Tuberculosis remains a major global health challenge, driven by the emergence of drug-resistant Mycobacterium tuberculosis strains and the limited efficacy of existing therapies. Protein tyrosine phosphatase B (PtpB), a secreted virulence factor essential for immune evasion and intracellular survival, represents an attractive molecular target for the development of novel antitubercular agents. In this study, an integrated in silico approach was employed to identify potential PtpB inhibitors from a series of anilinoquinazoline derivatives. Molecular docking-based virtual screening of thirty-five reported compounds was performed to evaluate their binding affinity toward the PtpB active site. Several ligands exhibited stronger docking scores than the reference drugs isoniazid and OMTS, with compound 10 emerging as a promising hit. Detailed interaction analysis supported its selection as a lead scaffold for further optimization. Consequently, compound 10 was used as a template to design nine novel analogues, among which compound 10b demonstrated markedly improved binding affinity and a favourable interaction profile within the active site. Molecular dynamics simulations over 100 ns confirmed the structural stability of the 10b-PtpB complex, as reflected by low RMSD fluctuations and persistent interactions with key catalytic residues. MM-GBSA free energy calculations further supported the enhanced binding propensity of compound 10b. Density functional theory (DFT) calculations revealed reduced HOMO-LUMO energy gaps for the lead compounds, indicating enhanced chemical reactivity. Furthermore, druglikeness and ADMET profiling showed that both the hit compound and the designed analogues comply with Lipinski's rule of five and possess acceptable pharmacokinetic and safety characteristics. Collectively, these findings identify compound 10b as a promising PtpB inhibitor with favourable stability, electronic characteristics, and pharmacokinetic properties, supporting its recommendation for further experimental validation as a potential antitubercular lead.

Background: Tuberculosis (TB) remains a major global health burden, exacerbated by prolonged therapy and rising drug resistance. Targeting pantothenate synthetase (PanC), an essential enzyme absent in humans, offers a promising therapeutic strategy. Objective: This study aimed to identify and optimize novel PanC inhibitors based on 2-methyl-chroman-3-yl formate scaffolds using an integrated computational approach. Methods: An in silico workflow integrating energy optimized pharmacophore (E-pharmacophore) modeling, hierarchical molecular docking (high-throughput virtual screening (HTVS), standard precision (SP), and extra precision (XP)), molecular mechanics generalized Born surface area (MM-GBSA) binding free energy calculations, ADMET prediction, and 200 ns molecular dynamics (MD) simulations was employed. A dataset of 1883 compounds was screened against the PanC crystal structure (PDB ID: 3COW). Results: Screening yielded 1437 pharmacophore-matched compounds. CHEMBL5173568 emerged as the lead scaffold with an MM-GBSA value of-67.64 kcal/mol. Bioisosteric optimization generated derivatives DC2 and DC7 with improved binding energies (-72.39 and-73.64kcal/mol, respectively). Interaction analysis revealed stable hydrogen bonding with His44, Lys160, and Thr184, alongside pi-pi interactions with Phe157. MD simulations confirmed structural stability, with RMSD values stabilizing around 2.0-2.4 & Aring; and persistent hydrogen bonding networks. ADMET analysis indicated favorable oral bioavailability but predicted CYP450 inhibition. Conclusion: DC2 and DC7 represent promising PanC inhibitors with enhanced binding stability; however, predicted metabolic liabilities highlight the need for further optimization and experimental validation.

The continued emergence of drug resistant Mycobacterium tuberculosis highlights the pressing need for novel therapeutic strategies targeting essential and underexploited bacterial pathways. In this study, an integrated in silico approaches was employed to rationally design benzofuro [3,2-d] pyrimidine-based inhibitors targeting mycobacterial membrane protein Large 3 (MmpL3), a key transporter involved in mycolic acid biosynthesis. A structure-based e-pharmacophore model comprising six energetically significant features was developed from the MmpL3 crystal structure (PDB ID: 7C2M) and used to screen a curated ChEMBL dataset, reducing 5752 compounds to 278 candidates. Subsequent QSAR modeling demonstrated robust predictive performance (R2 = 0.65, Q2 = 0.63), enabling activity-guided prioritization. Hierarchical molecular docking and MM-GBSA calculations identified three lead compounds (D3, D12, and D16) with enhanced binding affinities (ΔGbind = − 50.96– − 56.36 kcal/mol) relative to the reference ligand (− 49.85 kcal/mol). Molecular dynamics simulations over 200 ns confirmed the structural stability of the MmpL3–ligand complexes, with backbone RMSD values stabilizing below 2.6 Å and persistent hydrogen bonding within the binding cavity. ADMET profiling indicated favorable oral bioavailability and acceptable drug-likeness. Collectively, these findings highlight benzofuro[3,2-d]pyrimidine scaffolds as promising leads for MmpL3-targeted anti-tuberculosis drug development.

