Amide-functionalized cholic acid hybrids: design, bioactivity, and computational analysis

Abstract

A series of amide-linked cholic acid derivatives (3a–f) was synthesized through an efficient one-pot acyl chloride coupling strategy, yielding structurally diverse hybrids under mild conditions. The antioxidant potential of these derivatives was evaluated using the DPPH radical scavenging assay, with compounds 3b–d exhibiting the most pronounced activity, in an average of 50%. Antibacterial efficacy was investigated against both Staphylococcus aureus and Escherichia coli, revealing preferential activity toward Gram-positive strains, particularly for aromatic amide-bearing analogs. To elucidate the underlying molecular interactions, in silico investigations, including molecular docking, molecular dynamics simulations, and MM-PBSA binding free energy calculations, were conducted against the ATP-binding domain of bacterial DNA gyrase (GyrB). These computational studies revealed stable binding modes and favorable energetics that correlate with observed bioactivity. Density functional theory and ADMET predictions further supported the drug-like profiles and chemical reactivity of the most active compounds. These results demonstrate that the cholic acid scaffold can be effectively tailored to yield multifunctional agents with antioxidant and selective antibacterial properties, providing a promising framework for the development of novel antimicrobial candidates.

Amide-functionalized cholic acid hybrids were synthesized and identified as promising antibacterial agents. Experimental and computational analyses revealed antioxidant activity, selective bacterial inhibition, and stable DNA gyrase binding.

1. Introduction

Cholic acid is a naturally occurring carboxylic acid, widely recognized for its rigid steroidal backbone, amphiphilic nature, and chemical versatility.¹ The presence of three hydroxyl groups and a terminal carboxylic acid provides multiple reactive sites that facilitate molecular hybridization and functional derivatization.² Its facial amphiphilicity, hydrophilic hydroxyls oriented on one side and a hydrophobic steroidal surface on the other, enables interactions with both polar and nonpolar biological environments, thereby enhancing the bioavailability and target selectivity of hybrid molecules.³ Cholic acid is an important building block with a key role in chiral pool synthesis, drug delivery systems, steroid synthesis, and supramolecular chemistry.⁴ There are many commercially available cholic acid derivatives with potential application in the field of synthetic and medicinal chemistry such as methyl cholate (CAS number: 1448-36-8), a bile acid derivative that displays dose-dependent anti-hepatic fibrosis potential in both cellular and zebrafish models⁵ as well as could also be used as a key synthetic precursor for preparation of bioactive steroid derivatives and lipid-based drug delivery systems (Fig. 1).⁶

Fig. 1. Commercially available cholic acid and cholic acid derivatives with their biological potential.

Deoxycholic acid is also a commercially available cholic acid derivative with CAS number: 83-44-3, and has the potential of lipid emulsification in digestion.⁷ Chenodeoxycholic acid (CAS number: 474-25-9) is a known commercial cholic acid derivative known for treatment of hypertriglyceridaemia in men.⁸ Similarly, ursodeoxycholic acid (CAS 128-13-2) is also a commercially available cholic acid derivative with anti-inflammatory potential.⁹ Moreover, the commercially available lithocholic acid (CAS Number: 434-13-9) has been reported to have anti-aging effects in fruit flies, nematodes, and mice (Fig. 1).¹⁰

Moreover, numerous studies have exploited cholic acid as a biocompatible scaffold to design hybrid systems exhibiting potent antibacterial and antibiofilm activities.^11,12 These derivatives often act by disrupting bacterial membranes or potentiating conventional antibiotics, underscoring cholic acid's role as a privileged structural motif in antimicrobial drug design.¹³ On the other hand, nitrogen-containing molecules are valuable chemical architectures with diverse biological activities.^14–17 Therefore, interacting carboxylic acid with amine to create amide derivatives^18,19 having the steroid skeleton like cholic acid, may offer a strategic platform for developing novel bioactive amides with improved pharmacological profiles.²⁰

Amides are essential structural motifs found in proteins, natural products, pharmaceuticals, agrochemicals, and functional materials.²¹ Their chemical stability and biological relevance have made amide bond formation a central topic in modern synthetic chemistry, inspiring the development of diverse and efficient methodologies.^22,23 Amides serve as fundamental molecular anchors, providing structural rigidity while supporting a wide range of biological and physicochemical functions.²⁴ In recent years, amide containing compounds have gained increasing importance in medicinal and pharmaceutical chemistry due to their broad therapeutic potential and adaptable molecular frameworks.²⁵ Amides derived from naturally occurring carboxylic acids often exhibit potent biological activity, particularly against antibiotic-resistant bacterial strains,²⁶ that pose a major global health threat such as infections caused by carbapenem-resistant Gram-negative bacteria.^27,28 The inherent stability of the amide bond and its capacity for hydrogen bonding facilitate effective interactions with biological targets,^29,30 thereby enhancing pharmacological performance.^31,32 Numerous newly developed amide derivatives have demonstrated significant antibacterial activity,³³ positioning them as promising leads to complement or replace conventional antibiotics.³⁴ Moreover, these compounds offer versatile scaffolds³⁵ for rational molecular design²⁹ and optimization of next-generation antimicrobial agents capable of addressing multidrug-resistant infections.³⁶

Amide derivatives play a crucial role in contemporary synthetic and medicinal chemistry because of their diversity and broad therapeutic potential.³⁷ Fang et al. (2022) reported the synthesis of 2-amino-1-(morpholin-4-yl)ethanone (A) and 2-amino-1-(piperidin-1-yl)ethanone (B) via the reaction of morpholine and piperidine with glycine ester,^37,38 which showed notable antimicrobial activity (Fig. 2).

Fig. 2. Amide derivatives with antioxidant and antibacterial activities.

Rajput P. et al. (2018) highlighted several marketed drugs containing amide linkages as integral structural components, underscoring their diverse pharmacological relevance (C and D).³⁹ Kushwaha et al. (2011) synthetized a novel amide derivative and evaluated its antimicrobial potential by the disc diffusion assay, demonstrating appreciable activity against selected Gram-positive and Gram-negative bacteria (E).⁴⁰ Mahmood (2021) described compound F, which exhibited both antimicrobial and antioxidant activities.⁴¹ Marchetti et al. (2019) reported N-acyl histidine derivatives with strong biological potency (G).⁴²

In the recent time, advances in computational approaches, catalytic methodologies, and molecular design have enabled the development of functional organic systems with applications in both biomedical and material sciences.^43–46 In this regard, we reported the synthesis of cholic acid amide derivatives and their biological activities including anti-bacterial and antioxidant. Furthermore, in silico studies such as molecular docking, molecular dynamics and density functional theory DFT calculations, were performed to elucidate the interaction mechanisms between the synthesized compounds and their biological targets, thereby supporting the rational design of new bioactive molecules. Although, various amide functionalized cholic acid has been reported in the literature such as compound 3a and 3c as capable inhibitors of C. difficile spore germination⁴⁷ while compound 3f has possesses the antitumor potential,⁴⁸ but, compounds 3b, 3d, and 3e have not been explored for any biological activities yet as well as all these compounds have not been subjected to computational investigations. It is important to mention that the nitrosamine risk assessment is generally required during pharmaceutical development and larg scale preparation. Since no nitrosating agents were used in the present lab-scale synthesis, which focused on the preparation, characterization, and preliminary biological evaluation of the target compounds, comprehensive nitrosamine impurity testing was considered beyond the scope of this study.

2. Materials and methods

2.1. General procedure

All the reagents and solvents used were analytical grade and used without further purification. The reaction progress was monitored by thin-layer chromatography (TLC) on silica gel plates (0.25 mm thickness).

¹H and ¹³C Nuclear Magnetic Resonance (NMR) spectra were recorded using the Bruker-Avance, 600 MHz (Berlin, German). Chemical shifts were reported relative to the internal standard tetramethylsilane (δ 0.00 ppm) for ¹H NMR spectroscopy, with deuterated dimethyl sulfoxide (DMSO-d₆) (Cambridge Isotope Laboratories, USA) as solvent. The Fourier transform infrared (FTIR) spectra were recorded using a Shimadzu IR Prestige-21 spectrophotometer (Tokyo, Japan) equipped with an attenuated total reflectance (ATR) system.

Absorbance measurements were conducted using a 1 cm quartz cell and Model UV-5100 UV-visible spectrophotometer, operating within a wavelength range of 190–1000 nm and powered by Tungsten and Deuterium lamps.

2.2. Synthesis of compounds 3a–f

Following a modified literature procedure,⁴⁹ to a solution of cholic acid (0.74 mmol, 302 mg) in dichloromethane (5.0 mL) and triethylamine (2.22 mmol, 0.306 mL), thionyl chloride (0.74 mmol, 0.054 mL) was added dropwise. The reaction mixture was stirred at room temperature for 5 minutes, after which TLC analysis confirmed the complete conversion of cholic acid to the corresponding acid halide. Subsequently, a solution of the appropriate amine or aniline (2a–f, 0.74 mmol) and triethylamine (2.22 mmol, 0.306 mL) in dichloromethane (5.0 mL) were added to the reaction. The reaction was kept under stirring for 4 hours at room temperature. The products were obtained by evaporating the solvent. The residual thionyl chloride removed by washing with distilled water 3 times. The resulting residue was purified by chromatography column on silica gel using chloroform: methanol (9 : 1) as eluent to yield the pure amide products 3a–f.

