Evaluating the MDCK cell permeability of greenly synthesize bimetallic Ag/Zn Nanoparticles using leaf extract of Vallaris solanacea as a potential antipesticide-resistant agent.

Bimetallic nanoparticles, particularly Ag/Zn bimetallic nanoparticles, have gained increasing attention due to their unique properties, making them suitable for a variety of applications such as catalysis, water treatment, and environmental remediation. This study aimed to elucidate the use of bimetallic nanoparticles of Ag/Zn as an alternative to resistant pesticides for pest control. Furthermore, this research demonstrates that BNPs can target specific pollutants and degrade them through various mechanisms. BNP docking with the Nilaparvata lugens cytochrome P450 (CYP6ER1) protein exhibited the lowest binding energy of -7.5 kcal/mol. The cell permeability analysis of BNP in plant cells reveals that the BNP has 0 % permeability towards any cell at -10 kcal/mol energy, which is the lowest free energy translocation pathway. The harmful leftover residues of the pesticides have a higher chance of degradability in case of interaction with BNP validated by chemical-chemical interaction analysis. Additionally, MDCK permeability coefficient of small molecules based on the regression model was calculated for BNP which authenticated the efficiency of BNP. Moreover, Swiss ADMET simulated absorption using a boiled egg model with no blood-brain barrier and gastrointestinal crossing for the expected BNP molecule has been observed. Significantly, the findings indicate that employing bimetallic nanoparticles like Ag/Zn is a crucial strategy for bioremediation because they proficiently decompose pesticides while posing no risk to humans. Our results will facilitate the design of novel BNPs materials for environmental remediation and pest control ensuring human health safety that are predicated on bimetallic nanoparticles.

Investigating the anti-cancer compounds from Calliandra harrisii for precision medicine in pancreatic cancer via in-silico drug design and GC-MS analysis.

Pancreatic cancer is a fatal illness caused by mutations in multiple genes. Pancreatic cancer damages the organ that helps in digestion, resulting in symptoms including fatigue, bloating, and nausea. The use of medicinal plants has been crucial in the treatment of numerous disorders. The medicinal plant Calliandra Harrisi has been widely exploited for its possibilities in biology and medicine. The current study aimed to assess the biopotential of biologically active substances against pancreatic cancer. The GC-MS data of these phytochemicals from Calliandra Harrisi were further subjected to computational approaches with pancreatic cancer genes to evaluate their potential as therapeutic candidates. Molecular docking analysis revealed that N-[Carboxymethyl] maleamic acid is the leading molecule responsible for protein denaturation inhibition, having the highest binding affinity of 6.8 kJ/mol among all other compounds with KRAS inflammatory proteins. Furthermore, ADMET analysis and Lipinski's rule validation were also performed revealing its higher absorption in the gastrointestinal tract. The results of the hepatotoxicity test demonstrated that phytochemicals are non-toxic, safe to use, and do not cause necrosis, fibrosis, or vacuolar degeneration even at excessive levels. Calliandra Harrisi has phytoconstituents that have a variety of pharmacological uses in consideration.

Artificial Intelligence Assisted Pharmacophore Design for Philadelphia Chromosome-Positive Leukemia with Gamma-Tocotrienol: A Toxicity Comparison Approach with Asciminib.

BCR-ABL1 is a fusion protein as a result of a unique chromosomal translocation (producing the so-called Philadelphia chromosome) that serves as a clinical biomarker primarily for chronic myeloid leukemia (CML); the Philadelphia chromosome also occurs, albeit rather rarely, in other types of leukemia. This fusion protein has proven itself to be a promising therapeutic target. Exploiting the natural vitamin E molecule gamma-tocotrienol as a BCR-ABL1 inhibitor with deep learning artificial intelligence (AI) drug design, this study aims to overcome the present toxicity that embodies the currently provided medications for (Ph+) leukemia, especially asciminib. Gamma-tocotrienol was employed in an AI server for drug design to construct three effective de novo drug compounds for the BCR-ABL1 fusion protein. The AIGT's (Artificial Intelligence Gamma-Tocotrienol) drug-likeliness analysis among the three led to its nomination as a target possibility. The toxicity assessment research comparing AIGT and asciminib demonstrates that AIGT, in addition to being more effective nonetheless, is also hepatoprotective. While almost all CML patients can achieve remission with tyrosine kinase inhibitors (such as asciminib), they are not cured in the strict sense. Hence it is important to develop new avenues to treat CML. We present in this study new formulations of AIGT. The docking of the AIGT with BCR-ABL1 exhibited a binding affinity of -7.486 kcal/mol, highlighting the AIGT's feasibility as a pharmaceutical option. Since current medical care only exclusively cures a small number of patients of CML with utter toxicity as a pressing consequence, a new possibility to tackle adverse instances is therefore presented in this study by new formulations of natural compounds of vitamin E, gamma-tocotrienol, thoroughly designed by AI. Even though AI-designed AIGT is effective and adequately safe as computed, in vivo testing is mandatory for the verification of the in vitro results.

Chain-Engineering-Based De Novo Drug Design against MPXVgp169 Virulent Protein of Monkeypox Virus: A Molecular Modification Approach.

The unexpected appearance of the monkeypox virus and the extensive geographic dispersal of cases have prompted researchers to concentrate on potential therapeutic approaches. In addition to its vaccine build techniques, there should be some multiple integrated antiviral active compounds because of the MPV (monkeypox virus) outbreak in 2022. This study offers a computational engineering-based de novo drug discovery mediated by random antiviral active compounds that were screened against the virulent protein MPXVgp169, as one of the key players directing the pathogenesis of the virus. The screening of these candidates was supported by the use of 72 antiviral active compounds. The top candidate with the lowest binding affinity was selected for the engineering of chains or atoms. Literature assisted to identify toxic chains or atoms that were impeding the stability and effectiveness of antiviral compounds to modify them for enhanced efficacy. With a binding affinity of -9.4 Kcal/mol after chain, the lipophilicity of 0.41, the water solubility of 2.51 as soluble, and synthetic accessibility of 6.6, chain-engineered dolutegravir was one of the best active compounds, as proved by the computational engineering analysis. This study will revolutionize the era of drug engineering as a potential therapeutic strategy for monkeypox infection.