Exploring the Inhibitory Effects of Some Detergents on Mycobacterium avium subspecies paratuberculosis with Specific Focus on Zwitterionic Sulfobetaines

Abstract

Mycobacterium avium subspecies paratuberculosis (MAP) infects ruminants with Johne’s disease and is also involved in human inflammatory bowel syndrome, such as Crohn’s disease. With increasing drug resistance and zoonosis, there is a critical need for novel antimicrobial compounds having the potential to inhibit disease-causing bacteria. The present work examines the antimycobacterial activity of six detergent-like compounds, among which four are sulfobetaine-based zwitterionic detergents: amidosulfobetaine-14 (ASB-14), lauryl sulfobetaine (DDAPS), caprylyl sulfobetaine (D4266), and sulfobetaine 3-14 (SB3-14). Molecular docking and molecular dynamics (MD) simulations demonstrated higher binding affinities of ASB-14 and SB3-14 towards the carveol dehydrogenase (CD), catalase-related peroxidase (CRP), and dephospho-CoA kinase (DPCK) of MAP than the other compounds. MD simulation analysis showed less ligand root mean square deviation (RMSD) values for ASB-14 than SB3-14. MD simulations also revealed that certain regions in CRP and DPCK are perturbed to a greater extent upon binding to SB3-14 than ASB-14. Further, ADME studies and PASS predictions suggest good oral bioavailability and broad-spectrum bioactivity of both sulfobetaines, with minimal predicted toxicity for ASB-14, highlighting their efficacy as drug targets. Resazurin Microtiter Assay (REMA) indicates that SB3-14 exhibits inhibitory activity with a low MIC₅₀ value of 0.0937 mg/mL, whereas ASB-14 inhibits MAP at 0.75 mg/mL. The computational and experimental findings of this study allude that the viability of MAP can be affected by the zwitterionic compounds lacking aromatic groups. Collectively, sulfobetaines such as ASB-14 and SB3-14 are promising multitarget inhibitors of MAP, offering possibilities to limit zoonotic transmission for One Health interventions.

1. Introduction

Mycobacterium avium subspecies paratuberculosis (MAP) is an etiological agent of chronic granulomatous intestinal infection, i.e., Johne’s disease, in both domestic and wild animals. Johne’s disease can cause a significant threat to the population of cows and buffaloes worldwide, leading to reduced productivity, animal wasting, and even death. This is because the carrier animals shed MAP in their feces and milk, infecting surrounding animals, calves, and the farm environment. Estimating the true incidence of Johne’s disease is difficult since most infected cattle are asymptomatic. Additionally, there are challenges in diagnosing cows with early infection, thereby making treatment more challenging. In humans, MAP has been linked to Crohn’s disease and ulcerative colitis, which can result in colorectal cancer.

MAP is a highly resilient bacterium that can survive for extended periods, potentially many years. Various survival mechanisms have been identified in MAP, including a thick, impermeable cell wall, intracellular enzymes, efflux pumps, and adaptive mechanisms. This is because Mycobacteria spp. cell wall contains an inner phospholipid bilayer, an outer layer of α-alkyl, β-hydroxy mycolic acids, and other long-chain lipids. It has been estimated that “lipids” constitute nearly 60% of cellular dry weight. These lipid classes and subclasses consist of different combinations of aliphatic chains with the same core structure, but differing in chain length, saturation, or substitution of acyl or alkyl chains. The functional role of Mycobacteria spp. cell wall includes acting as an exchange barrier, metabolic activity, and immunological response to the intracellular environment of host macrophages. The dynamic changes in the lipid content facilitate Mycobacteria spp. to endure stressful conditions and inflict pathogenicity in the host. , Although Johne’s disease is not considered a direct zoonotic disease, shedding of the causative pathogen through milk, feces, and water sources may facilitate indirect human exposure. Studies reveal that MAP may be found in dairy products, including pasteurized and raw milk from sheep, goats, and cows; therefore, the risks for zoonosis cannot be neglected. Furthermore, the zoonotic potential of this bacterium and its capability of infecting a wide range of hosts underscore the importance of appropriate precautionary measures. Vaccines are available, however, only under strict regulation and specific conditions. Vaccination trials have been hindered by high costs and the practical challenges in developing countries.

World Organisation for Animal Health (WOAH) states that there is no known treatment for this disease, but it can be controlled through good sanitation practices, management techniques, and surveillance of adult animals. Treating Johne’s disease in animals is not practical using the traditional “test and cull” approach, as it is expensive and ineffective in controlling the disease. Therefore, it is important to develop noninvasive approaches for treating the disease. One way is to mitigate the load or inhibit MAP growth to reduce the risks of the disease in humans as well as animals. Numerous antimicrobial substances, mostly synthetic antibiotics, have been investigated and often failed in their ability to inhibit the growth of this slow-growing environmental pathogen.

Antibiotic discovery and development for “nontuberculous mycobacteria” is difficult due to innate antibiotic resistance, slow growth, and phagocytic cell residence. A few other challenges include species/strain selection, frequent colony switching, biofilm formation, and cell aggregation. Therefore, developing new and more efficient therapies to combat MAP is a crucial area of research, and there is a necessity to revisit the available therapeutic options. Surfactants that dissolve lipid membranes are widely used as antibacterial agents. An extract of Allium sativum Linn. containing linear alkyl benzene sulfonates (LABS) was found to inhibit a nonvirulent strain (H37Ra) of Mycobacterium tuberculosis (MTB). Another compound, mono-n-octyl phthalate (MOP), also has been shown to inhibit H37Ra in vitro. The antimicrobial effect of LABS, MOP, and dioctyl phthalate (DOP) on MTB H37Ra is only reported so far. Therefore, we hypothesized to investigate if these compounds could also inhibit pathogenic MAP from growing in vitro. Our efforts also include investigating whether some detergent compounds such as sodium dodecyl sulfate (SDS), sulfobetaines, namely, amidosulfobetaine-14 (ASB-14), myristyl sulfobetaine (SB3-14), lauryl sulfobetaine (DDAPS), and caprylyl sulfobetaine (D4266) could be used to help control MAP. It was identified that LABS disrupt the structural integrity of the nonvirulent MTB cell membrane and facilitate the rupture of the cell wall.

