Antiproliferative Activity Predictor: A New Reliable In Silico Tool for Drug Response Prediction against NCI60 Panel

Abstract

In vitro antiproliferative assays still represent one of the most important tools in the anticancer drug discovery field, especially to gain insights into the mechanisms of action of anticancer small molecules. The NCI-DTP (National Cancer Institute Developmental Therapeutics Program) undoubtedly represents the most famous project aimed at rapidly testing thousands of compounds against multiple tumor cell lines (NCI60). The large amount of biological data stored in the National Cancer Institute (NCI) database and many other databases has led researchers in the fields of computational biology and medicinal chemistry to develop tools to predict the anticancer properties of new agents in advance. In this work, based on the available antiproliferative data collected by the NCI and the manipulation of molecular descriptors, we propose the new in silico Antiproliferative Activity Predictor (AAP) tool to calculate the GI50 values of input structures against the NCI60 panel. This ligand-based protocol, validated by both internal and external sets of structures, has proven to be highly reliable and robust. The obtained GI50 values of a test set of 99 structures present an error of less than ±1 unit. The AAP is more powerful for GI50 calculation in the range of 4–6, showing that the results strictly correlate with the experimental data. The encouraging results were further supported by the examination of an in-house database of curcumin analogues that have already been studied as antiproliferative agents. The AAP tool identified several potentially active compounds, and a subsequent evaluation of a set of molecules selected by the NCI for the one-dose/five-dose antiproliferative assays confirmed the great potential of our protocol for the development of new anticancer small molecules. The integration of the AAP tool in the free web service DRUDIT provides an interesting device for the discovery and/or optimization of anticancer drugs to the medicinal chemistry community. The training set will be updated with new NCI-tested compounds to cover more chemical spaces, activities, and cell lines. Currently, the same protocol is being developed for predicting the TGI (total growth inhibition) and LC50 (median lethal concentration) parameters to estimate toxicity profiles of small molecules.

Design and Synthesis of Novel Thieno[3,2-c]quinoline Compounds with Antiproliferative Activity on RET-Dependent Medullary Thyroid Cancer Cells

“…In view of these considerations and with the goal of discovering new agents for the treatment of RET-altered thyroid cancer, in this work, we applied our experience in in silico virtual screenings − to evaluate a large structural database. In particular, we performed a virtual screening to assess the affinity of an in-house structural database (about 10,000 heterocyclic compounds) for the RET kinase as a focused biological target.…”

In Vitro Cytotoxic Effects of Ferruginol Analogues in Sk-MEL28 Human Melanoma Cells

“…Cell proliferation is a critical step in determining the effectiveness of cytotoxic small molecules [20]. We here chose the Sulforhodamine B (SRB) staining assay, developed and These antecedents prompted the creation of a library of semisynthetic ferruginol derivatives (Figure 1) by one of the authors (M. Gonzalez-Cardenete) and their collaborative screening against a panel of representative human cancer cells (SUM149, MDA-MB231, T47D and MCF07A549, HBL-100, HeLa, SW1573, T-47D, WiDr, NALM-06, KOPN-8, SUP-B15, UoCB1 and BCR-ABL), and also parasites (Leishmania sp.)…”

“…Cell proliferation is a critical step in determining the effectiveness of cytotoxic small molecules [20]. We here chose the Sulforhodamine B (SRB) staining assay, developed and utilised by the US National Cancer Institute, as it is considered the gold standard for this screening method [21].…”

“…We, therefore, employed the Antiproliferative Activity Predictor (AAP) tool to calculate the GI50 values of 18-aminoferruginol and its parent molecule against the NCI60 panel. This ligand-based protocol has proven highly reliable and robust, making it particularly suitable for predicting activity against the SK-MEL-28 cell line [20]. It also uses data based on the same antiproliferative test we chose [21].…”

“…It also uses data based on the same antiproliferative test we chose [21]. Figure 9 shows the predicted results for ferruginol and 18-aminoferruginol (−logGI 50 ), with values between 4 and 6 considered more reliable [20].…”