Lipophilicity Studies on Thiosemicarbazide Derivatives

Nature-Derived Compounds as Potential Bioactive Leads against CDK9-Induced Cancer: Computational and Network Pharmacology Approaches

Given the importance of cyclin-dependent kinases (CDKs) in the maintenance of cell development, gene transcription, and other essential biological operations, CDK blockers have been generated to manage a variety of disorders resulting from CDK irregularities. Furthermore, CDK9 has a crucial role in transcription by regulating short-lived anti-apoptotic genes necessary for cancer cell persistence. Addressing CDK9 with blockers has consequently emerged as a promising treatment for cancer. This study scrutinizes the effectiveness of nature-derived compounds (geniposidic acid, quercetin, geniposide, curcumin, and withanolide C) against CDK9 through computational approaches. A molecular docking study was performed after preparing the protein and the ligands. The selected blockers of the CDK9 exerted reliable binding affinities (−8.114 kcal/mol to −13.908 kcal/mol) against the selected protein, resulting in promising candidates compared to the co-crystallized ligand (LCI). The binding affinity of geniposidic acid (−13.908 kcal/mol) to CDK9 is higher than quercetin (−10.775 kcal/mol), geniposide (−9.969 kcal/mol), curcumin (−9.898 kcal/mol), withanolide C (−8.114 kcal/mol), and the co-crystallized ligand LCI (−11.425 kcal/mol). Therefore, geniposidic acid is a promising inhibitor of CDK9. Moreover, the molecular dynamics studies assessed the structure–function relationships and protein–ligand interactions. The network pharmacology study for the selected ligands demonstrated the auspicious compound–target–pathway signaling pathways vital in developing tumor, tumor cell growth, differentiation, and promoting tumor cell progression. Moreover, this study concluded by analyzing the computational approaches the natural-derived compounds that have potential interacting activities against CDK9 and, therefore, can be considered promising candidates for CKD9-induced cancer. To substantiate this study’s outcomes, in vivo research is recommended.

Biological Activity, Lipophilicity and Cytotoxicity of Novel 3-Acetyl-2,5-disubstituted-1,3,4-oxadiazolines

Antibiotic resistance is now a global problem, and the lack of effective antimicrobial agents for the treatment of diseases caused by resistant microbes is increasing. The 3-acetyl-2,5-disubstituted-1,3,4-oxadiazolines presented in this article may provide a good starting point for the development of potential new effective antimicrobial agents useful in the treatment of bacterial and fungal infections. Particular attention is drawn to the 1,3,4-oxadiazole derivative marked with the number 29 with 5-nitrofuran-2-yl substituent in its chemical structure. This substance showed a strong bactericidal effect, especially against Staphylococcus spp., and no cytotoxicity to the L929 normal cell line.

Predicting the membrane permeability of organic fluorescent probes by the deep neural network based lipophilicity descriptor DeepFl-LogP

Light microscopy has become an indispensable tool for the life sciences, as it enables the rapid acquisition of three-dimensional images from the interior of living cells/tissues. Over the last decades, super-resolution light microscopy techniques have been developed, which allow a resolution up to an order of magnitude higher than that of conventional light microscopy. Those techniques require labelling of cellular structures with fluorescent probes exhibiting specific properties, which are supplied from outside and therefore have to surpass cell membranes. Currently, major efforts are undertaken to develop probes which can surpass cell membranes and exhibit the photophysical properties required for super-resolution imaging. However, the process of probe development is still based on a tedious and time consuming manual screening. An accurate computer based model that enables the prediction of the cell permeability based on their chemical structure would therefore be an invaluable asset for the development of fluorescent probes. Unfortunately, current models, which are based on multiple molecular descriptors, are not well suited for this task as they require high effort in the usage and exhibit moderate accuracy in their prediction. Here, we present a novel fragment based lipophilicity descriptor DeepFL-LogP, which was developed on the basis of a deep neural network. DeepFL-LogP exhibits excellent correlation with the experimental partition coefficient reference data (R2 = 0.892 and MSE = 0.359) of drug-like substances. Further a simple threshold permeability model on the basis of this descriptor allows to categorize the permeability of fluorescent probes with 96% accuracy. This novel descriptor is expected to largely simplify and speed up the development process for novel cell permeable fluorophores.

Structure-based modification of carbonyl-diphenylpyrimidines (Car-DPPYs) as a novel focal adhesion kinase (FAK) inhibitor against various stubborn cancer cells

A family of carbonyl-substituted diphenylpyrimidine derivatives (Car-DPPYs) with strong activity against focal adhesion kinase (FAK), were described in this manuscript. Among them, compounds 7a (IC₅₀ = 5.17 nM) and 7f (IC₅₀ = 2.58 nM) displayed equal anti-FAK enzymatic activity to the lead compound TAE226 (6.79 nM). In particular, compound 7a also exhibited strong antiproliferative activity against several stubborn cancer cells, including AsPC-1 cells (IC₅₀ = 0.105 μM), BxPC-3 cells (IC₅₀ = 0.090 μM), and MCF-7/ADR cells (IC₅₀ = 0.59 μM). Additionally, compound 7a also showed great antitumor efficacy in vivo via aAsPC-1 cancer Xenograft mouse model. The preliminary mechanism study by Western blot analysis revealed that 7a repressed FAK phosphorylation in AsPC cancer cells. Taken together, the results indicate that compound 7a may serve as a promising preclinical candidate for treatment of stubborn cancers.