A Flexible Data Analysis Tool for Chemical Genetic Screens

High-Throughput Screening Platforms in the Discovery of Novel Drugs for Neurodegenerative Diseases

Neurodegenerative diseases (NDDs) are incurable and debilitating conditions that result in progressive degeneration and/or death of nerve cells in the central nervous system (CNS). Identification of viable therapeutic targets and new treatments for CNS disorders and in particular, for NDDs is a major challenge in the field of drug discovery. These difficulties can be attributed to the diversity of cells involved, extreme complexity of the neural circuits, the limited capacity for tissue regeneration, and our incomplete understanding of the underlying pathological processes. Drug discovery is a complex and multidisciplinary process. The screening attrition rate in current drug discovery protocols mean that only one viable drug may arise from millions of screened compounds resulting in the need to improve discovery technologies and protocols to address the multiple causes of attrition. This has identified the need to screen larger libraries where the use of efficient high-throughput screening (HTS) becomes key in the discovery process. HTS can investigate hundreds of thousands of compounds per day. However, if fewer compounds could be screened without compromising the probability of success, the cost and time would be largely reduced. To that end, recent advances in computer-aided design, in silico libraries, and molecular docking software combined with the upscaling of cell-based platforms have evolved to improve screening efficiency with higher predictability and clinical applicability. We review, here, the increasing role of HTS in contemporary drug discovery processes, in particular for NDDs, and evaluate the criteria underlying its successful application. We also discuss the requirement of HTS for novel NDD therapies and examine the major current challenges in validating new drug targets and developing new treatments for NDDs.

Drug Screening and Drug Repositioning as Promising Therapeutic Approaches for Spinal Muscular Atrophy Treatment

Spinal muscular atrophy (SMA) is the most common genetic disease affecting infants and young adults. Due to mutation/deletion of the survival motor neuron (SMN) gene, SMA is characterized by the SMN protein lack, resulting in motor neuron impairment, skeletal muscle atrophy and premature death. Even if the genetic causes of SMA are well known, many aspects of its pathogenesis remain unclear and only three drugs have been recently approved by the Food and Drug Administration (Nusinersen-Spinraza; Onasemnogene abeparvovec or AVXS-101-Zolgensma; Risdiplam-Evrysdi): although assuring remarkable results, the therapies show some important limits including high costs, still unknown long-term effects, side effects and disregarding of SMN-independent targets. Therefore, the research of new therapeutic strategies is still a hot topic in the SMA field and many efforts are spent in drug discovery. In this review, we describe two promising strategies to select effective molecules: drug screening (DS) and drug repositioning (DR). By using compounds libraries of chemical/natural compounds and/or Food and Drug Administration-approved substances, DS aims at identifying new potentially effective compounds, whereas DR at testing drugs originally designed for the treatment of other pathologies. The drastic reduction in risks, costs and time expenditure assured by these strategies make them particularly interesting, especially for those diseases for which the canonical drug discovery process would be long and expensive. Interestingly, among the identified molecules by DS/DR in the context of SMA, besides the modulators of SMN2 transcription, we highlighted a convergence of some targeted molecular cascades contributing to SMA pathology, including cell death related-pathways, mitochondria and cytoskeleton dynamics, neurotransmitter and hormone modulation.

Drug screen in patient cells suggests quinacrine to be repositioned for treatment of acute myeloid leukemia

To find drugs suitable for repositioning for use against leukemia, samples from patients with chronic lymphocytic, acute myeloid and lymphocytic leukemias as well as peripheral blood mononuclear cells (PBMC) were tested in response to 1266 compounds from the LOPAC¹²⁸⁰ library (Sigma). Twenty-five compounds were defined as hits with activity in all leukemia subgroups (<50% cell survival compared with control) at 10 μM drug concentration. Only one of these compounds, quinacrine, showed low activity in normal PBMCs and was therefore selected for further preclinical evaluation. Mining the NCI-60 and the NextBio databases demonstrated leukemia sensitivity and the ability of quinacrine to reverse myeloid leukemia gene expression. Mechanistic exploration was performed using the NextBio bioinformatic software using gene expression analysis of drug exposed acute myeloid leukemia cultures (HL-60) in the database. Analysis of gene enrichment and drug correlations revealed strong connections to ribosomal biogenesis nucleoli and translation initiation. The highest drug–drug correlation was to ellipticine, a known RNA polymerase I inhibitor. These results were validated by additional gene expression analysis performed in-house. Quinacrine induced early inhibition of protein synthesis supporting these predictions. The results suggest that quinacrine have repositioning potential for treatment of acute myeloid leukemia by targeting of ribosomal biogenesis.

