MTHFD1 interaction with BRD4 links folate metabolism to transcriptional regulation.

The histone acetyl reader bromodomain-containing protein 4 (BRD4) is an important regulator of chromatin structure and transcription, yet factors modulating its activity have remained elusive. Here we describe two complementary screens for genetic and physical interactors of BRD4, which converge on the folate pathway enzyme MTHFD1 (methylenetetrahydrofolate dehydrogenase, cyclohydrolase and formyltetrahydrofolate synthetase 1). We show that a fraction of MTHFD1 resides in the nucleus, where it is recruited to distinct genomic loci by direct interaction with BRD4. Inhibition of either BRD4 or MTHFD1 results in similar changes in nuclear metabolite composition and gene expression; pharmacological inhibitors of the two pathways synergize to impair cancer cell viability in vitro and in vivo. Our finding that MTHFD1 and other metabolic enzymes are chromatin associated suggests a direct role for nuclear metabolism in the control of gene expression.

A combinatorial screen of the CLOUD uncovers a synergy targeting the androgen receptor.

Approved drugs are invaluable tools to study biochemical pathways, and further characterization of these compounds may lead to repurposing of single drugs or combinations. Here we describe a collection of 308 small molecules representing the diversity of structures and molecular targets of all FDA-approved chemical entities. The CeMM Library of Unique Drugs (CLOUD) covers prodrugs and active forms at pharmacologically relevant concentrations and is ideally suited for combinatorial studies. We screened pairwise combinations of CLOUD drugs for impairment of cancer cell viability and discovered a synergistic interaction between flutamide and phenprocoumon (PPC). The combination of these drugs modulates the stability of the androgen receptor (AR) and resensitizes AR-mutant prostate cancer cells to flutamide. Mechanistically, we show that the AR is a substrate for γ-carboxylation, a post-translational modification inhibited by PPC. Collectively, our data suggest that PPC could be repurposed to tackle resistance to antiandrogens in prostate cancer patients.

Mapping the chemical chromatin reactivation landscape identifies BRD4-TAF1 cross-talk.

Bromodomain-containing proteins of the BET family recognize histone lysine acetylation and mediate transcriptional activation of target genes such as the MYC oncogene. Pharmacological inhibitors of BET domains promise therapeutic benefits in a variety of cancers. We performed a high-diversity chemical compound screen for agents capable of modulating BRD4-dependent heterochromatization of a generic reporter in human cells. In addition to known and new compounds targeting BRD4, we identified small molecules that mimic BRD4 inhibition without direct engagement. One such compound was a potent inhibitor of the second bromodomain of TAF1. Using this inhibitor, we discovered that TAF1 synergizes with BRD4 to control proliferation of cancer cells, making TAF1 an attractive epigenetic target in cancers driven by MYC.

Targeting a cell state common to triple-negative breast cancers.

Some mutations in cancer cells can be exploited for therapeutic intervention. However, for many cancer subtypes, including triple-negative breast cancer (TNBC), no frequently recurring aberrations could be identified to make such an approach clinically feasible. Characterized by a highly heterogeneous mutational landscape with few common features, many TNBCs cluster together based on their 'basal-like' transcriptional profiles. We therefore hypothesized that targeting TNBC cells on a systems level by exploiting the transcriptional cell state might be a viable strategy to find novel therapies for this highly aggressive disease. We performed a large-scale chemical genetic screen and identified a group of compounds related to the drug PKC412 (midostaurin). PKC412 induced apoptosis in a subset of TNBC cells enriched for the basal-like subtype and inhibited tumor growth in vivo. We employed a multi-omics approach and computational modeling to address the mechanism of action and identified spleen tyrosine kinase (SYK) as a novel and unexpected target in TNBC. Quantitative phosphoproteomics revealed that SYK inhibition abrogates signaling to STAT3, explaining the selectivity for basal-like breast cancer cells. This non-oncogene addiction suggests that chemical SYK inhibition may be beneficial for a specific subset of TNBC patients and demonstrates that targeting cell states could be a viable strategy to discover novel treatment strategies.

Ligand and structure-based classification models for prediction of P-glycoprotein inhibitors.

