Screening Of Compounds Research Articles

The application of natural language processing for the extraction of mechanistic information in toxicology

To study the ways in which compounds can induce adverse effects, toxicologists have been constructing Adverse Outcome Pathways (AOPs). An AOP can be considered as a pragmatic tool to capture and visualize mechanisms underlying different types of toxicity inflicted by any kind of stressor, and describes the interactions between key entities that lead to the adverse outcome on multiple biological levels of organization. The construction or optimization of an AOP is a labor intensive process, which currently depends on the manual search, collection, reviewing and synthesis of available scientific literature. This process could however be largely facilitated using Natural Language Processing (NLP) to extract information contained in scientific literature in a systematic, objective, and rapid manner that would lead to greater accuracy and reproducibility. This would support researchers to invest their expertise in the substantive assessment of the AOPs by replacing the time spent on evidence gathering by a critical review of the data extracted by NLP. As case examples, we selected two frequent adversities observed in the liver: namely, cholestasis and steatosis denoting accumulation of bile and lipid, respectively. We used deep learning language models to recognize entities of interest in text and establish causal relationships between them. We demonstrate how an NLP pipeline combining Named Entity Recognition and a simple rules-based relationship extraction model helps screen compounds related to liver adversities in the literature, but also extract mechanistic information for how such adversities develop, from the molecular to the organismal level. Finally, we provide some perspectives opened by the recent progress in Large Language Models and how these could be used in the future. We propose this work brings two main contributions: 1) a proof-of-concept that NLP can support the extraction of information from text for modern toxicology and 2) a template open-source model for recognition of toxicological entities and extraction of their relationships. All resources are openly accessible via GitHub (https://github.com/ontox-project/en-tox).

A genetically encoded biosensor to monitor dynamic changes of c-di-GMP with high temporal resolution

Monitoring changes of signaling molecules and metabolites with high temporal resolution is key to understanding dynamic biological systems. Here, we use directed evolution to develop a genetically encoded ratiometric biosensor for c-di-GMP, a ubiquitous bacterial second messenger regulating important biological processes like motility, surface attachment, virulence and persistence. The resulting biosensor, cdGreen2, faithfully tracks c-di-GMP in single cells and with high temporal resolution over extended imaging times, making it possible to resolve regulatory networks driving bimodal developmental programs in different bacterial model organisms. We further adopt cdGreen2 as a simple tool for in vitro studies, facilitating high-throughput screens for compounds interfering with c-di-GMP signaling and biofilm formation. The sensitivity and versatility of cdGreen2 could help reveal c-di-GMP dynamics in a broad range of microorganisms with high temporal resolution. Its design principles could also serve as a blueprint for the development of similar, orthogonal biosensors for other signaling molecules, metabolites and antibiotics.

Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification

As links between genotype and phenotype, small-molecule metabolites are attractive biomarkers for disease diagnosis, prognosis, classification, drug screening and treatment, insight into understanding disease pathology and identifying potential targets. Metabolomics technology is crucial for discovering targets of small-molecule metabolites involved in disease phenotype. Mass spectrometry-based metabolomics has implemented in applications in various fields including target discovery, explanation of disease mechanisms and compound screening. It is used to analyze the physiological or pathological states of the organism by investigating the changes in endogenous small-molecule metabolites and associated metabolism from complex metabolic pathways in biological samples. The present review provides a critical update of high-throughput functional metabolomics techniques and diverse applications, and recommends the use of mass spectrometry-based metabolomics for discovering small-molecule metabolite signatures that provide valuable insights into metabolic targets. We also recommend using mass spectrometry-based metabolomics as a powerful tool for identifying and understanding metabolic patterns, metabolic targets and for efficacy evaluation of herbal medicine.

Screening of Bioactive Compounds, Antioxidant and Antimicrobial Properties in the Leaf Extracts of Two Castanopsis Species

ABSTRACT The phytochemical compounds in the leaf extracts of Castanopsis indica and C. tribuloides were evaluated, and their antioxidant and antimicrobial potential were assessed. The TPC was found to be 193.12 and 159.49 mg GAE g−1 dry weight, and the TFC was 108.12 and 96.49 mg QE g−1 dry weight, for C. indica and C. tribuloides, respectively. C. indica had higher DPPH scavenging activity, with an IC50 value of 15.10 μg mL−1. Both extracts showed substantial antimicrobial activity against the tested bacteria. GC-MS analysis showed the presence of 76 VoCs in C. indica leaf, and 71 VoCs in C. tribuloides.