Small molecule screen reveals regulation of survival motor neuron protein abundance by Ras proteins

Small molecule modulators of protein activity have proven invaluable in the study of protein function and regulation. While inhibitors of protein activity are relatively common, small molecules that can increase protein abundance are rare. Small molecule protein upregulators with targeted activities would be of value in the study of the mechanisms underlying loss-of-function diseases. We developed a high-throughput screening approach to identify small molecule upregulators of the Survival of Motor Neuron protein (SMN), whose decreased levels cause the neurodegenerative disease spinal muscular atrophy (SMA). We screened 69,189 compounds for SMN upregulators and performed mechanistic studies on the most active compound, a bromobenzophenone analogue designated cuspin-1. Mechanistic studies of cuspin-1 revealed that increasing Ras signaling upregulates SMN protein abundance via an increase in translation rate. These findings suggest that controlled modulation of the Ras signaling pathway may benefit patients with SMA.

AutoLabDB: a substantial open source database schema to support a high-throughput automated laboratory

MOTIVATION

Modern automated laboratories need substantial data management solutions to both store and make accessible the details of the experiments they perform. To be useful, a modern Laboratory Information Management System (LIMS) should be flexible and easily extensible to support evolving laboratory requirements, and should be based on the solid foundations of a robust, well-designed database. We have developed such a database schema to support an automated laboratory that performs experiments in systems biology and high-throughput screening.

RESULTS

We describe the design of the database schema (AutoLabDB), detailing the main features and describing why we believe it will be relevant to LIMS manufacturers or custom builders. This database has been developed to support two large automated Robot Scientist systems over the last 5 years, where it has been used as the basis of an LIMS that helps to manage both the laboratory and all the experiment data produced.

Novel activity of acriflavine against colorectal cancer tumor cells

A high-throughput screen of the cytotoxic activity of 2000 molecules from a commercial library in three human colon cancer cell lines and two normal cell types identified the acridine acriflavin to be a colorectal cancer (CRC) active drug. Acriflavine was active in cell spheroids, indicating good drug penetration and activity against hypoxic cells. In a validation step based on primary cultures of patient tumor cells, acriflavine was found to be more active against CRC than ovarian cancer and chronic lymphocytic leukemia. This contrasted to the activity pattern of the CRC active standard drugs 5-fluorouracil, irinotecan and oxaliplatin. Mechanistic studies indicated acriflavine to be a dual topoisomerase I and II inhibitor. In conclusion, the strategy used seems promising for identification of new diagnosis-specific cancer drugs.

Optimization and application of median filter corrections to relieve diverse spatial patterns in microtiter plate data

The standard (STD) 5 × 5 hybrid median filter (HMF) was previously described as a nonparametric local backestimator of spatially arrayed microtiter plate (MTP) data. As such, the HMF is a useful tool for mitigating global and sporadic systematic error in MTP data arrays. Presented here is the first known HMF correction of a primary screen suffering from systematic error best described as gradient vectors. Application of the STD 5 × 5 HMF to the primary screen raw data reduced background signal deviation, thereby improving the assay dynamic range and hit confirmation rate. While this HMF can correct gradient vectors, it does not properly correct periodic patterns that may present in other screening campaigns. To address this issue, 1 × 7 median and a row/column 5 × 5 hybrid median filter kernels (1 × 7 MF and RC 5 × 5 HMF) were designed ad hoc, to better fit periodic error patterns. The correction data show periodic error in simulated MTP data arrays is reduced by these alternative filter designs and that multiple corrective filters can be combined in serial operations for progressive reduction of complex error patterns in a MTP data array.

