was sealed. The flask was placed in an oven at 60-80°C. Thin-layer chromatography (TLC) was utilized to periodically monitor the advancement of the reaction. After the reaction was complete (as determined by TLC), the mixture was allowed to cool to room temperature. The solid mixture was then suspended in chloroform. The suspension was filtered to remove the alumina, and the filtrate was concentrated under reduced pressure using a rotary evaporator to obtain the crude product. The crude product was recrystallized from ethanol, affording the steroidal hydrazone derivative as colorless crystals in 75% yield. The crystals were collected by filtration and air-dried. For comparative purposes, the title steroid was also synthesized by a conventional procedure reported in the literature [32] (Scheme 1). Melting points and mixed melting points were determined to confirm the identity of the CCHC synthesized via these two different approaches.

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Scheme 1.

Solid-state synthesis vs. conventional synthesis of steroid derivative (3): A comparison of yields and methods.

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Colorless crystals, yield (75%); m.p. 151°C; calculated analysis of C₃₀H₄₈ClN₃O: C, 71.75; H, 9.63; N, 8.37. found: C, 71.91, H, 10.09, N, 7.82%; IR (KBr, υ cm−1): 3380 (NH), 2296 (C≡N), 1703 (C=O), 1569 (C=C),1424 (N-H, in-plane bending), 1111 (N-N), 780 (C-Cl); ¹H NMR (CDCl₃, 400 MHz, ppm): δ 9.8 (s, 1H, NH, exchangeable with D₂O), 4.4 (1H, m, C3 α-H, W ½ = 17 Hz), 3.7 (s, 2H), 0.91 (s, 3H, C10-CH3), 0.73 (s, 3H, C13-CH3), 1.3-1.5 (side chain alkane), 0.91 and 0.85 (other methyl protons); 13C NMR (CDCl3, 100 MHz, ppm): δ163.5 (C=O), 154.9 (C6), 119.7 (C≡N), 57.8 (C3); HRMS: found 501.29, calcd for C₃₀H₄₈ClN₃O 501.35.

2.2. Computational studies: Quantum chemical calculations, Hirshfeld surface analysis, and molecular docking

Quantum chemical simulations were performed to examine the electronic characteristics and molecular geometry of CCHC (3). These computations were carried out using the widely employed B3LYP hybrid DFT in combination with the 6-311++G(d,p) basis set, which includes diffuse and polarization functions essential for accurately describing electron distribution and molecular interactions in organic compounds [33,34]. This level of theory has been validated in many previous studies and can be used to perform reliable geometry optimization and electronic structure prediction for similar organic molecules [35,36]. The calculations were performed in vacuo as well as using the Polarizable Continuum Model (PCM) with chloroform as solvent, implemented via Gaussian’s implicit solvation model. Based on the same computational level, vibrational frequency analysis confirmed that the optimized molecular structure was the true minimum. The results were visualized using GaussView [37]. Time-dependent density functional theory (TD-DFT) calculations were performed using the CAM-B3LYP and B3LYP functionals at the same level of theory in chloroform and gas phase to obtain electronic spectra of the molecule [38,39]. CAM-B3LYP was employed due to its superior ability to describe long-range charge transfer excitations, while B3LYP provided a robust comparison for general electronic transitions. Furthermore, the energy gap between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO), as well as the molecular electrostatic potential (MEP), were determined using DFT [40]. Multiwfn was used for analyzing non-covalent interactions (NCIs) [41]. A variety of parameters associated with these interactions can be calculated and interpreted using this software. A visual molecular dynamics (VMD) program [42] was also used to generate visual representations of computational data, such as isosurfaces. CrystalExplorer 21.5 facilitated the characterization of intermolecular interactions in the crystal structure by generating Hirshfeld surfaces and 2D fingerprint plots, thereby elucidating the nature of these interactions [43,44]. Molecular docking was performed using AutoDock software [45] to clarify the best binding conformation of the modified steroid produced using the solid-state technique with human serum albumin (HSA) [46]. The 3D crystal structure of HSA (PDB ID: 1AO6) was acquired from the Protein Data Bank. The structure of the synthesized steroid, obtained from crystallographic information files (CIF) recorded in the literature, was saved in PDB format. The preparation of HSA and steroid structures included the addition of polar hydrogen atoms, the assignment of AutoDockTools (ADT) atom types, and the integration of partial charges. The grid box centered on the HSA had dimensions of 75 × 75 × 75 Ź and a spacing of 0.375 Å. This grid was set to encompass key known binding sites on HSA, such as Sudlow’s Site I and Site II, ensuring that all relevant interaction regions could be explored. The Lamarckian genetic algorithm (LGA) was employed to determine the best binding site for the ligand on HSA using default parameters. Ten conformations were generated during the docking process, and the one exhibiting the minimal binding energy was chosen for subsequent analysis. The interactions between the protein and ligand were analyzed using the Protein-Ligand Interaction Analyzer (PLIP) web service [47]. The docking results were visualized and further analyzed using BIOVIA Discovery Studio [48]. Molecular dynamics simulation is used to verify molecular docking results and investigate protein-ligand complex stability. This work utilized normal mode analysis (NMA) dynamics simulation to analyze the Cα atoms of receptor proteins. This simulation used iMODS [49].

2.3. Spectroscopic studies of HSA-3β-Chloro-5α-cholestan-6-one cyanoacetic acid hydrazone interactions

3.1. Optimized molecular geometry

The optimized geometric parameters of 3β-Chloro-6-(2-cyanoacetylhydrazone)-5α-cholestane (3) were optimized using the B3LYP/6-311++G(d,p) method in the gas phase, and the results were then compared with the experimental data provided in Table 1. The optimized energy of the molecule was found to be -1872.1876 Hartree. Overall, the theoretical values ​​show good consistency with the experimental values, verifying the accuracy of the selected calculation method. The calculated bond lengths are very close to the experimental values, with deviations generally within 0.05–0.10 Å. The calculated bond length for C16-C11 is 1.85 Å, which is marginally longer than the experimentally observed value of 1.80 Å. In comparison, the N3-N4 bond length, calculated at 1.37 Å, closely matches the experimental measurement of 1.39 Å. Additionally, the theoretical value for the N4-H bond length is 1.01 Å, slightly exceeding the experimental value of 0.85 Å. This minor discrepancy could potentially be attributed to hydrogen bonding interactions present in the crystal structure. The theoretical bond angles exhibit high consistency with experimental data, with most deviations less than 2°. The C11–C16–H17 angle was calculated to be 103.3°, comparable to the experimental value of 109.0°. A slight difference was observed in the N3–C4–C46 angle, where the theoretical value (121.6°) was marginally smaller than the experimental value (123.5°). This could be attributed to environmental effects such as crystal packing forces absent in the gas-phase optimization.