We also elucidated the significance of the charge in exhibiting antibacterial activity. This idea stems from the role of isoniazid in killing mycobacteria, as it may become positively charged by taking up a proton. SDS is an anionic surfactant that denatures proteins. It inhibits both enveloped and nonenveloped viruses by solubilizing and denaturing their envelopes as well as capsid proteins. However, it lacks an aromatic group, has a single negative charge, and a long hydrocarbon chain. This makes SDS useful for determining whether the aromatic group is essential for inhibiting the growth of MAP. On the other hand, sulfobetaines are zwitterionic molecules with a positive charge and a negatively charged sulfonate group. They also contain a long hydrocarbon chain but lack an aromatic headgroup. Their potential as antibacterial agents depends on the alkyl chain length, and they are more effective against Gram-positive bacteria. Also, detergents are amphipathic compounds with a long hydrophobic carbon chain (tail) and a polar group (head). These long hydrocarbon chains congregate because of their hydrophobic interactions, and their polar group initiates hydrogen bonding with water molecules, forming micelles. These micelles are analogous to the biological membranes and not only are able to solubilize the bilayers but also the thick cell walls of bacteria. Therefore, studying sulfobetaines will help us to understand whether the aromatic group or positive charge has a role in inhibiting MAP growth. Without effective control programs in place, the bioload of MAP will be on the rise. Considering that billions of dairy animals and human beings exist in developing nations, the number of infected individuals could potentially run into millions. Therefore, the potential compounds, if identified, might further be used as lead molecules for drug development against MAP in infected animals, thereby improving disease management. In this study, the inhibitory roles of sulfobetaines were evaluated against different mycobacterial proteins. The efficacy and potential of these ligands were assessed by docking them to these mycobacterial proteins. In vitro experiments were also conducted to identify the best ligand, which was then compared with in silico experiments to evaluate its effectiveness in inhibiting the MAP.

2. Results and Discussion

2.1. Drug-Likeness Properties

Drug-like potential of ASB-14 and SB3-14 was assessed by evaluating key physicochemical and pharmacokinetic properties (Table ). First, the molecular masses of these two compounds (ASB-14: 434.32 Da and SB3-14: 363.60 Da) are less than 500 Da. Further, log P values of ASB-14 (2.30) and SB3-14 (2.66), suggest moderate lipophilicity, although both show low water solubility. Additionally, ASB-14 has 4 hydrogen bond acceptors and 1 donor, while SB3-14 has 3 acceptors with no hydrogen donor. Thus, both the compounds are adhering to Lipinski’s rule of five, suggesting favorable oral bioavailability. Molar refractivity of ASB-14 was slightly higher (121.93) compared with SB3-14 (104.51), indicating greater polarizability. The topological polar surface area (TPSA) values suggest good absorption potential for the compounds. Importantly, both compounds achieved a drug-likeness score of 0.55, indicating a promise for development as bioactive molecules.

1. Drug-Likeness Properties of Sulfobetaines .

Drug-Likeness properties	ASB-14	SB3-14
Lipinski’s rule	yes	yes
Molecular weight	434.32	363.60
log P o/w	2.30	2.66
log S	–4.58	–4.87
H-bond acceptor	4	3
H-bond donor	1	0
Ghose	no	no
Egan	yes	yes
Molar refractivity	121.93	104.51
TPSA	94.68	65.58
Drug-Likeness score	0.55	0.55

^alog P o/w: logarithm of octanol/water partition coefficient; log S: logarithm of solubility; TPSA: topological polar surface area.

2.2. Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADME/T)

The ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties of ASB-14 and SB3-14 were assessed for their pharmacokinetics and safety, which are as follows: Both compounds showed high human intestinal absorption and neither were substrates or inhibitors of P-glycoprotein, indicating low efflux-related bioavailability issues (Table ). These detergent compounds do not cross the blood–brain barrier (BBB), indicating plausible fewer side effects on the central nervous system (CNS). ASB-14 is predicted to inhibit CYP3A4, a key enzyme, while SB3-14 does not, possibly offering a metabolic safety advantage. ASB-14 and SB3-14 exhibited half-lives of 0.4 and 0.5 h, respectively. Toxicity profiling indicates that SB3-14 had lower mutagenic potential than ASB-14, but both are capable of blocking the hERG receptors. The risk for drug-induced liver injury was minimal for both, although ASB-14 had a slightly higher score. Overall, both compounds showed acceptable ADMET properties; SB3-14 had a more favorable metabolic and hepatotoxicity profile compared with ASB-14.

2. ADME Properties of Sulfobetaines .

	Properties	ASB-14	SB3-14
Absorption	Pgp-inhibitor	non-inhibitor	non-inhibitor
	Pgp-substrate	non-substrate	non-substrate
	Human intestinal absorption	high	high
Distribution	Blood–brain barrier	negative	negative
Metabolism	CYP450 1A2 inhibitor	non-inhibitor	non-inhibitor
	CYP450 3A4 inhibitor	yes	no
	CYP450 2C9 inhibitor	no	no
	CYP450 2C19 inhibitor	no	no
	CYP450 2D6 inhibitor	no	no
	Skin permeation	–5.09	–4.12
Excretion	t1/2	0.469	0.507
Toxicity	hERG blockers	0.632	0.706
	DILI (drug-induced liver injury)	0.002	0
	AMES (mutagenicity)	0.035	0.018
	Rat oral acute toxicity	0.321	0.619
	Human hepatotoxicity	0.474	0.069
	Neurotoxicity	0.34	0.675

^aPgp: P-glycoprotein; CYP450: Cytochrome P450.

