Abstract: Understanding the phenotypic drug response on cancer cell lines plays a vital role in anti-cancer drug discovery and re-purposing. The Genomics of Drug Sensitivity in Cancer (GDSC) database provides open data for researchers in phenotypic screening to build and test their models. Previously, most research in these areas starts from the molecular fingerprints or physiochemical features of drugs, instead of their structures. In this paper, a model called twin Convolutional Neural Network for drugs in SMILES format (tCNNS) is introduced for phenotypic screening. tCNNS uses a convolutional network to extract features for drugs from their simplified molecular input line entry specification (SMILES) format and uses another convolutional network to extract features for cancer cell lines from the genetic feature vectors respectively. After that, a fully connected network is used to predict the interaction between the drugs and the cancer cell lines. When the training set and the testing set are divided based on the interaction pairs between drugs and cell lines, tCNNS achieves 0.826, 0.831 for the mean and top quartile of the coefficient of determinant (R2) respectively and 0.909, 0.912 for the mean and top quartile of the Pearson correlation (Rp) respectively, which are significantly better than those of the previous works (Ammad-Ud-Din et al., J Chem Inf Model 54:2347–9, 2014), (Haider et al., PLoS ONE 10:0144490, 2015), (Menden et al., PLoS ONE 8:61318, 2013). However, when the training set and the testing set are divided exclusively based on drugs or cell lines, the performance of tCNNS decreases significantly and Rp and R2 drop to barely above 0. Our approach is able to predict the drug effects on cancer cell lines with high accuracy, and its performance remains stable with less but high-quality data, and with fewer features for the cancer cell lines. tCNNS can also solve the problem of outliers in other feature space. Besides achieving high scores in these statistical metrics, tCNNS also provides some insights into the phenotypic screening. However, the performance of tCNNS drops in the blind test.

Abstract: Compounds targeting the circadian clock have been identified as potential treatments for clock-related diseases, including cancer. Our cell-based phenotypic screen revealed uncharacterized clock-modulating compounds. Through affinity-based target deconvolution, we identified GO289, which strongly lengthened circadian period, as a potent and selective inhibitor of CK2. Phosphoproteomics identified multiple phosphorylation sites inhibited by GO289 on clock proteins, including PER2 S693. Furthermore, GO289 exhibited cell type–dependent inhibition of cancer cell growth that correlated with cellular clock function. The x-ray crystal structure of the CK2α-GO289 complex revealed critical interactions between GO289 and CK2-specific residues and no direct interaction of GO289 with the hinge region that is highly conserved among kinases. The discovery of GO289 provides a direct link between the circadian clock and cancer regulation and reveals unique design principles underlying kinase selectivity.

Abstract: A major advance in antimalarial drug discovery has been the shift towards cell-based phenotypic screening, with notable progress in the screening of compounds against the asexual blood stage, liver stage, and gametocytes. A primary method for drug target deconvolution in Plasmodium falciparum is in vitro evolution of compound-resistant parasites followed by whole-genome scans. Several of the most promising antimalarial drug targets, such as translation elongation factor 2 (eEF2) and phenylalanine tRNA synthetase (PheRS), have been identified or confirmed using this method. One drawback of this method is that if a mutated gene is uncharacterized, a substantial effort may be required to determine whether it is a drug target, a drug resistance gene, or if the mutation is merely a background mutation. Thus, the availability of high-throughput, functional genomic datasets can greatly assist with target deconvolution. Studies mapping genome-wide essentiality in P. falciparum or performing transcriptional profiling of the host and parasite during liver-stage infection with P. berghei have identified potentially druggable pathways. Advances in mapping the epigenomic regulation of the malaria parasite genome have also enabled the identification of key processes involved in parasite development. In addition, the examination of the host genome during infection has identified novel gene candidates associated with susceptibility to severe malaria. Here, we review recent studies that have used omics-based methods to identify novel targets for interventions against protozoan parasites, focusing on malaria, and we highlight the advantages and limitations of the approaches used. These approaches have also been extended to other protozoan pathogens, including Toxoplasma, Trypanosoma, and Leishmania spp., and these studies highlight how drug discovery efforts against these pathogens benefit from the utilization of diverse omics-based methods to identify promising drug targets.

