Docking Small Molecules to Predicted Off-Targets of the Cancer Drug Erlotinib Leads to Inhibitors of Lung Cancer Cell Proliferation with Suitable In vitro Pharmacokinetic Properties.

In an effort to develop a rational approach to identify anti-cancer agents with selective polypharmacology, we mine millions of docked protein-ligand complexes involving more than a thousand cancer targets from multiple signaling pathways to identify new structural templates for proven pharmacophores. Our method combines Support Vector Machine-based scoring to enrich the initial library of 1,592 molecules, with a fingerprint-based search for molecules that have the same binding profile as the EGFR kinase inhibitor erlotinib. Twelve new compounds were identified. In vitro activity assays revealed that three inhibited EGFR with IC(50) values ranging from 250 nM to 200 µM. Additional in vitro studies with hERG, CYP450, DNA and cell culture-based assays further compared their properties to erlotinib. One compound combined suitable pharmacokinetic properties while closely mimicking the binding profile of erlotinib. The compound also inhibited H1299 and H460 tumor cell proliferation. The other two compounds shared some of the binding profile of erlotinib, and one gave the most potent inhibition of tumor cell growth. Interestingly, among the compounds that had not shown inhibition of EGFR, four blocked H1299 and H460 proliferation, one potently with IC(50) values near 1 µM. This compound was from the menogaril family, which reached Phase II clinical trial for the treatment of lymphomas. This suggests that our computational approach comparing binding profile may have favored molecules with anti-cancer properties like erlotinib.

Uncovering the unfoldome: enriching cell extracts for unstructured proteins by acid treatment.

A method to enrich cell extracts in totally unfolded proteins was investigated. A literature search revealed that 14 of 29 proteins isolated by their failure to precipitate during perchloric acid (PCA) or trichloroacetic acid (TCA) treatment where also shown experimentally to be totally disordered. A near 100 000-fold reduction in yield was observed after 5% or 9% PCA treatment of total soluble E. coli protein. Despite this huge reduction, 158 and 142 spots were observed from the 5% and the 9% treated samples, respectively, on silver-stained 2-D SDS-PAGE gels loaded with 10 microg of protein. Treatment with 1% PCA was less selective with more visible spots and a greater than 3-fold higher yield. A substantial yield of unprecipitated protein was obtained after 3% TCA treatment, suggesting that the common use of TCA precipitation prior to 2-D gel analysis may result in loss of unstructured protein due to their failure to precipitate. Our preliminary analysis suggests that treating total protein extracts with 3-5% PCA and determining the identities of soluble proteins could be the starting point for uncovering unfoldomes (the complement of unstructured proteins in a given proteome). The 100 000-fold reduction in yield and concomitant reduction in number of proteins achieved by 5% PCA treatment produced a fraction suitable for analysis in its entirety using standard proteomic techniques. In this way, large numbers of totally unstructured proteins could be identified with minimal effort.