2.3. Prediction of Activity Spectra for Substances (PASS) Analysis

The LD₅₀ values for ASB-14 and SB3-14 are 400 and 660 mg/kg, respectively, making them fall in toxicity class 4. PASS analysis also suggests that SB3-14 may have potential adverse effects (Pa > 0.7), such as hematotoxicity, anemia, shivering, and reproductive failure, which are not observed with ASB-14 (Table ). However, both compounds possess promising pharmacological properties; ASB-14 inhibited glyceryl-ether monooxygenase, ceramide glucosyltransferase, and phosphatidylserine decarboxylase (Table ). SB3-14 demonstrated broader activities, including inhibition of cutinase, carnosine synthase, and carboxypeptidase Taq, as well as radioprotective, antianginal, and antisecretory effects. ASB-14, on the other hand, has a diverse activity profile, including radioprotective and antianginal activity, while SB3-14 displayed strong inhibition of lipid-associated enzymes, which may affect bacterial membrane biosynthesis. These findings highlight the pharmacological potential of both compounds and the need for further validation of their toxicity profiles.

3. PASS Analysis for Toxicity Properties of Sulfobetaines.

		ASB-14		SB3-14
		Predicted LD50: 400 mg/kg		Predicted LD50: 660 mg/kg
	Toxicity	Toxicity class: 4		Toxicity class: 4
S. No.		Pa	Pi	Pa	Pi
1	Anemia	-	-​	0.802	0.015
2	Hematotoxic	-​	-​	0.794	0.027
3	Shivering	-​	-​	0.802	0.037
4	Reproductive dysfunction	-​	-​	0.765	0.024
5	Thrombocytopoiesis inhibitor	0.786	0.007	-​	-

4. PASS Analysis for Biological Activity of Sulfobetaines .

		ASB-14		SB3-14
S. No.	Biological activity	Pa	Pi	Pa	Pi
1	Glyceryl-ether monooxygenase inhibitor	0.990	0.000	0.995	0.000
2	Ceramide glucosyltransferase inhibitor	0.954	0.000	0.905	0.000
3	Phosphatidylserine decarboxylase inhibitor	0.872	0.002	-​	-​
4	2-acylglycerol O-acyltransferase inhibitor	0.850	0.001	0.809	0.001
5	Coenzyme-B sulfethylthiotransferase inhibitor	0.839	0.001	0.889	0.001
6	Phospholipase A1 inhibitor	0.811	0.001	0.860	0.000
7	Galactolipase inhibitor	0.808	0.003	0.846	0.002
8	Acylcarnitine hydrolase inhibitor	0.779	0.016	0.911	0.004
9	Radioprotector	0.739	0.008	-​	-​
10	Anti-ischemic, cerebral	0.735	0.023	0.872	0.007
11	Mucositis treatment	0.731	0.046	-​	-​
12	CDP-glycerol glycerophosphotransferase inhibitor	0.718	0.022	-​	-​
13	Cutinase inhibitor	-​	-​	0.804	0.005
14	Carnosine synthase inhibitor	-​	-​	0.790	0.002
15	IgA-specific serine endopeptidase inhibitor	-​	-​	0.783	0.007
16	Alkylacetylglycerophosphatase inhibitor	-​	-​	0.781	0.011
17	Antianginal	-​	-​	0.751	0.006
18	Antisecretory	-​	-​	0.740	0.007
19	Carboxypeptidase Taq inhibitor	-​	-​	0.729	0.015
20	Mucomembranous protector	-​	-​	0.745	0.037
21	Hepatic disorders treatment	-​	-​	0.711	0.005
22	Macrophage colony-stimulating factor agonist	-​	-​	0.717	0.011
23	Sugar-phosphatase inhibitor	-​	-​	0.724	0.029
24	Lysine 2,3-aminomutase inhibitor	-​	-​	0.703	0.015
25	Exoribonuclease II inhibitor	-​	-​	0.705	0.016

^aPa: probability to be active; Pi: probability to be inactive.

2.4. Molecular Docking

Molecular docking was performed to evaluate the binding affinities and interactions of the sulfobetaines, viz, ASB-14 and SB3-14, with selected MAP target proteins, namely, carveol dehydrogenase (PDB ID: 3PGX), catalase-related peroxidase (PDB ID: 3E4W), and dephospho-CoA kinase (PDB ID: 6N39). Since 3-dimensional (3D) molecular structures of any membrane protein of MAP were not available, we could not carry out molecular docking of sulfobetaines on any membrane proteins of MAP. In PDB, we could get the 3D molecular structures of only cytosolic proteins of MAP and hence, we chose the above proteins for which molecular docking and simulation were carried out. Both ligands exhibit favorable binding energies, indicating strong and stable interactions with the respective target proteins. Among all of the proteins, ASB-14 displayed the most potent binding with CD (−11.09 kcal/mol), followed by CRP (−10.47 kcal/mol) and DPCK (−7.86 kcal/mol). Similarly, SB3–14 also shows consistent affinities, with binding energies for CD (−9.40 kcal/mol), CRP (−9.94 kcal/mol), and DPCK (−7.82 kcal/mol) (Table ). Detailed interaction analysis revealed that the complexes were stabilized through a combination of hydrogen bonds, salt bridges, alkyl-alkyl and π–alkyl interactions. Key interacting residues included Gly22, Val51, Asp46, and Gly114 in CD (Figures and ); Met90, Ala91, Arg70, and Tyr301 in CRP (Figures and ); both ASB-14 and SB3-14 form strong interactions with Asp 263 and Lys 367 in DPCK, indicating significant electrostatic interactions at the binding site of both the proteins (Figures and ). Docking studies also suggest that the quaternary ammonium nitrogen of all four sulfobetaine molecules has an ionic interaction with the cytoplasmic protein MAP-DPCK, a behavior not observed with other proteins (Figure ). Collectively, these results suggest that both ASB-14 and SB3-14 interact favorably with MAP proteins through multiple interactions, suggesting their potential as inhibitory candidates against Mycobacterium paratuberculosis.