Key dihedral angles demonstrated a good correlation between theoretical and experimental data, with most variations falling within an acceptable range. The calculated dihedral angle of C10–N3–N4–C46 was -179.9°, closely matching the experimental value of 178.8° [29]. This slight deviation suggests minimal conformational differences between the calculated gas-phase structure and the experimentally observed solid-state geometry. Conversely, the C42–H43–C50–N6 dihedral angle exhibited considerable discrepancy, with theoretical and experimental values of 179.4° and -158.5°, respectively. This discrepancy can likely be attributed to steric effects within the crystal lattice. The minor differences between theoretical and experimental values ​​can be attributed to differences in gas-phase optimization and condensed-phase experimental conditions. Factors such as intermolecular interactions, crystal packing, and environmental effects in the experimental setup can cause minor variations.

Comparison of DFT-calculated and experimentally determined (XRD) [29] structural parameters for the title CCHC, as given in Figure 1(a). Overlay of the DFT-optimized (green) and XRD (purple) structures. (b) Scatter plot of calculated bond lengths (B3LYP) versus experimentally determined bond lengths. The high correlation coefficient (R² = 0.9477) indicates good agreement between the calculated and experimentally determined bond lengths. (c) Scatter plot of calculated bond angles (B3LYP) versus experimentally determined bond angles. The very high correlation coefficient (R² = 0.9975) indicates that B3LYP accurately predicts the bond angles in this system. To evaluate the accuracy of the B3LYP function in predicting the molecular geometry of the modified steroids, the calculated bond lengths and bond angles were compared to experimental values. The results have been summarized in Figure 1, showing scatter plots comparing the B3LYP calculated values ​​to experimental data for bond lengths and bond angles (Figure 1b and c). The scatter plot for bond lengths exhibits a strong linear correlation (R² = 0.9477), indicating that B3LYP accurately predicts bond lengths within the molecule. Similarly, the scatter plot for bond angles shows excellent agreement between B3LYP predictions and experimental measurements, with R² values ​​as high as 0.9975. Together, these findings indicate that the B3LYP function provides a reliable description of the molecular geometry for the CCHC studied, providing confidence in the accuracy of subsequent calculations and analyses based on this level of theory.

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Figure 1.

Validation of DFT-optimized structure of CCHC (3): (a) Overlay of the molecular structures obtained from single-crystal XRD and DFT optimization. (b) Correlation plot of experimental vs. calculated (B3LYP) bond lengths. (c) Correlation plot of experimental vs. calculated (B3LYP) bond angles.

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The overlay of the DFT-optimized and XRD structures [29] in Figure 1(a) visually demonstrates excellent agreement between the DFT-optimized structure and the XRD structure. This is further supported by the high correlation coefficients between the calculated and experimental values ​​(R² = 0.9477 for bond lengths and R² = 0.9975 for bond angles). These results validate the accuracy of the B3LYP/6-311++G(d,p) method in predicting the geometry of steroids, making it suitable for subsequent computational studies, such as predicting spectral properties. The results presented in Table 1 and Figure 1 offer a detailed insight into the molecular geometry of the 3β-chlorocholestane molecule. Calculations were performed using the B3LYP functional combined with the 6-311++G(d,p) basis set, providing dependable predictions for bond lengths and angles. However, additional research may be required to enhance the accuracy of dihedral angle predictions [53,54], as standard DFT methods may have limitations in reproducing torsional parameters in flexible organic molecules. Discrepancies in dihedral angles (not shown in Table 1) can arise due to the gas-phase nature of DFT optimization, in contrast to the solid-state environment of X-ray crystallography. Incorporating dispersion-corrected functionals (e.g., B3LYP-D3) or employing conformational sampling techniques such as molecular dynamics may improve the agreement between calculated and experimental torsion angles, particularly in systems with complex intramolecular interactions.

From the ground-state DFT optimization, the frontier molecular orbital energies were also determined. The HOMO energy was calculated as -7.09 eV, and the LUMO energy was -1.25 eV. This results in a HOMO-LUMO energy gap of 5.84 eV (Egap = E_LUMO - E_HOMO). This ground-state energy gap helps to elucidate the molecule’s stability and reactivity. Specifically, a relatively large gap of 5.85 eV indicates that the molecule possesses high electronic stability, as a significant amount of energy would be required to excite an electron from the HOMO to the LUMO. This large energy barrier also suggests that the molecule is less prone to undergo facile electron transfer or chemical reactions under typical conditions, thus exhibiting lower reactivity.

3.2. FTIR analysis and simulated IR spectrum

The FTIR spectrum (Figure 2a) and simulated IR spectrum (Figure 2b) reveal the vibrational properties of the compound 3β-chloro-6-[2-(2-cyanoacetyl)hydrazine-1-methylene]-5α-cholestane in detail. The FTIR spectrum exhibits peaks at wavenumbers of 3380 cm⁻¹, 2922 cm⁻¹, 2861 cm⁻¹, 2296 cm⁻¹, 1703 cm⁻¹, and 780 cm⁻¹, which can be assigned to the stretching vibrations of the following functional groups: amine (N-H), methyl and methylene (sp3), nitrile (C≡N), carbonyl (C=O), and chloride (C-Cl). These experimental results are corroborated by the simulated IR spectrum, which exhibits excellent agreement with minor deviations likely arising from environmental factors such as intermolecular interactions or differences in phase.

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Figure 2.

Comparison of (a) Experimental FTIR Spectrum with (b) Calculated IR Spectrum at the B3LYP/6-311++G(d,p) Level (without scaling factor).

