This review provides the feasible literature on drug discovery through ML tools and techniques that are enforced in every phase of drug development to accelerate the research process and deduce the risk and expenditure in clinical trials. Machine learning techniques improve the decision-making in pharmaceutical data across various applications like QSAR analysis, hit discoveries, de novo drug architectures to retrieve accurate outcomes. Target validation, prognostic biomarkers, digital pathology are considered under problem statements in this review. ML challenges must be applicable for the main cause of inadequacy in interpretability outcomes that may restrict the applications in drug discovery. In clinical trials, absolute and methodological data must be generated to tackle many puzzles in validating ML techniques, improving decision-making, promoting awareness in ML approaches, and deducing risk failures in drug discovery.
In search of potential therapeutics for cancer, we described herein the synthesis, characterization, and in vitro anticancer activity of a novel series of curcumin analogues. The anticancer effects were evaluated on a panel of 60 cell lines, according to the National Cancer Institute (NCI) screening protocol. There were 10 tested compounds among 14 synthesized compounds, which showed potent anticancer activity in both one-dose and 5-dose assays. The most active compound of the series was 3,5-bis(4-hydroxy-3-methylstyryl)-1H-pyrazole-1-yl(phenyl)methanone (10) which showed mean growth percent of −28.71 in one-dose assay and GI50 values between 0.0079 and 1.86 µM in 5-dose assay.
We describe in this paper the synthesis of a novel series of anilino-2-quinazoline derivatives. These compounds have been screened against a panel of eight mammalian kinases and in parallel they were tested for cytotoxicity on a representative panel of seven cancer cell lines. One of them (DB18) has been found to be a very potent inhibitor of human "CDC2-like kinases" CLK1, CLK2 and CLK4, with IC 50 values in the 10-30 nM range. Interestingly, this molecule is inactive at 100M on the closely related "dualspecificity tyrosine-regulated kinase 1A" (DYRK1A). Extensive molecular simulation studies have been performed on the relevant kinases to explain the strong affinity of this molecule on CLKs, as well as its selectivity against DYRK1A.
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