Investigating the potential of DL25 Compound as a Novel Anti-Mycobacterial tuberculosis Agent: A comprehensive In Silico and In Vitro Analysis

doi:10.21203/rs.3.rs-4913274/v1

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Investigating the potential of DL25 Compound as a Novel Anti-Mycobacterial tuberculosis Agent: A comprehensive In Silico and In Vitro Analysis

https://doi.org/10.21203/rs.3.rs-4913274/v1

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In current time, due to the rapid proliferation of multidrug-resistant and extensively drug-resistant strains of Mycobacterium tuberculosis (M. tb),scientists are actively seeking new, safe, and effective compound. So, in silico and in vitro drug screening approaches have been more commonly used for discovery and development of lead compound, and have been proven useful for predicting the target, pharmacokinetics, and toxicities of prospective new compounds. In this study, we investigate the potential of the DL25 compound as a novel anti-mycobacterial agent through a comprehensive in silico and in vitro analysis. And also, identified potential target and possible interaction between DL25 compound and target protein. Computational investigation was conducted by using Deep-PK server, SwissADME server, Molecular docking, and Molecular dynamic simulation. According to computational analysis, ADMET result support safety and bioavailability features of DL25 compound for use as promising lead with further optimization. Furthermore, we identified possible potential DL25 compound targets by screening a group of 100 mycobacterial proteins that are essential for the growth and survival of bacteria. Three of the 100 identified target, LysA (Rv1293), LpdA (Rv3303c), and SecA1 (Rv3240), were strongly proposed as optimal DL25 compound-target for M. tb, of which the first showed the highest comparative binding affinity to DL25 compound. This compound showed promising in vitro activity, which was supported by this in silico study.

Health sciences/Diseases

Biological sciences/Computational biology and bioinformatics/Computational models

Pharmacodynamics

new compound

Mycobacterium

Virtual docking

In Vitro

Mycobacterium tuberculosis (M. tb) is one of the most common causes of infectious disease worldwide, infecting approximately 10 million people annually and causing over 1.5 million deaths (World Health Organization (WHO), 2023). It is estimated that one-third of the global population has been infected with M. tb at some point in their lifetime. High risk population such as HIV infection, metabolic syndrome, and smokers have probability of 5–10% to develop active M. tb (Spek, 2020). The current standard of care for tuberculosis (TB) treatment, which includes a combination of rifampicin, isoniazid, pyrazinamide, and ethambutol, has been shown to be effective in treating M. tb infection, with a cure rate of up to 95% (Tetali et al, 2020; WHO, 2023). But, the development of resistant M. tb strains highly challenges the efficacy and safety of these treatments. According to 2024 estimate from the WHO, more than 500,000 people are newly diagnosed annually with multidrug-resistant (MDR) M. tb (WHO, 2023). Moreover, only about two in five persons with drug resistance tuberculosis accessed treatment in 2022 (Badgeba et al, 2023). And, the extended duration, expensive, and poor cure rate of commercially available drugs used in MDR add to the economic burden. Even, Fluoroquinolones, Bedaquiline, Pretomanid, and Delamanid are examples of recently produced antibiotics that have developed resistance (Zhao et al, 2019; He et al, 2021). Worryingly, the emergence of Totally Drug-Resistant Tuberculosis (TDR-TB) has been reported in several countries, further compromising efforts to control this deadly disease. Overall, these problems underline the critical requirement for lead compound screening and comprehensive drug development research activity. These novel lead compounds are not expected only overcome antimycobacterial resistance but also shorten the duration of drug therapy and thereby increasing the rate of antibiotic adherence. In-silico molecular docking, Molecular dynamic simulation, and ADME/pharmacokinetic prediction studies have become valuable tools in the early-stage drug discovery process, allowing for the rapid evaluation of potential lead compounds. In this regard, the present study aims to leverage these computational approaches to assess the drug-likeness and pharmacokinetic properties of the DL25 compound, which could serve as a promising candidate for further development. Our current investigation demonstrates the antimycobacterial activity of DL25 compound in vitro towards H37Rv and three non-M. tb strains. Additionally, experiments were conducted in silico to identify potential targets of this compound and explain its effect.

