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Open AccessArticle

In Search of Outliers. Mining for Protein Kinase Inhibitors Based on Their Anti-Proliferative NCI-60 Cell Lines Profile

Faculty of Pharmacy, “Carol Davila” University of Medicine and Pharmacy, Traian Vuia 6, 020956 Bucharest, Romania
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Molecules 2020, 25(8), 1766; https://doi.org/10.3390/molecules25081766
Received: 15 March 2020 / Revised: 10 April 2020 / Accepted: 10 April 2020 / Published: 11 April 2020
Protein kinases play a pivotal role in signal transduction, protein synthesis, cell growth and proliferation. Their deregulation represents the basis of pathogenesis for numerous diseases such as cancer and pathologies with cardiovascular, nervous and inflammatory components. Protein kinases are an important target in the pharmaceutical industry, with 48 protein kinase inhibitors (PKI) already approved on the market as treatments for different afflictions including several types of cancer. The present work focuses on facilitating the identification of new PKIs with antitumoral potential through the use of data-mining and basic statistics. The National Cancer Institute (NCI) granted access to the results of numerous previously tested compounds on 60 tumoral cell lines (NCI-60 panel). Our approach involved analyzing the NCI database to identify compounds that presented similar growth inhibition (GI) profiles to that of existing PKIs, but different from approved oncologic drugs with other mechanisms of action, using descriptive statistics and statistical outliers. Starting from 34,000 compounds present in the database, we filtered 400 which displayed selective inhibition on certain cancer cell lines similar to that of several already-approved PKIs. View Full-Text
Keywords: protein kinase inhibitors; anti-proliferative fingerprint; anticancer drug screening; data-mining; NCI-60 cells; drug discovery; targeted therapy; drug repurposing protein kinase inhibitors; anti-proliferative fingerprint; anticancer drug screening; data-mining; NCI-60 cells; drug discovery; targeted therapy; drug repurposing
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MDPI and ACS Style

Ion, G.N.D.; Nitulescu, G.M. In Search of Outliers. Mining for Protein Kinase Inhibitors Based on Their Anti-Proliferative NCI-60 Cell Lines Profile. Molecules 2020, 25, 1766.

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