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Table 2 displays a comparative study of the theoretical (unscaled) and experimental frequencies and their corresponding assignments. The vibrational mode at 3531 cm⁻¹ (DFT) corresponds to the asymmetric stretching of the N–H bond, which was experimentally observed at 3380 cm⁻¹. The slight red shift in the experimental data is attributed to hydrogen bonding or environmental effects, such as simulation in the gas phase in the sample. Similarly, the C–H stretching vibrations of the angular methyl groups were theoretically observed at 3123, 3111, 3104, and 3097 cm⁻¹, and the corresponding experimental values ranged from 2922 to 2861 cm⁻¹, indicating good agreement between the calculated and measured frequencies. The characteristic vibrational modes of the steroid skeleton group were observed at 3092 cm⁻¹ (DFT) and 2967 cm⁻¹ (experimental), indicating the integrity of this functional group in the steroid molecule. The C=N stretching vibration is an important feature of the cyanoacetohydrazone group [55], predicted theoretically at 2396 cm⁻¹ and observed experimentally at 2296 cm⁻¹, emphasizing the contribution of this vibration to the electronic structure and reactivity of the CCHC. The carbonyl (C=O) stretching vibration is essential for the recognition of the acetyl group and is observed at 1772 cm⁻¹ (DFT) and 1703 cm⁻¹ (experimental). This consistent shift suggests the presence of conjugation effects or interactions with other functional groups. The C=C stretching vibration indicates the presence of an olefin group, detected theoretically at 1699 cm⁻¹ and experimentally at 1569 cm⁻¹, showing the role of conjugation in the molecule. The bending vibration of the N-H was identified theoretically at 1467 cm⁻¹ and experimentally at 1424 cm⁻¹, providing further evidence for the presence of an amine functional group. C–Cl asymmetric stretching vibrations were observed theoretically at 748 cm⁻¹ and experimentally at 780 cm⁻¹, confirming the presence of halide functional groups in the molecular framework.

Figure 3, with various subsections (Figures 3a–3f), shows the vibrational frequencies of key functional groups identified through simulation studies, including amine (N–H), nitrile (C≡N), carbonyl (C=O), alkene (C=C), and chloride (C–Cl). These groups exhibit prominent and well-defined peaks at 3531, 2396, 1772, 1699, and 748 cm⁻¹, respectively, without the application of a scaling factor. These peaks reflect intense dipole moment changes associated with their characteristic stretching vibrations. The carbonyl group (C=O) at 1772 cm⁻¹ is consistent with its presence in the acetyl functionality of the molecule. Additionally, the azomethine (C=N) group displays a peak at 2396 cm⁻¹, emphasizing its significant role in the CCHC’s structural framework and electronic properties. Overall, the theoretical calculations agree well with the experimental FT-IR data, demonstrating the reliability of the B3LYP/6-311++G(d,p) method in predicting vibrational properties, as shown in Figures 2, 3, and Table 2. The calculated IR frequencies were intentionally presented without applying a scaling factor to allow for a direct qualitative comparison between the theoretical and experimental spectra [56,57]. The minor differences between the theoretical and experimental frequencies are attributed to anharmonic effects and the absence of scaling factors in the theoretical calculations. These results validate the structural features of the steroid molecules and provide an understanding of their vibrational and electronic properties.

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Figure 3.

(a-f) Illustrates the key infrared (IR) vibrational modes of CCHC (3). Specifically, (a) presents the synthesized compound (3), while (b) through (f) depict the ν(CN), ν(C-Cl), ν(C=C), ν(C=O), and ν(N-H) stretches, respectively.

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3.3. UV-Vis spectral analysis and simulated UV-Vis spectrum

The experimental UV-Vis spectrum of the studied CCHC (Figure 4a) shows a prominent absorption peak at 239.06 nm in chloroform. This corresponds to a π-π* transition typically observed in conjugated systems, indicating electronic excitation within the molecular chromophore. The experimental spectrum indicates the presence of strong conjugation and electronic delocalization in the molecule. The theoretical UV-Vis spectrum calculated using TD-DFT with B3LYP and CAM-B3LYP functionals (Figure 4b) shows absorption peaks at 229.59 nm (B3LYP) and 223.63 nm (CAM-B3LYP). These values ​​are slightly blue-shifted compared to the experimental peaks, which is consistent with the known limitations of the TD-DFT method in underestimating solvent effects and other dynamic interactions. The CAM-B3LYP functional predicts slightly higher energy transitions, reflecting its better performance in accounting for charge transfer excitations. The major and minor contributions to the molecular orbitals have been listed in Table 3, summarizing the electronic transitions of the studied CCHC. For the experimental absorption peak (239.06 nm), the major contribution comes from the HOMO → LUMO transition with a significant oscillator strength (f = 0.7106). This transition highlights a strong π-π* interaction.

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Figure 4.

Experimental and theoretical UV-Vis spectra of the studied CCHC. (a) The experimental spectrum in chloroform shows a prominent absorption peak at 239.06 nm. (b) TD-DFT simulated spectra using B3LYP and CAM-B3LYP functionals in chloroform display absorption peaks at 229.59 nm and 223.63 nm, respectively, attributed to π-π* transitions.

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TD-DFT simulations predict that the B3LYP functional estimates a major electronic transition at 229.59 nm (HOMO → LUMO) with an oscillator strength (f) of 0.7106, closely matching the experimental results. Minor contributions from other orbitals (e.g., H-4 → L+10, H-3 → L+1) are observed at higher energies, indicating a complex electronic environment for the molecule. Using a different function, such as CAM-B3LYP, predicts a transition at 223.63 nm with significant contributions from H-2 → LUMO (16%) and H-2 → L+1 (13%), suggesting the involvement of higher-energy orbitals in the electronic excitation. The molecular structure (Figure 1) reveals a conjugated system involving multiple functional groups, including the cyano, NH, C=C within the hydrazone system, and the chloro-group, contributing to the molecule’s electronic properties. The presence of these electron-withdrawing groups enhances the molecule’s ability to stabilize its excited states, as evidenced by the high oscillator strengths in the TD-DFT calculations. These findings collectively support the conclusion that the experimentally observed absorption peak at 239.06 nm is primarily attributed to the HOMO → LUMO excitation, as predicted by both B3LYP and CAM-B3LYP functionals.

3.4. Frontier molecular orbitals and electrostatic potential analysis

The electronic properties of 3β-chloro-6-[2-(2-cyanoacetyl)hydrazine-1-methylene]-5α-cholestane 3 were analyzed based on the HOMO and LUMO energies (collectively referred to as frontier molecular orbitals) and the energy gap (Egap) (Figures 5a and b). The HOMO–LUMO energy gap (Egap) was computed using TD-DFT to estimate the optical gap [58,59], which is more relevant for understanding the photophysical properties and excitation behavior of the molecule, especially in solvent environments. HOMO represents the electron-donating ability of a molecule, while LUMO represents its electron-accepting ability. The energy gap (Egap = E_LUMO−E_HOMOE) is a key parameter for understanding the reactivity, stability, and optical properties of a molecule. In chloroform solvent, calculations performed using the TD-DFT-B3LYP functional yielded a LUMO energy of ELUMO =−1.28 eV and a HOMO energy of E_HOMO =−7.14 eV. The resulting energy gap is Egap = 5.86 eV. This moderate energy gap indicates a balance between electronic stability and reactivity, suggesting that the molecule can participate in electronic transitions and charge transfer processes with reasonable efficiency. Furthermore, in the gas phase, the HOMO and LUMO energies are calculated to be E_HOMO = −8.63 eV and E_LUMO = −0.16 eV, resulting in an energy gap of Egap=8.47 eV. The more significant energy gap observed in the gas phase compared to the solvated environment reflects the significant impact of solvent effects on the electronic structure. The absence of solvation makes the HOMO more stable than the LUMO, resulting in a broader energy gap, indicating that the molecule has more excellent intrinsic stability in isolation. The energy gap is an essential description of the chemical and physical behavior of a molecule. In chloroform, the narrowing of the energy gap indicates enhanced electron mobility, which may be beneficial for applications involving electron transfer or photoexcitation. In contrast, the widening of the energy gap in the gas phase indicates increased stability but reduced molecule reactivity in the absence of solvent. The results indicate that the surrounding environment is important in modulating the electronic properties of CCHC. These insights suggest potential applications in organic electronics, molecular sensors, or as a building block for supramolecular systems.