2.2.1. ((3R,5S,7R,8R,9S,10S,12S,13R,14S,17R)-3,7,12-trihydroxy-10,13-dimethylhexadeca-hydro-1H-cyclopenta[a]phenanthren-17-yl)pentanamide (3a)

White solid (266 mg), 70% yield. Melting point: 188 °C. IR (KBr pellet, cm⁻¹): 3410, 2950, 1700, 1200, 1050 and 700. UV (in MeOH) λ_max: 301 nm. ¹H-NMR (600 MHz, DMSO-d₆) δ 9.86 (s, 1H, N–H³⁰), 7.36–7.15 (m, 1H, Ar–H³⁵), 7.18 (dq, J = 13.6, 6.8 Hz, 1H, Ar–H³⁹), 7.11 (d, J = 7.8 Hz, 1H, Ar–H³⁸), 6.59 (dd, J = 8.2, 2.6 Hz, 1H, Ar–H³⁷), 5.13 (s, 1H, OH⁴), 5.04 (s, 1H, OH¹⁰), 3.86 (s, 1H, OH²⁴), 3.73 (s, 1H, H²³), 3.57 (s, 1H, H⁹), 3.43 (s, 3H, CH₃⁴¹), 3.08 (qd, J = 7.2, 4.6 Hz, 1H, H³), 2.46–2.40 (m, 1H, H^18″), 2.32 (ddt, J = 16.3, 11.7, 6.0 Hz, 2H, H^13″,18′), 2.22 (ddd, J = 25.2, 14.3, 7.0 Hz, 2H, H^5″,8″), 1.94–1.84 (m, 1H, H^1″), 1.75 (s, 3H, H^{7,13′,17″}), 1.83–1.63 (m, 2H, H^5′,25″), 1.62–1.42 (m, 3H, H^{2″,8′,14″}), 1.34 (d, J = 6.9 Hz, 1H, H^14′), 1.25–1.13 (m, 3H^{2′,17′,25′}), 0.97 (q, J = 9.3 Hz, 3H, H^1′,16,32), 0.94–0.84 (m, 6H, 2CH₃20,28), 0.79 (s, 1H), 0.79–0.71 (m, 4H, CH₃²², H³³) and 0.59 (dd, J = 9.9, 4.7 Hz, 1H, H¹³). ¹³C-NMR (150 MHz, DMSO-d₆) δ 174.26, 159.93, 138.38, 129.87, 115.06, 111.76, 105.24, 71.00, 70.24, 69.78, 51.67, 47.66, 46.10, 40.84, 40.53, 38.04, 35.94, 35.75, 34.83, 34.78, 33.24, 31.68, 30.84, 29.49, 28.84, 27.37, 24.73, 22.54, 17.63 and 13.08.

2.2.2. (R)-N-(2-chloro-5-nitrophenyl)-4-((3R,5S,7R,8R,9S,10S,12S,13R,14S,17R)-3,7,12-tri-hydroxy-10,13-dimethylhexadecahydro-1H-cyclopenta[a]phenanthren-17-yl)pentanamide (3b)

White solid (325 mg), 76% yield. Melting point: 194 °C. IR (KBr pellet, cm⁻¹): 3410, 2950, 1680, 1200, 1050 and 650. UV (in MeOH) λ_max: 407 nm. ¹H-NMR (600 MHz, DMSO-d₆) δ 11.93 (s, 1H, N–H³⁰), 7.64 (d, J = 2.8 Hz, 1H, Ar–H³⁴), 7.46 (s, 1H, Ar–H³⁶), 7.35 (d, J = 2.7 Hz, 1H, Ar–H³⁷), 4.32 (s, 1H, OH⁴), 4.11 (s, 1H, OH¹⁰), 4.01 (s, 1H, OH²⁴), 3.79 (q, J = 3.2 Hz, 1H, H²³), 3.61 (q, J = 3.3 Hz, 1H, H⁹), 3.19 (tq, J = 11.8, 4.4 Hz, 1H, H³), 2.27–2.06 (m, 4H, H^5″,8″,18), 1.99 (td, J = 12.1, 7.3 Hz, 1H, H^13″), 1.85–1.68 (m, 4H, H^{1″,13′,16,17′}), 1.71–1.61 (m, 2H, H^5′,8′), 1.49–1.32 (m, 6H, H^{2″,7,15,17′,25′,32}), 1.32–1.22 (m, 3H, H^{1′,25″,33}), 1.24–1.10 (m, 1H, H^14′), 1.02–0.89 (m, 4H, CH₃²⁰, H^2,31), 0.85 (ddd, J = 14.9, 9.6, 5.1 Hz, 1H, H^14″), 0.81 (s, 3H, CH₃²⁸) and 0.59 (s, 3H, CH₃²²). ¹³C-NMR (150 MHz, DMSO-d₆) δ 175.45, 147.59, 146.27, 130.48, 123.75, 111.08, 109.19, 71.46, 70.91, 66.72, 46.56, 46.50, 46.22, 41.99, 41.84, 40.52, 35.78, 35.52, 35.34, 34.86, 31.31, 31.27, 30.94, 30.88, 29.01, 26.68, 23.28, 23.09, 17.41 and 12.81.

2.2.3. (R)-N-benzyl-4-((3R,5S,7R,8R,9S,10S,12S,13R,14S,17R)-3,7,12-trihydroxy-10,13-dimethylhexadecahydro-1H-cyclopenta[a]phenanthren-17-yl)pentanamide (3c)

White solid (269 mg), 73% yield. Melting point: 190 °C. IR (KBr pellet, cm⁻¹): 3410, 2950, 1680, 1500, 1200 and 1050. UV (in MeOH) λ_max: 307 nm. ¹H-NMR (600 MHz, DMSO-d₆) δ 8.4 (s, 1H, N–H³⁰), 7.00 (s, 1H, Ar–H³⁸), 6.90 (d, J = 7.8 Hz, 2H, Ar–H36,40), 6.85 (d, J = 7.9 Hz, 2H, Ar–H37,39), 5.19 (s, 1H, OH⁴), 5.13–5.03 (m, 1H, OH¹⁰), 4.79 (s, 1H, OH³⁴), 3.88–3.81 (m, 2H, H9,23), 3.72 (s, 2H, H³⁴), 3.63 (d, J = 4.3 Hz, 1H, H³), 2.52–2.45 (m, 1H, H^8″), 2.42–2.34 (m, 1H, H^8′), 2.32–2.19 (m, 2H, H^13″,5″), 2.14 (dt, J = 22.2, 6.9 Hz, 1H, H^13′), 1.86 (dd, J = 11.5, 7.3 Hz, 1H, H^1″), 1.78 (s, 1H, H^8′), 1.71 (q, J = 9.7 Hz, 3H, H^{5′,14″,17″}), 1.63 (d, J = 12.4 Hz, 1H, H^25″), 1.45–1.38 (m, 1H, H¹⁷), 1.34 (s, 1H, H⁷), 1.31–1.22 (m, 1H, H¹⁸), 1.03 (s, 1H, H^2″), 1.06–0.98 (m, 1H, H^2′), 0.97 (s, 3H, CH₃²⁸), 0.90–0.79 (m, 6H, CH₃²², H^14′,25′), 0.75 (dd, J = 10.5, 6.4 Hz, 1H, H^1′), 0.65 (d, J = 5.1 Hz, 3H, CH₃²⁰), 0.62 (s, 2H, H16,32) and 0.54 (s, 1H, H³³). ¹³C-NMR (150 MHz, DMSO-d₆) δ 136.8, 121.4, 120.8, 108.4, 108.3, 101.1, 71.4, 70.9, 69.7, 47.6, 46.4, 45.2, 41.9, 38.0, 35.7, 35.5, 35.3, 34.8, 33.2, 30.8, 29.5, 28.8, 26.6, 23.1, 22.5, 19.1 and 12.8.

2.2.4. (4R)-N-(3-hydroxy-2-methylpropyl)-4-((3R,5S,7R,8R,9S,10S,12S,13R,14S,17R)-3,7,12-trihydroxy-10,13-dimethylhexadecahydro-1H-cyclopenta[a]phenanthren-17-yl)pentanamide (3d)

White solid (207 mg), 60% yield. Melting point: 183 °C. IR (KBr pellet, cm⁻¹): 3410, 2950, 1680, 1200 and 1050. UV (in MeOH) λ_max: 301 nm. ¹H-NMR (600 MHz, DMSO-d₆) δ 11.92 (s, 1H, N–H³³), 4.32 (d, J = 4.4 Hz, 1H, H^36″), 4.12 (dd, J = 3.7, 1.8 Hz, 1H, OH⁴), 4.01 (d, J = 3.4 Hz, 1H, H^36′), 3.81–3.77 (m, 1H, H²³), 3.66–3.58 (m, 2H, OH²⁴, H⁹), 3.58 (s, 2H, OH10,37), 3.23–3.15 (m, 1H, H³), 3.19 (s, 1H, H³⁴), 2.27–2.06 (m, 4H, H^{5″,8″,13″,18″}), 1.99 (td, J = 12.0, 7.3 Hz, 2H, H^1″,13′), 1.81 (d, J = 9.1 Hz, 1H, H^18″), 1.74–1.62 (m, 3H, H^{5′,17″,25″}), 1.49–1.40 (m, 4H, H^{1′,15,17′,31}), 1.40–1.10 (m, 8H, H^{2′,7,14′,25′,32,35}), 0.97 (dd, J = 12.4, 5.6 Hz, 2H, H^2′,30), 0.94 (s, 4H, CH₃²⁰, H^8′), 0.86 (dd, J = 14.3, 3.2 Hz, 2H, H^14′,16), 0.81 (s, 3H, CH₃²⁸) and 0.59 (s, 3H, CH₃²²). ¹³C-NMR (150 MHz, DMSO-d₆) δ 174.31, 71.46, 70.91, 66.72, 51.66, 46.56, 46.23, 41.99, 41.84, 40.52, 35.78, 35.52, 35.50, 35.34, 34.86, 33.24, 31.32, 31.27, 30.94, 30.88, 29.01, 27.75, 26.68, 23.27, 23.10, 17.42 and 12.81.