Brunn: an open source laboratory information system for microplates with a graphical plate layout design process

Background

Compound profiling and drug screening generates large amounts of data and is generally based on microplate assays. Current information systems used for handling this are mainly commercial, closed source, expensive, and heavyweight and there is a need for a flexible lightweight open system for handling plate design, and validation and preparation of data.

Results

A Bioclipse plugin consisting of a client part and a relational database was constructed. A multiple-step plate layout point-and-click interface was implemented inside Bioclipse. The system contains a data validation step, where outliers can be removed, and finally a plate report with all relevant calculated data, including dose-response curves.

Conclusions

Brunn is capable of handling the data from microplate assays. It can create dose-response curves and calculate IC₅₀ values. Using a system of this sort facilitates work in the laboratory. Being able to reuse already constructed plates and plate layouts by starting out from an earlier step in the plate layout design process saves time and cuts down on error sources.

Phenotype-based drug screening in primary ovarian carcinoma cultures identifies intracellular iron depletion as a promising strategy for cancer treatment

Primary cultures of patient tumor cells (PCPTC) have been used for prediction of diagnosis-specific activity and individual patient response to anticancer drugs, but have not been utilized as a model for identification of novel drugs in high throughput screening. In the present study, ovarian carcinoma cells from three patients were tested in response to a library of 3000 chemically diverse compounds. Eight hits were retrieved after counter screening using normal epithelial cells, and one of the two structurally related hit compounds was selected for further preclinical evaluation. This compound, designated VLX 50, demonstrated a broad spectrum of activity when tested in a panel of PCPTCs representing different forms of leukemia and solid tumors and displayed a high tumor to normal cell activity. VLX 50 induced delayed cell death with some features of classical apoptosis. Significant in vivo activity was confirmed on primary cultures of human ovarian carcinoma cells in mice using the hollow fiber model. Mechanistic exploration was performed using gene expression analysis of drug exposed tumor cells to generate a drug-specific signature. This query signature was analyzed using the Gene Set Enrichment Analysis and the Connectivity Map database. Strong connections to hypoxia inducible factor 1 and iron chelators were retrieved. The mechanistic hypothesis of intracellular iron depletion leading to hypoxia signaling was confirmed by a series of experiments. The results indicate the feasibility of using PCPTC for cancer drug screening and that intracellular iron depletion could be a potentially important strategy for cancer therapy.

Hybrid median filter background estimator for correcting distortions in microtiter plate data

Microtiter plate (MTP) assays often exhibit distortions, such as caused by edge-dependent drying and robotic fluid handling variation. Distortions vary by assay system but can have both systematic patterns (predictable from plate to plate) and random (sporadic and unpredictable) components. Random errors can be especially difficult to resolve by assay optimization alone, and postassay algorithms reported to date have smoothing effects that often blunt hits. We implemented a 5 x 5 bidirectional hybrid median filter (HMF) as a local background estimator to scale each data point to the MTP global background median and compared it with a recently described Discrete Fourier Transform (DFT) technique for correcting errors on computationally and experimentally generated MTP datasets. Experimental data were generated from a 384-well format fluorescent bioassay using cells engineered to express eGFP and DsRED. MTP arrays were produced with and without control treatments used to simulate hits in random wells. The HMF demonstrated the greatest improvements in MTP coefficients of variation and dynamic range (defined by the ratio of average hit amplitude to standard deviation, SD) for all synthetic and experimental MTPs examined. After HMF application to a MTP of eGFP signal from mouse insulinoma (MIN6) cells obtained by a plate-reader, the assay coefficient of variation (CV) decreased from 8.0% in the raw dataset to 5.1% and the hit amplitudes were reduced by only 1% while the DFT method increased the CV by 36.0% and reduced the hit amplitude by 21%. Thus, our results show that the bidirectional HMF provides superior corrections of MTP data distortions while at the same time preserving hit amplitudes and improving dynamic range. The software to perform hybrid median filter MTP corrections is available at http://bccg.burnham.org/HTS/HMF_Download_Page.aspx, password is pbushway.