Background Tuberculosis (TB) continues to pose a significant threat to global health, a problem intensified by the rise of strains of Mycobacterium tuberculosis that resist multiple drugs. Identifying novel inhibitors against essential bacterial targets is critical for developing effective therapies. Methods This research utilized computational techniques to discover new inhibitors targeting CYP121 enzymes of M. tuberculosis (PDB ID: 5IBG). We subjected a library of 37 compounds to a rigorous screening process including virtual screening, molecular docking, DFT calculations, ADMET profiling, and MD simulations. Results compound 19 showed the strongest binding interaction (MolDock score of -172.363) along with favourable pharmacological characteristics. Structural optimization yielded analogue 19c, which demonstrated improved score (MolDock score of -181.095) and greater stability during MD simulations, as indicated by reduced RMSD and RMSF values, persistent hydrogen bonds, and enhanced MM-GBSA binding energy. DFT investigations showed a narrower HOMO-LUMO gap for 19c, suggesting increased chemical reactivity. Additional analyses using non-covalent interaction (NCI-RDG) mapping and molecular electrostatic potential (MEP) profiling confirmed the existence of strong and well-defined interactions, along with favourable electrostatic complementarity inside the enzyme’s active site. The ADMET assessment further revealed desirable pharmacokinetic features, including good intestinal absorption and low toxicity risk. Conclusions Analogue 19c exhibits improved stability, binding affinity, and pharmacokinetic properties, highlighting its promise as a potent CYP121 inhibitor. These findings support further experimental validation of 19c as a prospective anti-tubercular agent.

Background Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a major global health challenge, particularly due to the rising prevalence of multidrug-resistant strains. Pantothenate synthetase (PanC), a key enzyme in coenzyme A biosynthesis, represents a promising and selective therapeutic target. Methods This study employed an integrated structure-based drug design workflow combining energy-optimized pharmacophore modeling, enrichment validation, molecular docking, MM-GBSA binding free energy calculations, ADMET prediction, and 200ns molecular dynamics (MD) simulations to optimize pyrazolopyridine derivatives targeting PanC (PDB ID: 3COY). Results A validated six-feature pharmacophore model demonstrated strong screening performance (AUC = 0.86; EF1% = 12.4). Virtual screening of 1,000 ChEMBL compounds yielded 55 high-confidence candidates, followed by hierarchical docking and free energy analysis. Designed derivatives M45 and M10 showed superior binding (XP scores: –10.96 and –10.49kcal/mol; ΔGBind: –76.40 and –74.59kcal/mol), outperforming the reference ligand (–40.10kcal/mol). Key stabilizing residues included Lys269, Asp139, Tyr175, and Ser301. MD simulations confirmed high stability (RMSD ≤ 2.3Å; hydrogen bond occupancy > 65%), with M45 exhibiting a deeper free energy minimum. ADME analysis indicated favorable drug-likeness and high gastrointestinal absorption. Conclusion M45 emerges as a promising PanC inhibitor with strong thermodynamic stability and favorable pharmacokinetic properties. This study establishes a robust computational framework for accelerating early-stage anti-TB drug discovery. However, the study is limited by the absence of experimental IC₅₀ and MIC validation data, possible synthetic accessibility constraints that may affect high-throughput synthesis, and predicted CYP inhibition profiles that suggest potential drug-drug interaction risks requiring further preclinical evaluation.