2.2.5. (4R)-N-(2-hydroxy-2-phenylethyl)-4-((3R,5S,7R,8R,9S,10S,12S,13R,14S,17R)-3,7,12-trihydroxy-10,13-dimethylhexadecahydro-1H-cyclopenta[a]phenanthren-17-yl)pentanamide (3e)

White solid (254 mg), 65% yield. Melting point: 192 °C. IR (KBr pellet, cm⁻¹): 3410, 2950, 1680, 1500, 1200 and 1050. UV (in MeOH) λ_max: 304 nm. ¹H-NMR (600 MHz, DMSO-d₆) δ 7.15 (d, J = 7.5 Hz, 2H, Ar–H^38,42), 7.10 (t, J = 7.5 Hz, 2H, Ar–H^39,41), 7.05 (q, J = 6.5 Hz, 1H, Ar–H⁴⁰), 7.01 (s, 1H, N–H³⁰), 4.88 (s, 1H, OH⁴), 4.77 (d, J = 6.6 Hz, 1H, OH¹⁰), 4.46 (s, 1H, OH²⁴), 4.21 (s, 1H, H^34″), 3.44–3.35 (m, 1H, H²³), 3.34–3.23 (m, 2H, H^3,34′), 3.12 (ddd, J = 14.8, 10.9, 6.3 Hz, 2H, OH³⁷, H⁹), 2.18 (s, 1H, H^5″), 2.08 (ddt, J = 16.1, 11.5, 5.8 Hz, 2H, H^18″,35), 1.97 (tt, J = 11.9, 6.3 Hz, 1H, H^17′), 1.89–1.78 (m, 1H, H^17″), 1.68–1.32 (m, 9H, H^{1″,2,5′,18″,25″}), 1.30–1.16 (m, 4H, H^8,14), 1.08–0.92 (m, 4H, H^7,16,32,33), 0.68 (dtt, J = 23.4, 15.7, 6.3 Hz, 4H, CH₂₈, H³¹), 0.53 (q, J = 11.6 Hz, 3H, CH₃²⁰), 0.47–0.41 (m, 1H, H^1′) and 0.35 (td, J = 9.3, 4.0 Hz, 1H, H^25′). ¹³C-NMR (150 MHz, DMSO-d₆) δ 174.2, 142.2, 128.5, 127.5, 127.5, 127.3, 71.0, 69.7, 67.0, 47.9, 47.6, 46.9, 46.1, 40.8, 40.5, 38.0, 36.3, 35.9, 35.7, 35.6, 34.8, 33.2, 30.9, 29.4, 28.8, 27.3, 24.7, 22.5, 17.6 and 13.0.

2.2.6. (R)-N-(1-hydroxy-2-methylpropan-2-yl)-4-((3R,5S,7R,8R,9S,10S,12S,13R,14S,17R)-3,7,12-trihydroxy-10,13-dimethylhexadecahydro-1H-cyclopenta[a]phenanthren-17-yl)pentanamide (3f)

White solid (220 mg), 62% yield. Melting point: 187 °C. IR (KBr pellet, cm⁻¹): 3410, 2950, 1680, 1570, 1200 and 1050. UV (in MeOH) λ_max: 302 nm. ¹H-NMR (600 MHz, DMSO-d₆) δ 9.07 (s, 1H, N–H³⁰), 5.19 (s, 1H, OH⁴), 5.08 (s, 1H, OH¹⁰), 3.93 (s, 1H, OH²⁴), 3.85 (dt, J = 11.1, 2.9 Hz, 1H, H³⁶), 3.64 (s, 1H, H²³), 3.50–3.38 (m, 1H, H⁹), 3.16 (qd, J = 7.3, 4.8 Hz, 1H, H³), 2.52–2.44 (m, 1H, H^18″), 2.38 (s, 2H, H^18″,37), 2.35–2.21 (m, 2H, H^5″,13″), 2.22–2.12 (m, 1H, H³¹), 1.94 (q, J = 9.5 Hz, 1H, H¹⁶), 1.90–1.20 (m, 20H, H^{1″,2,5′,7,8,14″,15,17″,25,32,33,35,38}), 1.09–1.00 (m, 1H, H^17′), 1.02–0.91 (m, 6H, CH₃^22,28), 0.93–0.79 (m, 5H, CH_3, H^1′,13′) and 0.74 (ddd, J = 14.8, 11.0, 5.6 Hz, 1H, H^14′). ¹³C-NMR (150 MHz, DMSO-d₆) δ 175.3, 71.4, 70.9, 69.7, 66.7, 54.8, 51.6, 46.4, 46.2, 41.9, 41.8, 40.8, 40.5, 35.7, 35.5, 35.3, 34.8, 33.2, 31.3, 30.8, 29.5, 29.0, 27.7, 27.3, 24.7, 23.1, 22.5, 17.4 and 12.8.

2.3. Antioxidant activity

Following a modified procedure,⁵⁰ solutions of compounds 3a–f were prepared in dimethyl sulfoxide (DMSO) at a concentration of 25, 50, 75 and 100 µg mL⁻¹. For each assay, 20 µL of the test solution was mixed with 180 µL of a DPPH solution (9.2 mg in 100 mL of methanol). Ascorbic acid was used as the positive control, while DMSO was used as the negative control. The reaction mixtures were incubated in the darkness at 37 °C, after which the absorbance was measured at 517 nm using a UV-visible spectrophotometer. The radical scavenging activity (%) was calculated as follow equation: inhibition (%) = [(A_blank – A_sample)/A_blank] × 100. Where A_blank and A_sample represent the absorbance of the control and test samples, respectively. The percentage inhibition reflects the DPPH radical scavenging capacity of each compound.

2.4. Antibacterial activity

The antibacterial activity of the synthesized compounds (3a–f) was evaluated using the disk diffusion method. Escherichia coli (ATCC 25922) and Staphylococcus aureus (ATCC 25923) were obtained from the American Type Culture Collection (ATCC, Rockville, MD, USA). Bacterial strains were cultured in nutrient broth and incubated at 37 °C for 16 h prior to use.

Sterile filter paper disks (6 mm diameter) were prepared using a punch and autoclaved at 121 °C in sealed containers. Compounds 3a–f were dissolved in DMSO at a concentration of 10 mg per 100 µL, and 10 µL of each solution was applied to individual sterile disks. DMSO was used as a negative control to verify the absence of solvent-induced antibacterial effects, while ciprofloxacin served as a positive control to confirm assay validity.

Bacterial suspensions were adjusted to approximately 1 × 10⁸ colony forming units (CFU) mL⁻¹ and uniformly spread onto nutrient agar plates. The compound-impregnated disks were placed on the inoculated agar surfaces using sterile forceps. Plates were incubated at 37 °C for 24 h. Antibacterial activity was determined by measuring the diameter of the inhibition zones surrounding each disk in millimeters (mm). The zone of inhibition was calculated using the following equation: zone of inhibition (mm) = diameter of inhibition zone (mm) – diameter of disk (mm). All experiments were performed under identical conditions to ensure reproducibility.

2.5. Molecular docking study

Molecular docking studies were performed to evaluate the interactions of the cholic amide derivatives 3a–f with the ATP-binding pocket of two bacterial DNA gyrase targets: E. coli DNA gyrase (GyrE) and S. aureus DNA gyrase (GyrS). The crystal structures of GyrE (PDB ID: 6YD9)⁵¹ and GyrS (PDB ID: 3U2D)⁵² were obtained from the Protein Data Bank. Before docking, co-crystallized ligands, ions, and water molecules were removed, followed by the addition of polar hydrogens and assignment of Gasteiger charges using AutoDockTools (ADT). The three-dimensional structures of compounds 3a–f and reference ligands were constructed in ChemDraw and energy-minimized using the MM2 force field in ChemBio3D v12.0.

Docking simulations were carried out in AutoDock 4.2, with grid dimensions of 40 × 40 × 40 points for GyrE and 50 × 50 × 50 points for GyrS at a grid spacing of 0.486 Å. The grid centers were set at coordinates (10.274, −4.317, 7.439) for GyrE and (0.195, 2.568, 24.190) for GyrS. Both protein targets and ligands were treated as rigid during docking. The Lamarckian genetic algorithm was employed as the search method, performing 10 independent docking runs per ligand–enzyme pair to generate distinct binding poses.

The resulting docking conformations were ranked according to binding affinity, and poses with RMSD values <2.0 Å were considered reliable. The final binding modes were selected based on the lowest free energy of binding and the presence of key hydrogen bonding and hydrophobic interactions. All visualizations and interaction analyses were carried out using PyMOL (DeLano Scientific) and Discovery Studio Visualizer 2016.

2.6. Density functional calculation

The two-dimensional (2D) chemicals structures of 3a–f were sketched in ChemDraw Professional Version 16.0.1.4 and exported in Structure Data File format. These files were imported into Avogadro 1.2.0 for initial geometry optimization using the MMFF94 force field to remove high-energy conformations.^53,54 The structures were then fully optimized in the aqueous phase using density functional theory (DFT) at the B3LYP/6-311G(d,p) level of theory without any symmetry constraints. Frontier molecular orbitals, global reactivity descriptors, and electrostatic properties were computed at the same level. GaussView 6.0.16 was used to prepare Gaussian input files and to visualize the frontier molecular orbitals and molecular electrostatic potential surfaces.⁵⁵ Reduced density gradient analyses were carried out with Multiwfn 3.7,⁵⁶ and the resulting isosurfaces were rendered in VMD.⁵⁷ This workflow provided detailed insight into electron density distribution, noncovalent interactions and potential reactive regions within the synthesized molecules. All calculations were performed in Gaussian 16 on a workstation equipped with a 13th Gen Intel Core i5 processor, 32 GB RAM and an NVIDIA GeForce RTX 3050 GPU.

2.7. Molecular dynamics simulation

Molecular dynamics simulations were performed in GROMACS 2022.5 for 100 ns at 300 K on a workstation with a 13th Gen Intel Core i5 processor, 32 GB RAM and an NVIDIA GeForce RTX 3050 GPU.⁵⁸ Ligand parameters were generated with the SwissParam server (https://old.swissparam.ch/), while protein topologies were built using the CHARMM27 force field and the TIP3P water model.^59,60 Each system was placed in a cubic TIP3P box with at least 1.0 nm between the solute and the box edge, neutralized and adjusted to physiological ionic strength with NaCl. Energy minimization was carried out with the steepest-descent algorithm for a maximum of 50 000 steps or until the maximum force was below 1000 kJ mol⁻¹ nm⁻¹. PME electrostatics, a 1.0 nm cutoff for short-range interactions and a force-switching scheme from 1.0 to 1.2 nm were applied.

