Current Computer - Aided Drug Design - Volume 21, Issue 7, 2025

Butyrylcholinesterase (BChE) plays a pivotal role in the progression of Alzheimer's disease. Empirical research demonstrated a fundamental alteration in the role of BChE concerning the reduction of cholinergic neurotransmission within the brains of individuals at advanced stages of Alzheimer's.

This study focuses on developing potent inhibitors for Butyrylcholinesterase (BChE) in the context of Alzheimer's disease (AD) treatment. Building upon previous research, a series of 44 aromatic tertiary amine-based compounds was investigated. Starting with ADME-Tox studies, the pharmacokinetic and pharmacodynamic properties of the compounds were analyzed to select promising candidates for BChE inhibition, which is a crucial factor in AD pathology.

Molecular docking analyses identified compound M18 as the most promising candidate, and further compounds (X9 and X10) were proposed based on M18's chemical structure. These compounds displayed superior properties in terms of binding energies and hydrogen bonds in comparison to M18.

The Molecular Dynamics (MD) simulations, which are over a 500 ns timeframe, confirmed the conformational stability of compounds X9 and X10, compared to M18. Overall, the stated results suggest that the proposed compounds, including X9 and X10 specifically, have a significant potential as candidates for BChE inhibition. This presents a promising avenue for therapeutic intervention in Alzheimer's disease.

Marine sediment bacteria have been generating considerable attention lately due to their potential as valuable reservoirs of novel antimicrobial agents.

In vitro and in silico antibacterial activities of antibacterial compounds isolated from the marine sediment bacterium Enterococcus lactis (S-2).

Coastal sediment samples were collected from Rameswaram, Ramnathapuram District, Tamil Nadu, India. Bacteria were isolated using the crowded plate method, and their phenotypic and genotypic characteristics were studied. Purified bacteria were cultured in large volumes, secondary metabolites were extracted, and novel antibacterial agents were isolated from the aqueous extract. Novel compound antibacterial activity was studied through in-silico and in-vitro. The mechanism activity of antibacterial activity was confirmed by a high-resolution transmission electron microscope.

Genotypic analysis confirmed that the isolated S-2 bacteria were Enterococcus lactis, and the aqueous extract showed antibacterial activity against Staphylococcus aureus (17 mm zone of inhibition) and Proteus mirabilis (12 mm zone of inhibition). A bioactive molecule, 13-hydroxy-9-(1-hydroxyethyl)-11-methoxy-2,4dioxapentacyclo[10.7.1.0³,⁷.0⁸,²⁰.0¹⁴,¹⁹]icosa-1(20),5,7,12,14(19), 16-hexane-18-one, was isolated from aqueous extracts of the S-2 bacterium. Chromatography and spectroscopic analysis confirmed the identity of the isolated compound. Novel compound potential antibacterial activity showing against S. aureus (18 mm zone of inhibition) and MIC 250 µg/mL, which was confirmed by tetrazolium staining. The antibacterial activity mechanism was confirmed by transmission electron microscopy. Molecular docking studies show good binding (-9.9 kcal/mol) of the compound with 3U2D, while molecular dynamic simulation studies confirm the conformationally stable structure of the complex between 3U2D and 13-hydroxy-9-(1-hydroxyethyl)-11-methoxy-2,4-dioxapentacyclo [10.7.1.0³, ⁷.0⁸,²⁰.0¹⁴,¹⁹]icosa-1(20),5,7,12,14(19), 16-hexane-18-one. It has been observed from the docking study of 3U2D with standard drug ciprofloxacin that the lower affinity is compared to the test ligand, which has a docking score of 7.3 kcal/mol. Out of interacting residues of protein 3U2D residue, Thr173 and Ile86 formed conventional hydrogen bonds.

Marine bacterium E. lactis produces a novel antibacterial compound (13-hydroxy-9-(1-hydroxyethyl)-11-methoxy-2,4-dioxapentacyclo[10.7.1.0³,⁷.0⁸,²⁰.0¹⁴,¹⁹]icosa-1(20),5,7,12, 14(19),16-hexane-18-one), which shows antibacterial activity against clinical S. aureus, confirmed by in vitro and in silico analysis. This molecule can used as a lead molecule for antibacterial activity.

MicroRNA-584-5p (miR-584-5p) plays an important role in certain types of cancer. However, its precise role in head and neck squamous cell carcinoma (HNSC) remains unknown.

Our aim was to investigate how miR-584-5p influences HNSC.

The Cancer Genome Atlas (TCGA) provided samples for the study. We use statistical methods to evaluate the diagnostic value, the prognostic value, and the correlation with the clinical features of miR-584-5p. We analyze the target genes and the regulatory network of miR-584-5p. Quantitative reverse transcriptase PCR (qRT-PCR) confirmed the expression of miR-584-5p in HNSC cell lines.

MiR-584-5p expression of miR-584-5p varied significantly among different types of cancer. A notable correlation was observed between elevated miR-584-5p expression and gender (p < 0.001) and histological grade (p < 0.001). Furthermore, high levels of miR-584-5p were found to be associated with a decrease in overall survival (HR: 1.44; 95% CI: 1.10-1.88; p = 0.007), progression-free survival (HR: 1.35; 95% CI: 1.02-1.79; p = 0.035) and disease-specific survival (HR: 1.54; 95% CI: 1.09-2.18; p = 0.016) in the context of HNSC. miR-584-5p demonstrated independent prognostic significance in HNSC and potentially contributes to disease progression through multiple pathways, such as dilated cardiomyopathy and hypertrophic cardiomyopathy. In particular, HNSC cell lines exhibited a substantial upregulation of miR-584-5p compared to normal epithelial cells.