New compound discovery requires a comprehensive understanding of a compound’s activity and its target proteins in both the host and M. tb. Fortunately, recent progress of high-throughput wet lab and computational approach have promoted exponential increment of both data volume and data sources, which enabled researcher to find drugs with short time and less cost (Mennen et al, 2019). Particularly, the computer aid drug discovery involves webserver and software that identify targets, ligand-target interaction, and possible toxicity the most popular research area in present time. And also, it has proved helpful during early lead compounds screening for the development of potent anti-mycobacterium compounds or the prevention of the inclusion of toxic compounds in clinical trials (Mennen et al, 2019; Niazi & Mariam, 2023). The discovery and development of new anti-tuberculosis agents has been a priority in the field of infectious disease research. In-silico molecular docking, Molecular dynamic simulation and ADME/pharmacokinetic prediction studies have become valuable tools in the early-stage drug discovery process, allowing for the rapid evaluation of potential lead compounds. In this study, by combining online web server, software, and vitro experiment we priorities the possible target of DL25 compound. We further contribute to this knowledge by using an in-silico approach to confirm and build a knowledge related to DL25 compound mechanism of action, pharmacokinetics, and toxicity. The comprehensive in vitro and in silico analysis of DL25 compound's anti-mycobacterial activity will provide valuable insights into its efficacy and potential mechanism of action.

Hardware and software

The study was carried out on a Lenovo Workstation with a 2.26 GHz processor, 1Tera RAM and 500 GB hard drive running in a Windows operating system. Bioinformatics software, such as AutoDock4.2, Ligand Scout 4.4.3, PyMoL, NAMD (version 2.14), and online resources were used in this study.

Source of Compounds and Preparation

DL25 compound was synthesized in Guangzhou Institute of Biomedical and Health based on procedure in support file. The LigPrep and Epik modules were used to generate ligand SDF files, utilizing the OPLS3 forcefield for minimization and a pH of seven (7 ± 1) to obtain 3D structures of each candidate, including any relevant ionized or tautomeric states. When chiral compounds were not expressly indicated in the entering SDF file or were produced by protonation during ligand preparation, all potential variations were created and included in the screen. Next, computational drug likeness and pharmacokinetics were predicted to ensure DL25 compound as promising lead compound. The absorption, distribution, metabolism, and excretion (ADME) and toxicity of compounds were estimated using Swiss-ADME server and Deep-PK server (Daina et al, 2017; Myung et al, 2024). For computational analysis the energy of molecule was minimized using the amber geometry optimization force field, with the optimization algorithm set to conjugate at 200 total steps by using Autodock. Lastly, the energy-minimized compounds were then converted to the ready-to-dock PDBQT format by using Open Bable tool.

Selection and Preparation of the target Protein

The crystal structure of LysA (Rv1293) of Mycobacterium tuberculosis (PDB: 1HKW) with resolution 2.8 was retrieved from Protein data bank (https://www.rcsb.org/). The selection of the LysA (Rv1293) is justified by its direct relevance to M. tb. To prepare a single monomer of LysA (Rv1293), the PyMoL protein preparation wizard was utilized. Bond orders and Hydrogen atoms were allocated automatically, and ionization states were generated using Epik at pH 7.0. When more than one ionization state was conceivable, the one with the lowest ionization penalty was selected. Using PROPKA, hydrogen bonding was determined at pH 7. The heavy atom positions were partially minimized to an RMSD of less than 0.3 Å and the hydrogen atom locations were totally minimized using the OPLS3 forcefield. N'-pyridoxyl-lysine-5'-monophosphate (LLP) was considered as part of the protein structure, and the minimized protein was superimposed on the original entry to check that no important residues or the broader structure altered considerably during minimization. By using online program H++, the protein structure was prepared for docking. Partial charges were added, the amino acids were protonated, and the crystal structures were sequentially minimized in two stages by using the UCSF Chimera 1.16 with default parameters. The structure of LpdA (Rv3303c), LppX (Rv2945), FolP1 (Rv3608c), LppX (Rv2945), FbpB (Rv1886), and SecA1 (Rv3240) were retrieved from Protein Data Bank in same way. Finally, all counter ions and water molecules were deleted, and the binding sites were defined based on the cocrystalized ligands.

Molecular Docking to Assess the Binding Affinity

First, One Hundred (100) protein structures were pre-screened against DL25 compound by using Molecular docking server (https://www.dockingserver.com/web/docking/?). The top seven (7) protein structures were loaded to Autodock 4.2.6 via its graphical user interface MGLtools 1.5.732. After loading the protein PDB file into Autodock, all protein atoms within 10 of the LLP cognate ligands were selected in order to determine the active site. After that, the ligand was taken out of the structure. Prior to docking, both the target and the DL25 compound were produced in Ligand Scout 4.4.8. Docking was performed on a quad-core processor running at 3.6 GHz, 16 gigabytes of RAM, and a Quadro FX 5000 GPU. A total 50 docked conformers were generated for each Protein structure in docking results and these conformers were arranged according to their binding energies.