Equilibration consisted of 400 ps in the NVT ensemble at 300 K using the V-rescale thermostat with separate coupling for solute and solvent under positional restraints, followed by 400 ps in the NPT ensemble at 1 bar with the Parrinello–Rahman barostat. Production runs were performed for 100 ns with a 2 fs timestep using the leap-frog integrator, PME electrostatics, LINCS constraints on bonds to hydrogen and identical nonbonded settings. Trajectories were stored every 10 ps. The same protocol was applied to the apo protein and the protein–ligand complexes to ensure consistent comparison of their structural and dynamical properties.

2.8. MM-PBSA calculations

Binding free energies (ΔG_bind) of the protein–ligand complexes were estimated using the g_mmpbsa (v1.6.3) package.^61–64 Snapshots were taken from the equilibrated 100 ns trajectories, sampling frames 1–5000 at one-frame intervals after removing water and ions. The MM-GBSA method was applied with an internal dielectric constant of 1.0, an external dielectric constant of 78.5 and a solvent probe radius of 1.4 Å. Nonpolar solvation energies were estimated from solvent-accessible surface area. Entropic terms were not included. Binding free energy was evaluated using:ΔG_Bind = G_complex − (G_protein + G_ligand)where G_complex, G_protein and G_ligand represent the free energies of the complex, the isolated protein and the isolated ligand, respectively. The same formalism is applicable to other biomolecular systems, including protein–protein and protein–DNA complexes.

2.9. AMET analysis

Pharmacokinetic and toxicity profiles of compounds 3a–f were predicted in silico using SwissADME (https://www.swissadme.ch/),⁶⁵ pkCSM (https://biosig.lab.uq.edu.au/pkcsm/),⁶⁶ and Deep-PK (https://biosig.lab.uq.edu.au/deeppk/),⁶⁷ web servers.

Key absorption parameters, including gastrointestinal absorption, Caco-2 permeability, P-glycoprotein substrate/inhibitor status, and oral bioavailability, were estimated alongside distribution properties such as blood–brain barrier penetration, fraction unbound in plasma, and steady-state volume of distribution. Metabolic predictions focused on substrate and inhibitor interactions with major cytochrome P450 isoforms (CYP1A2, CYP2C19, CYP2C9, CYP2D6, and CYP3A4). Excretion parameters, including total clearance and half-life, were evaluated, and toxicity endpoints such as AMES mutagenicity, hepatotoxicity, hERG channel inhibition, and skin sensitization were assessed. Drug-likeness metrics, including Lipinski's rule of five compliance, topological polar surface area, log P, solubility, and bioavailability scores, were also determined.

2.10. Statistical analysis

To assess statistical differences among treatments in both the antioxidant and antibacterial assays for compounds 3a–f, a one-way analysis of variance (ANOVA) was performed. When the ANOVA indicated significant variation among groups, Tukey's post hoc test was applied to identify specific pairwise differences, using a significance level of p ≤ 0.05. All statistical analyses were conducted using SPSS software (Version 25.0, Statistical Product and Service Solutions). Data are reported as the mean ± standard error of the mean (SEM).

3. Results and discussion

3.1. Synthesis of cholic acid functionalized with amides (3a–f)

The cholic acid amide derivatives were synthesized via a two-step reaction. In the first step, cholic acid was reacted with thionyl chloride to afford the corresponding acid chloride. In the second step, the resulting intermediate was reacted with the appropriate amine or aniline in dichloromethane, yielding the desired amide derivatives (3a–f) (Scheme 1).

Scheme 1. Synthesis of compounds 3a–f.

All cholic acid amide hybrids were obtained in moderate to good yields, and their structures were confirmed by NMR and IR spectroscopy. The ¹H NMR spectra exhibited characteristic signals for the cholic acid scaffold with characteristic signals consistent with its steroidal framework and hydroxyl substituents. Broad signals or multiplets observed at δ 3.4–4.0 ppm correspond to the hydrogen atoms attached to the hydroxyl-bearing carbons (C3, C7, and C12). The methine and methylene protons of the steroidal backbone appear as a complex multiplet pattern in the δ 0.80–2.50 ppm region, reflecting the rigid, highly substituted structure. The methyl protons at C18, C19, C21, and C27 – C29 as singlets or doublets between δ 0.65–1.00 ppm. The N–H proton of amide group appears as a singlet at δ 9.0–11.0 ppm, although it may be weak or absent due to exchange with trace water or solvent. The ¹³C NMR spectra showed a carbonyl resonance at δ 174–175 ppm, consistent with the amide framework. The FTIR spectra exhibited characteristic absorption bands at 3400 cm⁻¹ (νN–H), 1700 cm⁻¹ (νC O), and 1500 cm⁻¹ (νC C), confirming the presence of the expected amide and aromatic functional groups.

3.2. Antioxidant assay

The antioxidant activities of the synthesized compounds 3a–f was evaluated using the DPPH radical scavenging assay and expressed as percentage inhibition, with ascorbic acid employed as the reference antioxidant. As shown in Fig. 3, all tested compounds exhibited moderate antioxidant activity, with inhibition values ranging from 53.4% to 60.0%.

Fig. 3. Antioxidant activities of compounds 3a–f. The values are expressed as mean ± SEM (n = 3). Columns with different letters are significantly different (p < 0.05) from each other.

Among the evaluated derivatives, compounds 3c (59.9%) and 3b (59.8%) displayed the highest radical scavenging activities, followed closely by 3d (59.5%) and 3a (57.6%). In contrast, compounds 3f (55.8%) and 3e (53.4%) exhibited comparatively lower activity. The standard antioxidant ascorbic acid showed a higher inhibition value (81.5%), confirming the moderate antioxidant potential of the synthesized cholic acid amide derivatives.

The observed antioxidant activities are consistent with literature reports describing small heterocyclic and aromatic compounds that lack multiple phenolic hydroxyl groups.⁶⁸ Such compounds generally exert antioxidant effects through electron donation and radical stabilization mechanisms, rather than hydrogen atom transfer, which predominates in polyphenolic antioxidants. Functional groups such as amide linkages, heteroatoms (N and O), and conjugated aromatic systems are known to contribute to these moderate radical-scavenging properties.⁶⁹

Within the present series, the slightly enhanced activity observed for compounds 3a–d may be attributed to the presence of aromatic substituents that promote electronic delocalization and stabilize radical intermediates. Comparable inhibition ranges (50–65%) have been reported for heterocycle-based antioxidants, including substituted pyrimidines,⁷⁰ pyrroles,⁷¹ and imidazoles,⁷² when evaluated using DPPH or related assays, often showing moderate efficacy relative to standard antioxidants such as ascorbic acid, Trolox, or BHT.

Furthermore, these findings are in good agreement with previous studies reporting that cholic acid amide derivatives typically exhibit moderate DPPH scavenging activity, generally ranging from 45–65% inhibition at comparable concentrations. The lower activity relative to ascorbic acid can be rationalized by the absence of strongly hydrogen-donating phenolic hydroxyl groups, which are critical for high antioxidant efficiency.^73,74

3.3. Antibacterial assay

The antibacterial activity of the cholic acid amide derivatives (3a–f) against E. coli (Gram-negative) was evaluated using the zone of inhibition assay. Overall, the tested compounds exhibited moderate inhibitory effects, with inhibition zones ranging from 9 mm to 19 mm, which are lower than that of the reference antibiotic ciprofloxacin (25 mm) (Fig. 4). Among the synthesized derivatives, compound 3d displayed the highest activity against E. coli, producing an inhibition zone of 19 mm, followed by 3c (16 mm) and 3b (15 mm). These results indicate antibacterial potential, although still inferior to the standard drug. In contrast, compounds 3e (10 mm) and 3f (9 mm) showed weak inhibitory effects, suggesting limited efficacy against this Gram-negative strain.

Fig. 4. Antibacterial activity of cholic acid amide derivatives (3a–f) against E. coli and S. aureus, evaluated by the zone of inhibition method. Data are expressed as mean ± SEM (n = 3). Columns marked with different letters indicate statistically significant differences among treatments (p < 0.05).

The observed activity profile against E. coli is consistent with literature reports attributing the intrinsic resistance of Gram-negative bacteria to the presence of an outer membrane enriched in lipopolysaccharides, which acts as a permeability barrier and restricts the penetration of many small molecules.⁷⁵ Compounds that lack sufficient lipophilicity or specific uptake mechanisms often exhibit reduced antibacterial activity against E. coli. The comparatively higher activity observed for compound 3d may be associated with favorable electronic and steric features that enhance membrane permeation and/or improve interactions with intracellular targets.

Furthermore, the antibacterial evaluation against S. aureus (Gram-positive) revealed greater overall susceptibility to the synthesized cholic amide derivatives. The observed zones of inhibition ranged from 11 mm to 17 mm were higher for several compounds when compared with their activity against E. coli (Fig. 4). The most active compounds against S. aureus were 3d (17 mm) and 3e (16 mm), followed by 3b (15 mm). Interestingly, compound 3e, which exhibited weak activity against E. coli, showed improved inhibition against S. aureus, highlighting a clear Gram-selective antibacterial profile. This behavior is well documented in the literature, as Gram-positive bacteria lack an outer lipopolysaccharide membrane, allowing easier diffusion of small molecules toward the cytoplasmic membrane and intracellular targets.⁷⁶

Compounds 3a (11 mm) and 3c (12 mm) displayed modest activity, while 3f (12 mm) showed inhibition comparable to that observed against E. coli. Collectively, these findings emphasize the dominant role of cell wall architecture in determining antibacterial efficacy for this compound series. When compared with literature data for small heterocyclic or aromatic antibacterial agents evaluated using zone of inhibition assays, inhibition diameters between 10 mm and 20 mm are generally classified as moderate activity.⁷⁷ The preferential activity against S. aureus observed for several derivatives is consistent with reported trends for structurally related antimicrobial scaffolds. This Gram-positive selectivity may be advantageous for targeted antibacterial development, particularly against S. aureus, including resistant strains, pending further optimization and validation through minimum inhibitory concentration studies.