Abstract Tuberculosis (TB) remains a persistent global health challenge, increasingly complicated by drug-resistant Mycobacterium tuberculosis. Direct inhibition of enoyl-acyl carrier protein reductase (InhA) offers a promising strategy to bypass the prodrug activation limitations of isoniazid. Here, we present an integrated computational framework for the design and optimization of 5-amino-1 H-pyrazole-4-carbonitrile derivatives as direct InhA inhibitors, explicitly retaining the NADH cofactor throughout all structure-based analyses to preserve catalytic site fidelity. A validated e-pharmacophore model (AUC = 0.84; GH = 0.71) guided screening, followed by QSAR modeling (R² = 0.878; Q² = 0.845). Docking and post-docking MM-GBSA identified promising candidates, which were subsequently validated through 200 ns molecular dynamics simulations. Crucially, trajectory-based MM-GBSA calculations revealed averaged binding free energies of − 54.6 ± 3.2 kcal/mol (DC26) and − 57.8 ± 2.9 kcal/mol (DC28), highlighting deviations from single-snapshot estimates. Per-residue energy decomposition identified Tyr158, Met199, and NADH as dominant energetic contributors, with distinct interaction fingerprints differentiating DC26 and DC28. Principal component analysis confirmed stable conformational sampling with convergence into dominant binding basins. Collectively, DC28 emerges as the more energetically favorable inhibitor, while DC26 exhibits complementary interaction stability. These findings refine the energetic and mechanistic understanding of pyrazole-based InhA inhibition and provide a quantitatively validated framework for future anti-TB drug development.

Background: Inflammatory diseases, such as rheumatoid arthritis, pulmonary fibrosis, and autoimmune disorders, remain a challenge to treat with current therapeutics due to limited efficacy and adverse side effects. Targeting key mediators such as tumor necrosis factor-alpha (TNF-alpha), interleukin-1 beta (IL-113), and transforming growth factor-beta (TGF-13) offers a promising therapeutic strategy. Methods: Geniposide-derived compounds were designed as potential inhibitors of TNF-alpha, IL-113, and TGF-13 using advanced computational approaches, including QSAR modeling, Molecular docking, and molecular dynamics (MD) simulations, with ADMET profiling, and density functional theory (DFT) analysis to assess drug-likeness and electronic properties for molecular stability. Results: Among the newly designed analogues, compound AIF3 demonstrated superior binding affinity to IL-113 and TGF-13 compared with the lead compound and standard drugs. Structural modifications significantly improved the predicted biological activity of the newly designed analogues while QSAR analysis confirmed strong predictive reliability. MD simulations validated the stability of AIF3 within IL-113 and TGF-13 binding pockets, ADMET and DFT analyses supported favourable pharmacokinetic and electronic characteristics, further reinforcing its potential. Conclusion: This study highlights the potential of the AIF3 scaffolds derived from geniposidebased derivatives as novel anti-inflammatory agents with enhanced inhibitory potential against IL-113 and TGF-13, coupled with favourable drug-like properties. These findings underscore the promise of computational drug design in developing more effective therapeutics to overcome current limitations in the management of inflammatory diseases.

Tuberculosis (TB) is a chronic bacterial infection caused by Mycobacterium tuberculosis, affecting millions of people worldwide. Despite the availability of anti-TB drugs, the emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB strains has become a significant public health concern. Therefore, there is an urgent need to discover and develop new anti-TB agents with improved efficacy and reduced toxicity. In this study, we use computational methods to identify and design new chemical entities that could be effective anti-tuberculosis agents. The developed model meets numerous organizations' recommendations for statistically valid QSAR, with R² values of 0.990 and 0.978 for internal and external validation, respectively. The designed molecules 29f and 29l exhibit higher binding affinities (∆G) of -37.15 kcal/mol and -37.31 kcal/mol, respectively, when compared to rifampin as the reference drug (RC) with ∆G of -24.13 kcal/mol, which indicates that it is more stable than RC. ADMET evaluation shows improved therapeutic qualities of these newly developed compounds, demonstrated by a reduced maximum acceptable dosage. Further validation was carried out via molecular dynamic simulation, and these analyses prove that changes in protein conformation and dynamics as a response to ligand binding provide an in-depth view of the molecular mechanisms that determine the ligand’s efficacy and protein roles.