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Figure 5.

HOMO and LUMO orbitals with corresponding energy levels and gap (Eg) for CCHC (3) in (a) gas and (b) solvent phases (TD-DFT/B3LYP/6-311++G(d,p)). (c) 3D MEP map of CCHC (3).

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Computational analysis of the CCHC showed that it has a rigid steroid backbone and flexible functionalized side chains, a structural feature that suggests it has the potential to interact effectively with biological targets. The electrostatic potential map superimposed on the SCF total electron density surface (isoval = 0.0004) provides insight into the electron distribution. The electrostatic potential gradient ranges from highly negative regions (red) to highly positive regions (blue), highlighting the electronic heterogeneity of the CCHC. The most electron-rich regions (red) correspond to the oxygen atoms of the hydrazino subunit and the cyanoacetyl group (Figure 5c). These regions are potential sites for interaction with electrophiles, suggesting that the CCHC may have an affinity for positively charged biological targets. On the other hand, the electron-poor or electron-deficient regions (blue) are mainly located around the steroid core and the 3β-position chlorine atom. These regions may attract nucleophiles or negatively charged species, potentially interacting with the electron-rich biological environment. The presence of hydrazinylidene and cyanoacetyl functional groups significantly enhances the electronic diversity of the molecule. The carbonyl oxygen in the cyanoacetyl moiety exhibits a strong negative potential, making it a favorable site for binding to cationic proteins or metal ions. The electron-deficient chlorine atom and the hydrophobic steroid backbone contribute to the nucleophilic and hydrophobic interactions of the molecule. This unique combination of structural and electronic features suggests its potential for various biological activities, including interactions with proteins, enzymes, and receptors. This dual electronic property lays the foundation for exploring its potential as a pharmaceutical chemotherapeutic agent.

3.5. Hirshfeld surface analysis, 2D fingerprint plots, and the significance of enrichment ratio assessment

The Hirshfeld surface for the modified steroid was constructed to understand the intermolecular interactions responsible for stabilizing the crystal lattice, as shown in Figure 6(a), providing information about regions of close contact and hydrogen bonding. Red regions on the surface indicate regions of significant intermolecular contacts, while white and blue regions indicate regions with weak or no contacts. Prominent red regions are clearly visible near hydrogen donors and acceptors in the visualization, confirming strong hydrogen bonding interactions, particularly involving O···H/H···O and N···H/H···N. The presence of these interactions aligns with the calculated enrichment ratios, demonstrating their critical role in crystal stabilization. A 2D fingerprint is an effective way to represent the complex information contained in a crystal. It visually summarizes the frequency of different combinations of values ​​on the Hirshfeld surface of a molecule. Molecular interactions in the crystal structure of a CCHC synthesized via solid phase methods were analyzed using Hirshfeld surface analysis and 2D fingerprint plots. The interactions were decomposed into categories including H···H/H···H, N···H/H···N, O···H/H···O, Cl···H/H···Cl, and C···H/H···C, as mentioned in Figures 6(b-g). The surface contribution score was calculated for each interaction, and the enrichment ratio was determined to quantify the importance of these interactions relative to their expected proportions. The fingerprint shows that H...H/H...H interactions dominate, accounting for 66.0% of the Hirshfeld surface. This is expected due to the high number of hydrogen atoms in the molecular formula. Other significant reciprocal interactions include N···H/H···N (15.2%), Cl···H/H···Cl (7.8%), O···H/H···O (7.4%), and C···H/H···C (3.4%). These values ​​indicate that a complex network of hydrogen bonds and van der Waals forces stabilizes the crystal packing. The fingerprint highlights the sharp spikes corresponding to specific close contacts, such as O···H/H···O, indicating the presence of hydrogen bonds involving oxygen atoms.

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Figure 6.

Hirshfeld surface analysis of CCHC (3): (a) 3D Hirshfeld surface mapped over d_norm showing NCIs. (b-g) 2D fingerprint plots illustrating the percentage contribution of H···H, N···H, O···H, Cl···H, and C···H contacts, along with the overall (full) fingerprint.

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The enrichment ratio (E_XY) assesses the relative importance of different intermolecular interaction types in a crystal structure (Table 4). E_XY values ​​greater than 1 indicate that a particular interaction type is too common compared to its random occurrence, indicating that it plays an essential role in stabilizing crystal packing. Conversely, values ​​less than 1 indicate underrepresentation, meaning a less prominent contribution to the overall crystal structure. In this study, the E_XY values ​​of various intermolecular interactions were analyzed. For the H···H/H···H interaction, the E_XY was close to 1 (1.02), indicating that the frequency of hydrogen-hydrogen interactions occurs close to the random expectation. This suggests that these interactions have a minimal impact on crystal packing. In contrast, the N···H/H···N interaction exhibited a high enrichment ratio of 3.63, strongly suggesting that nitrogen plays a crucial role in stabilizing the crystal structure. This significant enrichment may be attributed to the formation of hydrogen bonds, which involve directional interactions between nitrogen and hydrogen atoms. Similarly, the Cl···H/H···Cl interaction showed a high enrichment ratio of 2.91, emphasizing the importance of chlorine-mediated interactions in stabilizing crystal packing. This could involve halogen bonding or other electrostatic interactions involving chlorine atoms.