ChemBank: a small-molecule screening and cheminformatics resource database

ChemBank (http://chembank.broad.harvard.edu/) is a public, web-based informatics environment developed through a collaboration between the Chemical Biology Program and Platform at the Broad Institute of Harvard and MIT. This knowledge environment includes freely available data derived from small molecules and small-molecule screens and resources for studying these data. ChemBank is unique among small-molecule databases in its dedication to the storage of raw screening data, its rigorous definition of screening experiments in terms of statistical hypothesis testing, and its metadata-based organization of screening experiments into projects involving collections of related assays. ChemBank stores an increasingly varied set of measurements derived from cells and other biological assay systems treated with small molecules. Analysis tools are available and are continuously being developed that allow the relationships between small molecules, cell measurements, and cell states to be studied. Currently, ChemBank stores information on hundreds of thousands of small molecules and hundreds of biomedically relevant assays that have been performed at the Broad Institute by collaborators from the worldwide research community. The goal of ChemBank is to provide life scientists unfettered access to biomedically relevant data and tools heretofore available primarily in the private sector.

Phenotype-based screening of mechanistically annotated compounds in combination with gene expression and pathway analysis identifies candidate drug targets in a human squamous carcinoma cell model

The squamous cell carcinoma HeLa cell line and an epithelial cell line hTERT-RPE with a nonmalignant phenotype were interrogated for HeLa cell selectivity in response to 1267 annotated compounds representing 56 pharmacological classes. Selective cytotoxic activity was observed for 14 of these compounds dominated by cyclic adenosine monophosphate (cAMP) selective phosphodiesterase (PDE) inhibitors, which tended to span a representation of the chemical descriptor space of the library. The PDE inhibitors induced delayed cell death with features compatible with classical apoptosis. The PDE inhibitors were largely inactive when tested against a cell line panel consisting of hematological and nonsquamous epithelial phenotypes. In a genome-wide DNA microarray analysis, PDE3A and PDE2A were found to be significantly increased in HeLa cells compared to the other cell lines. The pathway analysis software PathwayAssist was subsequently used to extract a list of proteins and small molecules retrieved from Medline abstracts associated with the hit compounds. The resulting list consisted of major parts of the cAMP-protein kinase A pathway linking to ERK, P38, and AKT. This molecular network may provide a basis for further exploitation of novel candidate targets for the treatment of squamous cell carcinoma.

Forward in reverse: how reverse genetics complements chemical genetics

Pharmaceutical discovery has a renewed interest in physiological screening, while chemical genomics initiatives will soon provide a large amount of cellular assay data. However, there is no single robust approach to connect active compounds with their targets, limiting their experimental and therapeutic use. Systematic matching of chemical genetic phenotypes with reverse genetic phenotypes would provide a valuable starting point for many investigations.

Identification of inhibitors of ribozyme self-cleavage in mammalian cells via high-throughput screening of chemical libraries

We have recently described an RNA-only gene regulation system for mammalian cells in which inhibition of self-cleavage of an mRNA carrying ribozyme sequences provides the basis for control of gene expression. An important proof of principle for that system was provided by demonstrating the ability of one specific small molecule inhibitor of RNA self-cleavage, toyocamycin, to control gene expression in vitro and vivo. Here, we describe the development of the high-throughput screening (HTS) assay that led to the identification of toyocamycin and other molecules capable of inhibiting RNA self-cleavage in mammalian cells. To identify small molecules that can serve as inhibitors of ribozyme self-cleavage, we established a cell-based assay in which expression of a luciferase (luc) reporter is controlled by ribozyme sequences, and screened 58,076 compounds for their ability to induce luciferase expression. Fifteen compounds able to inhibit ribozyme self-cleavage in cells were identified through this screen. The most potent of the inhibitors identified were toyocamycin and 5-fluorouridine (FUR), nucleoside analogs carrying modifications of the 7-position and 5-position of the purine or pyrimidine bases. Individually, these two compounds were able to induce gene expression of the ribozyme-controlled reporter approximately 365-fold and 110-fold, respectively. Studies of the mechanism of action of the ribozyme inhibitors indicate that the compounds must be incorporated into RNA in order to inhibit RNA self-cleavage.