3.4. Molecular docking study

To investigate the potential mechanism of action of the cholic acid amide derivatives and to assess their ability to interact with the ATP-binding region of DNA gyrase subunit B (GyrB), molecular docking studies were performed for compounds 3a–f against GyrB from E. coli and S. aureus. The selection of bacterial DNA gyrase subunit B (GyrB) as the molecular target was based on its well-established and essential role in bacterial DNA replication, transcription, and chromosome segregation, making it one of the most validated targets for antibacterial drug discovery. Specifically, the ATP-binding domain of GyrB is responsible for providing the energy required for DNA supercoiling through ATP hydrolysis, and its inhibition leads to bacterial cell death.

The predicted binding free energies and the key ligand–protein interactions identified for each complex are summarized in Table 1. Overall, the calculated binding affinities ranged from −5.02 kcal mol⁻¹ to −8.48 kcal mol⁻¹, indicating moderate to favorable interactions with the ATP-binding pocket of GyrB, depending on both compound structure and bacterial species.

Table 1. Molecular docking results of compounds 3a–f.

Compound	Target protein	Binding energya	Key interacting residues
3a	E. coli DNA GyrB	−8.48	Asp49, Asp73, Gly77
	S.aureus ATPase GyrB	−6.6	Asp45, Glu46, Thr138
3b	E. coli DNA GyrB	−5.54	Asp49, Asp73, Gly77
	S.aureus DNA GyrB	−6.09	Asp45, Ser43, Glu46, Thr138
3c	E. coli DNA GyrB	−7.02	Asp49, Glu50, Asp73, Gly77
	S.aureus DNA GyrB	−7.22	Gly73
3d	E. coli DNA GyrB	−5.02	Val43, Asn46, Val71
	S.aureus DNA GyrB	−5.38	Arg72, Tyr51
3e	E. coli DNA GyrB	−5.20/-5.01b	Asp49, Glu50, Thr165/Glu50, Asp73, Arg76, Gly77, Thr165
	S.aureus DNA GyrB	−5.33/-6.78b	Ser93; Thr138/N.A.
3f	E. coli DNA GyrB	−5.27	Asn46
	S.aureus DNA GyrB	−6.33	Asp69; Gly73

^akcal mol⁻¹.

^b R/S stereosisomeers of 2-amino-1-phenylethanol. N.A. Not available.

For E. coli, the docking protocol was first validated through re-docking of the reference ligand into the E. coli GyrB binding site, yielding a docking score of −7.25 kcal mol⁻¹ and an RMSD of 0.9009 Å, thus confirming the reliability of the chosen parameters (Fig. 5 – Chart A). Among the evaluated compounds, 3a exhibited the most favorable binding toward E. coli GyrB, with a binding energy of −8.48 kcal mol⁻¹, suggesting the formation of a particularly stable ligand–protein complex. Compound 3c also showed good affinity (−7.02 kcal mol⁻¹), whereas compounds 3b, 3d, 3e, and 3f displayed weaker binding, with docking scores between −5.02 kcal mol⁻¹ and −5.54 kcal mol⁻¹.

Fig. 5. 3D binding poses and interactions of the reference ligand (Chart – A) and compound 3a (Chart – B) in the E. coli ATP-binding site of GyrB.

All derivatives were found to occupy the ATP-binding pocket in a manner analogous to the reference ligand in E. coli protein. The cholic acid scaffold consistently aligned within the hydrophobic region of the site, whereas the amide substituent extended toward the polar region. A key hydrogen bond interaction with Gly77 was observed. Compound 3a showed the lowest binding energy (-8.48 kcal mol⁻¹) and four hydrogen bonds with Asp49 (2.04 Å), Asp73 (1.99 Å), Arg76 (3.13 Å) and Gly77 (1.97 Å) (Fig. 5 – Chart B).

For compound 3e, two closely similar binding energies were obtained, corresponding to its R and S enantiomers. The two amide diastereomers derived from racemic 2-amino-1-phenylethanol exhibited similar binding conformations within the GyrE active site, with binding energies of −5.20 kcal mol⁻¹ and −5.01 kcal mol⁻¹, respectively. In both diastereomers (3eR and 3eS), the amide carbonyl made hydrogen bonding with Thr165 and Gly77, with bond distances of 2.18 Å for 3eR and 2.05 Å for 3eS. These interactions suggest that the amide moiety is important for stabilizing the ligand–enzyme complex and orienting the cholic acid scaffold appropriately within the ATP-binding pocket.

For S. aureus, redocking of the reference ligand into the ATP-binding site of GyrB produced a docking score of −7.65 kcal mol⁻¹ and an RMSD value of 1.142 Å, confirming the reliability and accuracy of the selected docking parameters (Fig. 6 – Chart A). The docking simulations against S. aureus GyrB revealed a different affinity profile. Docking results for compounds 3a–f are summarized in Table 1.

Fig. 6. 3D binding poses and interactions of the reference ligand (Chart – A) and compound 3c (Chart – B) in the S. aureus ATP-binding site of GyrB.

Compound 3c showed the strongest interaction, with a binding energy of −7.22 kcal mol⁻¹ (Fig. 6 – Chart B), followed by 3e (−6.78 kcal mol⁻¹ for S enantiomer), 3a (−6.60 kcal mol⁻¹), and 3f (−6.33 kcal mol⁻¹). Compounds 3b and 3d exhibited comparatively weaker affinities, with binding energies of −6.09 kcal mol⁻¹ and −5.38 kcal mol⁻¹, respectively.

Several complexes showed interactions with residues known to be critical for ATP binding and hydrolysis, including Asp45, Glu46, Thr138, Gly73, Asp69, and Ser93. In addition, compound 3e displayed enantiomer-dependent behavior in S. aureus, with binding energies of −5.33 kcal mol⁻¹ and −6.78 kcal mol⁻¹, suggesting a stereochemical sensitive binding mode.

For S. aureus GyrB, the affinity pattern differed notably, with 3c and 3e showing enhanced binding compared to their performance against E. coli. The frequent involvement of conserved residues such as Asp45, Glu46, and Thr138 is consistent with binding at the ATPase domain of GyrB, a well-established target for antibacterial agents. Interactions involving Gly73 and Asp69 further support stable ligand accommodation within this pocket. The pronounced enantiomeric effect observed for 3e in S. aureus suggests a more sterically constrained binding environment relative to E. coli GyrB.

When compared with literature data, the binding energies obtained here (approximately −6.00 kcal mol⁻¹ to −8.50 kcal mol⁻¹) fall within the range commonly reported for ATP-competitive GyrB inhibitors, including aminocoumarin derivatives and heterocycle-based small molecules, which typically display docking scores between −7.00 kcal mol⁻¹ and −10.00 kcal mol⁻¹.⁷⁸ Moreover, the identification of key residues such as Asp45, Glu46, Gly73, and Thr138 agrees well with previous docking and crystallographic studies describing the molecular determinants of GyrB inhibition.⁷⁹

Additionally, derivatives containing aromatic or benzyl amide substituents exhibited more favorable docking scores compared to those with aliphatic amide groups, indicating a stronger stabilization within the ATP-binding pocket and suggesting greater inhibitory potency. This trend is consistent with the microbiological assay results, in which compounds bearing hydrophobic or electron-rich aromatic moieties showed higher biological activity. These observations suggest that both electronic effects and steric bulk of the substituents on the amide moiety play important roles in modulating ligand–protein interactions within the active site. Overall, the molecular docking analysis supports the proposed mechanism of action of the synthesized derivatives as GyrB inhibitors and underscores key structural features that could be further refined to enhance potency and selectivity in future compound optimization efforts.

3.5. Molecular dynamics simulation

Molecular dynamics (MD) simulations were conducted to assess the structural stability and dynamic behavior of the D1 protein in its apo form and in complex with ligands 3a–3f. Several structural descriptors, including backbone root-mean-square deviation (RMSD), residue-wise root-mean-square fluctuation (RMSF), radius of gyration (R_g), solvent-accessible surface area (SASA), hydrogen-bond profiles, and potential energy trajectories, were analyzed to evaluate the impact of ligand binding on both global and local protein dynamics.

Backbone RMSD analysis was used to monitor the overall stability of each system throughout the production phase of the simulations (Fig. 7 – Chart A). The apo protein rapidly equilibrated and remained stable, with RMSD values fluctuating between 0.25 and 0.30 nm, indicating preservation of its native conformation. Protein complexes with ligands 3f, 3eR, and 3eS exhibited comparable RMSD profiles, suggesting that these ligands do not perturb the overall protein fold. In contrast, complexes formed with 3b and 3c showed slightly elevated RMSD values, reaching up to 0.35 nm, indicative of increased conformational flexibility and a more dynamic binding environment. The 3d-protein complex displayed a relatively narrow RMSD distribution, consistent with restricted backbone motion, which may correlate with its comparatively weaker binding interactions. Although transient RMSD spikes were observed in some trajectories, these fluctuations were short-lived and did not reflect any irreversible structural destabilization.

Fig. 7. Molecular dynamics analysis of complexes 3a–f. RMSD profiles (Chart – A), residue-wise RMSF values (Chart – B), radius of gyration (R_g) (Chart – C), and solvent-accessible surface area (SASA) (Chart – D).

Local flexibility was further examined through RMSF analysis (Fig. 7 – Chart B). All systems exhibited higher fluctuations at the N-terminal region and solvent-exposed loop segments, while the structured core of the protein remained comparatively rigid. This behaviour was consistent across the apo and ligand-bound systems, indicating that ligand binding did not induce unfavourable local distortions. Notably, complexes with 3a, 3eS, and 3f demonstrated slightly reduced residue fluctuations near the binding site, suggesting a stabilizing effect on neighbouring amino acid residues. Conversely, complexes with 3b and 3c showed modest increases in local flexibility in these regions, in agreement with their higher RMSD values and weaker MM–PBSA binding energies.

