Background: The development of Multi-Target-Directed Ligands (MTDLs) has emerged as a significant strategy for addressing complex, overlapping pathologies such as cancer and Alzheimer’s disease (AD). This study aims to provide a robust computational framework for the design of dual-target inhibitors. Methods: This study presents an integrated and rigorous computational pipeline combining Quantitative Structure–Activity Relationship (QSAR) modeling, Molecular Docking, and Molecular Dynamics (MD) simulations with Dynamic Cross-Correlation Matrix (DCCM) analysis. Using a dataset of 57 known tubulin inhibitors, two high-performing QSAR models were developed to guide the rational design of 16 novel trimethoxyphenyl-based analogues. Results: Following ADMET and drug-likeness filtering, Lead Candidates 15 and 16 were identified. Quantitative activity predictions confirmed their enhanced potency thresholds, which were subsequently validated through static docking against β-tubulin (PDB: 4O2B) and Acetylcholinesterase (PDB: 1EVE). In total, 100 ns MD simulations and MM-GBSA calculations demonstrated superior binding stability and energetically favorable profiles for both targets, while DCCM analysis confirmed the functional synchrony of the protein–ligand complexes. Conclusions: The results provide a validated structural hypothesis for dual-target inhibition. The identified leads, 15 and 16, demonstrate strong predictive potential and are prioritized for chemical synthesis and in vitro biological evaluation.

Alzheimer’s disease (AD) represents an escalating global neuropharmacological crisis, with prevalence in high-growth demographic regions such as India projected to exceed 14 million by 2040. This study addresses the urgent need for high-potency, dual-site acetylcholinesterase (AChE) inhibitors through an integrated computational pipeline. We address the failure of mono-target paradigms by designing scaffolds capable of simultaneously anchoring the Catalytic Active Site (CAS) and the Peripheral Anionic Site (PAS). A robust GA-MLR QSAR model was developed from 115 quinoline analogs using 11,135 descriptors. Lead candidates were prioritized via cavity directed molecular docking (7XN1) and 100 ns molecular dynamics (MD) simulations. The five-descriptor model (R² = 0.7569, $Q_{LOO}^2$ = 0.7244) was validated by an external set of 8 experimental compounds ($R_{ext}^2$ = 0.8620). Lead Compound 19 emerged as a superior candidate (ΔG = −11.1 kcal/mol), exhibiting a stable MD trajectory (PL-RMSD ≈ 2.4 Å) and preserving essential Gly121-His447 catalytic anti-correlations. This study provides a statistically validated scaffold and computational mechanistic foundation for future in vitro experimental validation, advancing the high throughput screening of neuroprotective agents on a global scale.

Aim: To evaluate the Neuroprotective activity of Biophytum reinwardtii Platinum nanoparticles Methods: Biophytum reinwerdtii platinum nanoparticles were subjected to evaluation of the neuroprotection activity in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine induced zebra fishes. Experimental fishes are divided into 5 groups, each containing 8 fishes. Group I is considered a normal group; Group II is a toxic group means treated with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine 225 mg/kg, i.p. for 5 days; Group III, IV, and V are treatment groups means treated with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (225 mg/kg) with 0.3 µmol, 0.4µmol, and 0.5 µmol of Biophytum reinwardtii Platinum nanoparticles respectively for 5 days. Results: In the in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine group, locomotor activity and complex I activity are decreased, Malondialdehyde levels increased, antioxidants, and catecholamines levels decreased, whereas Biophytum reinwardtii Platinum nanoparticles treated fishes exhibit significant locomotor and increased levels of antioxidants and catecholamines. Conclusion: These results suggest that Biophytum reinwardtii Platinum nanoparticles. Showed significant neuroprotection activity in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine -induced Parkinson’s zebra fishes.

Alzheimer’s disease (AD) represents a escalating global neuropharmacological crisis, with prevalence in high-growth demographic regions such as India projected to exceed 14 million by 2040. This study addresses the urgent need for high-potency, dual-site acetylcholinesterase (AChE) inhibitors through an integrated computational pipeline. Background: We address the failure of mono-target paradigms by designing scaffolds capable of simultaneously anchoring the Catalytic Active Site (CAS) and the Peripheral Anionic Site (PAS). Methods: A robust GA-MLR QSAR model was developed from 115 quinoline analogues using 11,135 descriptors. Lead candidates were prioritized via blind molecular docking (7XN1) and 100-ns molecular dynamics (MD) simulations. Results: The five-descriptor model (R2 = 0.7569, QLOO2 = 0.7244) was validated by an external set of 8 experimental compounds (Rext2 = 0.8620). Lead Compound 19 emerged as a superior candidate (ΔG = -11.1 kcal/mol), exhibiting a stable MD trajectory (PL-RMSD ≈ 2.4 Å) and preserving essential Gly121-His447 catalytic anti-correlations. Conclusions: This study provides a statistically validated scaffold and mechanistic foundation for future biomimetic chromatography validation, advancing the high-throughput screening of neuroprotective agents on a global scale.

Objective: The escalating challenge posed by multidrug-resistant tuberculosis (MDR-TB) necessitates the discovery of potent treatment agents. This study aims to synthesize, characterize, and evaluate the antitubercular potential of 33 novel 2,3-(4-aminobenzamido)benzoic acid derivatives (1–33). Methods: The synthesis involved a three-stage reaction series starting with p-aminobenzoic acid treated with concentrated hydrochloric acid to obtain its salt. This was further modified to ammonium benzoyl chloride using thionyl chloride. The ammonium benzoyl chloride was then condensed with 2 or 3 benzoic acids to yield the desired 2,3-(4-aminobenzamido)benzoic acid derivatives. The structures of these compounds were elucidated using FT-IR, HR-MS, ¹H, and ¹³C NMR. Their antituberculosis activity was assessed using the Alamar blue dye assay against Mycobacterium tuberculosis H37RV. Results and Discussion: Out of the 33 synthesized compounds, 12 showed sensitivity to Mycobacterium tuberculosis (MTB). Notably, five compounds (14), (18), (19), (26), and (30) demonstrated significant potency, with minimal inhibitory concentrations (MICs) of 1.6 µg/mL, nearly 50 times lower than the standard drug. These results strongly suggest the potential of these compounds as effective tuberculosis therapeutics. Conclusions: The synthesized series of 2,3-(4-aminobenzamido)benzoic acid derivatives have shown promising antituberculosis activity. Specifically, compounds (14), (18), (19), (26), and (30) exhibited noteworthy potency. It is crucial that future research focuses on further screening the active compounds (2–4), (10), (14), (18), (19), (21), (26), (28), (30), and (33) for antimicrobial strains and evaluating compounds (14), (18), (19), (26), and (30) using the DHFR enzyme-specific assay to advance the development of effective tuberculosis treatments.