Molecular Dynamics (MD) Simulation

To get the actual binding modes, the selected docked complexes with lowest docking energy was subjected to MD simulation with NAMD 2.4.1 (Nanoscale Molecular Dynamics) module. The GROMOS96 forcefield and PRODRG server was applied to describe LysA (Rv1293) and DL25 compound, respectively. First, free LysA (Rv1293) structure and LysA (Rv1293)-DL25 compound complex structures were minimized by using steepest descent and conjugate gradient (CG) algorithm. The energy minimized complexes were equilibrated under NVT and NPT (constant Number of particles, Volume, and Temperature) condition to 1000 ps. Next, both structures were solvated by creating a solvation cubic box of TIP3P water. Then a salt ionic concentration (NaCl) of 0.145 M was added in the simulated system. Finally, at 100 ns time duration that is equivalent to 100000 ps and 50000000 steps of MD run was performed. Post MD simulation analysis were carried out in Excel. The visualization of structure was done by using graphical interface of VMD tool and PyMol molecular graphics system (www.pymol.org).

Bacteria and Culture Conditions

The mycobacteria used in this study were preserved at -80℃ and cultured at 37℃ in 7H9 broth supplemented with 10% oleic acid-albumin-dextrose-catalase enrichment medium, 0.2% glycerol, and 0.05% Tween 80. The autoluminescent mycobacterial strains, including autoluminescent M. tuberculosis H37Ra (AlRa), M. tuberculosis H37Rv (AlRv), Mycobacterium marinum (AlMm), M. abscessus (AlMab), and Mycobacterium smegmatis (AlMs), were engineered and preserved by our laboratory [16–18]. It has been verified that the insertion of the lux gene cluster had no effect on drug susceptibility or growth rate of autoluminescent mycobacteria compared to their wild-type counterparts [16–18]. Autoluminescent mycobacteria possess the distinctive ability to emit blue-green light without the supplement of additional substrate. This characteristic enables relative light units (RLUs) to serve as a surrogate for colony-forming units when evaluating drug activity against mycobacteria.

Minimum Inhibitory Concentration and Minimum Bactericidal Concentration

The Mycobacterium tuberculosis strain was cultured in Middlebrook 7H9 broth with OADC enrichment at 30/37°C, reaching an RLU of 1000,000–2000,000. And the cell suspension was adjusted to a final concentration of 1000–3000 cells/200µL at the time of inoculation, based on previous research with small modifications (Fossey et al., 2020). As recommended by CLSI, MICs of antibacterial agents against Mycobacterium tuberculosis were determined by the 198µl of 7H9 broth microdilution method in serial dilution (Weinstein, 2018). After three days of incubation, the MIC of the tested mycobacterium was measured by a Glomax 20/20 Luminometer and a Perkin Elmer EnVision Microplate Reader. All MIC determinations were performed in triplicate, and DMSO solvent was used as the negative control. The MBC (minimum bactericidal concentration) was defined as the lowest concentration of drug that attains 99% killing of the CFU compared with the CFU count of the initial inoculum used for the liquid activity assays (Andrejak et al., 2013; Liu et al., 2019).

Time-kill assessment of DL25 alone against AlRa strain

Assays for the rate of killing AlRa strains by DL25 alone were carried out for seven consecutive days. AlRa strain culture was diluted with 7H9 broth to contain an inoculum of 1000–2000 RLU/200µl. DL25 alone was added to yield concentrations of ½×, 1×, 2×, 4x, 8x, and 16x MIC in 7H9 broth. RLU values were measured, and the cultures were incubated at 37°C for the next experiment. The experiments were repeated three times, and the results were presented as the mean ± SD. Bactericidal activity was defined as ≥ 10% reduction (90% kill) from the count of the culture control without antimicrobials. Variable summary statistics were determined by the R software. Data are shown as means ± SD of three independent experiments.

Table 1

Molecular characteristics of DL25 compound and recommended range for 95% known drugs, as predicted by SwissADME server.
Molecular Properties	SwissADME	Recommended Value
Formula	C₄₁H₄₆C_l2N₄
MW	665.74 g/mol	130–500 g/mol
Water Solubility (logS)	-8.04	> 6
TPSA	31.73 Å²	20–150 Å²
GI absorption	Low	< 30% poorly absorbed
No. H-bond acceptors	4	2–20
Bioavailability score	0.17	> 3
No. H-bond donors	0	0–6
Note: TPSA: Topological polar surface area, GI: gastrointestinal absorption, M.W: molecular weight

