Summary Discovering the unintended “off-targets” that predict adverse drug reactions (ADRs) is daunting by empirical methods alone. Drugs can act on multiple protein targets, some of which can be unrelated by traditional molecular metrics, and hundreds of proteins have been implicated in side effects. We therefore explored a computational strategy to predict the activity of 656 marketed drugs on 73 unintended “side effect” targets. Approximately half of the predictions were confirmed, either from proprietary databases unknown to the method or by new experimental assays. Affinities for these new off-targets ranged from 1 nM to 30 μM. To explore relevance, we developed an association metric to prioritize those new off-targets that explained side effects better than any known target of a given drug, creating a Drug-Target-ADR network. Among these new associations was the prediction that the abdominal pain side effect of the synthetic estrogen chlorotrianisene was mediated through its newly discovered inhibition of the enzyme COX-1. The clinical relevance of this inhibition was borne-out in whole human blood platelet aggregation assays. This approach may have wide application to de-risking toxicological liabilities in drug discovery.

Colloidal aggregation of organic molecules is the dominant mechanism for artifactual inhibition of proteins, and controls against it are widely deployed. Notwithstanding an increasingly detailed understanding of this phenomenon, a method to reliably predict aggregation has remained elusive. Correspondingly, active molecules that act via aggregation continue to be found in early discovery campaigns and remain common in the literature. Over the past decade, over 12 thousand aggregating organic molecules have been identified, potentially enabling a precedent-based approach to match known aggregators with new molecules that may be expected to aggregate and lead to artifacts. We investigate an approach that uses lipophilicity, affinity, and similarity to known aggregators to advise on the likelihood that a candidate compound is an aggregator. In prospective experimental testing, five of seven new molecules with Tanimoto coefficients (Tc’s) between 0.95 and 0.99 to known aggregators aggregated at relevant concentrations. Ten of 19 with Tc’s between 0.94 and 0.90 and three of seven with Tc’s between 0.89 and 0.85 also aggregated. Another three of the predicted compounds aggregated at higher concentrations. This method finds that 61 827 or 5.1% of the ligands acting in the 0.1 to 10 µM range in the medicinal chemistry literature are at least 85% similar to a known aggregator with these physical properties and may aggregate at relevant concentrations. Intriguingly, only 0.73% of all drug-like commercially available compounds resemble the known aggregators, suggesting that colloidal aggregators are enriched in the literature. As a percentage of the literature, aggregator-like compounds have increased 9-fold since 1995, partly reflecting the advent of high-throughput and virtual screens against molecular targets. Emerging from this study is an aggregator advisor database and tool (http://advisor.bkslab.org), free to the community, that may help distinguish between fruitful and artifactual screening hits acting by this mechanism.

Many small molecules, including bioactive molecules and approved drugs, spontaneously form colloidal aggregates in aqueous solution at micromolar concentrations. Though it is widely accepted that aggregation leads to artifacts in screens for ligands of soluble proteins, the effects of colloid formation in cell-based assays have not been studied. Here, seven anticancer drugs and one diagnostic reagent were found to form colloids in both biochemical buffer and in cell culture media. In cell-based assays, the antiproliferative activities of three of the drugs were substantially reduced when in colloidal form as compared to monomeric form; a new formulation method ensured the presence of drug colloids versus drug monomers in solution. We also found that Evans Blue, a dye classically used to measure vascular permeability and to demonstrate the “enhanced permeability and retention (EPR) effect” in solid tumors, forms colloids that adsorb albumin, as opposed to older literature that suggested the reverse.

G-protein-coupled receptors (GPCRs) are key signaling molecules and are intensely studied. Whereas GPCRs recognizing small-molecules have been successfully targeted for drug discovery, proteinrecognizing GPCRs, such as the chemokine receptors, claim few drugs or even useful small molecule reagents. This reflects both the difficulties that attend protein-protein interface inhibitor discovery, and the lack of structures for these targets. Imminent structure determination of chemokine receptor CXCR4 motivated docking screens for new ligands against a homology model and subsequently the crystal structure. More than 3 million molecules were docked against the model and then against the crystal structure; 24 and 23 high-scoring compounds from the respective screens were tested experimentally. Docking against the model yielded only one antagonist, which resembled known ligands and lacked specificity, whereas the crystal structure docking yielded four that were dissimilar to previously known scaffolds and apparently specific. Intriguingly, several were potent and relatively small, with IC 50 values as low as 306 nM, ligand efficiencies as high as 0.36, and with efficacy in cellular chemotaxis. The potency and efficiency of these molecules has few precedents among protein-protein interface inhibitors, and supports structure-based efforts to discover leads for chemokine GPCRs.drug design | virtual screening | promiscuous aggregation G -protein-coupled receptors (GPCRs) play a central role in many normal physiological pathways and altered diseased states, and are the targets of approximately 30% of marketed drugs (1). Ligand discovery against small-molecule GPCRs such as the bioamine receptors has been particularly productive, as have structure-based screens against their crystal structures (2-5). Targeting larger-molecule-recognizing GPCRs has been more difficult. Although multiple reagents are available for lipid and peptidergic GPCRs, their molecular weights are substantially higher than those typical for bioamine receptors, and they are less ligand efficient. This reflects the challenges faced in ligand discovery against peptide-protein and lipid-protein interfaces. These difficulties are still more acute against chemokine GPCRs, which recognize folded proteins of ∼100 amino acids in length and are thus protein-protein interface (PPI) targets (6). Although there are several example drugs in this class, such as maraviroc, plerixafor, and vorapaxar, finding organic molecules with good affinity and the physical properties of oral drugs is notoriously difficult for PPI targets, as reflected in the high molecular weight and hydrophobicity of the few PPI drugs (7).A public competition to predict ligand complexes with the structure of C-X-C chemokine receptor 4 (CXCR4) inspired us to bring structure-based discovery to bear against a key member of the chemokine family (8). CXCR4 natively recognizes the CXCL12 chemokine, an 8-kDa protein. Like many other PPI targets, CXCR4 plays a key signaling role: it is constitutively expres...

Antibodies are key reagents in biology and medicine, but commercial sources are rarely recombinant and thus do not provide a permanent and renewable resource. Here, we describe an industrialized platform to generate antigens and validated recombinant antibodies for 346 transcription factors (TFs) and 211 epigenetic antigens. We describe an optimized automated phage display and antigen expression pipeline that in aggregate produced about 3000 sequenced Fragment antigen-binding domain that had high affinity (typically EC50<20 nm), high stability (Tm∼80 °C), good expression in E. coli (∼5 mg/L), and ability to bind antigen in complex cell lysates. We evaluated a subset of Fabs generated to homologous SCAN domains for binding specificities. These Fragment antigen-binding domains were monospecific to their target SCAN antigen except in rare cases where they cross-reacted with a few highly related antigens. Remarkably, immunofluorescence experiments in six cell lines for 270 of the TF antigens, each having multiple antibodies, show that ∼70% stain predominantly in the cytosol and ∼20% stain in the nucleus which reinforces the dominant role that translocation plays in TF biology. These cloned antibody reagents are being made available to the academic community through our web site recombinant-antibodies.org to allow a more system-wide analysis of TF and chromatin biology. We believe these platforms, infrastructure, and automated approaches will facilitate the next generation of renewable antibody reagents to the human proteome in the coming decade.