Targeting Breast Cancer with N-Acetyl-D-Glucosamine: Integrating Machine Learning and Cellular Assays for Promising Results.

BACKGROUND: Breast cancer is a common cancer with high mortality rates. Early diagnosis is crucial for reducing the prognosis and mortality rates. Therefore, the development of alternative treatment options is necessary. OBJECTIVE: This study aimed to investigate the inhibitory effect of N-acetyl-D-glucosamine (D-GlcNAc) on breast cancer using a machine learning method. The findings were further confirmed through assays on breast cancer cell lines. METHODS: MCF-7 and 4T1 cell lines (ATCC) were cultured in the presence and absence of varying concentrations of D-GlcNAc (0.5 mM, 1 mM, 2 mM, and 4 mM) for 72 hours. A xenograft mouse model for breast cancer was established by injecting 4T1 cells into mammary glands. D-GlcNAc (2 mM) was administered intraperitoneally to mice daily for 28 days, and histopathological effects were evaluated at pre-tumoral and post-tumoral stages. RESULTS: Treatment with 2 mM and 4 mM D-GlcNAc significantly decreased cell proliferation rates in MCF-7 and 4T1 cell lines and increased Fas expression. The number of apoptotic cells was significantly higher than untreated cell cultures (p < 0.01 - p < 0.0001). D-GlcNAc administration also considerably reduced tumour size, mitosis, and angiogenesis in the post-treatment group compared to the control breast cancer group (p < 0.01 - p < 0.0001). Additionally, molecular docking/dynamic analysis revealed a high binding affinity of D-GlcNAc to the marker protein HER2, which is involved in tumour progression and cell signalling. CONCLUSION: Our study demonstrated the positive effect of D-GlcNAc administration on breast cancer cells, leading to increased apoptosis and Fas expression in the malignant phenotype. The binding affinity of D-GlcNAc to HER2 suggests a potential mechanism of action. These findings contribute to understanding D-GlcNAc as a potential anti-tumour agent for breast cancer treatment.

Data mining and molecular dynamics analysis to detect HIV-1 reverse transcriptase RNase H activity inhibitor.

HIV-1 is a deadly virus that affects millions of people worldwide. In this study, we aimed to inhibit viral replication by targeting one of the HIV-1 proteins and identifying a new drug candidate. We used data mining and molecular dynamics methods on HIV-1 genomes. Based on MAUVE analysis, we selected the RNase H activity of the reverse transcriptase (R.T) enzyme as a potential target due to its low mutation rate and high conservation level. We screened about 94,000 small molecule inhibitors by virtual screening. We validated the hit compounds' stability and binding free energy through molecular dynamics simulations and MM/PBSA. Phomoarcherin B, known for its anticancer properties, emerged as the best candidate and showed potential as an HIV-1 reverse transcriptase RNase H activity inhibitor. This study presents a new target and drug candidate for HIV-1 treatment. However, in vitro and in vivo tests are required. Also, the effect of RNase H activity on viral replication and the interaction of Phomoarcherin B with other HIV-1 proteins should be investigated.

Synthesis of Adenine-based Fluorescent and Naked-eye Chemosensors: Specific DNA Probes for The Detection of Bacterial Pathogens.

A rapid and confident tool to identify and diagnose bacterial pathogens with more accuracy using DNA as fingerprints is necessary. Herein, we report a smart chemosensor having a terminal adenine sticking to the thymine of single-stranded DNA (ssDNA) through supramolecular interactions and, which leaves ssDNA when the same ssDNA matches with the targeting desired DNA. We have synthesized a naked-eye coloured chemosensor with carbazole. As a model genetic material, DNA of Clavibacter michiganensis subsp. michiganensis was hybridized to ssDNA and immobilized over nitrocellulose membrane. The prepared adenine-chemosensor, by passing through the nitrocellulose-ssDNA membrane caused the formation of ssDNA nitrocellulose-ssDNA-adenine-chemosensor. FTIR results of the immobilized ssDNAs showed that the matching of same ssDNA releases the adenine-chemosensor from the surface of nitrocellulose-ssDNA that results in formation of the double stranded DNA. The selectivity of chemosensor was also confirmed with different bacterial DNA (Bacillus subtilis) as control. These data highlights accurate and reliable results of a new diagnostic kit prototype promising for further studies, which is able to diagnose DNA quickly and precisely.

Molecular dynamics analysis of N-acetyl-D-glucosamine against specific SARS-CoV-2's pathogenicity factors.

The causative agent of the pandemic identified as SARS-CoV-2 leads to a severe respiratory illness similar to SARS and MERS with fever, cough, and shortness of breath symptoms and severe cases that can often be fatal. In our study, we report our findings based on molecular docking analysis which could be the new effective way for controlling the SARS-CoV-2 virus and additionally, another manipulative possibilities involving the mimicking of immune system as occurred during the bacterial cell recognition system. For this purpose, we performed molecular docking using computational biology techniques on several SARS-CoV-2 proteins that are responsible for its pathogenicity against N-acetyl-D-glucosamine. A similar molecular dynamics analysis has been carried out on both SARS-CoV-2 and anti-Staphylococcus aureus neutralizing antibodies to establish the potential of N-acetyl-D-glucosamine which likely induces the immune response against the virus. The results of molecular dynamic analysis have confirmed that SARS-CoV-2 spike receptor-binding domain (PDB: 6M0J), RNA-binding domain of nucleocapsid phosphoprotein (PDB: 6WKP), refusion SARS-CoV-2 S ectodomain trimer (PDB: 6X79), and main protease 3clpro at room temperature (PDB: 7JVZ) could bind with N-acetyl-D-glucosamine that these proteins play an important role in SARS-CoV-2's infection and evade the immune system. Moreover, our molecular docking analysis has supported a strong protein-ligand interaction of N-acetyl-D-glucosamine with these selected proteins. Furthermore, computational analysis against the D614G mutant of the virus has shown that N-acetyl-D-glucosamine affinity and its binding potential were not affected by the mutations occurring in the virus' receptor binding domain. The analysis on the affinity of N-acetyl-D-glucosamine towards human antibodies has shown that it could potentially bind to both SARS-CoV-2 proteins and antibodies based on our predictive modelling work. Our results confirmed that N-acetyl-D-glucosamine holds the potential to inhibit several SARS-CoV-2 proteins as well as induce an immune response against the virus in the host.