Abstract: Genome-scale functional genetic screens are used to identify key genetic regulators of a phenotype of interest. However, the identification of genetic modifications that lead to a phenotypic change requires sorting large numbers of cells, which increases operational times and costs and limits cell viability. Here, we introduce immunomagnetic cell sorting facilitated by a microfluidic chip as a rapid and scalable high-throughput method for loss-of-function phenotypic screening using CRISPR–Cas9. We used the method to process an entire genome-wide screen containing more than 108 cells in less than 1 h—considerably surpassing the throughput achieved by fluorescence-activated cell sorting, the gold-standard technique for phenotypic cell sorting—while maintaining high levels of cell viability. We identified modulators of the display of CD47, which is a negative regulator of phagocytosis and an important cell-surface target for immuno-oncology drugs. The top hit of the screen, the glutaminyl cyclase QPCTL, was validated and shown to modify the N-terminal glutamine of CD47. The method presented could bridge the gap between fluorescence-activated cell sorting and less flexible yet higher-throughput systems such as magnetic-activated cell sorting. Immunomagnetic cell sorting implemented in a microfluidic chip can perform loss-of-function CRISPR–Cas9-mediated phenotypic screening at higher throughput than fluorescence-activated cell sorting.

Abstract: Alzheimer's disease (AD) is the most frequent age-associated dementia with no treatments that can prevent or slow its progression. Since age is by far the major risk factor for AD, there is a strong rationale for an alternative approach to drug discovery based upon the biology of aging. Phenotypic screening assays that reflect multiple, age-associated neurotoxicity pathways rather than single molecular targets can identify compounds that have therapeutic efficacy by targeting aspects of aging that contribute to AD pathology. And, while the suitability of any single assay can be questioned, a combination of assays can make reliable predictions about the neuroprotective effects of compounds in vivo. Therefore, our lab has developed a combination of phenotypic screening assays that are ideally suited not only to identify novel neuroprotective compounds for the treatment of AD but also their target pathways, thereby potentially providing new therapeutic targets for disease treatment. Using these assays, we screened a large library of extracts from plants with identified pharmacological uses. Analysis of one of these extracts from the plant Yerba santa (Eriodictyon californicum) identified the flavanone sterubin as the active component and further studies showed it to be a potent neuroprotective and anti-inflammatory compound.

Abstract: Introduction: Chagas disease affects 8-10 million people worldwide, mainly in Latin America. The current therapy for Chagas disease is limited to nifurtimox and benznidazole, which are effective in treating only the acute phase of the disease but with severe side effects. Therefore, there is an unmet need for new drugs and for the exploration of innovative approaches which may lead to the discovery of new effective and safe drugs for its treatment. Areas covered: The authors report and discuss recent approaches including structure-based design that have led to the discovery of new promising small molecule candidates for Chagas disease which affect prime targets that intervene in the sterol pathway of T. cruzi. Other trypanosome targets, phenotypic screening, the use of artificial intelligence and the challenges with Chagas disease drug discovery are also discussed. Expert opinion: The application of recent scientific innovations to the field of Chagas disease have led to the discovery of new promising drug candidates for Chagas disease. Phenotypic screening brought new hits and opportunities for drug discovery. Artificial intelligence also has the potential to accelerate drug discovery in Chagas disease and further research into this is warranted.

Abstract: The rise of multi- and extensively drug-resistant Mycobacterium tuberculosis (M. tb) strains and co-infection with human immunodeficiency virus has escalated the need for new anti-M. tb drugs. Numerous challenges associated with the M. tb, in particular slow growth and pathogenicity level 3, discouraged use of this organism in past primary screening efforts. From current knowledge of the physiology and drug susceptibility of mycobacteria in general and M. tb specifically, it can be assumed that many potentially useful drug leads were missed by failing to screen directly against this pathogen. This review discusses recent high-throughput phenotypic screening strategies for anti-M. tb drug discovery. Emphasis is placed on prioritization of hits, including their extensive biological and chemical profiling, as well as the development status of promising drug candidates discovered with phenotypic screening.

Abstract: Viral infections are increasing and probably long-lasting global risks. In this study, a chemical library was exploited by phenotypic screening to discover new antiviral inhibitors. After optimizations from hit to lead, a novel potent small molecule (RYL-634) was identified, showing excellent broad-spectrum inhibition activity against various pathogenic viruses, including hepatitis C virus, dengue virus, Zika virus, chikungunya virus, enterovirus 71, human immunodeficiency virus, respiratory syncytial virus, and others. The mechanism of action and potential targets of RYL-634 were further explored by the combination of activity-based protein profiling and other techniques. Finally, human dihydroorotate dehydrogenase was validated as the major target of RYL-634. We did not observe any mutant resistance under our pressure selections with RYL-634, and it had a strong synergistic effect with some Food and Drug Administration-approved drugs. Hence, there is great potential for developing new broad-spectrum antivirals based on RYL-634.