Tuberculosis remains a critical global health challenge, necessitating the urgent development of novel therapeutics. In this study, we employed an integrated computational approach to design and evaluate potent inhibitors targeting enoyl-acyl carrier protein reductase (InhA) in Mycobacterium tuberculosis. A robust 2D quantitative structure–activity relationship (QSAR) model was developed, demonstrating high predictive accuracy (R2 = 0.966, Q2LOO = 0.957) and interpretability through descriptors AATSC6i, SCH-5, and maxdssC. Molecular docking studies identified compounds with superior binding affinities, notably Compound 14 (− 118.234 kcal/mol), which exhibited key interactions with active-site residues such as ALA191 and ILE215. Density functional theory (DFT) calculations provided insights into electronic properties and reactivity, confirming the stability of lead compounds. Drug-likeness and ADMET profiling revealed favourable pharmacokinetic properties, including high intestinal absorption and minimal toxicity risks. Based on its favourable binding profile and non-toxic ADMET properties, compound 14 was selected as a template for designing two novel derivatives. These analogues demonstrated improved docking scores (− 132.579 and − 125.894 kcal/mol), high intestinal absorption (> 88

Pancreatic cancer is an abnormal cell growth in the pancreas. In 2021, approximately 60,430 individuals were diagnosed in the USA, with the annual increasing incidence rates. Pancreatic cancer is anticipated to become the second leading cause of cancer mortality by 2030. This escalating challenge has prompted a search for innovative therapeutic agents. Virtual screening, a computational technique, was employed to discover novel drug-like compounds from a diverse set of 30 chemical compounds, sourced from the PubChem database. These compounds were evaluated based on some important properties, including pharmacokinetics, lipophilicity, drug-likeness, water-solubility, and physicochemical characteristics. Seventeen compounds emerged as promising candidates for pancreatic cancer treatment. Subsequent molecular docking studies focused on the Kras-G12D protein target and identified Ligand 18 as the leading candidate, exhibiting a binding energy (BE) of -10.5 kcal mol-1 and extensive interactions with the target protein. Additionally, a newly designed compound, D4, displayed an even higher BE of -10.8 kcal mol-1, fitting more effectively into the protein's binding site than existing drugs like Gemcitabine and Irinotecan. All newly designed compounds met the five scientists' rule, indicating favorable drug-likeness and bioavailability. These findings pave the way for developing a new generation of less toxic therapeutic compounds for pancreatic cancer treatment. Keywords: virtual screening, binding energy, kras-G12D, pancreatic cancer, designed compounds.

The rising threat of multidrug-resistant Mycobacterium tuberculosis (MDR-TB) has intensified the demand for novel therapeutic options. This study utilized a comprehensive computational approach to identify potential inhibitors targeting the DNA gyrase enzyme of M. tuberculosis. A selection of 40 anti-tubercular compounds underwent molecular docking to evaluate their binding affinity to the target protein. The top-performing molecules were assessed further using ADMET prediction tools to determine their pharmacokinetic properties and drug-likeness. To explore the electronic behaviour and stability of selected ligands, Density Functional Theory (DFT) calculations were conducted. Additionally, molecular dynamics (MD) simulations over 250 nanoseconds provided insights into the conformational stability of the protein-ligand complexes. The MM/GBSA method was employed to estimate binding free energies, supporting the molecular docking outcomes. Among the compounds, complexes 25 and 39 showed the highest binding affinities (-127.57 and -138.03 kcal/mol) respectively, outperforming standard anti-TB drugs; Isoniazid (-52.99 kcal/mol), Ethambutol (-68.92 kcal/mol), and Pyrazinamide (-60.16 kcal/mol). ADMET analysis confirmed acceptable oral bioavailability and low toxicity. DFT results revealed that compound 19 possessed favourable electronic characteristics. MD simulations demonstrated the structural stability of all complexes, with compound 19 showing minimal fluctuation throughout the trajectory. MM/GBSA results supported the docking findings, identifying compounds 25 and 39 as top binders with ΔG bind values of -48.32 and -49.30 kcal/mol, respectively. This study identifies compounds 25 and 39 as promising candidates for further investigation as multidrug-resistant anti-TB agents, given their high affinity for the target site, robust stability, and promising pharmacokinetic profiles.

We initiate the algebraic study of the semigroup of one-to-one order-preserving partial contraction mappings of a totally ordered set {1,2,… ,n} , which we denote by 𝒪𝒞ℐ_n . In particular, we characterise the Green’s relations and their starred analogues in 𝒪𝒞ℐ_n . We also compute the rank of 𝒪𝒞ℐ_n as 2n-1 .