O···H/H···O interactions also show significant enrichment with an E_XY of 1.91, confirming the active participation of oxygen in hydrogen bonding in the crystal structure. In contrast, the C···H/H···C interactions appear underrepresented with an E_XY of 0.65. This finding is consistent with the weaker nature of C-H interactions compared to polar bonds involving electronegative atoms such as N, O, and Cl. The high contribution and enrichment of H...H/H...H interactions emphasize the significant role of van der Waals forces in crystal packing. Meanwhile, the significant enrichment of N···H/H···N and Cl···H/H···Cl interactions reflects the key role of polar bonds in stabilizing the molecular structure. The participation of O···H/H···O interactions highlights the ability of oxygen atoms to participate in strong hydrogen bonds, further supporting molecular packing. The low enrichment of C···H/H···C interactions indicates their underrepresentation, which can be attributed to the lack of strong directional interactions associated with these bonds. Hirshfeld surface analysis combined with 2D fingerprints and enrichment ratios revealed a complex network of hydrogen bonds and van der Waals interactions in C₃₀H₄₈ClN₃O. H···H/H···H interactions dominate, while polar interactions involving N, O, and Cl are enriched, highlighting their role in maintaining the integrity of the molecular structure. These findings highlight the importance of Hirshfeld surface analysis as a tool to reveal molecular interaction mechanisms in crystal engineering.

3.6. Non-covalent interactions and reduced density gradient analysis

Non-covalent interaction (NCI) analysis of 3β-Chloro-6-(2-cyanoacetylhydrazone)-5α-cholestane (3) was carried out using B3LYP/6-311++G(d,p) level of theory. The RDG isosurface (Figure 7a) and the corresponding scatter plot (Figure 7b) reveal the nature and spatial distribution of interactions in 3. The RDG isosurface plot (Figure 7a) shows significant regions of non-covalent interactions, visualized by gradient isosurfaces color-coded with the symbol (λ₂)ρ. Blue regions correspond to attractive interactions such as hydrogen bonding, while green regions represent van der Waals interactions. Red regions represent steric repulsion. The blue regions near the hydrazine subunit highlight the possibility of strong hydrogen bonding interactions, which contribute to the molecular stability and potential reactivity of 3β-Chloro-6-(2-cyanoacetylhydrazone)-5α-cholestane (3). The scatter plot (Figure 7b) relates the decreasing density gradient (RDG) to the sign of (λ₂)ρ to distinguish between attractive, van der Waals, and repulsive interactions. Points in the negative (λ₂)ρ region (blue) confirm the presence of strong hydrogen bonding interactions, especially around polar functional groups. The green region reflects van der Waals interactions, which dominate in the hydrophobic core of the steroid backbone. Red points at positive (λ₂)ρ indicate repulsive steric effects, mainly around bulky substituents, such as the chloro-group at the 3β position. Single crystal XRD studies reported in the literature [29] further confirmed the molecular packing and structural stability in the following ways: Intramolecular hydrogen bonding: C4B—H4BA···N3B bonds stabilize the ring structure (numbering system reported in the literature). Crystal packing: Intermolecular N—H···O hydrogen bonds and C—H···O interactions form sandwich structures. Chain formation: C—H···N interactions generate ring structures that connect the molecules into chains along the a-axis. These structural insights are consistent with the interaction patterns revealed by NCI and Hirshfeld’s analysis. The intra- and intermolecular hydrogen bonds reported in the X-ray studies are consistent with the strong local interactions visualized in the Reduced Density Gradient (RDG) isosurfaces and the significant N···H, O···H, and H···H contributions in the fingerprint plots. The combination of RDG, X-ray Diffraction (XRD) data, Hirshfeld surfaces, and single crystals lays out a comprehensive understanding of the non-covalent interaction network of the CCHC (3). XRD data shed light on the role of specific hydrogen bonds in stabilizing the ring structure and crystal packing, while RDG and Hirschfeld quantitatively analyze these interactions and graph them visually, confirming their relative importance. This integrated approach enhances the understanding of the structure and function of the CCHC, particularly the interaction-driven packing and stability properties.

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Figure 7.

(a) NCI scatter plot and (b) RDG analysis of the modified steroid at B3LYP/6-311++G(d,p) level. RDG cutoff: sign(λ2)ρ = 0.5 au. Color scale: -0.035 to 0.02 au (blue: attractive, green: van der Waals, red: repulsive).

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3.7. Analysis of steroid (3)-human serum albumin binding studies

HSA-steroid binding studies have been investigated to elucidate the interaction and binding mechanisms between human serum albumin and steroids. As a steroid transport protein, HSA affects the bioavailability and distribution of steroids inside the body. Diverse spectroscopic techniques, such as UV–vis absorption, fluorescence spectroscopy, and CD, were used to investigate the binding of 3β-chloro-cholestane-6-one 2-cyanoacetylhydrazone (3) to HSA. These approaches offer significant insights into the molecular mechanisms underlying steroid biology and their associations with HSA [60,61]. Furthermore, these techniques help to identify the specific amino acid residues to which steroids bind and to quantify the binding affinity of steroids to HSA.

3.7.1. Ultraviolet-visible absorption analysis

The UV–vis spectra of HSA in the presence of increasing concentrations of CCHC (3β-chloro-6-hydrazinomethylene-5α-cholestane) have been shown in Figure 8(a). A noticeable enhancement in absorbance at 280 nm suggests that the interaction of CCHC with HSA perturbs the local environment of aromatic amino acid residues, particularly tryptophan. The absence of a wavelength shift implies that the overall tertiary structure of HSA remains largely intact. Figure 8(b) shows a clear linear correlation between CCHC concentration and absorbance intensity, indicating a consistent and quantifiable binding interaction. These observations support the involvement of non-covalent forces and highlight CCHC’s potential for specific engagement with HSA.

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Figure 8.

(a) UV-Vis spectra of HSA at a fixed concentration (5.0 µM) with increasing concentrations of 3β-chloro-6-hydrazinylidene-5α-cholestane (0.0 to 20.0 µM). The increased absorbance at 280 nm indicates ligand-induced alterations in the microenvironment of HSA’s aromatic residues, and (b) Plot depicting absorbance at 280 nm in relation to the steroid component concentration (0 to 20.0 µM), illustrating a linear correlation in binding interaction with HSA. The upward trend confirms dose-dependent interactions, indicating that ligand binding impacts the tertiary structure of HAS.

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This interaction signifies the formation of non-covalent bonds, such as hydrogen bonding, hydrophobic interactions, or van der Waals forces, between CCHC and HSA. The linear relationship between CCHC concentration and the increase in absorbance over the studied range (0–20 μM) suggests a consistent, potentially single-site or similar-affinity binding mechanism on the HSA molecules. This UV-Vis analysis, along with the trends shown in Figure 8, highlights the establishment of a specific protein-ligand interaction and highlights the potential of CCHC as a well-defined ligand for HSA. These findings provide insights into the strength and nature of the interaction and contribute to understanding its pharmacokinetic and pharmacodynamic implications.