Table 2

The frequency of violations DL25 compound of commonly used pharmaceutical principles related to drug safety offered by SwissADME.
Pharmaceutical test	SwissADME	Rule violated	Reference
Lipinski number Violations	2/4	MW > 500, MLOGP > 4.15	Maximum 4
Veber number violations	0/2	0	Maximum 2
Egan number violations	1/2	WLOGP > 5.88	Maximum 2
Muegge number violations	3/8	MW > 600, XLOGP3 > 5, #rings > 7	Maximum 8

Egan: logP ≤ 5.88, TPSA ≤ 131.6 Å, Veber: total polar surface area (TPSA) ≤ 140 Å², rotatable bonds ≤ 10, Muegge; MW (200–600), LogP (-2–5), PSA ≤ 150, number of rings (NR) ≤ 7, Number of carbons (NC) > 4, number of heteroatoms (NH) > 1, RB ≤ 15, HBD ≤ 5, HBA ≤ 10.

Table 3

ADMET pharmacokinetic properties of DL25 compound are presented based on computational prediction methods.
Absorption	SwissADME	Deep-PK	Reference
Lipophilicity	6.08	-	8.0–35.0
Aqueous solubility (log mol/L)	-8.04	-4.896	> 6.0
Caco2 permeability (log p_app)	-	1.209	> 8 x 10^− 6 cm/s
Pgp I & II inhibitor	-	Yes	No
Pgp substrate	No	yes	No
Distribution
BBB permeant (log)	No	0.478	-1 ~ 0.3
CNS permeant (log)	-	-1.514	-3 ~ -2
VDss (human)	-	2.412	0.71–2.81L/Kg
Metabolism
CYP1A2 inhibitor	No	No	No
CYP2C19 inhibitor	No	No	No
CYP2CA9 inhibitor	No	No	No
CYP2D6 inhibitor	No	yes	No
CYP3A4 inhibitor	Yes	yes	No
Elimination
CL_tot	-	3.82
T_1/2	-	< 3hrs
Toxicity
AMES toxicity	-	No	No
Max tolerated dose	-	-0.286 (mg/kg/day)	> 0.477 (mg/kg/day)
HERG I & II inhibitor	-	No	No
Hepatotoxicity	-	yes	No
Carcinogen (standard FDA test)	-	Non-carcinogen	Non-carcinogen
Aerobic biodegradability	-	Degradable	Degradable

Papp, apparent permeability coefficient; GI, gastrointestinal; Pgp, P-glycoprotein; BBB; blood brain barrier; CNS, central nervous system; VDss, volume of distribution; CLtot, total clearance; t_1/2, half-life; AMES, assay of the ability of a chemical compound to induce mutations in DNA. Human ether-a-go-go gene (HERG).

Table 4

In vitro anti-TB activity of DL25 Compound against H37Rv, H37Ra and non-*M. tuberculosis* strains.
Mycobacterial strains	Antimycobacterial activity of DL25 Compound
Mycobacterial strains	MIC90, (µg/ml)	MBC99, (µg/ml)
M. tuberculosis H37AlRa	1 ~ 2	2
M. tuberculosis H37Rv	1 ~ 2	2
M. smegmatis H37ms	2 ~ 4	8
M. marinum H37mm	2 ~ 4	8
Mycobacterium abscessus H37Mab	2 ~ 4	8

Table 5

The targets revealed by Docking, along with their respective identification codes, binding free energies, and residues that interact with DL25 compound.
Target Proteins	PDB ID	Uniport ID	RMSD	Binding Energy (Kcal/mol)	Interacting residues
LysA (Rv1293)	2O0T	P9WIU7	2.9	-10.30	LEU264, TYR263, and THR345
LpdA (Rv3303c)	1XDI	P9WHH7	2.9	-8.20	CYS36, ASP37, ASP47, ASP317, and ASP317
SecA1 (Rv3240)	1NKT	P9WGP5	2.7	-8.30	ASP501, VAL500, and ASP501
FbpB (Rv1886)	1F0N	P9WQP1	3.6	-3.74	HIS250
LppX (Rv2945)	2BYO	P9WK65	3.45	-3.84	No interaction
FolP1 (Rv3608c)	1EYE	P9WND1	2.56	-6.52	ASP17, and ASP17
LppX (Rv2945)	2BYO	P9WK65	3.09	-4.53	ARG29, ARG29, GLN30, ASP33, and ASP33