Screening of an annotated compound library for drug activity in a resistant myeloma cell line

PURPOSE

Resistance to anticancer drugs is a major problem in chemotherapy. In order to identify drugs with selective cytotoxic activity in drug-resistant cancer cells, the annotated compound library LOPAC1280, containing compounds from 56 pharmacological classes, was screened in the myeloma cell line RPMI 8226 and its doxorubicin-resistant subline 8226/Dox40.

METHODS

Cell survival was measured by the Fluorometric Microculture Cytotoxicity Assay.

RESULTS

Selective cytotoxic activity in 8226/Dox40 was obtained for 33 compounds, with the most pronounced difference observed for the glucocorticoids. A microarray analysis of the cells showed a difference in mRNA-expression for the glucocorticoid receptor suggesting potential mechanisms for the difference in glucocorticoid sensitivity. In the presence of the glucocorticoid-receptor antagonist RU486, the sensitivity to the glucocorticoids was reduced and a similar effect level in RPMI 8226 and 8226/Dox40 was achieved.

CONCLUSION

In conclusion, screening of mechanistically annotated compounds on drug-resistant cancer cells can identify compounds with selective activity and provide a basis for the development of novel treatments of drug-resistant malignancies.

Using small molecules to overcome drug resistance induced by a viral oncogene

We used small molecule screening to discover compounds and mechanisms for overcoming E6 oncogene-mediated drug resistance. Using high-throughput screening in isogenic cell lines, we identified compounds that potentiate doxorubicin's lethality in E6-expressing colon cancer cells. Such compounds included quaternary ammonium salts, protein synthesis inhibitors, 11-deoxyprostaglandins, and two additional classes of compounds-analogs of 1,3-bis(4-morpholinylmethyl)-2-imidazolidinethione (a thiourea) and acylated secondary amines that we named indoxins. Indoxins upregulated topoisomerase IIalpha, the target of doxorubicin, thereby increasing doxorubicin lethality. We developed a photolabeling strategy to identify targets of indoxin and discovered a nuclear actin-related protein complex as a candidate indoxin target.

Chemical genetics and orphan genetic diseases

Many orphan diseases have been identified that individually affect small numbers of patients but cumulatively affect approximately 6%-10% of the European and United States populations. Human genetics has become increasingly effective at identifying genetic defects underlying such orphan genetic diseases, but little progress has been made toward understanding the causal molecular pathologies and creating targeted therapies. Chemical genetics, positioned at the interface of chemistry and genetics, can be used for elucidation of molecular mechanisms underlying diseases and for drug discovery. This review discusses recent advances in chemical genetics and how small-molecule tools can be used to study and ultimately treat orphan genetic diseases. We focus here on a case study involving spinal muscular atrophy, a pediatric neurodegenerative disease caused by homozygous deletion of the SMN1 (survival of motor neuron 1) gene.

Enrichment of High-Throughput Screening Data with Increasing Levels of Noise Using Support Vector Machines, Recursive Partitioning, and Laplacian-Modified Naive Bayesian Classifiers

High-throughput screening (HTS) plays a pivotal role in lead discovery for the pharmaceutical industry. In tandem, cheminformatics approaches are employed to increase the probability of the identification of novel biologically active compounds by mining the HTS data. HTS data is notoriously noisy, and therefore, the selection of the optimal data mining method is important for the success of such an analysis. Here, we describe a retrospective analysis of four HTS data sets using three mining approaches: Laplacian-modified naive Bayes, recursive partitioning, and support vector machine (SVM) classifiers with increasing stochastic noise in the form of false positives and false negatives. All three of the data mining methods at hand tolerated increasing levels of false positives even when the ratio of misclassified compounds to true active compounds was 5:1 in the training set. False negatives in the ratio of 1:1 were tolerated as well. SVM outperformed the other two methods in capturing active compounds and scaffolds in the top 1%. A Murcko scaffold analysis could explain the differences in enrichments among the four data sets. This study demonstrates that data mining methods can add a true value to the screen even when the data is contaminated with a high level of stochastic noise.