5. Molecular Docking Results of MAP Proteins with Sulfobetaines.

S. No.	Protein	Ligands	Binding Energy (ΔG)	Ligand Efficiency	Bond Type	Interacting amino acids
1	Carveol dehydrogenase (PDB ID: 3PGX)	ASB-14	–11.09	–0.38	hydrogen bond	Val 51
					attractive charge	Asp 46
					carbon–hydrogen	Gly 22 and 114
					alkyl	Val 163, 211, Met 215, Pro 208
		SB3-14	–9.40	–0.39	carbon–hydrogen	Arg 25, Ala 49, Pro 50 and 59
					attractive charge	Asp 46
					alkyl	Val 163
2	Catalase-related peroxidase (PDB ID: 3E4W)	ASB-14	–10.47	–0.36	hydrogen bond	Met 90, Ala 91, Ser 304
					carbon–hydrogen	Leu 34, Tyr 301
					π-donor hydrogen	His 35
					alkyl	Ile 21, Val 300
		SB3-14	–9.94	–0.41	hydrogen bond	Arg 70, Ser 72, Ala 91
					carbon–hydrogen	Phe 277, Arg 308
					alkyl	Ile 21, Ala 33, Arg 32, 297, Leu 34, Phe 120 and 296, Tyr 301, Val 300
3	Dephospho-CoA kinase (PDB ID: 6N39)	ASB-14	–7.86	–0.27	hydrogen bond	Gly 246, Lys 259, Tyr 381
					attractive charge	Asp 263, Lys 385
					salt bridge	Lys 367
					alkyl	Phe 345, 349 and 389, Val 296, Ala 346
		SB3-14	–7.82	–0.33	hydrogen bond	Lys 259, Tyr 381
					carbon–hydrogen	Ser 247
					attractive charge	Asp 263, Lys 385
					salt bridge	Lys 367
					alkyl	Phe 345, 349 and 389, Val 245, Ala 346

^aResidues interacting with both ASB-14 and SB3-14 are shown in bold font.

1.

Molecular interaction analysis of MAP-carveol dehydrogenase with ASB-14 represented in (A) best binding position of the ligand with the protein; (B) Two-dimensional interaction showing hydrogen bonds, electrostatic, and hydrophobic interactions with key residues (GLY22, VAL51, ASP46, GLY114); (C) Hydrogen bond analysis (donor: purple; acceptor: green); (D) Solvent-accessible surface interaction highlighting the buried nature of the ligand within the hydrophobic cavity of the protein; (E) 3D representation showing optimal orientation and binding of ASB-14 within the catalytic pocket.

2.

Molecular interaction analysis of MAP-carveol dehydrogenase with SB3-14 represented in (A) best binding position of the ligand with the protein; (B) Two-dimensional interaction showing hydrogen bonds, electrostatic, and hydrophobic interactions with key residues (ARG25, ASP46, ALA49, PRO50, PRO59); (C) Hydrogen bond analysis (donor: purple; acceptor: green); (D) Solvent-accessible surface interaction highlighting the buried nature of the ligand within the hydrophobic cavity of the protein; (E) 3D representation showing optimal orientation and binding of SB3-14 within the catalytic pocket.

3.

Molecular interaction analysis of MAP-catalase-related peroxidase with ASB-14 represented in (A) best binding position of the ligand with the protein; (B) Two-dimensional interaction showing hydrogen bonds, electrostatic, and hydrophobic interactions with key residues (LEU34, HIS35, MET90, ALA91, TYR301, SER304); (C) Hydrogen bond analysis (donor: purple; acceptor: green); (D) Solvent-accessible surface interaction highlighting the buried nature of the ligand within the hydrophobic cavity of the protein; (E) 3D representation showing optimal orientation and binding of ASB-14 within the catalytic pocket.

4.

Molecular interaction analysis of MAP-catalase-related peroxidase with SB3-14 represented in (A) best binding position of the ligand with the protein; (B) Two-dimensional interaction showing hydrogen bonds, electrostatic, and hydrophobic interactions with key residues (ARG70, SER72, ALA91, PHE277, ARG308); (C) Hydrogen bond analysis (donor: purple; acceptor: green); (D) Solvent-accessible surface interaction highlighting the buried nature of the ligand within the hydrophobic cavity of the protein; (E) 3D representation showing optimal orientation and binding of SB3-14 within the catalytic pocket.

5.

Molecular interaction analysis of MAP-dephospho-CoA kinase with ASB-14 represented in (A) best binding position of the ligand with the protein; (B) Two-dimensional interaction showing hydrogen bonds, electrostatic, and hydrophobic interactions with key residues (GLY246, ASP263, LYS259, LYS367, LYS385, TYR381); (C) Hydrogen bond analysis (donor: purple; acceptor: green); (D) Solvent-accessible surface interaction highlighting the buried nature of the ligand within the hydrophobic cavity of the protein; (E) 3D representation showing optimal orientation and binding of ASB-14 within the catalytic pocket.