3.7.2. Fluorescence quenching mechanism

Fluorescence spectroscopy has emerged as a highly effective technique for investigating a range of phenomena in biomacromolecules, such as interactions between proteins and drugs, structural alterations, and the mechanisms behind fluorescence quenching in these interactions [62]. The fluorescence of proteins can be attributed to aromatic amino acids, primarily tryptophan, tyrosine, and phenylalanine. Tryptophan is often the dominant fluorophore in proteins, and its fluorescence can be used to study the active site of HSA. Tyrosine and phenylalanine also fluoresce but are usually much weaker than tryptophan. The fluorescence of tyrosine can be reduced through ionization or by interactions with chemical groups located close to tryptophan. The study explores the titration of 3β-Chloro-6-(2-cyanoacetylhydrazone)-5α-cholestane (3) with HSA to investigate the binding mechanism and the formation of a complex between HSA and steroid (3). The HSA concentration was constant at 5 μM, as the 3β-Chloro-6-(2-cyanoacetylhydrazone)-5α-cholestane (3) concentration was varied from 2.5 μM to 20 μM at different temperatures (298 K, 303 K, and 310 K). Fluorescence spectra of HSA were acquired to assess the interaction between HSA and CCHC (Figure 9a). A fluorescence emission peak was observed for HSA at approximately 340 nm. The observed decrease in peak fluorescence intensity correlated with an increase in steroid concentration from 2.5 μM to 20 μM, indicating the formation of a steroid-HSA complex. At 20 μM, fluorescence intensity decreased by ∼54%, with no change in emission wavelength. This suggests the presence of a non-covalent interaction between steroid 3 and HSA. The addition of steroid 3 resulted in a gradual quenching of HSA fluorescence. This quenching was concentration-dependent, with a more pronounced effect at 20 μM. Fluorescence quenching could occur statically, through stable complex formation (where the quenching constant, Kq, diminishes with temperature due to decreased diffusion), or dynamically, via transient collisions (where Kq escalates with temperature due to an increased collision frequency). Dynamic quenching does not necessitate binding; it maintains protein structure and function. The Stern-Volmer equation quantified quenching, as illustrated in Figure 9(b) for HSA and steroid (3).

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Figure 9.

(a) Fluorescence emission spectra of HSA in the presence of increasing concentrations of steroid 3 (0–20 μM), with HSA concentration maintained at 5 μM in sodium phosphate buffer (pH 7.4) at 298 K. (b) Stern–Volmer plot of F₀/F versus steroid 3 concentration, illustrating fluorescence quenching of HSA by steroid 3 at 298 K. (c) Modified Stern–Volmer plot of log[(F₀−F)/F] versus log[steroid 3], depicting the binding affinity and number of binding sites involved in the HSA–steroid 3 interaction.

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The Stern–Volmer quenching constant K_SV is a key parameter for evaluating the quenching efficiency of a CCHC on a fluorophore, such as human serum albumin (HSA). A higher K_SV value reflects a more remarkable quenching ability. In this study, the K_SV value for the quencher was determined to be 5.01 × 10⁴ M⁻¹ at 298 K, indicating moderate quenching efficiency. The bimolecular quenching constant (kq) was calculated using the relation:

(5)

$\text{kq}={\text{K}}_{\text{SV}}/\tau 0$

where τ0 is the average lifetime of HSA in the excited state, typically around 10⁻⁹ seconds for proteins. The calculated kq value of 5.01 × 10¹³ M⁻¹ significantly exceeds the diffusion-controlled limit, indicating that the quenching mechanism is predominantly static. The bimolecular quenching constant, Kq, is crucial for comprehending the interaction between HSA and ligands. Using the linear regression plot of F0/F versus [Q], the interaction between HSA and steroids (3) at 298 K was obtained. The K_SV and Kq were determined to be approximately 10⁴ M⁻¹ and 10¹³ M⁻¹s⁻¹. This suggests that a stable ground-state complex forms between the quencher and HSA, leading to fluorescence quenching. The linear Stern–Volmer plot and the high correlation coefficient (R²=0.9908) further support this conclusion. This study notes that the mechanism of quenching between HSA and 3β-Chloro-6-(2-cyanoacetylhydrazone)-5α-cholestane likely initiates with a static quenching mechanism, as mentioned in the literature [63]. To further elucidate the binding interaction between the quencher and HSA, a modified Stern–Volmer equation was employed (Figure 9c). This method involves plotting log(F0−F/F) versus log[Q] to determine the binding constant (Kb) and the number of binding sites (n) on HSA. The slope of the resulting linear plot represents the number of binding sites, while the intercept corresponds to the logarithmic binding constant (logKb). The slope of the regression equation derived from the double logarithmic plot was 1.14173 ± 0.01728, and the intercept was 3.79 (log₁₀​(K_b​)=−1.42162, antilogarithm (base 10) of both sides) (Figure 9c). The slope close to 1 indicates that the quencher interacts with a single high-affinity binding site on ​​HSA. The binding constant (Kb) was calculated to be 3.79 × 10⁴ M⁻¹, indicating that the binding affinity between the quencher and ​​HSA is moderate. This value indicated that CCHC (3) bound well to HSA. The observed binding affinity, while large, is moderate, favoring reversible interactions under physiological conditions. This property highlights a key aspect of biological processes. The moderate binding affinity demonstrated in this study provides deep perceptions of the functional dynamics of HSA and its varied roles in physiological systems. Furthermore, the calculated Gibbs free energy (ΔG∘) for the binding of HSA to steroids was −6.224 kcal mol⁻¹ at 298 K, indicating that the binding process is spontaneous under standard conditions. Molecular docking studies yielded a binding score of −8.32 kcal mol⁻¹, consistent with a significant interaction between HSA and steroid 3. These values fall within the range of binding affinities typically observed for biologically relevant protein-ligand interactions, further supporting the experimental results. The high agreement between the experimental binding affinity and the binding score predicted by molecular docking further validates the existence and significance of the interaction between HSA and steroid 3. The Stern-Volmer and modified Stern-Volmer quenching of HSA by CCHC (3) was investigated at various temperatures, including 298 K, 303 K, and 310 K. Fluorescence intensity data obtained at 298 K was compared with two other temperatures, 303 K and 310 K, as given Table 5.

Table 5. Fluorescence quenching of HSA by steroid 3 at various temperatures.