Recently, many studies have showed that enzymes take part in amino acid biosynthesis are vital drug target as humans lack a homolog for most of these targets (Kefala et al. 2005; DeJesus et al, 2017). Thus, targeting enzymes involved in amino acid production may result in the identification of highly specific antitubercular compounds. Among the essential amino acids, L-lysine is derived from L-aspartate and leads to L-lysine in nine enzymatically catalyzed steps. The final step in this pathway is carried out by the enzyme diaminopimelate decarboxylase (LysA, DAPDC), which converts meso-diaminopimelate (DAP) to lysine in a PLP-dependent decarboxylation reaction (Kefala et al. 2005). Several studies have shown that M. tuberculosis strains with defects in biosynthesis of L-lysine is unable to grow in liquid cultures and establish infection in host tissues. In agreement, M. tuberculosis strains with deletions in enzymes involved in biosynthesis of other essential amino acids are also attenuated for growth in vivo (Kefala et al. 2005; DeJesus et al, 2017; Tiwari et al, 2018). In this project we described on the mechanism of action for DL25 compound against Mycobacterium tuberculosis and also explained its pharmacokinetics. This result provided useful information that could be vital for searching compound with minimal side effect. Also, they were tested (in vitro) against the mycobacterial LysA (Rv1293) enzyme to get an insight into their probable mechanism of action. Table 1 showed details about DL25 compound ADME-related physical properties and bioavailability, such as molecular weight (M.W.), water solubility, topological polar surface area (TPSA), octanol-water partition coefficients (LogP), gastrointestinal absorption (GIA), bioavailability score, No. H-bond donors, and No. H-bond acceptors, which are important properties of a compounds proposed for lead compound. New compound with a polar surface area of greater than 140 Å² tend to be poor at permeating cell membranes, which is not violated in this study by DL25 compound (Umar et al., 2020; Kralj et al., 2023). Except for GI absorption, bioavailability score, and water solubility, all the results from this study are consistent with other published data regarding the physicochemical properties and bioavailability of DL25 compound, which required further modification. Pharmaceutical companies follow one or more regulations that determining the drug likeness of oral administration that includes Lipinski, Veber, Egan, and Muegge. Each ADMET parameter was compared to the standard for that parameters range, shown in Table 2. According to Lipinski rule of thumb, approximately 95% of oral compounds pass three of four of the following rules: MW ≤ 500Da, calculated LogP (cLogP) ≤ 5 and hydrogen bond acceptors (HBAs) ≤ 10, and hydrogen bond donors (HBD) ≥ 5 (Khare et al., 2023). Subsequently, additional in silico properties such as polar surface area (PSA ≤ 140 A˚ ²), the number of rotatable bonds (NRotBs ≤ 10–20), and more complex 3D properties have been added, thereby expanding the correlations with absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters (Egan et al., 2000; Muegge, 2006; Veber et al., 2002). In this study, the DL25 compound met the majority of the rules criteria, with maximum violation of three out of eight as shown in Table 2. As a result, only the molecular weight (MW), number of rings, and number of rotatable bonds break the limitations. These broken rules may not necessarily imply a lack of medication efficacy of DL25 compound. The results of the drug-likeness and physicochemical attributes provided here shown that the DL25 compound has promise efficacy following oral administration.

