In Silico Screening for Novel Leucine Aminopeptidase Inhibitors with 3,4-Dihydroisoquinoline Scaffold

Unveiling the ESR1 Conformational Stability and Screening Potent Inhibitors for Breast Cancer Treatment

BACKGROUND

The current study recognizes the significance of estrogen receptor alpha (ERα) as a member of the nuclear receptor protein family, which holds a central role in the pathophysiology of breast cancer. ERα serves as a valuable prognostic marker, with its established relevance in predicting disease outcomes and treatment responses.

METHODS

In this study, computational methods are utilized to search for suitable drug-like compounds that demonstrate analogous ligand binding kinetics to ERα.

RESULTS

Docking-based simulation screened out the top 5 compounds - ZINC13377936, NCI35753, ZINC35465238, ZINC14726791, and NCI663569 against the targeted protein. Further, their dynamics studies reveal that the compounds ZINC13377936 and NCI35753 exhibit the highest binding stability and affinity.

CONCLUSION

Anticipating the competitive inhibition of ERα protein expression in breast cancer, we envision that both ZINC13377936 and NCI35753 compounds hold substantial promise as potential therapeutic agents. These candidates warrant thorough consideration for rigorous In vitro and In vivo evaluations within the context of clinical trials. The findings from this current investigation carry significant implications for the advancement of future diagnostic and therapeutic approaches for breast cancer.

Therapeutic effect on Alveolar echinococcosis by targeting EM-Leucine aminopeptidase

Alveolar echinococcosis (AE) is a parasitic disease caused by E. multilocularis metacestodes and it is highly prevalent in the northern hemisphere. We have previously found that vaccination with E. multilocularis Leucine aminopeptidase (EM-LAP) induced specific immune response and had an inhibiting effect on the parasites. In this study, the therapeutic effect of recombinant EM-LAP (rEM-LAP) on AE was evaluated and verified using Ubenimex, a broad-spectrum inhibitor of LAP. The results reveal that rEM-LAP could inhibit cyst growth and invasion and induce specific immunity response in BALB/c mice infected with E. multilocularis protoscoleces. The ultrasonic, MRI, and morphological results show that treatment with rEM-LAP inhibits E. multilocularis infection and reduces cyst weight, number, fibrosis and invasion. The same effect is observed for the treatment with Ubenimex by inhibiting LAP activity. The indirect ELISA shows that rEM-LAP could induce specific immunity response and produce high levels of IgG, IgG1, IgG2a, IgM, and IgA, and the serum levels of IFN-γ and IL-4 are significantly increased compared to the control groups, indicating that treatment with rEM-LAP leads to a Th1 and Th2 mixed-type immune response. This study suggests that EM-LAP could be a potential therapeutic target of E. multilocularis infection.

Exploring the anti-SARS-CoV-2 main protease potential of FDA approved marine drugs using integrated machine learning templates as predictive tools

Since the inception of COVID-19 pandemic in December 2019, socio-economic crisis begins to rise globally and SARS-CoV-2 was responsible for this outbreak. With this outbreak, currently, world is in need of effective and safe eradication of COVID-19. Hence, in this study anti-SAR-Co-2 potential of FDA approved marine drugs (Biological macromolecules) data set is explored computationally using machine learning algorithm of Flare by Cresset Group, Field template, 3D-QSAR and activity Atlas model was generated against FDA approved M-pro SARS-CoV-2 repurposed drugs including Nafamostat, Hydroxyprogesterone caporate, and Camostat mesylate. Data sets were categorized into active and inactive molecules on the basis of their structural and biological resemblance with repurposed COVID-19 drugs. Then these active compounds were docked against the five different M-pro proteins co-crystal structures. Highest LF VS score of Holichondrin B against all main protease co-crystal structures ranked it as lead drug. Finally, this new technique of drug repurposing remained efficient to explore the anti-SARS-CoV-2 potential of FDA approved marine drugs.

Aziridine Opening via a Phenonium Ion Enables Synthesis of Complex Phenethylamine Derivatives

We report that the treatment of unsymmetrical 2,3-disubstituted aziridines with TiCl4 yields β-phenethylamine products via the intermediacy of a phenonium ion. Derivatization of the products obtained via this method is demonstrated. Computational analysis of the reaction pathway provides insight into the reaction mechanism, including the selectivity of the phenonium opening.

Synthesis of some novel coumarin isoxazol sulfonamide hybrid compounds, 3D-QSAR studies, and antibacterial evaluation

With the progressive and ever-increasing antibacterial resistance pathway, the need for novel antibiotic design becomes critical. Sulfonamides are one of the more effective antibiotics against bacteria. In this work, several novel sulfonamide hybrids including coumarin and isoxazole group were synthesized in five steps starting from coumarin-3-carboxylic acid and 3-amino-5-methyl isoxazole and assayed for antibacterial activity. The samples were obtained in good to high yield and characterized by FT-IR, ¹³C-NMR, ¹H-NMR, CHN and melting point techniques. 3D-QSAR is a fast, easy, cost-effective, and high throughput screening method to predict the effect of the compound's efficacy, which notably decreases the needed price for experimental drug assay. The 3D-QSAR model displayed acceptable predictive and descriptive capability to find r2 and q2 the pMIC of the designed compound. Key descriptors, which robustly depend on antibacterial activity, perhaps were explained by this method. According to this model, among the synthesized sulfonamide hybrids, 9b and 9f had the highest effect on the gram-negative and gram-positive bacteria based on the pMIC. The 3D-QSAR results were confirmed in the experimental assays, demonstrating that our model is useful for developing new antibacterial agents. The work proposes a computationally-driven strategy for designing and discovering new sulfonamide scaffold for bacterial inhibition.