6.

Molecular interaction analysis of MAP-dephospho-CoA kinase with SB3-14 represented in (A) best binding position of the ligand with the protein; (B) Two-dimensional interaction showing hydrogen bonds, electrostatic, and hydrophobic interactions with key residues (SER247, ASP263, LYS259, LYS367, LYS385, TYR381); (C) Hydrogen bond analysis (donor: purple; acceptor: green); (D) Solvent-accessible surface interaction highlighting the buried nature of the ligand within the hydrophobic cavity of the protein; (E) 3D representation showing optimal orientation and binding of SB3-14 within the catalytic pocket.

7.

Schematic illustration of key interactions between all sulfobetaine ligands with MAP-dephospho-CoA kinase. Docking results show that the quaternary ammonium nitrogen atom and oxygen atom of all sulfobetaine compounds exhibit ionic interactions (red dotted lines) and hydrogen bond formation (green dotted lines) with the ASP263, LYS367, and LYS259 residues of the cytoplasmic MAP-DPCK protein, thereby enhancing its significance in binding and MAP-DPCK inhibition.

We also docked p-dodecyl benzene sulfonate (DBS: one type of LABS) on these target proteins, in which aromatic ring was found to have alkyl and sigma bonds with CD; π–π and alkyl bonds with CRP and no interaction was found with DPCK. However, the ΔG values (binding energy) were similar to those of sulfobetaines, but experimentally DBS did not show encouraging inhibition compared with that of sulfobetaines (see the Supporting Information).

2.5. Molecular Dynamics Simulations

Molecular dynamics simulations were performed to evaluate the structural stability and interaction dynamics of DPCK, CRP, and CD in complex with ASB-14 and SB3-14 detergent compounds. RMSD and RMSF analysis ensured that all complexes continued to be stable during the simulation, with SB3-14 showing lower backbone RMSD values and higher stability within binding sites, especially with CRP. Both the ligands preserved protein rigidity, with fluctuations primarily within loop areas. Radius of gyration and SASA analysis show ASB-14 complexes to be more compact, but with increased solvent exposure allowing for better interaction. Hydrogen bond analysis showed 1–5 bonds per complex, with SB3-14 having more consistent interactions and ASB-14 displaying intermittent, but stronger bonding. ΔG values (binding energy) indicate favorable contributions attributed to van der Waals and electrostatic interactions, particularly for the ASB-14-CRP complex (Table and Figures , , and ). In general, both ASB-14 and SB3-14 formed stable, energy-favored complexes with MAP target enzymes, indicating their promise as multitarget leads with complementary stability and flexibility profiles. Results of the molecular dynamics simulations and docking establish the conformational stability and resilience of these interactions during the simulation time.

8.

Molecular dynamics simulation of carveol dehydrogenase with both ligands is displayed in (A) root mean square deviation (RMSD) of CD-ASB14 and CD-SB3-14 complexes over time. CD-SB3-14 (black) shows high RMSD values, whereas CD-ASB14 maintains low RMSD; (B) Time evolution of ligand RMSD with respect to the protein for CD-ASB14 and CD-SB3-14. CD-ASB14 demonstrates lower and more consistent ligand RMSD values, suggesting stable ligand binding; (C) Root mean square fluctuation (RMSF) of protein residues for CD-ASB14 and CD-SB3-14 complexes. Both complexes have similar residue flexibility patterns; (D) Time-dependent radius of gyration of the two complexes. CD-SB3-14 maintains slightly higher Rg values, indicating more expansion; (E) SASA profiles for CD-ASB14 and CD-SB3-14 over time. CD-SB3-14 exhibits greater solvent accessibility; (F) Number of hydrogen bonds formed between the ligand and protein during the simulation. Both ligands generally maintain a favorable number of hydrogen bonds, but SB3-14 shows more sustained and consistent hydrogen bonding; (G) Comparison of different energy components (van der Waals, electrostatic, solvation, total binding energy) between CD-ASB14 and CD-SB3-14. Both complexes exhibit favorable binding energies.

9.

Molecular dynamics simulation of catalase-related peroxidase with both ligands is displayed in (A) root mean square deviation (RMSD) of CRP-ASB14 and CRP-SB3-14 complexes over time. Both complexes stabilize after initial fluctuations, with CRP-SB3-14 (black) showing low RMSD values; (B) Time evolution of ligand RMSD with respect to the protein for peroxidase-ASB14 and CRP-SB3-14. CRP-SB314 demonstrates lower and more consistent ligand RMSD values, suggesting stable ligand binding; (C) Root mean square fluctuation (RMSF) of protein residues for CRP-ASB14 and CRP-SB3-14 complexes. Both complexes have similar residue flexibility patterns; (D) Time-dependent radius of gyration of the two complexes. CRP-SB3-14 maintains slightly higher Rg values, indicating more expansion; (E) SASA profiles for CRP-ASB14 and CRP-SB3-14 over time. CRP-SB3-14 exhibits greater solvent accessibility; (F) Number of hydrogen bonds formed between the ligand and protein during the simulation. CRP-ASB14 complex consistently forms hydrogen bonds, while CRP-SB3-14 shows higher variability but generally remains within 2–5 bonds; (G) Comparison of different energy components (van der Waals, electrostatic, solvation, total binding energy) between CRP-ASB14 and CRP-SB3-14. Both complexes exhibit favorable binding energies.

10.