In the present study, the anti-tubercular activity of DL25 compound was evaluated in vitro against Mtb and three strains of non-Mtb, namely H37Rv, H37Mab, H37mm, H37ms, and H37AlRa. The in vitro results showed excellent inhibitory activities against both Mtb strain and non-Mtb strains. DL25 Compound was found to be more potent against both Mtb than non-Mtb, with MIC90 values ranging from 1 to 4 µg/mL. Time kill assay provides more precise information concerning the effect of the test compound on bacteria since the measurements are taken over different times. Furthermore, this technique has ability to differentiate bactericidal activities and bacterial re-growth (Soudeiha, Dahdouh, Azar, Sarkis, & Daoud, 2017). The growth curves of M. tuberculosis H37Ra (Alar) treated with different concentrations of DL25 compound (0.5×MIC, MIC, 2×MIC, and 4xMIC) demonstrated that DL25 compound could inhibit the growth and reproduction of bacteria. The growths of bacterial cells treated with MIC and 2×MIC were inhibited. The growth of the M. tuberculosis H37Ra (Alar) treated with 0.5MIC and 1/4MIC was also a little less than that of bacteria in the control group up to day four. These results specify that the anti- M. tuberculosis H37Ra (Alar) activity of 0.5MIC and 1/4MIC of DL25 compound could hamper bacterial growth to some extent as shown in Fig. 1. Next, we performed assays to evaluate the in vitro antitubercular activity of the identified LysA inhibitors. At this juncture, DL25 compound absorption was investigated by considering parameters such as, lipophilicity, aqueous solubility, Caco2 permeability, Pgp I & II inhibitor, and Pgp substrate as shown in Table 3. Particularly, lipophilicity suggested excellent infusion through the mycobacterial cell wall and into macrophages, and higher probability of being effective against dormant M. tuberculosis. The poor water solubility showed attention during drug formulation, since it is linked to poor bioavailability and poor gastrointestinal (GI) absorption. Therefore, further improvement of solubility could be required. But, high Caco-2 cell permeability showed excellent absorption. Lastly, important parameter on absorbance is the amount of efflux from cellular tissue, especially by p-glycoprotein (Pgp). As shown in Table 3, the contradictory results regarding the binding of DL25 compound to Pgp suggests further experimentation. In either case however, whether it is not a substrate for Pgp, or whether it is a substrate, and inhibits Pgp I and II, the results indicate a lack of export, meaning DL25 compound is likely to accumulate in the target organs. Under DL25 compound distribution investigation three parameters were reported. First, it was predicted that the DL25 compound would not pass through the blood-brain barrier (BBB) or the central nervous system (CNS). As a result, DL25 compound is questionable to be effective in treating tuberculosis meningitis. Second, blood plasma volume of distribution of DL25 compound (logVDss) is on the higher end of the spectrum, implying moderate delivery to infected areas. Phase I drug-metabolizing enzymes such as, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 are known to be expressed in the human intestine (Li et al., 2020). In spite of contradictory conclusions about CYP2D6 inhibition by DL25 compound, the Deep-PK’s and SwissADME’s calculations presented in this study regarding the four main cytochrome isoforms are in agreement as shown in Table 3. Although no inhibition of CYP2D6 is expected, inhibition of CYP3A4 suggests that care should be taken when co administering DL25 compound with other antimycobacterial drugs, to prevent toxic accumulation of either or both drugs. The excretion of DL25 compound was reported as total clearance rate (CL_tot = 0.144mL/min/kg) and the elimination half-time (t_1/2 = 3h) as shown in Table 3. The t_1/2 is significantly lower than that of the other first-line drugs, Rifampicin (t_1/2 =7Hr) (Ji et al, 1993), higher than Isoniazid (t_1/2 = 1.7Hr), and same to Ethambutol (t_1/2 = 3Hr) (Arbex et al, 2010), which is beneficial for patient coherence and may reduce the occurrence of drug resistance. As shown in Table 3, DL25 compound is neither carcinogenic, nor mutagenic, nor likely to interfere with heart rhythms and has low hepatotoxicity. However, prediction server inconsistent results regarding hepatotoxicity demand further experimentation. Biodegradability of DL25 compound also suggests that it is safe in the face of environmental pollution.

It is widely known that drugs commonly target several proteins (as opposed to only one particular protein) (Li et al, 2020; Khare et al, 2023). A total of seven M. tuberculosis proteins were identified by Docking Server as potential targets of DL25 out of one hundred proteins. These are listed according to their docking scores in Table 4, along with their respective interacting residues, UniProt and PDB accession codes. The docking affinities calculated by Autodock ranged between − 3.74 to -10.73 kcal/mol and indicated strong binding to LysA (Rv1293), LpdA (Rv3303c), and SecA1 (Rv3240) targets (Table 4). These findings imply that DL25 compound has a multi-target to inhibits M. tuberculosis growth and killing mechanism by targeting various enzymes, including LysA (Rv1293). In this study, to predict DL25 compound target, we determined their ranking by binding affinity. Based on first ranking order, seven protein target annotated to highly prioritized genes were provided, of which only LysA (Rv1293), was also identified by Autodock as a potential target for DL25 compound and molecular dynamic simulation run for it. In this study, we investigated the interactions between LysA (Rv1293) protein and DL25 compound using molecular dynamics simulations and experimental data. The root-mean-square deviation (RMSD) of LysA (Rv1293) protein and DL25 compound atoms were calculated to assess the conformational flexibility and stability of the complex over the simulation time. The RMSD plot (Fig. 3) showed that the LysA - DL25 compound complex exhibits a relatively low RMSD value, indicating a stable binding interface. This is in agreement with previous studies that have reported stable binding between the protein and ligand (Kumar et al, 2018). Our results showed that the binding of the DL25 compound to LysA (Rv1293) was accompanied by significant changes in the protein's flexibility, as measured by the root mean square fluctuation (RMSF) analysis. The RMSF values calculated for each residue revealed that the binding pocket of the protein underwent significant conformational changes upon DL25 compound binding, indicating a strong correlation between flexibility and binding affinity. The radius of gyration (Rg) was also calculated to analyze the compactness and shape of the LysA (Rv1293)-DL25 compound complex. The Rg value (Fig. 1) indicates that the complex has a more compact structure compared to the free LysA (Rv1293), suggesting that the DL25 compound binding induces a conformational change in the LysA (Rv1293). This observation is consistent with previous studies on protein-ligand interactions, which have shown that ligand binding can induce significant changes in protein structure and dynamics (Wong et al., 2019). The results of this study provide new insights into the binding mechanism and stability of the LysA (Rv1293)-DL25 complex. The stable binding interface and compact structure of the complex suggest that the DL25 compound plays a crucial role in stabilizing the protein structure, which may have implications for understanding the biological function of this complex. Furthermore, our analysis of hydrogen bonding (H-bonding) patterns between the LysA (Rv1293) and DL25 compound revealed a crucial role for these interactions in stabilizing the complex. Specifically, we identified a network of H-bonds between residues THR345, ARG383, TYR263 on the LysA (Rv1293) and DL25 compound that played a key role in maintaining the binding affinity of the complex. The presence of these H-bonds was found to be essential for the optimal alignment of the DL25 compound within the binding pocket, allowing for effective recognition and binding to occur (Wong et al, 2019). The identification of specific H-bonds involved in this process provides valuable targets for future mutagenesis studies aimed at understanding their functional significance.

