The CoQ oxidoreductase FSP1 acts parallel to GPX4 to inhibit ferroptosis.

Ferroptosis is a form of regulated cell death that is caused by the iron-dependent peroxidation of lipids1,2. The glutathione-dependent lipid hydroperoxidase glutathione peroxidase 4 (GPX4) prevents ferroptosis by converting lipid hydroperoxides into non-toxic lipid alcohols3,4. Ferroptosis has previously been implicated in the cell death that underlies several degenerative conditions2, and induction of ferroptosis by the inhibition of GPX4 has emerged as a therapeutic strategy to trigger cancer cell death5. However, sensitivity to GPX4 inhibitors varies greatly across cancer cell lines6, which suggests that additional factors govern resistance to ferroptosis. Here, using a synthetic lethal CRISPR-Cas9 screen, we identify ferroptosis suppressor protein 1 (FSP1) (previously known as apoptosis-inducing factor mitochondrial 2 (AIFM2)) as a potent ferroptosis-resistance factor. Our data indicate that myristoylation recruits FSP1 to the plasma membrane where it functions as an oxidoreductase that reduces coenzyme Q10 (CoQ) (also known as ubiquinone-10), which acts as a lipophilic radical-trapping antioxidant that halts the propagation of lipid peroxides. We further find that FSP1 expression positively correlates with ferroptosis resistance across hundreds of cancer cell lines, and that FSP1 mediates resistance to ferroptosis in lung cancer cells in culture and in mouse tumour xenografts. Thus, our data identify FSP1 as a key component of a non-mitochondrial CoQ antioxidant system that acts in parallel to the canonical glutathione-based GPX4 pathway. These findings define a ferroptosis suppression pathway and indicate that pharmacological inhibition of FSP1 may provide an effective strategy to sensitize cancer cells to ferroptosis-inducing chemotherapeutic agents

Representation of target-bound drugs by computed conformers: implications for conformational libraries

BACKGROUND: The increasing number of known protein structures provides valuable information about pharmaceutical targets. Drug binding sites are identifiable and suitable lead compounds can be proposed. The flexibility of ligands is a critical point for the selection of potential drugs. Since computed 3D structures of millions of compounds are available, the knowledge of their binding conformations would be a great benefit for the development of efficient screening methods. RESULTS: Integration of two public databases allowed superposition of conformers for 193 approved drugs with 5507 crystallised target-bound counterparts. The generation of 9600 drug conformers using an atomic force field was carried out to obtain an optimal coverage of the conformational space. Bioactive conformations are best described by a conformational ensemble: half of all drugs exhibit multiple active states, distributed over the entire range of the reachable energy and conformational space. A number of up to 100 conformers per drug enabled us to reproduce the bound states within a similarity threshold of 1.0 Å in 70% of all cases. This fraction rises to about 90% for smaller or average sized drugs. CONCLUSION: Single drugs adopt multiple bioactive conformations if they interact with different target proteins. Due to the structural diversity of binding sites they adopt conformations that are distributed over a broad conformational space and wide energy range. Since the majority of drugs is well represented by a predefined low number of conformers (up to 100) this procedure is a valuable method to compare compounds by three-dimensional features or for fast similarity searches starting with pharmacophores. The underlying 9600 generated drug conformers are downloadable from the Super Drug Web site [1]. All superpositions are visualised at the same source. Additional conformers (110,000) of 2400 classified WHO-drugs are also available

Darwin Core: An Evolving Community-Developed Biodiversity Data Standard

Biodiversity data derive from myriad sources stored in various formats on many distinct hardware and software platforms. An essential step towards understanding global patterns of biodiversity is to provide a standardized view of these heterogeneous data sources to improve interoperability. Fundamental to this advance are definitions of common terms. This paper describes the evolution and development of Darwin Core, a data standard for publishing and integrating biodiversity information. We focus on the categories of terms that define the standard, differences between simple and relational Darwin Core, how the standard has been implemented, and the community processes that are essential for maintenance and growth of the standard. We present case-study extensions of the Darwin Core into new research communities, including metagenomics and genetic resources. We close by showing how Darwin Core records are integrated to create new knowledge products documenting species distributions and changes due to environmental perturbations

AV-65, a novel Wnt/β-catenin signal inhibitor, successfully suppresses progression of multiple myeloma in a mouse model

Multiple myeloma (MM) is a malignant neoplasm of plasma cells. Although new molecular targeting agents against MM have been developed based on the better understanding of the underlying pathogenesis, MM still remains an incurable disease. We previously demonstrated that β-catenin, a downstream effector in the Wnt pathway, is a potential target in MM using RNA interference in an in vivo experimental mouse model. In this study, we have screened a library of more than 100 000 small-molecule chemical compounds for novel Wnt/β-catenin signaling inhibitors using a high-throughput transcriptional screening technology. We identified AV-65, which diminished β-catenin protein levels and T-cell factor transcriptional activity. AV-65 then decreased c-myc, cyclin D1 and survivin expression, resulting in the inhibition of MM cell proliferation through the apoptotic pathway. AV-65 treatment prolonged the survival of MM-bearing mice. These findings indicate that this compound represents a novel and attractive therapeutic agent against MM. This study also illustrates the potential of high-throughput transcriptional screening to identify candidates for anticancer drug discovery

Finding the needle in the haystack: why high-throughput screening is good for your health

High-throughput screening is an essential component of the toolbox of modern technologies that improve speed and efficiency in contemporary cancer drug development. This is particularly important as we seek to exploit, for maximum therapeutic benefit, the large number of new molecular targets emerging from the Human Genome Project and cancer genomics. Screening of diverse collections of low molecular weight compounds plays a key role in providing chemical starting points for iterative optimisation by medicinal chemistry. Examples of successful drug discovery programmes based on high-throughput screening are described, and these offer potential in the treatment of breast cancer and other malignancies

Designing Focused Chemical Libraries Enriched in Protein-Protein Interaction Inhibitors using Machine-Learning Methods

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is freely available on request from our CDithem platform website, www.CDithem.com

Small-molecule-induced DNA damage identifies alternative DNA structures in human genes.