The ABC transporter P-glycoprotein (P-gp) actively transports a wide range of drugs and toxins out of cells, and is therefore related to multidrug resistance and the ADME profile of therapeutics. Thus, development of predictive in silico models for the identification of P-gp inhibitors is of great interest in the field of drug discovery and development. So far in silico P-gp inhibitor prediction was dominated by ligand-based approaches because of the lack of high-quality structural information about P-gp. The present study aims at comparing the P-gp inhibitor/noninhibitor classification performance obtained by docking into a homology model of P-gp, to supervised machine learning methods, such as Kappa nearest neighbor, support vector machine (SVM), random fores,t and binary QSAR, by using a large, structurally diverse data set. In addition, the applicability domain of the models was assessed using an algorithm based on Euclidean distance. Results show that random forest and SVM performed best for classification of P-gp inhibitors and noninhibitors, correctly predicting 73/75% of the external test set compounds. Classification based on the docking experiments using the scoring function ChemScore resulted in the correct prediction of 61% of the external test set. This demonstrates that ligand-based models currently remain the methods of choice for accurately predicting P-gp inhibitors. However, structure-based classification offers information about possible drug/protein interactions, which helps in understanding the molecular basis of ligand-transporter interaction and could therefore also support lead optimization.

Random mutagenesis of the prokaryotic peptide transporter YdgR identifies potential periplasmic gating residues.

The peptide transporter (PTR) family represents a group of proton-coupled secondary transporters responsible for bulk uptake of amino acids in the form of di- and tripeptides, an essential process employed across species ranging from bacteria to humans. To identify amino acids critical for peptide transport in a prokaryotic PTR member, we have screened a library of mutants of the Escherichia coli peptide transporter YdgR using a high-throughput substrate uptake assay. We have identified 35 single point mutations that result in a full or partial loss of transport activity. Additional analysis, including homology modeling based on the crystal structure of the Shewanella oneidensis peptide transporter PepT(so), identifies Glu(56) and Arg(305) as potential periplasmic gating residues. In addition to providing new insights into transport by members of the PTR family, these mutants provide valuable tools for further study of the mechanism of peptide transport.

Exhaustive sampling of docking poses reveals binding hypotheses for propafenone type inhibitors of P-glycoprotein.

Overexpression of the xenotoxin transporter P-glycoprotein (P-gp) represents one major reason for the development of multidrug resistance (MDR), leading to the failure of antibiotic and cancer therapies. Inhibitors of P-gp have thus been advocated as promising candidates for overcoming the problem of MDR. However, due to lack of a high-resolution structure the concrete mode of interaction of both substrates and inhibitors is still not known. Therefore, structure-based design studies have to rely on protein homology models. In order to identify binding hypotheses for propafenone-type P-gp inhibitors, five different propafenone derivatives with known structure-activity relationship (SAR) pattern were docked into homology models of the apo and the nucleotide-bound conformation of the transporter. To circumvent the uncertainty of scoring functions, we exhaustively sampled the pose space and analyzed the poses by combining information retrieved from SAR studies with common scaffold clustering. The results suggest propafenone binding at the transmembrane helices 5, 6, 7 and 8 in both models, with the amino acid residue Y307 playing a crucial role. The identified binding site in the non-energized state is overlapping with, but not identical to, known binding areas of cyclic P-gp inhibitors and verapamil. These findings support the idea of several small binding sites forming one large binding cavity. Furthermore, the binding hypotheses for both catalytic states were analyzed and showed only small differences in their protein-ligand interaction fingerprints, which indicates only small movements of the ligand during the catalytic cycle.

Probing the stereoselectivity of P-glycoprotein-synthesis, biological activity and ligand docking studies of a set of enantiopure benzopyrano[3,4-b][1,4]oxazines.

A series of enantiomerically pure benzopyrano[3,4-b][1,4]oxazines have been synthesised and tested for their ability to inhibit P-glycoprotein. Reducing the conformational flexibility of the molecules leads to remarkable differences in the activity of diastereoisomers. Docking studies into a homology model of human P-gp provide first insights into potential binding areas for these compounds.

Using structural and mechanistic information to design novel inhibitors/substrates of P-glycoprotein.

Design of inhibitors of P-glycoprotein still represents a challenging task for medicinal chemists. The polyspecificity of the transporter combined with the limited structural information renders rational drug design approaches rather ineffective. Within this article we will exemplify how recent insights into structure and mechanism of P-glycoprotein may aid in design of potent inhibitors.

Impact of the Recent Mouse P-Glycoprotein Structure for Structure-Based Ligand Design.

P-Glycoprotein (P-gp), a transmembrane, ATP-dependent drug efflux transporter, has attracted considerable interest both with respect to its role in tumour cell multidrug resistance and in absorption-distribution and elimination of drugs. Although known since more than 30 years, the understanding of the molecular basis of drug/transporter interaction is still limited, which is mainly due to the lack of structural information available. However, within the past decade X-ray structures of several bacterial homologues as well as very recently also of mouse P-gp have become available. Within this review we give an overview on the current status of structural information available and on its impact for structure-based drug design.