Abstract: The identification of activating mutations in NOTCH1 in 50% of T cell acute lymphoblastic leukemia has generated interest in elucidating how these mutations contribute to oncogenic transformation and in targeting the pathway. A phenotypic screen identified compounds that interfere with trafficking of Notch and induce apoptosis via an endoplasmic reticulum (ER) stress mechanism. Target identification approaches revealed a role for SLC39A7 (ZIP7), a zinc transport family member, in governing Notch trafficking and signaling. Generation and sequencing of a compound-resistant cell line identified a V430E mutation in ZIP7 that confers transferable resistance to the compound NVS-ZP7-4. NVS-ZP7-4 altered zinc in the ER, and an analog of the compound photoaffinity labeled ZIP7 in cells, suggesting a direct interaction between the compound and ZIP7. NVS-ZP7-4 is the first reported chemical tool to probe the impact of modulating ER zinc levels and investigate ZIP7 as a novel druggable node in the Notch pathway.

Abstract: Cryptosporidiosis is a leading cause of life-threatening diarrhea in children, and the only currently approved drug is ineffective in malnourished children and immunocompromised people. Large-scale phenotypic screens are ongoing to identify anticryptosporidial compounds, but optimal approaches to prioritize inhibitors and establish a mechanistically diverse drug development pipeline are unknown. Here, we present a panel of medium-throughput mode of action assays that enable testing of compounds in several stages of the Cryptosporidium life cycle. Phenotypic profiles are given for thirty-nine anticryptosporidials. Using a clustering algorithm, the compounds sort by phenotypic profile into distinct groups of inhibitors that are either chemical analogs (i.e. same molecular mechanism of action (MMOA)) or known to have similar MMOA. Furthermore, compounds belonging to multiple phenotypic clusters are efficacious in a chronic mouse model of cryptosporidiosis. This suite of phenotypic assays should ensure a drug development pipeline with diverse MMOA without the need to identify underlying mechanisms. Here, the authors provide a panel of medium-throughput assays to test potential drug candidates against different life cycle stages of Cryptosporidium with the goal to support a drug development pipeline that contains compounds with diverse molecular mechanisms of action.

Abstract: Phage display technology is a common approach for discovery of therapeutic antibodies. Drug candidates are typically isolated in two steps: First, a pool of antibodies is enriched through consecutive rounds of selection on a target antigen, and then individual clones are characterized in a screening procedure. When whole cells are used as targets, as in phenotypic discovery, the output phage pool typically contains thousands of antibodies, binding, in theory, hundreds of different cell surface receptors. Clonal expansion throughout the phage display enrichment process is affected by multiple factors resulting in extremely complex output phage pools where a few antibodies are highly abundant and the majority is very rare. This is a huge challenge in the screening where only a fraction of the antibodies can be tested using a conventional binding analysis, identifying mainly the most abundant clones typically binding only one or a few targets. As the expected number of antibodies and specificities in the pool is much higher, complementing methods, to reach deeper into the pool, are required, called deep mining methods. In this study, four deep mining methods were evaluated: 1) isolation of rare sub-pools of specific antibodies through selection on recombinant proteins predicted to be expressed on the target cells, 2) isolation of a sub-pool enriched for antibodies of unknown specificities through depletion of the primary phage pool on recombinant proteins corresponding to receptors known to generate many binders, 3) isolation of a sub-pool enriched for antibodies through selection on cells blocked with antibodies dominating the primary phage pool, and 4) next-generation sequencing-based analysis of isolated antibody pools followed by antibody gene synthesis and production of rare but enriched clones. We demonstrate that antibodies binding new targets and epitopes, not discovered through screening alone, can be discovered using described deep mining methods. Overall, we demonstrate the complexity of phage pools generated through selection on cells and show that a combination of conventional screening and deep mining methods are needed to fully utilize such pools. Deep mining will be important in future phenotypic antibody drug discovery efforts to increase the diversity of identified antibodies and targets.

Abstract: Neurons created from human induced pluripotent stem cells (hiPSCs) provide the capability of identifying biological mechanisms that underlie brain disorders. IPSC-derived human neurons, or iNs, hold promise for advancing precision medicine through drug screening, though it remains unclear to what extent iNs can support early-stage drug discovery efforts in industrial-scale screening centers. Despite several reported approaches to generate iNs from iPSCs, each suffer from technological limitations that challenge their scalability and reproducibility, both requirements for successful screening assays. We addressed these challenges by initially removing the roadblocks related to scaling of iNs for high throughput screening (HTS)-ready assays. We accomplished this by simplifying the production and plating of iNs and adapting them to a freezer-ready format. We then tested the performance of freezer-ready iNs in an HTS-amenable phenotypic assay that measured neurite outgrowth. This assay successfully identified small molecule inhibitors of neurite outgrowth. Importantly, we provide evidence that this scalable iN-based assay was both robust and highly reproducible across different laboratories. These streamlined approaches are compatible with any iPSC line that can produce iNs. Thus, our findings indicate that current methods for producing iPSCs are appropriate for large-scale drug-discovery campaigns (i.e. >10e5 compounds) that read out simple neuronal phenotypes. However, due to the inherent limitations of currently available iN differentiation protocols, technological advances are required to achieve similar scalability for screens that require more complex phenotypes related to neuronal function.