Temperature (K)	R2	Ksv (×104M−1)	Kq (1013×M⁻1s⁻1)	R2	Kb (×104 M−1)	n
298	0.9908	5.01	5.01	0.9986	3.79	1
303	0.9932	6.32	6.32	0.9165	0.947	1.7
310	0.9911	6.08	6.08	0.9435	3.45	1.3

The fluorescence quenching values for HSA-steroid 3 interactions at different temperatures (298-310 K) have been summarized in Table 5. Stern-Volmer quenching constant (K_SV) values, which reflect quenching efficiency, rise slightly with increasing temperature (Figure 10a), indicating that temperature can affect the quenching process. The increase in K_SV may result from conformational changes in the protein that make the fluorophore more accessible to the quencher at higher temperatures. The Stern-Volmer quenching constant (Ksv) and its trend (increase and decrease with temperature from 298K to 319K) indicate that both static and dynamic quenching mechanisms contribute to the observed fluorescence quenching. In general, dynamic quenching is diffusion-controlled and increases with temperature, while static quenching is caused by complex formation, which may be weakened at higher temperatures. Since Ksv increases initially but decreases slightly at 310 K, this suggests a mixed quenching mechanism, with changes in binding affinity depending on temperature. The Kq values ​​are significantly higher than the diffusion-controlled limit (∼10¹⁰ M⁻¹s⁻¹), ranging between 5.01 × 10¹³ M⁻¹s⁻¹ at 298 K and 6.08 × 10¹³ M⁻¹s⁻¹ at 310 K. Such high values ​​confirm the involvement of static quenching via complex formation, ruling out purely dynamic quenching.

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Figure 10.

Quenching of HSA Fluorescence by Steroid 3. (a) Stern-Volmer plots (F0/F vs. [Steroid 3]) at 303 K and 310 K. (b) Modified Stern-Volmer plots (log[(F0-F)/F] vs. log[Steroid 3]) at the same temperatures.

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The binding constant (Kb) revealed temperature-dependent changes, decreasing at 303 K (0.947 × 10⁴ M⁻¹) but increasing again at 310 K (3.45 × 10⁴ M⁻¹). These fluctuations advocate potential conformational changes in the protein-ligand complex, which may alter the accessibility of binding sites at different temperatures. The number of binding sites (n) also varies, being 1 at 298 K, 1.7 at 303 K, and 1.3 at 310 K, suggesting that temperature affects the binding behavior of the ligand (Figure 10b). The increase in n at 303 K conveys that more binding sites may be available due to the relaxation or reorganization of the protein structure. However, the further decrease at 310 K may be due to partial unfolding or decreased ligand affinity due to increased molecular motion. The R² values ​​for the Stern-Volmer and modified Stern-Volmer equations were consistently high (∼0.99), confirming the consistency of the obtained data. However, the slightly lower R² value for the modified Stern-Volmer equation at 303 K (0.9165) indicates that temperature-induced changes may affect the bond interactions at this point.

Fluorescence quenching data imply that the ligand-HSA interaction involves both static and dynamic quenching. Temperature-dependent binding suggests protein structural changes alter binding affinity and site availability. The observed Kb and n changes show that the ligand-protein complex adapts structurally at different temperatures, affecting binding behavior. This study clarifies the molecular interactions that influence ligand binding to HSA, which may affect drug-protein interaction research.

3.7.4. Protein conformational shifts induced by binding

CD spectroscopy is an effective technique to monitor changes in the secondary structure of proteins, especially upon interaction with ligands or small molecules [66]. CD spectroscopy was employed to evaluate changes in the secondary structure of HSA upon interaction with CCHC at different molar ratios (1:1 and 1:2). Far-UV CD spectra revealed two characteristic negative bands at ∼209 nm and ∼220 nm, corresponding to π → π* and n → π* transitions in α-helical structures (Figure 11). Native HSA showed well-defined bands, confirming high α-helical content. Upon ligand binding, alterations were observed, with the 209 nm band showing reduced intensity and the 220 nm band exhibiting a slight blue shift. These spectral changes indicate a dose-dependent interaction between the ligand and HSA, leading to measurable conformational shifts within the HSA protein structure. Quantitative analysis showed a decrease in α-helical content by 1.2% at a 1:1 molar ratio and 12.2% at 1:2, suggesting that ligand binding perturbs the protein’s secondary structure in a concentration-dependent manner. These changes are likely due to hydrogen bonding or hydrophobic interactions between HSA and the ligand. Despite these alterations, the overall α-helical framework of HSA remained largely intact. Such conformational adjustments may influence the functional properties of HSA, potentially affecting its ligand-binding affinity and transport role, consistent with previous studies reporting ligand-induced structural modulation in serum albumins.

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Figure 11.

CD spectra of HSA and its complexes with CCHC (3) at different molar ratios.

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3.8. Molecular docking analysis

Molecular docking studies were performed to investigate the interaction of the target CCHC with HSA (PDB ID: 1AO6). The binding interactions were visualized through a combination of 3D and 2D diagrams highlighting the docking results (Figure 12). Docking results showed that the CCHC binds predominately within subdomain IB of HSA (Figures 12a-c). HSA contains a binding site within its IB subdomain that accommodates various molecules such as drugs, hormones, and fatty acids. The crystal structure (PDB ID: 1AO6) reveals the spatial arrangement of this binding site. The potency of HSA as a drug delivery vehicle arises from its ability to bind to receptors and undergo continuous recycling within the circulatory system. This domain is known for its essential role in drug binding and transport. The primary interacting residues include HIS146, ARG145, ILE142, LEU182, TYR138, and GLU425 (subdomain III A), all of which are part of or closely associated with the IB domain. The binding of the ligand within subdomain IB is stabilized by a combination of hydrogen bonding and hydrophobic interactions. Hydrogen bonding is observed at residues HIS146 and ARG145, indicating that strong polar interactions keep the ligand bound within the binding pocket. Hydrophobic interactions are formed with LEU182, TYR138, and ILE142, which further stabilize the position of the ligand within the domain and provide a conformation with the lowest binding energy of -8.322 kcal mol⁻¹. The 2D interaction diagram shown in Figure 12(e) confirms the strong affinity of the CCHC for the IB domain. In particular. HIS146 and ARG145 form crucial hydrogen bonds with the ligand, which are essential for its binding. The hydrophobic environment created by residues such as LEU182 and TYR138 enhances the stability of the ligand within the binding site. Other amino acid residues within the receptor’s active site also contribute to ligand stabilization through van der Waals interactions, further strengthening the ligand-receptor complex (Figures 12d-f). Molecular docking studies provided a detailed understanding of the binding mechanism between the CCHC and HSA. The combination of hydrogen bonding, hydrophobic interactions, and alkyl and pi-alkyl interactions highlighted the potential of the CCHC as a bioactive molecule. Moreover, the presence of amino acid GLU425, which belongs to subdomain IIIA, indicates that the studied CCHC interacts with multiple domains. These findings pave the way for further experimental validation and pharmacokinetic studies. Moreover, NMA dynamics simulations were performed on the C-α atoms of the receptor protein to understand the interactions of the amino acids with the modified steroid (3). Figure13(a) depicts the interactions of the receptor amino acids with the steroid (3). The receptor forms various interactions with the steroid molecule, including hydrogen bonds and hydrophobic interactions. Notable residues such as HIS146(A), TYR138(A), and LEU185(A) are the major contributors to the binding affinity as indicated by their proximity and distance interaction. This highlights the important residues involved in stabilizing the steroid (3) in the active site of the receptor. Figure 13(b) displays the B-factor/mobility plot, which sheds light on the receptor’s main-chain deformability. The deformability plot shows areas with a lot of flexibility, especially near residues like HIS105, LYS106, and PRO113. These areas could be hinged inside the receptor. These flexible parts probably help the structure change when a ligand binds, which makes it easier for the receptor to fit steroids. On the other hand, areas that are hard to bend, like those near CYS514, show a stiffer shape that probably keeps the receptor’s structure stable.