Oxidative stress, triggered by an imbalance between reactive free radicals and the body’s antioxidant defenses, is linked to numerous health disorders including neurodegenerative ailments, cancer, and cardiovascular diseases. This study evaluates twenty-nine novel antioxidant flavonoids for their potential as therapeutic agents, focusing on drug-likeness, molecular interactions, pharmacokinetics, and electronic properties. Using SwissADME for drug-likeness analysis, all selected flavonoids met essential criteria. Molecular docking studies with the Keap1 protein identified Compounds 1, 13, and 15 as top performers, achieving MolDock scores of − 110.910, − 110.941, and − 117.329 kcal/mol, respectively, which indicate strong binding affinities. These compounds demonstrated significant interactions with key residues such as ARG-330 and GLU-250, whereas Ascorbic acid and Trolox showed lower scores of − 77.366 and − 101.037 kcal/mol, respectively. Pharmacokinetic predictions suggested high gastrointestinal absorption and blood–brain barrier permeability for the top flavonoids, with bioavailability scores of 0.55, compared to 0.56 for Ascorbic acid and 0.55 for Trolox. In the DFT assessment, HOMO–LUMO energy gaps were found to be 4.460 eV for Compound 1, 4.530 eV for Compound 13, and 4.520 eV for Compound 15, reflecting strong antioxidant activity. Additionally, electrophilicity indices ranged from − 3.993 to − 4.072, indicating significant electron-donating potential. QSAR analysis highlighted differences in dipole moments, hydrophobicities, and polar surface areas among the compounds, suggesting varied therapeutic potential. This study highlights the promising potential of novel flavonoids as effective antioxidant agents. Evaluations of their drug-likeness, molecular interactions, and pharmacokinetic properties indicate a favorable profile for therapeutic applications. High binding affinities in molecular docking with the Keap1 protein suggest these flavonoids can modulate oxidative stress pathways, offering protection against various health disorders. Pharmacokinetic predictions show high gastrointestinal absorption and blood–brain barrier permeability, ensuring these compounds reach their target sites effectively. The use of advanced computational methods, such as DFT and QSAR analysis, enhances understanding of their properties and mechanisms. Overall, these findings support the development of effective antioxidant therapies for oxidative stress-related conditions.

The emergence of multidrug-resistant strains severely challenges tuberculosis (TB) management, necessitating the development of novel therapeutics targeting unexplored virulence pathways. The enzyme Protein Tyrosine Phosphatase B (PtpB), a critical contributor to the virulence of Mycobacterium tuberculosis, is an attractive target for developing new therapeutic inhibitors. This study describes the comprehensive computational design and evaluation of a series of novel Naryl oxamic acid derivatives as potential PtpB inhibitors. A robust 2D-QSAR model was developed (R2 = 0.911, Q2 = 0.885) utilizing three key molecular descriptors (AATS6v, ATSC2p, SpMin8_Bhe) to predict anti-tubercular activity. Among 36 screened compounds, 18 and 8 emerged as top candidates, demonstrating superior MolDock scores (-112.006 and -108.369 kcal/mol, respectively) and stable interactions with critical PtpB residues (ARG63, ARG166) compared to the reference drug isoniazid. Molecular dynamics simulations confirmed the stability of the ligand-PtpB complexes over 100 ns. Ten new analogues of compound 18 were designed (18A-18I), with analogue 18E showing the strongest predicted binding to the target enzyme. Density Functional Theory (DFT) calculations revealed a lower energy gap (Delta E = 3.68 eV) for compound 18, indicating heightened reactivity, while Molecular Electrostatic Potential (MEP) and Non-Covalent Interaction (NCI) analyses provided insights into favourable interaction sites and intramolecular stability. All screened compounds, particularly 18, complied with Lipinski's rules and displayed promising predicted ADMET properties, including high intestinal absorption and minimal toxicity risks. These findings collectively nominate the N-aryl