Global protein compactness was assessed by analyzing the radius of gyration (R_g) (Fig. 7 – Chart C). Complexes with 3a and 3b exhibited slightly reduced R_g values compared to the apo protein, indicating a modest tightening of the overall structure upon ligand binding. In contrast, complexes with 3c and 3f showed minor increases in R_g fluctuations; however, these remained within normal limits and did not suggest large-scale conformational rearrangements. The 3eR complex closely followed the apo protein profile, further supporting a stable binding mode without perturbation of global protein architecture.

Changes in solvent exposure were evaluated through SASA analysis (Fig. 7 – Chart D). All ligand-bound complexes displayed SASA values comparable to those of the apo protein, fluctuating within a narrow range, indicating that ligand binding did not significantly alter the global solvent accessibility of the protein surface. Complexes with 3a, 3eS, 3eR, and 3f closely tracked the apo SASA profile, while the 3d complex showed moderate yet acceptable variability. The most pronounced deviations were observed for 3b, which exhibited several short-lived SASA spikes corresponding to transient increases in surface exposure. These events were reversible and did not indicate unfolding or structural destabilization. Overall, the SASA results confirm that the protein maintains its global surface characteristics across all simulated complexes.

The potential energy profiles confirmed the overall stability of the simulated systems (Fig. 8 – Chart A). The apo protein equilibrated at approximately −6 × 10⁵ kJ mol⁻¹, while the ligand-bound complexes stabilized near −4 × 10⁵ kJ mol⁻¹. Importantly, no systematic drift or large fluctuations were observed in any trajectory, demonstrating that ligand binding does not induce energetic instability and that all simulations reached and maintained equilibrium.

Fig. 8. Molecular dynamics analysis of complexes 3a–f: potential energy (Chart – A) and number of hydrogen bonds (Chart – B).

Hydrogen-bond analysis further revealed that all systems maintained stable interaction networks throughout the simulation period (Fig. 8 – Chart B). Most ligand–protein complexes consistently formed three to five hydrogen bonds, indicating persistent stabilizing contacts within the binding site. Occasional transient increases in hydrogen-bond numbers were attributed to temporary side-chain rearrangements or water-mediated interactions rather than permanent structural changes. Variations observed at the lower end of the hydrogen-bond distribution among ligands reflect differences in interaction lifetimes and are consistent with the RMSD trends discussed above.

Taken together, these results demonstrate that the protein preserves its structural integrity across all ligand-bound states. While the ligands differ in their ability to locally stabilize residues within or near the binding pocket, none induced protein unfolding or large-scale conformational rearrangements. These findings support the suitability of the cholic acid amide derivatives as structurally compatible ligands for the ATP-binding site of DNA gyrase and reinforce the reliability of the docking and MD-based interaction analyses.

3.6. MM-PBSA calculations

MM-PBSA calculations were performed on the production trajectories to quantify the relative binding affinities of ligands 3a–f (Table 2). The calculated total binding free energies (ΔG_TOTAL) ranked the ligands as follows: 3f (−40.80 kcal mol⁻¹) > 3eR (−39.08 kcal mol⁻¹) > 3eS (−35.75 kcal mol⁻¹) > 3a (−32.87 kcal mol⁻¹) > 3c (−28.48 kcal mol⁻¹) > 3b (−16.49 kcal mol⁻¹) ≈ 3d (−15.78 kcal mol⁻¹). This ranking was consistent throughout the simulation window, with no systematic drift in the instantaneous binding energies and only high-frequency fluctuations characteristic of frame-wise MM-PBSA analysis.

Table 2. MM-PBSA binding energies of ligands 3a–f^a.

Ligand	ΔVDWAALSb	ΔEELb	ΔEGBb	ΔESURFb	ΔGGASb	ΔGSOLVb	ΔTOTALb
3a	−42.05 ± 0.04	−19.06 ± 0.10	34.25 ± 0.08	−6.01 ± 0.01	−61.11 ± 0.10	28.24 ± 0.08	−32.87 ± 0.04
3b	−25.55 ± 0.11	−8.49 ± 0.10	21.03 ± 0.12	−3.49 ± 0.01	−34.03 ± 0.17	17.54 ± 0.11	−16.49 ± 0.08
3c	−41.10 ± 0.04	−16.83 ± 0.08	35.28 ± 0.07	−5.83 ± 0.01	−57.93 ± 0.09	29.45 ± 0.07	−28.48 ± 0.05
3d	−21.54 ± 0.09	−8.53 ± 0.09	17.16 ± 0.08	−2.87 ± 0.01	−30.07 ± 0.11	14.29 ± 0.08	−15.78 ± 0.06
3eS	−37.40 ± 0.03	−27.77 ± 0.08	34.56 ± 0.06	−5.14 ± 0.00	−65.17 ± 0.08	29.42 ± 0.06	−35.75 ± 0.04
3eR	−37.68 ± 0.03	−36.20 ± 0.08	39.90 ± 0.06	−5.10 ± 0.00	−73.88 ± 0.08	34.80 ± 0.06	−39.08 ± 0.04
3f	−39.69 ± 0.04	−35.34 ± 0.10	40.18 ± 0.08	−5.95 ± 0.00	−75.03 ± 0.11	34.23 ± 0.08	−40.80 ± 0.06

^aValues are presented as mean ± SD.

^bkcal mol⁻¹. ΔVDWAALS: van der Waals interaction energy, ΔEEL: electrostatic interaction energy, ΔEGB: polar solvation free energy calculated via the Poisson–Boltzmann model, ΔESURF: nonpolar solvation energy based on solvent-accessible surface area, ΔGGAS: total gas-phase energy, ΔGGAS = ΔVDWAALS + ΔEEL, ΔGSOLV: total solvation energy, ΔGSOLV = ΔEGB + ΔESURF, ΔTOTAL: total binding free energy, ΔTOTAL = ΔGGAS + ΔGSOLV.

Energy decomposition revealed that favorable gas-phase interactions (ΔG_GAS = ΔE_vdW + ΔE_elec) were the primary contributors to ligand binding. van der Waals interactions dominated stabilization across the compound series, with ΔE_vdW values ranging from approximately −21 to −42 kcal mol⁻¹. Electrostatic contributions were particularly significant for the strongest binders (3f, 3eS and 3eR) exhibiting large negative ΔE_elec values (approximately −28 to −36 kcal mol⁻¹). The combined effect of these interactions resulted in highly favorable ΔG_GAS values (≈−73 to −75 kcal mol⁻¹) for the top-ranked ligands. In contrast, compounds 3b and 3d showed weaker van der Waals and electrostatic contributions, leading to less favorable gas-phase interaction energies and reduced overall binding affinity.

Solvation effects opposed binding in all systems, primarily due to the polar solvation term (ΔG_GB), whereas the nonpolar surface contribution (ΔG_SURF) provided only minor stabilization. For moderate and weak binders, the solvation penalty offset a larger fraction of the favorable gas-phase interactions, explaining the intermediate affinities of 3a and 3c and the low binding energies observed for 3b and 3d. Thus, the balance between gas-phase stabilization and solvation penalties ultimately governed the final ΔG_TOTAL values.

Time-resolved binding free energy profiles demonstrated that all protein–ligand complexes remained energetically stable over the 100 ns simulation (Fig. 9). The instantaneous binding energies fluctuated within the expected range for MM-PBSA calculations, displaying high-frequency variations without upward drift or destabilizing spikes. The trajectories clustered closely, indicating sustained ligand binding throughout the simulation. Notably, ligands 3f, 3eR, 3eS, and 3c maintained consistently lower and more stable energy profiles, whereas 3b and 3d occupied higher-energy regions with larger fluctuations. This temporal behavior corroborates the averaged MM-PBSA results and confirms that the most favorable ligands not only bind more strongly but also form more persistent and dynamically stable interactions with the target enzyme.

Fig. 9. Binding energies of compounds 3a–f.

3.7. DFT analysis

3.7.1. Geometry optimization

Density functional theory (DFT) calculations were performed using the B3LYP functional in conjunction with the 6-311G(d,p) basis set. The B3LYP functional combined with the 6-311G(d,p) basis set was employed due to its unique compromise between computational cost and accuracy for the investigation of molecular geometries, molecular electrostatic potentials, frontier molecular orbitals, and global reactivity parameters. This level of theory has been extensively and effectively applied to the electronic structure analysis of newly synthesized organic compounds and is reliable for comparative studies of molecular properties.

The optimized geometries of compounds 3a–f, whose corresponding numbered two-dimensional structures are shown in Fig. 10, converged to highly stable molecular conformations.

Fig. 10. Optimized geometries of compounds 3a–f at B3LYP/6-311G(d,p).

Geometry optimization resulted in root-mean-square (RMS) forces on the order of 10⁻⁶ Hartree·Bohr⁻¹ and maximum forces below 10⁻⁵ Hartree·Bohr⁻¹, values that are significantly more stringent than typical default convergence thresholds (Table 3).⁸⁰ These results indicate the attainment of high-quality local minima on the potential energy surface (PES), suggesting that the optimized structures correspond to robust, low-energy molecular configurations.⁸¹

Table 3. Computed total energies, dipole moments, RMS, cartesian forces, and maximum cartesian forces for compounds 3a–f at the B3LYP/6-311G(d,p).

Compounds	Total energya	Dipole momentb	RMS cartesian forcec	Maximum cartesian forcec
3a	−1640.96	7.82	1.00 × 10−6	1.10 × 10−5
3b	−2190.58	12.79	2.00 × 10−6	1.60 × 10−5
3c	−1565.72	7.56	1.00 × 10−6	9.00 × 10−6
3d	−1488.50	7.70	1.00 × 10−6	4.00 × 10−6
3e	−1680.30	9.52	9.00 × 10−6	6.50 × 10−5
3f	−1527.84	10.49	1.00 × 10−6	4.00 × 10−6

^aHartrees.

^bDebye.

