The <i>In Vitro</i> Pharmacological Profile of Drugs as a Proxy Indicator of Potential <i>In Vivo</i> Organ Toxicities

The potential of a drug to cause certain organ toxicities is somehow implicitly contained in its full pharmacological profile, provided the drug reaches and accumulates at the various organs where the different interacting proteins in its profile, both targets and off-targets, are expressed. Under this assumption, a computational approach was implemented to obtain a projected anatomical profile of a drug from its <i>in vitro</i> pharmacological profile linked to protein expression data across 47 organs. It was observed that the anatomical profiles obtained when using only the known primary targets of the drugs reflected roughly the intended organ targets. However, when both known and predicted secondary pharmacology was considered, the projected anatomical profiles of the drugs were able to clearly highlight potential organ off-targets. Accordingly, when applied to sets of drugs known to cause cardiotoxicity and hepatotoxicity, the approach is able to identify heart and liver, respectively, as the organs where the proteins in the pharmacological profile of the corresponding drugs are specifically expressed. When applied to a set of drugs linked to a risk of Torsades de Pointes, heart is again the organ clearly standing out from the rest and a potential protein profile hazard is proposed. The approach can be used as a proxy indicator of potential <i>in vivo</i> organ toxicities

Figure 4

<p> <b>a) Venn diagram of the protein targets predicted for the selective cytotoxic compounds to HCT116 and MRC-5 cell lines; b) distribution across protein families of the 115 targets predicted to interact uniquely with selective cytotoxic compounds to tumor cells; and c) distribution across enzyme classes of the 67 enzymes present in the list of 115 putative cancer targets.</b></p

Profiles of experimental affinity data of the 20 drugs, among 4,819, hitting more than 5 targets found solely in tumor selective compounds.

<p>Only affinities above 1 µM are considered. Color coding reflects pAffinity ranges: white 6–7; light grey 7–8; dark grey 8–9; black >9. Color codes for targets refer to HDACs (yellow), kinases (orange), and other (green).</p

Figure 2

<p> <b>a) Correlation of two independent viability values determined for the same compound and b) distribution of viability values for the chemical library of 30,000 compounds.</b></p

Distribution of oncogene probabilities for the proteins predicted uniquely for compounds selective to HCT116 (black) and MRC-5 (light grey) and the proteins found in both selective sets (dark grey).

<p>NA collects all proteins for which oncogene probabilities were not available from CGPrio <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0035582#pone.0035582-Furney1" target="_blank">[34]</a>.</p

List of 42 proteins with OncoScore >0.7 among the 115 proteins identified by the DIVISS approach.

<p>The OncoScore is the oncogene probability calculated from CGPrio <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0035582#pone.0035582-Furney1" target="_blank">[34]</a>.The arrows next to the gene name mark the set of 10 proteins from this list that are known to be significantly altered (corrected p-value <0.05) in terms of up- or down-regulation in colon cancer, as extracted from the IntOGen platform <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0035582#pone.0035582-Gundem1" target="_blank">[33]</a>.</p

Schematic flowchart of the DIVISS approach applied in this work leading to the identification of 115 proteins of potential relevance to cancer.

<p>Schematic flowchart of the DIVISS approach applied in this work leading to the identification of 115 proteins of potential relevance to cancer.</p

Figure 3

<p> <b>a) Distribution of the cytotoxicity (IC50 values) of the selected compounds on HCT116 and MRC5 cells and b) distribution of the selective cytotoxicity against HCT116. NT means “non toxic”.</b></p