J. Med. Chem. dimethylformamide (1 mL) was treated with 60% sodium hydride in oil (20 mg) for 20 min, and then with ethyl iodide (0.02 mL) for 20 min longer. The mixture was concentrated to dryness at 0.1 mm, taken up in ethyl acetate, washed with sodium bicarbonate solution, dried (Mg#O$, concentrated to dryness, and triturated with ether to afford the ester as an off-white solid, mp 110-118 OC (30 mg, 31%). Similarly, 3s was prepared from 3a i991,34, m 9 -2 5~ 2579 through the use of tert-butyl 4-(2-aminoethyl)phenylacetate.% An array of cis-, trans-, and dihydrostilbenes and some N-arylbenzylamines were synthesized and evaluated for their cytotoxicity in t.he five cancer cell cultures A-549 lung carcinoma, MCF-7 breast carcinoma, HT-29 colon adenocarcinoma, SKMEL-5 melanoma, and MLM melanoma. Several cis-stilbenes, structurally similar to combretastatins, were highly cytotoxic in all five cell lines and these were also found to be active as inhibitora of tubulin polymerization. The most active compounds also inhibited the binding of colchicine to tubulin. The most potent of the new compounds, both as a tubulin polymerization inhibitor and as a cytotoxic agent, was (Z)-l-(4-methoxyphenyl)-2-(3,4,5-trimethoxyphenyl)ethene (Sa). This substance was almost as potent as combretastatin A-4 (la), the most active of the combretastatins, as a tubulin polymerization inhibitor. Compound 5a was found to be approximately 140 times more cytotoxic against HT-29 colon adenocarcinoma cells and about 10 times more cytotoxic against MCF-7 breast carcinoma cells than combretastatin A-4. However, 5a was found to be about 20 times less cytotoxic against A-549 lung carcinoma cells, 30 times less cytotoxic against SKMEL-5 melanoma cells, and 7 times less cytotoxic against MLM melanoma cells than combretastatin A-4. The relative potencies 5a > 8a > 6a for the cis, dihydro, and trans compounds, respectively, as inhibitors of tubulin polymerization are in agreement with the relative potencies previously observed for combretastatin A-4 (la), dihydrocombretastatin A-4 (IC), and transcombretastatin A-4 (lb). The relative potencies 5a > 8a > 6a were also reflected in the results of the cytotoxicity assays. Structure-activity relationships of this group of compounds are also discussed.

A series of stilbenes has been prepared and tested for cytotoxicity in the five human cancer cell lines A-549 non-small cell lung, MCF-7 breast, HT-29 colon, SKMEL-5 melanoma, and MLM melanoma. The cis stilbenes 6a-f proved to be cytotoxic in all five cell lines, with potencies comparable to that of combretastatin A-4. These cytotoxic compounds were all potent inhibitors of tubulin polymerization. The corresponding trans stilbenes 7b-f were inactive as tubulin polymerization inhibitors and were significantly less cytotoxic in the five cancer cell lines. In the dihydro series, 8b, 8c, and 8f were inactive as tubulin polymerization inhibitors, while 8a, 8d, and 8e were less active than the corresponding cis compounds 6a, 6d, and 6e. The lack of tubulin polymerization inhibitory activity and cytotoxicity displayed by the phenanthrene 23b, which was synthesized as a conformationally rigid analogue of the lead compound 1, indicates that the activity of the stilbenes is not due to a totally planar conformation. Similarly, inactivity of the conformationally restricted analogue 26 suggests that the biologically active conformation of 1a resembles that of the cis alkene 1. Additional inactive compounds prepared include the benzylisoquinoline series 28-32 as well as the protoberberines 38 and 39. Shortening the two-carbon bridge of 1a to a one-carbon bridge in the diphenylmethane 20 resulted in a decrease in cytotoxicity and tubulin polymerization inhibitory activity. Although the corresponding benzophenone 18 was as active as 1a as a tubulin polymerization inhibitor, it was less cytotoxic than 1a, and the benzhydrol 19 was essentially inactive. With the exception of the amide 15c, which displayed low antitubulin activity, all of the phenylcinnamic acid derivatives 14a-c and 15a-f were inactive in the tubulin polymerization inhibition assay. The acid 14b and the ester 15a were cytotoxic in several of the cancer cell cultures in spite of their inactivity as tubulin polymerization inhibitors.

Exosomes are the smallest extracellular vesicles present in most of the biological fluids. They are found to play an important role in cell signaling, immune response, tumor metastasis, etc. Studies have shown that these vesicles also have diagnostic and therapeutic roles for which their accurate detection and quantification is essential. Due to the complexity in size and structure of exosomes, even the gold standard methods face challenges. This comprehensive review discusses the various standard methods such as ultracentrifugation, ultrafiltration, size-exclusion chromatography, precipitation, immunoaffinity, and microfluidic technologies for the isolation of exosomes. The principle of isolation of each method is described, as well as their specific advantages and disadvantages. Quantification of exosomes by nanoparticle tracking analysis, flow cytometry, tunable resistive pulse sensing, electron microscopy, dynamic light scattering, and microfluidic devices are also described, along with the applications of exosomes in various biomedical domains.

Optical microscopy has emerged as a key driver of fundamental research since it provides the ability to probe into imperceptible structures in the biomedical world. For the detailed investigation of samples, a high-resolution image with enhanced contrast and minimal damage is preferred. To achieve this, an automated image analysis method is preferable over manual analysis in terms of both speed of acquisition and reduced error accumulation. In this regard, deep learning (DL)-based image processing can be highly beneficial. The review summarises and critiques the use of DL in image processing for the data collected using various optical microscopic techniques. In tandem with optical microscopy, DL has already found applications in various problems related to image classification and segmentation. It has also performed well in enhancing image resolution in smartphone-based microscopy, which in turn enablse crucial medical assistance in remote places. Graphical abstract

The repurposing of FDA approved drugs is presently receiving attention for COVID-19 drug discovery. Previous studies revealed the binding potential of several FDA-approved drugs towards specific targets of SARS-CoV-2; however, limited studies are focused on the structural and molecular basis of interaction of these drugs towards multiple targets of SARS-CoV-2. The present study aimed to predict the binding potential of six FDA drugs towards fifteen protein targets of SARS-CoV-2 and propose the structural and molecular basis of the interaction by molecular docking and dynamic simulation. Based on the literature survey, fifteen potential targets of SARS-CoV-2, and six FDA drugs (Chloroquine, Hydroxychloroquine, Favipiravir, Lopinavir, Remdesivir, and Ritonavir) were selected. The binding potential of individual drug towards the selected targets was predicted by molecular docking in comparison with the binding of the same drugs with their usual targets. The stabilities of the best-docked conformations were confirmed by molecular dynamic simulation and energy calculations. Among the selected drugs, Ritonavir and Lopinavir showed better binding towards the prioritized targets with minimum binding energy (kcal/mol), cluster-RMS, number of interacting residues, and stabilizing forces when compared with the binding of Chloroquine, Favipiravir, and Hydroxychloroquine, later drugs demonstrated better binding when compared to the binding with their usual targets. Remdesvir showed better binding to the prioritized targets in comparison with the binding of Chloroquine, Favipiravir, and Hydroxychloroquine, but showed lesser binding potential when compared to the interaction between Ritonavir and Lopinavir and the prioritized targets. The structural and molecular basis of interactions suggest that the FDA drugs can be repurposed towards multiple targets of SARS-CoV-2, and the present computational models provide insights on the scope of repurposed drugs against COVID-19.