Cervical cancer continues to pose a significant health challenge, especially in resource-limited settings, highlighting the need for the development of novel therapeutic agents. This study investigates the potential of 2,4-diphenyl indenol [1,2-b] pyridinol derivatives as inhibitors targeting the epidermal growth factor receptor (EGFR) through computational drug discovery methods. A genetic algorithm-multiple linear regression (GA-MLR) model was created, achieving strong predictive accuracy with R² = 0.9243, Q² = 0.8957, CCC = 0.9021, and MAE = 0.034. Molecular docking studies indicated that ligand 57 displayed the highest binding affinity of -29.2313 kcal/mol, followed by ligands 111 (-29.1459 kcal/mol) and 110 (-29.9082 kcal/mol), all of which stabilize key EGFR residues. Molecular dynamics (MD) simulations confirmed the stability of ligand 111, showing an improved binding free energy of -18.2235 kcal/mol. Additionally, pharmacokinetic analysis further validated their favorable ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties, supporting their potential as drug-like candidates. These findings establish a strong foundation for the development of EGFR-targeted therapies for cervical cancer.

The increasing emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) Mycobacterium tuberculosis strains has intensified the need to discover new therapeutic agents essential for bacterial enzymes. DNA gyrase subunit B (GyrB), a validated anti-tubercular target, was explored in this study using a computational approach to identify potent inhibitors among 6-sulfonyl-8-nitrobenzothiazinone derivatives. A collection of 44 structurally diverse derivatives underwent molecular docking, revealing compounds 21 and 26 as top candidates with superior binding scores than the standard drugs, Isoniazid and Pyrazinamide. To further verify these results, molecular dynamics simulations were performed over a 100 ns duration, examining metrics like root mean square deviation (RMSD), root mean square fluctuation (RMSF), and radius of gyration to confirm complex stability. Additionally, calculations of binding free energy through the MM/GBSA method provided strong validation of the initial docking results, with compound 21 demonstrating the most favourable ΔG_bind (-47.86 kcal/mol), followed closely by compound 26 (-44.60 kcal/mol). Pharmacokinetic profiling indicated high intestinal absorption, acceptable bioavailability, and minimal CYP-mediated metabolic liabilities, particularly for compound 26, which also showed a non-mutagenic profile in AMES predictions. Density functional theory (DFT) analysis revealed narrow energy band gaps and high electrophilicity indices, suggesting superior electronic reactivity and interaction potential. These findings highlight compounds 21 and 26 as promising GyrB inhibitors with favourable stability, pharmacokinetics, and drug-like features, warranting further experimental validation as potential anti-TB drug candidates.

Sickle cell disease (SCD), a multiorgan disease that is one of the most common genetic ailments, affects about 15 million people globally. The findings for drugs that bind to hemoglobin and adjust the oxygenation condition have been a key component of SCD treatment. The goal of this study was to use computational methods to find lead compounds, design novel bioactive molecules that are strong SCD inhibitors, and gain further knowledge about their reaction process. With data demonstrating predictive properties of R2 = 0.990, R_pred^2 = 0.980, and Q_CV^2 = 0.987, the developed QSAR model is statistically reliable and highly predictive. It also satisfies the established standards for sound models, which are recommended by numerous institutions. According to the study, the designed molecules (DM) exhibit predicted biological activity (pIC50) of 6.843, 6.671, and 6.912 in comparison to pIC50 of 5.403 for the TM and 4.956 for the SD. Additionally, molecules DM1, DM2, and DM3 exhibit better drug ratings of 0.67, 0.56, and 0.91, respectively, compared to drug scores of 0.44 for TM and 0.49 for SD, suggesting better pharmacokinetic properties than TM and SD. The protein-DM3 complex showed higher binding free energies than the protein-L-glutamate complex, indicating that it is more stable, according to MD simulation, which was used to determine the stability of the proposed molecule.

In this study, a quantitative structure-activity relationship (QSAR) approach was employed to predict the inhibitory activities of quinoline-based hybrids as potential inhibitors of α-glucosidase, an enzyme crucial in carbohydrate metabolism. The predictive models were generated using genetic function approximation (GFA) and among them, model 2 emerges as the most effective boasting validation metrics of correlation coefficient of the training set (R2trn) = 0.909, adjusted correlation coefficient (R2adj) = 0.889, cross-validation coefficient (Q2cv) = 0.835 and correlation coefficient of test set (R2test) = 0.745. Statistical evaluations, encompassing Mean effect, p-values, Y-scrambling and applicability domain analysis, confirmed the impact of the descriptors, showed statistical significance and reliability of the selected model. Subsequently, four potent compounds were designed, and their inhibitory activities were predicted. Remarkably, the designed compounds exhibited superior inhibitory potential compared to the template compound used as a reference. Furthermore, detailed analysis of the binding interactions of the designed compounds within the active site of the target receptor pdb id: (3TOP), revealed a strong binding affinity surpassing that of acarbose, a known α-glucosidase inhibitor. The dynamic simulations of complex with higher scores demonstrated remarkable stability through various analyses, indicating their potential as promising candidates for diabetes treatment. The (ADME) properties of the designed compounds were also investigated, indicating their pharmacological effectiveness and potential as drug candidates. Additionally, Density Functional Theory (DFT) studies highlighted compound 2 as being particularly reactive and possessing a propensity for electron transfer or donation. This research offers valuable insights for designing future α-glucosidase inhibitors with increased potency.