^cHartrees Bohr⁻¹.

Analysis of the total electronic energies revealed differences in relative molecular stability across the series, with compound 3b exhibiting the lowest total energy (−2190.58 Hartree) and compound 3d the highest (−1488.50 Hartree). The calculated dipole moments ranged from 7.56 to 12.79 debye, reflecting substantial variation in molecular polarity among the derivatives. It should be noted, however, that the reported structures correspond to local minima rather than global energy minima, and that additional conformational sampling may be required for highly flexible systems. Nevertheless, the tight convergence criteria achieved during optimization indicate that these geometries are reliable and well suited for subsequent electronic structure analyses, molecular docking, and binding free energy calculations.

3.7.2. Frontier molecular orbitals analysis

Frontier molecular orbital (FMO) analysis revealed that substituent effects play a decisive role in governing the electronic properties and predicted reactivity of compounds 3a–f, resulting in marked differences in electron-donating and electron-accepting behavior across the series (Fig. 11).

Fig. 11. Frontier molecular orbital of 3a–f at B3LYP/6-311G(d,p).

The calculated HOMO energies ranged from −6.10 to −7.28 eV, indicating relatively modest variations in electron-donor strength among the derivatives. In contrast, the LUMO energies exhibited a broader distribution (−0.85 to −3.21 eV), reflecting stronger substituent-dependent modulation of electron-acceptor capacity.

Consequently, the HOMO–LUMO energy gaps (ΔE) spanned from 4.05 to 7.11 eV. Compound 3b displayed the narrowest gap, suggesting higher electronic reactivity, increased polarizability, and a greater propensity for charge-transfer interactions. In contrast, compound 3f exhibited the widest gap, indicative of enhanced electronic stability and reduced charge-transfer character. Visualization of the frontier orbitals revealed compound-specific electronic distributions. In 3a, both the HOMO and LUMO are predominantly localized on the anisole–amine fragment. For 3b, the frontier orbitals are delocalized over the nitro- and chloro-substituted aromatic ring, consistent with the strong electron-withdrawing nature of these substituents. In compounds 3c–e, the steroidal core contributes minimally to the frontier orbitals, with electron density largely confined to the appended substituents. Conversely, in 3f, the HOMO is mainly localized on the steroid backbone, while the LUMO shifts toward the attached substituent, suggesting a more pronounced intramolecular charge-transfer pathway, and decreasing the hydrogen bonding of amide group.

Across the entire series, HOMO electron density is primarily associated with aromatic regions, indicating potential susceptibility toward electrophilic attack, whereas LUMO density is concentrated around electron-withdrawing functionalities, identifying favorable sites for nucleophilic interactions. Taken together with the calculated dipole moments and optimized geometries, these FMO characteristics demonstrate that substituent electronics strongly influence both the directionality and magnitude of electron flow in compounds 3a–f, thereby shaping their chemical reactivity and potential binding behavior toward biological targets.

3.7.3. Global reactivity descriptors

The calculated ionization potentials (I) and electron affinities (A) closely reflect the trends observed for the HOMO and LUMO energies across the series (Table 4). Compound 3b exhibits the highest electron affinity combined with a relatively low ionization potential, accounting for its narrow HOMO–LUMO gap and enhanced electronic reactivity. In contrast, compounds 3e and 3f display higher ionization potentials, consistent with lower HOMO energies and a reduced tendency to donate electron density. The global descriptors electronegativity (χ) and chemical potential (µ) further emphasize the strong electron-withdrawing character of 3b (χ = 5.24), whereas the remaining compounds fall within a moderate range (χ = 3.5–3.9).

Table 4. Global reactivity descriptors of compounds3a–f^a.

Parameters	Equations	3a	3b	3c	3d	3e	3f
HOMO (eV)		−6.10	−7.26	−6.84	−6.86	−7.05	−7.28
LUMO (eV)		−0.85	−3.21	−0.66	−0.20	−0.79	−0.16
ΔEHOMO–LUMO (eV)		5.25	4.05	6.18	6.66	6.26	7.11
I	I = −EHOMO	6.10	7.26	6.84	6.86	7.05	7.28
A	A = −ELUMO	0.85	3.21	0.66	0.20	0.79	0.16
χ		3.47	5.24	3.75	3.53	3.92	3.72
M	µ = −(χ)	−3.47	−5.24	−3.75	−3.53	−3.92	−3.72
H		2.63	2.03	3.09	3.33	3.13	3.56
S		0.38	0.49	0.32	0.30	0.32	0.28
Ω		2.30	6.77	2.28	1.87	2.45	1.95
ω +		0.89	4.41	0.79	0.52	0.88	0.53
ω −		4.36	9.64	4.54	4.05	4.80	4.25
S		0.19	0.25	0.16	0.15	0.16	0.14
ΔEback donation		−0.66	−0.51	−0.77	−0.83	−0.78	−0.89
N		0.44	0.15	0.44	0.53	0.41	0.51
ΔNmax		1.32	2.59	1.21	1.06	1.25	1.05
σ 0		0.19	0.25	0.16	0.15	0.16	0.14

^a I = Ionization energy, A = electron affinity, χ = electronegativity, µ = chemical potential, η = chemical hardness, S = chemical softness, ω = electrophilicity index, ω⁺ = electron accepting capability, ω⁻ = electron donating capability, s = global softness, N = nucleophilicity index, ΔN_max = additional electronic charge, σ₀ = optical softness.

Chemical hardness (η) values indicate that 3f is the hardest species (3.56 eV), in agreement with its wide HOMO–LUMO gap and enhanced electronic stability, while chemical softness (S) is greatest for 3b and lowest for 3f, confirming that 3b is the most polarizable and chemically responsive compound in the series. Consistently, the electrophilicity index (ω) reaches its maximum for 3b (6.77), highlighting its strong propensity to accept electron density. Conversely, nucleophilicity-related descriptors (ω⁻, N, and ΔN_max) indicate that compounds 3a, 3c, 3d, and 3f possess comparatively stronger electron-donating character than 3b. Back-donation energy values follow a similar trend, with 3f showing the most negative contribution, indicative of greater electronic stabilization and lower reactivity.

Overall, these global reactivity descriptors identify 3b as the most electrophilic and chemically soft member of the series, driven by its high electron affinity and narrow energy gap, whereas 3f and 3d emerge as the least reactive compounds due to their high hardness and low softness. Collectively, these parameters provide a mechanistic rationale for the observed variations in predicted reactivity and binding tendencies among the cholic acid amide derivatives 3a–f.

3.7.4. Molecular electrostatic potential surface

The molecular electrostatic potential (MEP) surfaces of compounds 3a–f show distinct patterns of charge separation that align well with their optimized dipole moments (Fig. 12).

Fig. 12. Molecular electrostatic potential surface of compounds 3a–f.

Compounds 3a and 3b display moderately polarized surfaces, with negative potential localized around heteroatom-rich regions, consistent with their comparatively lower dipole moments. Structures 3c–e exhibit broader and deeper negative potential zones, indicating stronger intramolecular polarization and reflecting the rise in dipole moment across this subset. Among them, 3e presents the most intense electron-rich surface, supporting its larger dipole moment and suggesting an enhanced capacity to act as a nucleophilic or hydrogen-bond accepting site. Compound 3d also shows pronounced negative potential around electronegative centers, in agreement with its elevated dipole moment and expected reactivity toward electrophilic species. In contrast, 3f features a more evenly distributed potential surface that matches its moderate dipole moment and implies weaker site-specific reactivity.

The MEP analysis provides an electronic rationale for the binding modes and energetic trends observed in the docking and MM-PBSA studies. In compounds 3a–f, regions of negative electrostatic potential are predominantly localized around the amide carbonyl oxygen and adjacent heteroatoms, which coincide with the primary hydrogen-bonding interactions identified within the ATP-binding pocket of GyrB. For instance, the pronounced negative potential observed in compounds 3c and 3f around the amide functionality correlates well with their ability to form stabilizing hydrogen bonds with Gly73, Gly77, Thr138, and Ser93, as revealed by docking against the S. aureus and E. coli GyrB structures.

In addition, the intense electron-rich region in compound 3e is consistent with its hydrogen-bond interactions involving Ser93 and Thr138, supporting the role of localized negative potential in anchoring the ligand within the binding site. Conversely, compound 3f, which exhibits a more evenly distributed MEP surface, relies predominantly on van der Waals and hydrophobic contacts rather than strong directional electrostatic interactions—an observation that aligns with its MM-PBSA profile, where favorable ΔE_vdW contributions dominate binding despite a reduced electrostatic component. The comparatively weaker and more diffuse negative potential of compounds 3b and 3d is consistent with their reduced hydrogen-bond persistence and higher solvation penalties, explaining their less favorable total binding free energies.

Overall, the spatial correspondence between MEP minima and interacting GyrB residues highlights the importance of electrostatic complementarity in stabilizing ligand–protein complexes and provides a mechanistic link between electronic structure, binding energetics, and biological activity within the cholic acid amide series. The MEP maps revealed that regions of negative electrostatic potential were predominantly localized around the amide carbonyl oxygen atoms and hydroxyl groups of the cholic acid scaffold, indicating favorable sites for hydrogen bond acceptance with amino acid residues such as Asp49, Asp73, Gly77, Asp45, and Glu46 observed in the docking studies.

In addition, regions of positive electrostatic potential were mainly distributed around the amide N–H groups and hydroxyl hydrogen atoms, supporting their role as hydrogen bond donors within the ATP-binding pocket of DNA gyrase GyrB. Compound 3b, which exhibited strong electron-withdrawing substituents and the highest electrophilicity index, showed a more pronounced polarization of the MEP surface, consistent with its enhanced capacity for electrostatic interactions. Similarly, compounds 3a and 3c, which displayed favorable docking scores, presented well-defined electron-rich regions around the amide group that contributed to stable binding poses. These observations strengthen the proposed binding mechanism and demonstrate that the distribution of electrostatic potential significantly influences the stabilization of ligand–protein complexes, complementing the docking and MM-PBSA results.