Guanine-rich DNA sequences that can adopt non-Watson-Crick structures in vitro are prevalent in the human genome. Whether such structures normally exist in mammalian cells has, however, been the subject of active research for decades. Here we show that the G-quadruplex-interacting drug pyridostatin promotes growth arrest in human cancer cells by inducing replication- and transcription-dependent DNA damage. A chromatin immunoprecipitation sequencing analysis of the DNA damage marker γH2AX provided the genome-wide distribution of pyridostatin-induced sites of damage and revealed that pyridostatin targets gene bodies containing clusters of sequences with a propensity for G-quadruplex formation. As a result, pyridostatin modulated the expression of these genes, including the proto-oncogene SRC. We observed that pyridostatin reduced SRC protein abundance and SRC-dependent cellular motility in human breast cancer cells, validating SRC as a target of this drug. Our unbiased approach to define genomic sites of action for a drug establishes a framework for discovering functional DNA-drug interactions

Automated High-Content Live Animal Drug Screening Using C. elegans Expressing the Aggregation Prone Serpin α1-antitrypsin Z

The development of preclinical models amenable to live animal bioactive compound screening is an attractive approach to discovering effective pharmacological therapies for disorders caused by misfolded and aggregation-prone proteins. In general, however, live animal drug screening is labor and resource intensive, and has been hampered by the lack of robust assay designs and high throughput work-flows. Based on their small size, tissue transparency and ease of cultivation, the use of C. elegans should obviate many of the technical impediments associated with live animal drug screening. Moreover, their genetic tractability and accomplished record for providing insights into the molecular and cellular basis of human disease, should make C. elegans an ideal model system for in vivo drug discovery campaigns. The goal of this study was to determine whether C. elegans could be adapted to high-throughput and high-content drug screening strategies analogous to those developed for cell-based systems. Using transgenic animals expressing fluorescently-tagged proteins, we first developed a high-quality, high-throughput work-flow utilizing an automated fluorescence microscopy platform with integrated image acquisition and data analysis modules to qualitatively assess different biological processes including, growth, tissue development, cell viability and autophagy. We next adapted this technology to conduct a small molecule screen and identified compounds that altered the intracellular accumulation of the human aggregation prone mutant that causes liver disease in α1-antitrypsin deficiency. This study provides powerful validation for advancement in preclinical drug discovery campaigns by screening live C. elegans modeling α1-antitrypsin deficiency and other complex disease phenotypes on high-content imaging platforms

Methodological approaches in application of synthetic lethality screening towards anticancer therapy

A promising direction in the development of selective less toxic cancer drugs is the usage of synthetic lethality concept. The availability of large-scale synthetic low-molecular-weight chemical libraries has allowed HTS for compounds synergistic lethal with defined human cancer aberrations in activated oncogenes or tumour suppressor genes. The search for synthetic lethal chemicals in human/mouse tumour cells is greatly aided by a prior knowledge of relevant signalling and DNA repair pathways, allowing for educated guesses on the preferred potential therapeutic targets. The recent generation of human/rodents genome-wide siRNAs, and shRNA-expressing libraries, should further advance this more focused approach to cancer drug discovery

Interaction of Rio1 Kinase with Toyocamycin Reveals a Conformational Switch That Controls Oligomeric State and Catalytic Activity

Rio1 kinase is an essential ribosome-processing factor required for proper maturation of 40 S ribosomal subunit. Although its structure is known, several questions regarding its functional remain to be addressed. We report that both Archaeoglobus fulgidus and human Rio1 bind more tightly to an adenosine analog, toyocamycin, than to ATP. Toyocamycin has antibiotic, antiviral and cytotoxic properties, and is known to inhibit ribosome biogenesis, specifically the maturation of 40 S. We determined the X-ray crystal structure of toyocamycin bound to Rio1 at 2.0 Å and demonstrated that toyocamycin binds in the ATP binding pocket of the protein. Despite this, measured steady state kinetics were inconsistent with strict competitive inhibition by toyocamycin. In analyzing this interaction, we discovered that Rio1 is capable of accessing multiple distinct oligomeric states and that toyocamycin may inhibit Rio1 by stabilizing a less catalytically active oligomer. We also present evidence of substrate inhibition by high concentrations of ATP for both archaeal and human Rio1. Oligomeric state studies show both proteins access a higher order oligomeric state in the presence of ATP. The study revealed that autophosphorylation by Rio1 reduces oligomer formation and promotes monomerization, resulting in the most active species. Taken together, these results suggest the activity of Rio1 may be modulated by regulating its oligomerization properties in a conserved mechanism, identifies the first ribosome processing target of toyocamycin and presents the first small molecule inhibitor of Rio1 kinase activity