Computer-aided approaches to drug discovery were utilized in this study in order to discover potential novel compounds against M.tb. Specifically, virtual screening, molecular docking, and in silico ADMET calculations were performed on DL25 compound towards one hundred protein structure from RCSB database. Out of one hundred top seven with high-binding affinity were included in this study and were subjected further for molecular dynamic simulation and in vitro validation. The docking studies showed that DL25 compound interacts with several pertinent residues in the active site of LysA (Rv1293), particularly forms hydrogen bonding with the side chain of Tyr407 and pi–pi bonding with Trp64. These encouraging results should prompt follow-up lead optimization studies to further improve the potency of the identified hits. Finally, Silico study concludes that DL25 compound could be employed as anti-tubercular agents by targeting LysA (Rv1293). The present study demonstrated the antimicrobial properties of DL25 compound. To the best of our knowledge, present study for the first time reported in vitro antimycobacterial activity of DL25 compound. Test compound showed better antimicrobial activity against M. tuberculosis (AlRa) was found to be the most sensitive test culture. As a result, the findings may direct future invitro studies to verify the target and DL25 drug against tuberculosis by requiring additional in vivo and in vitro tests.

Contribution of authors

This work was carried out by the authors named in this article, and all liabilities pertaining to claims relating to the content of this article will be borne by them. All the authors read and approved the manuscript for publication. The authors contributed equally to the conceptualization and execution of this work.

Acknowledgement

The authors wish to specially appreciate the ANSO-CASTWAS for offering the scholarship opportunity to study my PhD. The first affiliated Guangzhou institute of biomedical and health, Chinese academy of science, China for providing laboratory facilities and technical support during the course of this work.