Molecular dynamics simulation of dephospho-CoA kinase with both ligands is displayed in (A) root mean square deviation (RMSD) of DPCK-ASB14 and DPCK-SB3-14 complexes over time. Both complexes stabilize after initial fluctuations, with DPCK-ASB14 (red) showing consistent low RMSD values, indicating greater structural stability of the protein–ligand complex; (B) Time evolution of ligand RMSD with respect to the protein for DPCK-ASB14 and DPCK-SB3-14. DPCK-ASB14 demonstrates lower and more consistent ligand RMSD values, suggesting stable ligand binding inside the protein pocket, whereas DPCK-SB3-14 shows greater fluctuations over time; (C) Root mean square fluctuation (RMSF) of protein residues for DPCK-ASB14 and DPCK-SB3-14 complexes. Both complexes have similar residue flexibility, with notable peaks corresponding to loop regions, but overall lower flexibility for DPCK-ASB14; (D) Time-dependent radius of gyration of the two complexes. DPCK-ASB14 maintains slightly higher Rg values, indicating more expansion; (E) SASA profiles for DPCK-ASB14 and DPCK-SB3-14 over time. DPCK-ASB14 exhibits greater solvent accessibility. (F) Number of hydrogen bonds formed between the ligand and protein during the simulation. DPCK-ASB14 complex consistently forms hydrogen bonds, while DPCK-SB3-14 shows higher variability but generally remains within 2–6 bonds; (G) Comparison of different energy components (van der Waals, electrostatic, solvation, total binding energy) between DPCK-ASB14 and DPCK-SB3-14. Both complexes exhibit favorable binding energies.

2.6. Anti-MAP Activity Detection by REMA Assay

Sulfobetaines are actually zwitterionic molecules, whereby they possess a positive charge due to the presence of a quaternary ammonium moiety, in addition to the negatively charged sulfonate group. Moreover, sulfobetaine molecules contain a long hydrocarbon chain, but they lack aromatic group. Therefore, the results from sulfobetaines were helpful to know the significance of the aromatic group and the positive charge for inhibiting MAP growth in vitro (Figure ). The antimycobacterial potential of six detergent compounds was evaluated using the Resazurin Microtiter Assay (Figure and Table S6). Absorbance was recorded after adding resazurin and incubating the plates for a further 24 h. Among all the compounds tested, ASB-14 and SB3-14 showed the strongest inhibitory activity, with an MIC₅₀ of 0.0937 mg/mL for SB3-14 and 0.75 mg/mL for ASB-14. Both compounds exhibited robust, dose-dependent inhibition rates, indicating their potential to disrupt MAP survival by affecting the bacterial membrane integrity.

11.

Schematic representation of the chemical structures of the detergent compounds selected for testing their antimycobacterial activity against MAP. They include anionic detergents: sodium dodecyl sulfate (SDS) and linear alkyl benzene sulfonate (LABS) and zwitterionic detergents: amidosulfobetaine-14 (ASB-14), sulfobetaine 3-10 (D4266), sulfobetaine 3-12 (DDAPS), and sulfobetaine 3-14 (SB3-14).

12.

Resazurin Microtiter Assay against MAP of (A) SB3-14 (MIC₅₀: 0.0937 mg/mL) and (B) ASB-14 (MIC₅₀: 0.75 mg/mL) in triplicate; observation after 24 h of adding resazurin dye.

The observed bactericidal activity may be attributed to disruption of membrane integrity, consistent with the surfactant-like nature of these compounds and membrane-targeting mechanisms as previously reported for similar molecules. However, our analysis with SDS, which lacks an aromatic group and has a single negative charge as well as a long hydrocarbon chain, did not show inhibition of MAP growth. This indicates that the compounds lacking an aromatic ring or having zwitterionic character are more effective than the compounds with an aromatic group or negative charges in inhibiting the growth of MAP organisms (Table S6).

3. Conclusion

The motivation of this study stems from the previous two investigations by Muniyan et al., which demonstrated the inhibitory activity of detergents containing aromatic groups (LABS and MOP), in liquid culture. , In order to understand the influence of the aromatic group, we wanted to choose a few detergents that lacked the aromatic group, yet containing sulfur. Furthermore, to comprehend the effect of charge as well, we chose to study sulfobetaine-based zwitterionic detergents. This study now demonstrates the potential of the zwitterionic detergents as promising anti-MAP agents. Though six compounds were tested in the initial screening stage, the inhibition was very conspicuous with two detergents: ASB-14 and SB3-14; in fact, the other two sulfobetaines, DDAPS and D4266, also elicited better inhibition than DBS, suggesting the significance of zwitterionic character rather than the aromatic group (Table S6). Therefore, ASB-14 and SB3-14 were selected to perform computational molecular docking, ADMET profiling, and antimycobacterial assay. Both compounds exhibit favorable drug-likeness and pharmacokinetic profiles, complying with Lipinski’s rule of five and showing high intestinal absorption with minimal CNS toxicity risks. Results from molecular docking showed that ASB-14 possesses enhanced binding affinity toward all three MAP target proteins, notably with CD, relative to SB3-14. These interactions were stabilized due to the formation of hydrogen bonds, hydrophobic, and electrostatic interactions with key residues. However, experimental validation by REMA assay established that antimycobacterial activity of SB3-14 was more potent (MIC₅₀: 0.0937 mg/mL) compared with ASB-14 (MIC₅₀: 0.75 mg/mL). The greater activity of SB3-14 could be due to its increased binding stability, decreased toxicity, and better physicochemical properties. These results also highlight that hydrophobic chain length and zwitterionic character are important in mycobacterial membrane disruption, in contrast to anionic detergents, e.g., SDS. Interestingly, among the three proteins, only MAP-DPCK was found to have ionic interactions with the quaternary amine group and with the sulfonate group of both sulfobetaines; whereby the negatively charged side chain of Asp and the positively charged side chain of Lys in MAP-DPCK, respectively, form salt–bridge interactions with positively charged nitrogen (quaternary amine group) and negatively charged oxygen (sulfonate) (Figure ). The overall integrative in silico and in vitro research identifies both ASB-14 and SB3-14 as effective, multitarget, detergent-based MAP inhibitors and provides new insight into lipid-interacting antimycobacterial agents. However, these proposed protein-binding interactions remain computational predictions and hence require experimental validation, but the surfactant-like nature of these compounds suggests a plausible dual mechanism of action, whereby these sulfobetaines could permeate through the mycobacterial cell envelope and then interact with intracellular targets chosen in this study. So, the membrane permeability of the first-line and second-line antimycobacterial drugs can be enhanced if/when the drugs are administered along with these detergent-like compounds. Such an approach could potentially improve the efficacy of existing therapies by reducing the drug dosage and perhaps might be useful to combat antimicrobial resistance (AMR). However, membrane fluidity assays involving the zwitterionic compounds together with a few drugs are imperative for not only comprehensively validating this hypothesis in vitro and in vivo, but also to obtain more insights. Nevertheless, it appears from this study that the zwitterionic character of the detergents can be more significant than the aromatic group, which might be ascribed to the choice of proteins taken here. Perhaps, the aromatic group may also contribute to a significant extent if membrane proteins are chosen as the targets for docking and simulations.

