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A remarkable Ugi4CR approach to access a library of isatin-based α-acetoamide carboxamide oxindole derivatives with promising antiproliferative activity.

Herein, we demonstrate a simple, rapid and green synthesis of 2,4-dimethoxy-THPQs under microwave irradiation and their antiproliferative activity, in silico ADMET and drug-likeness studies were carried out.

In this work, we propose a general methodology to assess the bioactive potential (BP) of extracts in the quest of vegetable-based drugs. To exemplify the method, we studied the anticancer potential (AP) of four endemic species of genus

Based on a previously prepared lead compound, a new series of hybrid compounds was prepared and tested against six human tumour cell lines. These new triazole linked tetrahydropyran–oxazole hybrids were prepared evaluating the impact of the LogP for the proposed modifications. The compounds exhibited good antiproliferative results when compared with standards cisplatin and 5-fluorouracil. A series of triazole linked tetrahydropyran–oxazole hybrids was synthesized based on a previously reported lead compound with selective antiproliferative activity against human tumour cell lines. The series was prepared to evaluate the impact of LogP and different modifications in the activity, and the new compounds were assayed against A549, HBL-100, HeLa, SW1573, T-47D, and WiDr cell lines. Also, the potentiality to be P-gp substrate was tested. The compounds exhibited good antiproliferative results when compared with the standards cisplatin and 5-fluorouracil. In silico studies to evaluate pharmacokinetic properties using pkCSM software were also carried out.

In this study, we demonstrate a simple, highly efficient, rapid and convenient series of 2,4-dimethoxy-tetrahydropyrimido[4,5

Natural products represent an excellent source of unprecedented anticancer compounds. However, the identification of the mechanism of action remains a major challenge. Several techniques and methodologies have been considered, but with limited success. In this work, we explored the combination of live cell imaging and machine learning techniques as a promising tool to depict in a fast and affordable test the mode of action of natural compounds with antiproliferative activity. To develop the model, we selected the non-small cell lung cancer cell line SW1573, which was exposed to the known antimitotic drugs paclitaxel, colchicine and vinblastine. The novelty of our methodology focuses on two main features with the highest relevance, (a) meaningful phenotypic metrics, and (b) fast Fourier transform (FFT) of the time series of the phenotypic parameters into their corresponding amplitudes and phases. The resulting algorithm was able to cluster the microtubule disruptors, and meanwhile showed a negative correlation between paclitaxel and the other treatments. The FFT approach was able to group the samples as efficiently as checking by eye. This methodology could easily scale to group a large amount of data without visual supervision.