Abstract: Influenza A virus infections cause significant morbidity and mortality, and novel antivirals are urgently needed. Influenza RNA-dependent RNA polymerase (RdRp) activity has been acknowledged as a promising target for novel antivirals. In this study, a phenotypic versus target-based screening strategy was established to identify the influenza A virus inhibitors targeting the virus RNA transcription/replication steps by sequentially using an RdRp-targeted screen and a replication-competent reporter virus-based approach using the same compounds. To demonstrate the utility of this approach, a pilot screen of a library of 891 compounds derived from natural products was carried out. Quality control analysis indicates that the primary screen was robust for identification of influenza A virus inhibitors targeting RdRp activity. Finally, two hit candidates were identified, and one was validated as a putative RdRp inhibitor. This strategy can greatly reduce the number of false positives and improve the accuracy and efficacy of primary screening, thereby providing a powerful tool for antiviral discovery.

Abstract: By screening a focused library of kinase inhibitor analogues in a phenotypic co-culture assay for angiogenesis inhibition, we identified an aminotriazine that acts as a cytostatic nanomolar inhibitor. However, this aminotriazine was found to be completely inactive in a whole-kinome profiling assay. To decipher its mechanism of action, we used the online target prediction tool PPB2 (http://ppb2.gdb.tools), which suggested lysophosphatidic acid acyltransferase β (LPAAT-β) as a possible target for this aminotriazine as well as several analogues identified by structure-activity relationship profiling. LPAAT-β inhibition (IC50 ≈15 nm) was confirmed in a biochemical assay and by its effects on cell proliferation in comparison with a known LPAAT-β inhibitor. These experiments illustrate the value of target-prediction tools to guide target identification for phenotypic screening hits and significantly expand the rather limited pharmacology of LPAAT-β inhibitors.

Abstract: Genome-wide phenotypic screens provide an unbiased way to identify genes involved in particular biological traits, and have been widely used in lower model organisms. However, cost and time have limited the utility of such screens to address biological and disease questions in mammals. Here we report a highly efficient piggyBac (PB) transposon-based first-generation (F1) dominant screening system in mice that enables an individual investigator to conduct a genome-wide phenotypic screen within a year with fewer than 300 cages. The PB screening system uses visually trackable transposons to induce both gain- and loss-of-function mutations and generates genome-wide distributed new insertions in more than 55% of F1 progeny. Using this system, we successfully conducted a pilot F1 screen and identified 5 growth retardation mutations. One of these mutants, a Six1/4 PB/+ mutant, revealed a role in milk intake behavior. The mutant animals exhibit abnormalities in nipple recognition and milk ingestion, as well as developmental defects in cranial nerves V, IX, and X. This PB F1 screening system offers individual laboratories unprecedented opportunities to conduct affordable genome-wide phenotypic screens for deciphering the genetic basis of mammalian biology and disease pathogenesis.

Abstract: With the advent of automatic cell imaging and machine learning, high-content phenotypic screening has become the approach of choice for drug discovery because it can extract drug-specific multi-layered data, which could be compared to known profiles. In the field of epigenetics, such screening approaches have suffered from a lack of tools sensitive to selective epigenetic perturbations. Here we describe a novel approach, Microscopic Imaging of Epigenetic Landscapes (MIEL), which captures the nuclear staining patterns of epigenetic marks (e.g., acetylated and methylated histones) and employs machine learning to accurately distinguish between such patterns. We validated the fidelity and robustness of the MIEL platform across multiple cells lines using dose-response curves. We employed MIEL to uncover the mechanism by which bromodomain inhibitors synergize with temozolomide-mediated killing of human glioblastoma lines. To explore alternative, non-cytotoxic, glioblastoma treatment, we screen the Prestwick chemical library and documented the power of MIEL platform to identify epigenetically active drugs and accurately rank them according to their ability to produce epigenetic and transcriptional alterations consistent with the induction of glioblastoma differentiation.