3.7.5. ESP charges

The ESP-derived atomic charges of compounds 3a–f show a clear and consistent polarization pattern centered on the heteroatom-rich regions of each molecule, in line with both the MEP surfaces and dipole moment trends (Fig. 13).

Fig. 13. ESP-derived atomic charges for compounds 3a–f.

Oxygen and nitrogen atoms carry the most negative charges across the series, with values typically around −0.36 e for O4 and O10 and reaching as low as −0.71 to −0.72 e for O29, confirming their role as the dominant nucleophilic sites. Adjacent aromatic and substituted carbons show the strongest positive charge accumulation, such as C3 and C9, which remain above +0.43 e in all compounds and rise to +0.85–0.93 e at C19 depending on the substituent environment.

Compounds 3c and 3e display the sharpest charge separation, with more negative oxygen centers (O24 at −0.37 to −0.41 e) and highly polarized carbons such as C12 and C23, which increase to +0.32–0.73 e, form stronger and more persistent hydrogen bonds in docking simulations, consistent with their favorable electrostatic (ΔE_elec) contributions in MM-PBSA calculations. In particular, the highly negative O29 center in 3e (−0.71 to −0.72 e) aligns with its observed hydrogen-bond interactions with Ser93 and Thr138 in S. aureus GyrB, supporting the enhanced stabilization of the ligand within the ATP-binding site. In contrast, 3a and 3f show more moderate variations between electron-rich and electron-poor atoms, consistent with their lower dipole moments and less pronounced MEP features.

The MEP surfaces and ESP-derived atomic charges provide a clear electronic rationale for the binding modes and relative affinities observed in the docking and MM-PBSA analyses. Across compounds 3a–f, the most negative MEP regions and highest negative ESP charges are consistently localized on heteroatom-rich functionalities, particularly the amide carbonyl and hydroxyl oxygen atoms (e.g., O4, O10, and O29), which act as dominant hydrogen-bond acceptors during protein binding. These electron-rich sites correlate directly with the hydrogen-bonding interactions observed in the GyrB ATP-binding pocket, notably with residues such as Gly77, Thr138, Ser93, and Asp45, which were recurrently involved in stabilizing ligand–enzyme complexes in both E. coli and S. aureus models. In addition, positively charged aromatic and substituted carbon centers (e.g., C3, C9, and C19) further complement this interaction pattern by engaging hydrophobic regions of the binding pocket, reinforcing ligand positioning.

Overall, the strong agreement between MEP extrema, ESP charge localization, docking interactions, and MM-PBSA energy decomposition demonstrates that electronic polarization and heteroatom charge density are key determinants of binding affinity and stability for this cholic acid amide series, offering a coherent structure-electrostatics-binding relationship that can guide future optimization.

3.7.6. NCI analysis

The NCI analysis of compounds 3a–f corroborates the structural trends identified from the MEP and ESP charge distributions and provides a rationale for the differences observed in their optimized geometries and energetic parameters. All derivatives exhibit green RDG isosurfaces, indicative of dispersion-dominated stabilization across both aromatic and aliphatic regions. Localized red regions are observed near sterically congested substituents, reflecting repulsive interactions that become more pronounced in the more heavily substituted derivatives (Fig. 14).

Fig. 14. RDG isosurface from NCI analysis, mapped with sign(λ₂)ρ, showing attractive, repulsive and weak dispersion interactions of compounds 3a–f.

These features are further evidenced in the RDG versus sign(λ₂)ρ scatter plots (Fig. 15), which display a dense population of points at small negative sign(λ₂)ρ values corresponding to weak attractive interactions, alongside a broader distribution at positive values associated with steric repulsion. Bulkier compounds, such as 3d and 3e, show more intense positive sign(λ₂)ρ contributions, whereas 3a and 3b exhibit relatively higher densities in the weakly attractive region, suggesting stronger dispersion interactions.

Fig. 15. RDG vs. electron density scatter plot illustrating the distribution and nature of non-covalent interactions in the system of compounds 3a–f.

Furthermore, the green RDG isosurfaces across the steroidal backbone and aromatic substituents, highlights the key role of noncovalent dispersion interactions in anchoring the cholic acid scaffold within the hydrophobic regions of the GyrB binding site. These dispersion contacts align spatially with hydrophobic residues lining the ATP-binding pocket, while localized red regions near bulky substituents in compounds such as 3d and 3e reflect steric congestion that correlates with increased RMSF values and less favorable solvation penalties. Notably, compounds with balanced electrostatic complementarity and dispersion stabilization, such as 3e and 3f, achieved the most favorable overall MM-PBSA energies, whereas molecules dominated by steric repulsion or weaker electrostatic gradients (e.g., 3b and 3d) showed reduced binding affinity.

Collectively, the convergence of MEP, ESP, NCI, docking, and MM-PBSA analyses underscores that optimal GyrB inhibition in this series arises from a synergistic interplay between localized electrostatic interactions at the amide functionality and extensive van der Waals contacts provided by the cholic acid framework.

3.7.7. ADMET predictions

In silico ADMET profiling of compounds 3a–f revealed distinct trends across absorption, distribution, metabolism, excretion, and toxicity parameters that complement the experimental and computational binding analyses (See SI). Predicted gastrointestinal absorption was high for five of the six derivatives, whereas compound 3b exhibited the lowest absorption, consistent with its higher topological polar surface area (TPSA) and reduced Caco-2 permeability.

Predicted Caco-2 permeability varied across the series, with compound 3c showing the highest permeability (log P_app = 1.015 × 10⁻⁶ cm s⁻¹) and 3b the lowest (0.646 × 10⁻⁶ cm s⁻¹), in agreement with the increased polarity and charge localization observed in its MEP and ESP analyses. All compounds were predicted to be P-glycoprotein substrates, while only 3e showed potential P-gp inhibitory behavior, which may influence intracellular exposure. Blood–brain barrier penetration was negligible for all derivatives, consistent with their molecular weights and polar surface areas.

Plasma protein-binding predictions indicated moderate to high binding across the series, with fraction unbound (F_u) values ranging from 0.020 to 0.118. Compounds 3d and 3f exhibited the highest unbound fractions, whereas 3c showed the lowest, suggesting stronger plasma interactions that may limit its systemic availability. The predicted steady-state volume of distribution (V_Dss) ranged from −0.14 to +0.63 log L kg⁻¹, with compound 3e displaying the greatest tissue distribution, consistent with its higher dipole moment and more pronounced MEP polarization. Metabolic liability predictions indicated that all derivatives are CYP3A4 substrates without inhibitory potential, while CYP2C19 substrate activity was predicted for all compounds except 3e. Predicted clearance values ranged from −0.223 to 0.787 log mL min⁻¹ kg⁻¹, with most compounds exhibiting estimated half-lives below 3 h, except for 3d and 3f, which showed comparatively longer half-life predictions.

Toxicity assessments predicted no AMES mutagenicity for any compound. However, hepatotoxicity liability was identified for compounds 3a, 3c, 3d, and 3e, whereas 3b and 3f were predicted to be non-hepatotoxic. Although none of the compounds were predicted to inhibit hERG class I channels, potential class II hERG liability was observed for 3d, 3e, and 3f, indicating the need for further cardiac safety evaluation. Drug-likeness analysis revealed a single Lipinski rule violation (molecular weight >500 Da) for compounds 3a, 3b, and 3e.⁸² TPSA values ranged from 89.8 to 135.6 Ų, and consensus log P values from 2.50 to 4.06, supporting overall moderate oral drug-like properties.

Taken together, these predictions highlight both opportunities and limitations within the compound series. Compounds 3c and 3e combine favorable permeability and solubility with strong docking and MM-PBSA binding profiles; however, their predicted hepatotoxicity represents a significant concern. In contrast, compounds 3b and 3f exhibit improved hepatic safety, although the low absorption of 3b and the predicted hERG class II liability of 3f may constrain further development. Based on the integrated biological, docking, molecular dynamics, MM-PBSA, and ADMET analyses, compounds 3c and 3f emerge as prioritized candidates for further optimization. Recommended next steps include in vitro Caco-2 and PAMPA assays to validate permeability, liver microsomal and hepatocyte assays to assess metabolic stability and hepatotoxicity, hERG electrophysiological studies to evaluate cardiac risk, and plasma protein-binding experiments. Subsequent in vivo pharmacokinetic and safety studies will be required to validate these computational predictions prior to advancement.

4. Conclusion

This study reports the design and synthesis of cholic acid-based amide derivatives (3a–f) using a one-pot strategy. Biological evaluation underscored antioxidant capacity across the synthetized compounds, with select compounds showing enhanced DPPH radical scavenging activity, likely attributable to favorable electronic features imparted by specific amide substituents.

Antibacterial screening demonstrated a trend of preferential inhibition against S. aureus relative to E. coli, aligning with the known differential permeability barriers of Gram-positive versus Gram-negative bacterial envelopes. Notably, aromatic amide derivatives emerged as the most active antibacterial agents, highlighting the impact of amine substituent identity on bioactivity.

The integration of computational methods provided mechanistic insight into the observed biological profiles. Molecular docking revealed favorable engagement of the synthesized hybrids within the ATP-binding pocket of DNA gyrase, with key stabilizing interactions identified for the more active compounds. Subsequent MD simulations confirmed the dynamic stability of these complexes, while MM-PBSA analyses reinforced the relative binding affinities observed in docking. Complementary DFT and ADMET analyses suggested acceptable electronic characteristics and drug-likeness, supporting the potential of selected derivatives for further optimization.

The combined synthetic, biological, and computational evidence establishes a solid foundation for future efforts focusing on detailed mechanism elucidation, structure–activity relationship expansion, and in vivo antibacterial evaluation, ultimately guiding the rational design of improved antimicrobial agents derived from bile acid scaffolds.

Conflicts of interest

There are no conflicts to declare.

Data availability

The data related to this research article is included in the supplementary information (SI). Supplementary information is available. See DOI: https://doi.org/10.1039/d6ra03651a.