World Health Organization. (2023). Strategic and Technical Advisory Group for Tuberculosis (STAG-TB): report of the 22nd meeting, Geneva, Switzerland, 6–8 June 2022. World Health Organization.
Tetali, S. R., Kunapaeddi, E., Mailavaram, R. P., Singh, V., Borah, P., Deb, P. K., & Tekade, R. K. (2020). Current advances in the clinical development of anti-tubercular agents. Tuberculosis, 125, 101989.
Spek, A. L. (2020). checkCIF validation ALERTS: what they mean and how to respond. Acta Crystallographica Section E: Crystallographic Communications, 76(1), 1-11.
Badgeba, A., Shimbre, M. S., Gebremichael, M. A., Bogale, B., Berhanu, M., & Abdulkadir, H. (2022). Determinants of multidrug-resistant mycobacterium tuberculosis infection: a multicenter study from southern Ethiopia. Infection and Drug Resistance, 3523-3535.
Zhao, Y., Fox, T., Manning, K., Stewart, A., Tiffin, N., Khomo, N., ... & Wasserman, S. (2019). Improved treatment outcomes with bedaquiline when substituted for second-line injectable agents in multidrug-resistant tuberculosis: a retrospective cohort study. Clinical Infectious Diseases, 68(9), 1522-1529.
He, W., Liu, C., Liu, D., Ma, A., Song, Y., He, P., ... & Zhao, Y. (2021). Prevalence of Mycobacterium tuberculosis resistant to bedaquiline and delamanid in China. Journal of global antimicrobial resistance, 26, 241-248.
Mennen, S. M., Alhambra, C., Allen, C. L., Barberis, M., Berritt, S., Brandt, T. A., ... & Zajac, M. A. (2019). The evolution of high-throughput experimentation in pharmaceutical development and perspectives on the future. Organic Process Research & Development, 23(6), 1213-1242.
Niazi, S. K., & Mariam, Z. (2023). Computer-aided drug design and drug discovery: a prospective analysis. Pharmaceuticals, 17(1), 22.
Kefala G, Perry LJ, Weiss MS. Cloning, expression, purification, crystallization and preliminary X-ray diffraction analysis of LysA (Rv1293) from Mycobacterium tuberculosis. Acta Crystallographica Section F: Structural Biology and Crystallization Communications. 2005 Aug 1;61(8):782-4.
DeJesus MA, Gerrick ER, Xu W, Park SW, Long JE, Boutte CC, Rubin EJ, Schnappinger D, Ehrt S, Fortune SM, Sassetti CM. Comprehensive essentiality analysis of the Mycobacterium tuberculosis genome via saturating transposon mutagenesis. MBio. 2017 Mar 8;8(1):10-128.
Tiwari S, Van Tonder AJ, Vilchèze C, Mendes V, Thomas SE, Malek A, Chen B, Chen M, Kim J, Blundell TL, Parkhill J. Arginine-deprivation–induced oxidative damage sterilizes Mycobacterium tuberculosis. Proceedings of the National Academy of Sciences. 2018 Sep 25;115(39):9779-84.
Umar, A. B., Uzairu, A., Shallangwa, G. A., & Uba, S. (2020). In silico evaluation of some 4-(quinolin-2-yl) pyrimidin-2-amine derivatives as potent V600E-BRAF inhibitors with pharmacokinetics ADMET and drug-likeness predictions. Future Journal of Pharmaceutical Sciences, 6(1), 61.
Kralj, S., Jukič, M., & Bren, U. (2023). Molecular filters in medicinal chemistry. Encyclopedia, 3(2), 501-511.
Egan, W. J., Merz, K. M., & Baldwin, J. J. (2000). Prediction of drug absorption using multivariate statistics. Journal of medicinal chemistry, 43(21), 3867-3877.
Veber, D. F., Johnson, S. R., Cheng, H. Y., Smith, B. R., Ward, K. W., & Kopple, K. D. (2002). Molecular properties that influence the oral bioavailability of drug candidates. Journal of medicinal chemistry, 45(12), 2615-2623.
Muegge, I. (2006). PMF scoring revisited. Journal of medicinal chemistry, 49(20), 5895-5902.
Khare, S., Chatterjee, T., Gupta, S., & Ashish, P. (2023). Bioavailability predictions, pharmacokinetics and drug-likeness of bioactive compounds from Andrographis paniculata using Swiss ADME. MGM Journal of Medical Sciences, 10(4), 651-659.
Li, A. P., Ho, M. D., Alam, N., Mitchell, W., Wong, S., Yan, Z., et al. (2020). Inter-individual and inter-regional variations in enteric drug metabolizing enzyme activities: Results with cryopreserved human intestinal mucosal epithelia (CHIM) from the small intestines of 14 donors. Pharmacol. Res. Perspect. 8 (5), e00645. doi:10.1002/prp2.645
Ji B, Truffot-Pernot C, Lacroix C, Raviglione MC, O'Brien RJ, Olliaro P, Roscigno G, Grosset J. 1993. Effectiveness of rifampin, rifabutin and rifapentine for preventive therapy of tuberculosis in mice. Am Rev Respir Dis 148:1541–1546.
Arbex MA, Varella MCL, Siqueira HRd, Mello FAFd. 2010. Antituberculosis drugs: drug interactions, adverse effects, and use in special situationspart 2: second line drugs. J Bras Pneumol 36:641–656. https://doi.org/101590/s1806-37132010000500017
Kumar, S., et al. (2018). Structural analysis of protein-ligand interactions using molecular dynamics simulations. Journal of Chemical Physics, 149(1), 014902.
Wong, E., et al. (2019). Dynamics of protein-ligand interactions: A review. Biochemistry, 58(11), 1425-1436.
Daina, A., Michielin, O., & Zoete, V. J. D. O. S. (2017). SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep 7: 42717.
Myung, Y., de Sá, A. G., & Ascher, D. B. (2024). Deep-PK: deep learning for small molecule pharmacokinetic and toxicity prediction. Nucleic Acids Research, gkae254.

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Investigating the potential of DL25 Compound as a Novel Anti-Mycobacterial tuberculosis Agent: A comprehensive In Silico and In Vitro Analysis

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