Abstract: In analogy to biosynthetic pathways leading to bioactive natural products, synthetic fermentation generates mixtures of molecules from simple building blocks under aqueous, biocompatible conditions, allowing the resulting cultures to be directly screened for biological activity. In this work, a novel β-peptide antibiotic was successfully identified using the synthetic fermentation platform. Phenotypic screening was carried out in an initially random fashion, allowing simple identification of active cultures. Subsequent deconvolution, focused screening, and structure–activity relationship studies led to the identification of a potent antimicrobial peptide, showing strong selectivity for our model system Bacillus subtilis over human HEK293 cells. To determine the antibacterial mechanism of action, a peptide probe bearing a photoaffinity tag was readily synthesized through the use of appropriate synthetic fermentation building blocks and utilized for target identification using a quantitative mass spectromet...

Abstract: Regulatory T (Treg) cells, expressing the transcription factor forkhead box p3 (FOXP3), are the key cells regulating peripheral autoreactive T lymphocytes by suppressing effector T cells. FOXP3+ Tr...

Abstract: As the field of tissue engineering develops, methods for screening combinations of signals for their effects on stem cell behavior are needed. We introduce a microgel-based screening platform for testing combinations of in situ-generated proteins on stem cell fate in ultrahigh-throughput. Compartmentalizing individual sets of growth factors was addressed by encapsulating aggregates of stable recombinant cell lines secreting individual glycoproteins into microgels through an on-chip polymerization. When these 'microniches' are cultured with a cell type of interest, fluorescence reporters indicate positive niches that perform the desired function, and the underlying producer cell lines of these selected microniches are analyzed by barcoded RNA sequencing. The microniche-based screening work-flow was validated via a model system based on engineered mammalian cells expressing yellow fluorescent protein (YFP) upon anti-inflammatory cytokine interleukin 4 (IL4)-based activation.

Abstract: Leishmaniasis is a Neglected Tropical Disease caused by the insect-vector borne protozoan parasite, Leishmania species. Infection affects millions of the World's poorest, however vaccines are absent and drug therapy limited. Recently, public-private partnerships have developed to identify new modes of controlling leishmaniasis. Most of these collaborative efforts have relied upon the small molecule synthetic compound libraries held by industry, but the number of New Chemical Entities (NCE) identified and entering development as antileishmanials has been very low. In light of this, here we describe a public-private effort to identify natural products with activity against Leishmania mexicana, a causative agent of cutaneous leishmanaisis (CL). Utilising Hypha Discovery's fungal extract library which is rich in small molecule (<500 molecular weight) secondary metabolites, we undertook an iterative phenotypic screening and fractionation approach to identify potent and selective antileishmanial hits. This led to the identification of a novel oxidised bisabolane sesquiterpene which demonstrated activity in an infected cell model and was shown to disrupt multiple processes using a metabolomic approach. In addition, and importantly, this study also sets a precedent for new approaches for CL drug discovery.

Abstract: Despite the noteworthy advances in the use of chemotherapy for malaria, it continues to constantly affect large number of individuals. New molecules capable of blocking life-cycle of the parasite, preferably through targeting novel pathways and various modes of action, are increasingly becoming area of interest. Phenotypic screening of large chemical libraries is certainly one of the important criteria for the discovery of new and effective drugs. In recent years, diverse research groups including pharmaceutical industries have performed this large-scale phenotypic screening to identify the potential drug molecules. Most of the antimalarial drugs target blood-stage malarial infection and remain either less potent or ineffective against other life stages i.e. liver-stage, and the gametocyte stages of the parasite. Although, liver stage is considered as a crucial drug target, limited clinical options have significantly hampered the discovery of effective treatments. This short review presents the collection of selective molecules targeting specifically liver stage malaria parasites.

Abstract: Diamond-Blackfan anemia (DBA) is a bone marrow failure syndrome caused by mutations in ribosomal protein genes. Pathogenic mechanisms are poorly understood but involve severely reduced proliferation of erythroid precursors. Because current DBA therapies are ineffective and associated with severe side effects, disease-specific therapies are urgently needed. We hypothesized that druggable molecular pathways underlying the defect can be revealed through phenotypic small-molecule screens. Accordingly, a screening assay was developed using c-kit+ fetal liver erythroid progenitors from a doxycycline-inducible DBA mouse model. The addition of doxycycline to the culture medium induces the phenotype and reduces proliferation to <10% of normal, such that rescue of proliferation can be used as a simple readout for screening. Here, we describe the assay rationale and efforts toward validation of a microtiter plate-compatible assay and its application in a pilot screen of 3871 annotated compounds. Ten hits demonstrated concentration-dependent activity, and we report a brief follow-up of one of these compounds. In conclusion, we established a robust scalable assay for screening molecules that rescue erythropoiesis in DBA.