It is possible that miR-584-5p could serve as a promising patent for a therapeutic target and prognostic biomarker for people with HNSC.

Si-Ni-San (SNS) is the formula prescription of Traditional Chinese Medicine (TCM) with anti-depression properties, but its underlying mechanisms remain unclear.

This study provides novel approaches for the study of TCM and offers new opportunities for exploring the pharmacological properties of SNS.

The ingredients in SNS implicated in the treatment of depression were identified and studied using network pharmacology. SwissTargetPrediction and molecular docking were used to study the interaction of SNS ingredients and their targets. The protective effect of these ingredients and their cocktail in rat pheochromocytoma cells (PC12) exposed to corticosterone (Cor) were evaluated using the CCK-8 assay, Hoechst 33342 staining, 2',7'-dichlorodihydro fluorescein diacetate (H2DCFDA) staining, 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging assay, and in-cell Western analysis.

The network pharmacology study showed that the HIF-1 signaling pathway was the most crucial pathway implicated in the anti-depressive property of SNS. MAPK1 (ERK2), MAPK3 (ERK1), AKT1, VEGFA, STAT3, and EGF were identified as hub target proteins in the HIF-1 signaling pathway. Quercetin, naringenin, licochalcone A, and kaempferol from SNS, which targeted the six proteins mentioned above, were used to create a cocktail. This cocktail exerted protective properties, decreased the oxidative stress in PC12 exposed to Cor, and successfully regulated the expressions of AKT1, p-AKT1, ERK1, ERK2, p-ERK1/2, STAT3, p-STAT3, and VEGFA induced by Cor exposure. The SwissTargetPrediction and molecular docking study showed that the cocktail may regulate the HIF-1 signaling pathway by directly binding with AKT1 and MAPK1.

The cocktail from SNS comprised of quercetin, naringenin, licochalcone A, and kaempferol exerts anti-depression potentiality by modulating the HIF-1 signaling pathway via direct interactions with AKT1 and MAPK1.

Virtual screening (VS) could select possible effective candidates from a large number of organic compounds, which plays an important role in network pharmacology. Virtual screening is a very important step in network pharmacology.

The accuracy of screening compounds directly determines the subsequent network construction, target determination and pathway analysis. In order to improve the accuracy of screening the important compounds in herbs for treating diabetes, a novel methodology based on complex-valued flexible neural tree (CVFNT) model and negative sample selection algorithm is presented.

In our method, diabetes-related targets were obtained by literature search. According to diabetes-related targets, active compounds were searched from the public database. The negative sample selection algorithm based on Tanimoto index was proposed to establish inactive compound set. The CVFNT model optimized was utilized to screen effective candidate compounds.

Our proposed method performs better than eight classical classifiers in terms of TPR, FPR, Precision, Specificity, F1, AUC and ROC curve. Our method could also predict 18 compounds from Liangxue Sanyu Decoction, which are involved in the treatment of diabetes.

Our proposed method could effectively improve the identification accuracy of diabetes-related compounds, enhance the performance of network pharmacology analysis, and provide a new idea for drug research and development for the treatment and prevention of diabetes.

The incidence of CRC has increased worldwide over the past decade. The statistics report from WHO highlights the increased severity and fatality rate of CRC among the populations. Wnt/β-catenin is recognized as the resource for cell regeneration and cancer signaling pathways driven by frizzled receptor cofactors. Aberrant regulation of Wnt/β-catenin suppression is an important challenge in treating CRC management.

The SFRP1 comprises a cysteine-rich region that is homologous to the putative Wnt-binding sites of Frizzled proteins, with the potential to impede and alter the cascade of Wnt signaling. Indirect regulation, like targeting Wnt antagonist SFRP1, is an alternative strategy to suppress the cancer signals by enhancing the apoptotic activity. Hence, this study aimed to approach the SFRP1 protein as a therapeutic target to inhibit Wnt signaling in colorectal cancer. Further, it aimed to identify the lead compounds against the SFRP1 protein, to inhibit the oncogenic expression of CRC, which might be possible and druggable using computational approaches, recognizing the importance of the SFRP1 protein role in CRC.

The homology-modeled SFRP1 structure was refined, and virtual screening was performed against the anti-cancer drugs and natural drug databases to find the best hit molecules. The molecular docking, MD, and MMGBSA analysis confirmed the firm binding of SFRP1 complexes to identify the potent CRC inhibitors.

The amino acid residues Arg5, Arg11, Ala13, Lys 245, Lys274, Phe147, Pro99, and Ser277 are essential for ligand binding and show similar interactions for SFRP1 complexes. The ADME/T profile for top hits is acceptable in range and obtains the drug-likeness property. The 100ns run for MD simulation confirms the stability of protein complexes.

Overall, the findings of this study reveal that the lead compounds screened are capable of inhibiting SFRP1 against CRC. Targeting SFRP1 paves the way for new platforms in the field of cancer and the therapeutic sector for new approachable finds.