Although sulfobetaines have been well explored for their antimicrobial action (e.g., medical and antifouling applications) on various organisms, − investigations on their role as bioactive lead compounds on Mycobacteria spp. are scarce. Hence, this study bridges the gap by demonstrating the inhibitory activity of sulfobetaine-based zwitterionic detergents on the MAP. However, further research is needed to understand the structural optimization, formulation, and extensive in vitro and in vivo studies to confirm the therapeutic activity and safety profile. This multitarget approach provides a promising direction toward the development of potent interventions against paratuberculosis.

4. Materials and Methods

4.1. Pharmacokinetic Analysis and ADME/T Studies

The ligands (ASB-14 and SB3-14) were predicted for drug-likeness properties by ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity studies by ADMETlab 3.0 (https://admetlab3.scbdd.com/server/) and SwissADME (http://www.swissadme.ch/). The chosen filters for the prediction of drug-likeness were Lipinski’s rule of five, hydrogen acceptors and donors, molar refractivity, and bioavailability score. These rules were evaluated and subjected to ADME prediction. The pharmacokinetic parameters, absorption and distribution, and metabolism were considered for selection of compounds as drug candidates. Additionally, prediction of blood–brain barrier (BBB), identification of P-glycoprotein (Pgp) substrates/inhibitors, and half-life were assessed. Also, various toxicity parameters, such as the maximum tolerated human dose, hepatotoxicity, skin reactivity, mutagenicity, LD₅₀, and toxicity class, were studied using the ProTox-3.0 server (https://tox.charite.de/protox3/index.php?site=home).

4.2. Toxicity Prediction Using PASS Server

Toxicity profiles of all ligands were assessed using the Prediction of Activity Spectra for Substances (PASS) server. The canonical SMILES representations of the ligands were obtained from the PubChem database (http://pubchem.ncbi.nlm.nih.gov/) and submitted to the PASSWay2 drug prediction server (http://www.pharmaexpert.ru/passonline/) for analysis. PASS server is used to anticipate the biological activity of substances, along with any potential adverse consequences can also be evaluated. The server predicts the probability of activity (Pa) and probability of inactivity (Pi) for various biological effects, including potential toxicity risks. A Pa ≥ 0.7 (70%) is considered significant for toxicity prediction, ensuring high accuracy in assessing potential adverse effects. ,

4.3. Screening of Ligands with Different Mycobacterial Proteins

4.3.1. Preparation of MAP Proteins

The three-dimensional structures of mycobacterial proteins, carveol dehydrogenase (3PGX), catalase-related peroxidase (3E4W), and dephospho-CoA kinase (6N39) were acquired in PDB format from the Protein Data Bank (Figure ). These proteins are located in the cytoplasm of the MAP bacteria. Subsequently, AutoDock 4.0 was used for the protein preparation before docking. This process involves removing water molecules, repairing missing atoms, and adding polar hydrogen atoms to enhance the structural integrity and ensure high accuracy during docking.

13.

Selected targets of MAP for molecular docking and molecular dynamics simulation: (A) carveol dehydrogenase, PDB ID: 3PGX; (B) catalase-related peroxidase, PDB ID: 3E4W; (C) dephospho-CoA kinase (DPCK), PDB ID: 6N39.

4.3.2. Preparation of Ligands and Grid Box

DBS (LABS; CID: 8485), ASB-14 (CID: 4046965), D4266 (CID: 161111), SB3-14 (CID: 84705), and DDAPS (CID: 84703) 2D conformers were obtained from the PubChem database. The ligand’s 3D structures were visualized using the Chimera software. The active site residues of each protein were acquired from literature and the UniProtKB database and were used to determine the grid size and center, with a fixed grid spacing of 0.375 Å. ,

4.3.3. Docking and Visualization

Molecular docking of mycobacterial proteins with SB3-14, ASB-14, DDAPS, D4266, DBS, and Isoniazid was carried out by Autodock 4.0. For each ligand, a total of 100 independent runs were performed with a maximum of 25,00000 energy evaluations using the Lamarckian genetic algorithm. The algorithm was programmed to carry out 27000 operations on a single population of 200 individuals. Subsequently, the optimal docked conformation was chosen and visualized using BIOVIA Discovery Studio and Chimera.