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Figure 12.

Molecular docking of steroid 3 with the 1AI9 protein: (a) receptor, (b) ligand (steroid 3), and (c) binding site. (d) 3D and (e) 2D interaction profiles of steroid 3 within the 1AI9 binding site. (f) Protein-ligand interaction analysis with HSA visualized using PLIP.

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Figure 13.

(a) Protein-ligand interactions: Interaction map highlighting key residues stabilizing the ligand within the receptor’s active site. (b) Protein flexibility: B-factor analysis identifies regions of high deformability, indicative of potential hinge regions facilitating conformational changes. (c) Covariance map showcasing correlated (red), uncorrelated (white), and anti-correlated (blue) motions between residues, revealing dynamic coupling and the intricate mechanisms underlying protein function.

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The covariance map in Figure 13(c) illustrates the interconnectedness of residues within the entire receptor. The red areas show motions that are linked, which could mean areas of cooperative structural dynamics that are necessary for ligand binding and receptor function. On the other hand, the blue areas show motions that are not related to each other. These may be caused by structural changes that are being made to compensate for the receptor. White areas show motions that are not connected to each other. They suggest that residues that are less involved in ligand-induced conformational changes are moving on their own. This study elucidates the dynamic residue-residue interactions within the protein, a crucial aspect for comprehending receptor function and its interplay with the steroid ligand (3). Molecular docking and subsequent NMA provide a computationally efficient approach to evaluate the intrinsic motions and flexibility of the protein-ligand complex by analyzing collective movements of the Cα atoms. This knowledge is crucial for elucidating the molecular basis of receptor function and exploring potential avenues for drug discovery.

Ligand-based pharmacophore modeling was performed to identify key structural features that are essential for the biological activity of CCHC (Figure 14a). The model was generated based on the molecular features of the ligand, focusing on essential pharmacophore features such as hydrogen bond donors, hydrogen bond acceptors, and hydrophobic regions. The pharmacophore plot revealed that the cholestane core of the ligand forms significant hydrophobic interactions, while the cyanoacetate hydrazone moiety contributes to hydrogen bonding. The presence of chlorine atoms in the steroid backbone further suggests the possibility of halogen interactions, which may enhance the binding affinity of the ligand. The pharmacophore features obtained from the model provide valuable insights into the key interactions required for optimal receptor binding and can guide the design of more effective analogs.

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Figure 14.

(a) Ligand-based pharmacophore model of CCHC, highlighting key pharmacophoric features and (b) Receptor-ligand pharmacophore model of CCHC with PDB: 1AO6, showing key binding interactions.

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The receptor-ligand pharmacophore modeling was further performed using the best docking pose of CCHC within the active site of PDB: 1AO6 (human aldose reductase) (Figure 14b). The docking analysis revealed a well-defined binding pocket containing hydrophobic and polar amino acid residues that interact with the pharmacophore elements of the ligand. Key residues such as TYR116, ARG145, and GLU425 were found to form hydrogen bonding interactions, while LEU182, LEU185, and LEU463 contribute to the hydrophobic stability of the steroid framework. The receptor-ligand pharmacophore highlighted the critical role of these interactions in maintaining strong binding affinity, further validating the docking results. The combination of ligand- and receptor-ligand pharmacophore-based models provides a comprehensive understanding of the molecular interactions that control ligand binding and facilitates the rational design of novel inhibitors against aldose reductase.

3.9. Evaluating sustainability: Greenness and whiteness metrics

The green chemistry profile of the synthesis of 3β-Chloro-6-(2-cyanoacetylhydrazone)-5α-cholestane was evaluated using the ComplexMoGAPI application. The assessment comprehensively evaluated the environmental impact of the method by considering various factors such as solvent usage, energy consumption, reaction conditions, and waste generation. The calculated green score was 81, indicating that the adopted protocol is well aligned with the principles of green chemistry (Figure 15). The method employs a solvent-free grinding technique using activated basic alumina, eliminating the need for hazardous organic solvents during the reaction stage. This significantly reduces environmental impact and minimizes chemical waste. Additionally, the reactions are carried out at moderate temperatures (60-80°C), ensuring lower energy consumption compared to conventional reflux syntheses.

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Figure 15.

Greenness assessment of the developed approach was performed using the ComplexMoGAPI application, revealing an overall greenness score of 81. The color-coded sections represent different environmental, safety, and efficiency parameters, where green indicates favorable/sustainable aspects, yellow indicates acceptable/moderate aspects, and red indicates unfavorable/critical aspects, confirming the sustainability of the approach.

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Post-reaction work-up involves simple filtration and recrystallization, further contributing to sustainability by avoiding complex purification steps that typically require large amounts of solvents. Despite the high overall greenness score, the use of chloroform in the purification step slightly impacted the evaluation results, as chloroform is classified as a volatile organic compound (VOC) with potential environmental and health impacts. Future optimization could focus on replacing chloroform with more environmentally friendly alternatives, such as ethyl acetate or EtOH extracts, to further improve the environmental friendliness of the method. The obtained results highlight the effectiveness of mechanochemical approaches in green organic synthesis. This strategy not only enhances sustainability but also ensures high efficiency, as demonstrated by the 75% yield of the steroidal hydrazone derivative. Comparative analysis with the conventional synthesis method further emphasizes the advantages of this approach, reinforcing its potential as an environmentally benign alternative for steroidal modifications.