ADVANCES IN CHEMICAL GENETICS

Chemical genetics is an emerging approach for studying biological systems using chemical tools. This strategy aims to reveal the macromolecules responsible for regulating biological systems; thus, the approach shares much in common with genetics. In both strategies, one must (a) develop an assay that reports on a biological process of interest, (b) perturb this process systematically (with mutations or small molecules), and (c) determine the target of each perturbation to reveal macromolecules (i.e., proteins and genes) regulating the process of interest. In this review, we discuss advances and challenges in this field that have emerged over the past four years. Several technologies have converged, raising the hope that it may be possible to systematically apply chemical probes to biological processes.

Diverse small-molecule modulators of SMN expression found by high-throughput compound screening: early leads towards a therapeutic for spinal muscular atrophy

We have exploited the existence of a second copy of the human SMN gene (SMN2) to develop a high-throughput screening strategy to identify potential small molecule therapeutics for the genetic disease spinal muscular atrophy (SMA), which is caused by the loss of the SMN1 gene. Our screening process was designed to identify synthetic compounds that increase the total amount of full-length SMN messenger RNA and protein arising from the SMN2 gene, thereby suppressing the deleterious effects of losing SMN1. A cell-based bioassay was generated that detects SMN2 promoter activity, on which greater than 550,000 compounds was tested. This resulted in the identification of 17 distinct compounds with confirmed biological activity on the cellular primary assay, belonging to nine different structural families. Six of the nine scaffolds were chosen on the basis of their drug-like features to be tested for their ability to modulate SMN gene expression in SMA patient-derived fibroblasts. Five of the six compound classes altered SMN mRNA levels or mRNA splicing patterns in SMA patient-derived fibroblasts. Two of the compound classes, a quinazoline compound series and an indole compound, also increased SMN protein levels and nuclear gem/Cajal body numbers in patient-derived cells. In addition, these two distinct scaffolds showed additive effects when used in combination, suggesting that they may act on different molecular targets. The work described here has provided the foundation for a successful medicinal chemistry effort to further advance these compounds as potential small molecule therapeutics for SMA.

Indoprofen upregulates the survival motor neuron protein through a cyclooxygenase-independent mechanism

Most patients with the pediatric neurodegenerative disease spinal muscular atrophy have a homozygous deletion of the survival motor neuron 1 (SMN1) gene, but retain one or more copies of the closely related SMN2 gene. The SMN2 gene encodes the same protein (SMN) but produces it at a low efficiency compared with the SMN1 gene. We performed a high-throughput screen of approximately 47,000 compounds to identify those that increase production of an SMN2-luciferase reporter protein, but not an SMN1-luciferase reporter protein. Indoprofen, a nonsteroidal anti-inflammatory drug (NSAID) and cyclooxygenase (COX) inhibitor, selectively increased SMN2-luciferase reporter protein and endogenous SMN protein and caused a 5-fold increase in the number of nuclear gems in fibroblasts from SMA patients. No other NSAIDs or COX inhibitors tested exhibited this activity.

Phoslactomycin targets cysteine-269 of the protein phosphatase 2A catalytic subunit in cells

According to the chemical genetic approach, small molecules that bind directly to proteins are used to analyze protein function, thereby enabling the elucidation of complex mechanisms in mammal cells. Thus, it is very important to identify the molecular targets of compounds that induce a unique phenotype in a target cell. Phoslactomycin A (PLMA) is known to be a potent inhibitor of protein Ser/Thr phosphatase 2A (PP2A); however, the inhibitory mechanism of PP2A by PLMA has not yet been elucidated. Here, we demonstrated that PLMA directly binds to the PP2A catalytic subunit (PP2Ac) in cells by using biotinylated PLMA, and the PLMA-binding site was identified as the Cys-269 residue of PP2Ac. Moreover, we revealed that the Cys-269 contributes to the potent inhibition of PP2Ac activity by PLMA. These results suggest that PLMA is a PP2A-selective inhibitor and is therefore expected to be useful for future investigation of PP2A function in cells.