4.4. Molecular Dynamics Simulations

Protein–ligand molecular dynamics (MD) simulations were carried out employing ScientiFlow, a software that combines GROMACS 2024.3, SwissParam, and GMX_MMPBSA for streamlined setup and running. − Coordinates for the starting point were retrieved from molecular docking by picking the top-ranking pose for simulations. Ligands were parametrized with SwissParam, and protein residues missing were modeled with Swiss-Model. The TIP3P water model and CHARMM36 force field were used and each complex was solvated in a triclinic box and then neutralized with 0.15 M NaCl. Following energy minimization using the steepest descent algorithm, equilibration was carried out in two stages: NVT ensemble at 300 K and NPT ensemble at 1 bar. Production MD runs took 150 ns with a 2 fs time step, periodic boundary conditions, and Particle Mesh Ewald for long-range electrostatics. Postsimulation calculations were done for RMSD, RMSF, radius of gyration, hydrogen bond analysis, SASA, and Dynamic Secondary Structure Prediction (DSSP). Binding free energy (ΔG) was calculated using GMX_MMPBSA for last 10 ns of the trajectory with both MMPBSA and GBSA approaches.

4.5. Culture of MAP

Indian Bison Type strain of MAP (S5 strain) was procured from the Microbial Culture Collection maintained by the Department of Biotechnology at GLA University in Mathura, Uttar Pradesh, India, and investigations were carried out at the same facility. The isolate was identified by ZN staining and was well characterized by molecular methods using standard protocols. In brief, the genomic DNA of MAP was isolated using the protocol by Van Embden et al. and subjected to quality control as well as characterization using IS900 PCR. Further, the amplification of the IS1311 insertion sequence was carried out using the forward and reverse primers, M56 and M119, respectively. This was followed by PCR-Restriction Endonuclease Digestion and Analysis (PCR-REA) using the endonuclease enzymes (HinfI and MseI) for IS1311. The S5 strain of MAP was cultivated at 37 °C in Middlebrook 7H9 broth (Merck), which was supplemented with Mycobactin J (Allied Monitor), 10% (v/v) OADC (Merck), and 0.2% (v/v) glycerol. The cultures were allowed to grow until reaching an optical density at 600 nm (OD₆₀₀) of 0.123, which corresponds to 0.5 McFarland units, and this is equivalent to 1.5 × 10⁸ cfu/mL. This pure culture of MAP that was undergoing routine quality control was used for experimentation.

4.5.1. Minimum Inhibitory Concentration Studies of Sulfobetaines on MAP

4.5.1.1. Indicator and Drug Stock Preparation

Pure forms of isoniazid and rifampicin powder (Merck, references I3377-5G and 557303-5G) were dissolved in 5% DMSO to achieve a stock solution concentration of 1 mg/mL. Similarly, a 1 mg/mL stock solution of linear alkyl benzene sulfonates (LABS: dodecyl benzene sulfonate (DBS)), sodium dodecyl sulfate (SDS), and sulfobetaines (ASB-14, SB3-14, DDAPS, D4266) was also prepared under aseptic conditions. Serial 2-fold dilutions were done to achieve final test concentrations for the detergents, ranging from 0.0039 to 1 mg/mL, while rifampicin (75–300 μg/mL) and isoniazid (12.5–50 μg/mL) concentrations were used as controls. A freshly prepared solution of 0.05 μg/mL resazurin sodium salt (Sigma-Aldrich, reference R7017) served as the indicator solution.

4.5.1.2. Resazurin Microtiter Assay (REMA Assay)

The REMA assay, as described in Navabharath et al., was performed with a few modifications. An inoculum of 100 μL of bacterial suspension was prepared by mixing 50 μL of fresh media and 50 μL of 0.5 CFU McFarland MAP culture. The drug micro-dilutions ranged from 1 to 0.0039 mg/mL were included in triplicate in a flat-bottom 96-well plate. The plate included standards such as isoniazid, a positive control, a blank made of fresh media, a vehicle control containing 5% DMSO, and a negative control. The plates were sealed with a GENAXY qPCR seal and incubated at 37 °C for 6–14 days, after which 32 μL of freshly prepared 0.05% resazurin sodium salt solution was added to each well of the plate. Further incubation was done for 24 h at 37 °C. The color shift from blue to pink indicates bacterial growth, and an ELISA reader was used to check the colorimetric changes at 595 nm. The minimum inhibitory concentration (MIC) was calculated by measuring the lowest concentration of the drug where there is no increase in the post- and preincubation absorbance readings.

MIC = lowest concentration of drug inhibiting the growth + highest concentration of drug allowing the growth of microorganisms/2.

Glossary

Abbreviations

ssp

subspecies

WOAH

World Organisation for Animal Health

SMILES

Simplified Molecular Input Line Entry System

ZN

Ziel–Neelson

PCR

Polymerase Chain Reaction

ETR

Extremely Long Tandem Repeats

QUB

Queen’s University Belfast minisatellites

MIRU

Mycobacterial Interspersed Repetitive Unit

The data supporting the findings may be shared by corresponding authors upon reasonable request.

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsomega.6c04053.

• Additional ADMET, docking, and REMA assay data of DBS. (PDF)

S.U. carried out the laboratory experimentations, data curation, software analysis, and drafting of the manuscript. V.S. conceptualized the idea pertaining to the choice of detergents, obtaining resources, and performed formal analysis of data. S.G. designed the experiments related to microbial inhibition, acquisition of the funds, obtaining resources, and overall project administration. All authors arrived at a consensus on the final version of the manuscript.

The authors thank the SEED Grant 2022–23 (RGEMS) File No.: SG20220072 by Vellore Institute of Technology (VIT).

The authors declare no competing financial interest.