Project description:Eukaryotic life depends upon the interplay between vast networks of signaling pathways composed of upwards of 109-1010 proteins per cell. The integrity and normal operation of the cell requires that these proteins act in a precise spatial and temporal manner. The ubiquitin system is absolutely central to this process and perturbation of its function contributes directly to the onset and progression of a wide variety of diseases, including cancer, metabolic syndromes, neurodegenerative diseases, autoimmunity, inflammatory disorders, infectious diseases, and muscle dystrophies. Whilst the individual components and the overall architecture of the ubiquitin system have been delineated in some detail, how ubiquitination might be successfully targeted, or harnessed, to develop novel therapeutic approaches to the treatment of disease, currently remains relatively poorly understood. In this review, we will provide an overview of the current status of selected small molecule ubiquitin system inhibitors. We will further discuss the unique challenges of targeting this ubiquitous and highly complex machinery, and explore and highlight potential ways in which these challenges might be met.
Project description:Tissue transglutaminase (TG2) is a multifunctional protein with enzymatic, GTP-ase, and scaffold properties. TG2 interacts with fibronectin (FN) through its N-terminus domain, stabilizing integrin complexes, which regulate cell adhesion to the matrix. Through this mechanism, TG2 participates in key steps involved in metastasis in ovarian and other cancers. High-throughput screening identified several small molecule inhibitors (SMI) for the TG2/FN complex. Rational medicinal chemistry optimization of the hit compound (TG53) led to second-generation analogues (MT1-6). ELISA demonstrated that these analogues blocked TG2/FN interaction, and bio-layer interferometry (BLI) showed that the SMIs bound to TG2. The compounds also potently inhibited cancer cell adhesion to FN and decreased outside-in signaling mediated through the focal adhesion kinase. Blockade of TG2/FN interaction by the small molecules caused membrane ruffling, delaying the formation of stable focal contacts and mature adhesions points and disrupted organization of the actin cytoskeleton. In an in vivo model measuring intraperitoneal dissemination, MT4 and MT6 inhibited the adhesion of ovarian cancer cells to the peritoneum. Pretreatment with MT4 also sensitized ovarian cancer cells to paclitaxel. The data support continued optimization of the new class of SMIs that block the TG2/FN complex at the interface between cancer cells and the tumor niche.
Project description:The human fungal pathogen Candida albicans can form biofilms on biotic and abiotic surfaces, which are inherently resistant to antifungal drugs. We screened the Chembridge Small Molecule Diversity library containing 30,000 "drug-like" small molecules and identified 45 compounds that inhibited biofilm formation. These 45 compounds were then tested for their abilities to disrupt mature biofilms and for combinatorial interactions with fluconazole, amphotericin B, and caspofungin, the three antifungal drugs most commonly prescribed to treat Candida infections. In the end, we identified one compound that moderately disrupted biofilm formation on its own and four compounds that moderately inhibited biofilm formation and/or moderately disrupted mature biofilms only in combination with either caspofungin or fluconazole. No combinatorial interactions were observed between the compounds and amphotericin B. As members of a diversity library, the identified compounds contain "drug-like" chemical backbones, thus even seemingly "weak hits" could represent promising chemical starting points for the development and the optimization of new classes of therapeutics designed to target Candida biofilms.
Project description:There is growing interest in therapeutic intervention that targets disease-relevant RNAs using small molecules. While there have been some successes in RNA-targeted small-molecule discovery, a deeper understanding of structure-activity relationships in pursuing these targets has remained elusive. One of the best-studied tertiary-structured RNAs is the theophylline aptamer, which binds theophylline with high affinity and selectivity. Although not a drug target, this aptamer has had many applications, especially pertaining to genetic control circuits. Heretofore, no compound has been shown to bind the theophylline aptamer with greater affinity than theophylline itself. However, by carrying out a high-throughput screen of low-molecular-weight compounds, several unique hits were identified that are chemically distinct from theophylline and bind with up to 340-fold greater affinity. Multiple atomic-resolution X-ray crystal structures were determined to investigate the binding mode of theophylline and four of the best hits. These structures reveal both the rigidity of the theophylline aptamer binding pocket and the opportunity for other ligands to bind more tightly in this pocket by forming additional hydrogen-bonding interactions. These results give encouragement that the same approaches to drug discovery that have been applied so successfully to proteins can also be applied to RNAs.
Project description:Bioactive small molecules, such as drugs or metabolites, bind to proteins or other macro-molecular targets to modulate their activity, which in turn results in the observed phenotypic effects. For this reason, mapping the targets of bioactive small molecules is a key step toward unraveling the molecular mechanisms underlying their bioactivity and predicting potential side effects or cross-reactivity. Recently, large datasets of protein-small molecule interactions have become available, providing a unique source of information for the development of knowledge-based approaches to computationally identify new targets for uncharacterized molecules or secondary targets for known molecules. Here, we introduce SwissTargetPrediction, a web server to accurately predict the targets of bioactive molecules based on a combination of 2D and 3D similarity measures with known ligands. Predictions can be carried out in five different organisms, and mapping predictions by homology within and between different species is enabled for close paralogs and orthologs. SwissTargetPrediction is accessible free of charge and without login requirement at http://www.swisstargetprediction.ch.