Hepatitis B is a liver infection caused by the hepatitis B virus which usually spread through contact with blood, semen or other body fluids of an infected person. If not treated with caution, hepatitis B virus would gradually grow into a more severe state which results in scarring of the liver, abnormal functionality of the liver and in due time, liver cancer or cirrhosis. In this research, molecular docking studies was carried out on dehydroandrographolide and andrographolide derivatives as anti-hepatitis B virus agents against HBV target (Nucleoside diphosphate kinase) with the pdb ID: 4C6A. The drug-likeness and pharmacokinetic properties of the investigated molecules were also studied. The molecular docking study carried out on the anti-hepatitis B virus agents has explored their theoretical binding affinities with the active sites of the HBV target (Nucleoside diphosphate kinase) in a range of -112.23 to -175.17kcal/mol. Compounds A9 has the highest binding affinity of -175.17kcal/mol out of the 20 dehydroandrographolide and andrographolide derivatives investigated. It formed 4 conventional hydrogen bond interactions with LYS16 (2.77 Å), TYR56 (1.96 Å), ARG109 (3.04 Å) and GLY123 (2.43 Å) amino acid residues. It also formed the carbon-hydrogen bond with LYS16 (2.62 Å), ARG92 (2.62 Å) and ARG92 (2.75 Å) amino acid residues, respectively. It further formed Alkyl hydrophobic bond interaction with ARG92 (4.49 Å), ILE95 (5.18 Å), LEU68 (3.85 Å) and Pi-Alkyl hydrophobic with TYR56 (4.58 Å), HIS59 (5.18 Å), ALA14 (4.82) amino acid residues, respectively. The drug likeness and pharmacokinetics properties prediction performed showed that the studied compounds including the best lead compounds were drug-like in nature with good pharmacokinetics properties and they all have bioavailability score of 0.55, respectively. The DFT studies revealed that compound 2 and 8 among the best five compounds are more reactive having lower energy band gap of 4.3eV, respectively.

Background: The global burden of tuberculosis and the rise of drug-resistant Mycobacterium tuberculosis strains continue to challenge effective disease control, underscoring the need for novel therapeutic agents with improved efficacy and safety profiles. Objective: This study aimed to design and computationally evaluate hydantoin-based derivatives as potential InhA inhibitors for anti-tubercular drug development. Methods: A series of sixty-three compounds were subjected to molecular docking-based virtual screening to identify promising InhA inhibitors. Molecular dynamics simulations were performed to characterize ligand-protein interactions and stability. The candidates were assessed for drug-likeness and pharmacokinetic properties, while density functional theory (DFT) calculations were conducted to examine their electronic reactivity. Results: Six compounds (3, 23, 25, 28, 45, and 53) exhibited higher binding affinities, with MolDock scores from-137.26 to-151.66 kcal/mol and re-rank scores between-99.26 and-112.32 kcal/mol, outperforming isoniazid (-48.59 and-45.69 kcal/mol). Compound 53 showed stable binding over a 300 ns simulation and served as a template for new derivative design. This yielded six analogues with improved affinities (MolDock: -156.53 to-170.37 kcal/ mol; re-rank: -120.18 to-134.43 kcal/mol). Pharmacological profiling confirmed favourable drug-likeness and ADMET properties with minimal Lipinski violations. DFT analysis revealed strong electronic reactivity, particularly for compounds 23 and 53b. Conclusion: These results highlight compounds 23 and 53b as promising scaffolds for InhA inhibition and suggest their potential as lead structures for future anti-tubercular drug discovery.