Project description:Oligonucleotides are designed to target RNA using base pairing rules, but they can be hampered by poor cellular delivery and nonspecific stimulation of the immune system. Small molecules are preferred as lead drugs or probes but cannot be designed from sequence. Herein, we describe an approach termed Inforna that designs lead small molecules for RNA from solely sequence. Inforna was applied to all human microRNA hairpin precursors, and it identified bioactive small molecules that inhibit biogenesis by binding nuclease-processing sites (44% hit rate). Among 27 lead interactions, the most avid interaction is between a benzimidazole (1) and precursor microRNA-96. Compound 1 selectively inhibits biogenesis of microRNA-96, upregulating a protein target (FOXO1) and inducing apoptosis in cancer cells. Apoptosis is ablated when FOXO1 mRNA expression is knocked down by an siRNA, validating compound selectivity. Markedly, microRNA profiling shows that 1 only affects microRNA-96 biogenesis and is at least as selective as an oligonucleotide.
Project description:The Ras-like GTPases RalA and RalB are important drivers of tumour growth and metastasis. Chemicals that block Ral function would be valuable as research tools and for cancer therapeutics. Here we used protein structure analysis and virtual screening to identify drug-like molecules that bind to a site on the GDP-bound form of Ral. The compounds RBC6, RBC8 and RBC10 inhibited the binding of Ral to its effector RALBP1, as well as inhibiting Ral-mediated cell spreading of murine embryonic fibroblasts and anchorage-independent growth of human cancer cell lines. The binding of the RBC8 derivative BQU57 to RalB was confirmed by isothermal titration calorimetry, surface plasmon resonance and (1)H-(15)N transverse relaxation-optimized spectroscopy (TROSY) NMR spectroscopy. RBC8 and BQU57 show selectivity for Ral relative to the GTPases Ras and RhoA and inhibit tumour xenograft growth to a similar extent to the depletion of Ral using RNA interference. Our results show the utility of structure-based discovery for the development of therapeutics for Ral-dependent cancers.
Project description:Most small molecule drugs interact with unintended, often unknown, biological targets and these off-target interactions may lead to both preclinical and clinical toxic events. Undesired off-target interactions are often not detected using current drug discovery assays, such as experimental polypharmacological screens. Thus, improvement in the early identification of off-target interactions represents an opportunity to reduce safety-related attrition rates during preclinical and clinical development. In order to better identify potential off-target interactions that could be linked to predictable safety issues, a novel computational approach to predict safety-relevant interactions currently not covered was designed and evaluated. These analyses, termed Off-Target Safety Assessment (OTSA), cover more than 7,000 targets (~35% of the proteome) and > 2,46,704 preclinical and clinical alerts (as of January 20, 2019). The approach described herein exploits a highly curated training set of >1 million compounds (tracking >20 million compound-structure activity relationship/SAR data points) with known in vitro activities derived from patents, journals, and publicly available databases. This computational process was used to predict both the primary and secondary pharmacological activities for a selection of 857 diverse small molecule drugs for which extensive secondary pharmacology data are readily available (456 discontinued and 401 FDA approved). The OTSA process predicted a total of 7,990 interactions for these 857 molecules. Of these, 3,923 and 4,067 possible high-scoring interactions were predicted for the discontinued and approved drugs, respectively, translating to an average of 9.3 interactions per drug. The OTSA process correctly identified the known pharmacological targets for >70% of these drugs, but also predicted a significant number of off-targets that may provide additional insight into observed in vivo effects. About 51.5% (2,025) and 22% (900) of these predicted high-scoring interactions have not previously been reported for the discontinued and approved drugs, respectively, and these may have a potential for repurposing efforts. Moreover, for both drug categories, higher promiscuity was observed for compounds with a MW range of 300 to 500, TPSA of ~200, and clogP ≥7. This computation also revealed significantly lower promiscuity (i.e., number of confirmed off-targets) for compounds with MW > 700 and MW<200 for both categories. In addition, 15 internal small molecules with known off-target interactions were evaluated. For these compounds, the OTSA framework not only captured about 56.8% of in vitro confirmed off-target interactions, but also identified the right pharmacological targets for 14 compounds as one of the top scoring targets. In conclusion, the OTSA process demonstrates good predictive performance characteristics and represents an additional tool with utility during the lead optimization stage of the drug discovery process. Additionally, the computed physiochemical properties such as clogP (i.e., lipophilicity), molecular weight, pKa and logS (i.e., solubility) were found to be statistically different between the approved and discontinued drugs, but the internal compounds were close to the approved drugs space in most part.
Project description:We describe the molecular design, synthesis, and investigation of a series of acridine-triaminotriazine macrocycles that selectively bind to CTG trinucleotide repeats in DNA with minimal nonspecific binding. The limited conformational flexibility enforces the stacking of the triaminotriazine and acridine units. Isothermal titration calorimetry studies and Job plot analyses revealed that the ligands bound to d(CTG) mismatched sites. The acridine and triaminotriazine units were shown to intramolecularly π-stack in aqueous solutions. Compared to a noncyclic analog, the macrocycles showed an almost 10-fold lower cytotoxicity in HeLa cells and up to 4-fold higher transcription inhibition of d(CTG·CAG)74.