Targeting EMT using low-dose Teniposide by downregulating ZEB2-driven activation of RNA polymerase I in breast cancer

Metastatic dissemination from the primary tumor is a complex process that requires crosstalk between tumor cells and the surrounding milieu and involves the interplay between numerous cellular-signaling programs. Epithelial–mesenchymal transition (EMT) remains at the forefront of orchestrating a shift in numerous cellular programs, such as stemness, drug resistance, and apoptosis that allow for successful metastasis. Till date, there is limited success in therapeutically targeting EMT. Utilizing a high throughput screen of FDA-approved compounds, we uncovered a novel role of the topoisomerase inhibitor, Teniposide, in reversing EMT. Here, we demonstrate Teniposide as a potent modulator of the EMT program, specifically through an IRF7–NMI mediated response. Furthermore, Teniposide significantly reduces the expression of the key EMT transcriptional regulator, Zinc Finger E-Box Binding Homeobox 2 (ZEB2). ZEB2 downregulation by Teniposide inhibited RNA polymerase I (Pol I) activity and rRNA biogenesis. Importantly, Teniposide treatment markedly reduced pulmonary colonization of breast cancer cells. We have uncovered a novel role of Teniposide, which when used at a very low concentration, mitigates mesenchymal-like invasive phenotype. Overall, its ability to target EMT and rRNA biogenesis makes Teniposide a viable candidate to be repurposed as a therapeutic option to restrict breast cancer metastases.

Two-point immobilization of M3 muscarinic receptor: a method for recognizing receptor antagonists in natural products

In the investigation of active ingredients from natural products, current technologies relying on drug–target affinity recognition analysis face significant challenges. This is primarily due to their limited specificity and inability to provide downstream pharmacodynamic information, such as agonistic or antagonistic activity. In this study, a two-point method was developed by immobilizing M3 acetylcholine receptor (M3R) through the combination of the conformation-specific peptide BJ-PRO-13a and the HaloTag trap system. We systematically assessed the specificity of the immobilized M3R using known M3R antagonists (pirenzepine and atropine) and agonists (cevimeline and pilocarpine). By frontal analysis and nonlinear chromatography, the performance of immobilized M3R was evaluated in terms of binding kinetics and thermodynamics of four drugs to the immobilized M3R. Additionally, we successfully identified two M3R antagonists within an extract from Daturae Flos (DF), specifically hyoscyamine and scopolamine. Our findings demonstrate that this immobilization method effectively captures receptor-ligand binding interactions and can discern receptor agonists from antagonists. This innovation enhances the efficiency of receptor chromatography to determine binding-affinity in the development of new drugs, offering promise for the screening and characterization of active compounds, particularly within complex natural products.

Abstract PO5-27-02: A Tumor Emboli Platform for Morphometric Analysis, Drug screening and for Intravital Optical Imaging in a Murine Model to Simulate Clinicopathological Features of Inflammatory Breast Cancer

Abstract Background: Inflammatory breast cancer (IBC) is distinguished by the presence of tumor emboli, clusters of tumor cells, found within breast parenchyma and dermal lymphatic vessels. These emboli serve as a crucial clinicopathological hallmark, believed to underlie the characteristic diffuse growth pattern and aggressive progression observed in IBC patients, with nearly 30% of patients presenting with metastatic disease at diagnosis. However, the rarity of this cancer and the absence of a solid tumor mass pose challenges in obtaining biospecimens, particularly those with evidence of tumor emboli. To address this pressing need for preclinical models that replicate this distinctive tumor growth pattern, we describe a tumor emboli culture platform that facilitates live imaging, enables compound screening by assessing various phenotypes of the emboli, and permits evaluation of emboli in an in vivo murine model. Methods: The tumor emboli culture system was evaluated for physiological measurements corresponding to dermal lymphatic vessels and subsequently employed to generate tumor emboli from diverse patient-derived cell lines and PDX. Confocal microscopy was employed to characterize cellular information across multiple slices of the tumor emboli. This provided a comprehensive, multi-parametric analysis of single-cell and spheroid phenotypes, including measurements of number, size, shape, and viability of the organoids. Furthermore, we developed imaging algorithms to evaluate phenotypic changes in tumor emboli in response to anti-cancer drug treatment. We also optimized a technique that allows for in vivo tumor emboli implantation including in a transgenic mice with red fluorescent lymphatic vasculature that were surgically implanted with a dorsal skin window chamber. This allowed for intravital optical imaging of the local tumor microenvironment and adjacent skin. Results: Our culture platform enables live imaging of the tumor emboli generated over a span of 7-10 days, maintaining key parameters including kinematic and dynamic viscosity, density along with sheer wall stress within the reported physiological range for lymphatics. Through higher resolution confocal image acquisition and multi-parametric analysis, we conducted particle counting and classification, providing statistically significant insights into the integrity of tumor emboli over time. Additionally, the developed algorithms allowed for quantitative analysis of images from tumor emboli cultures subjected to anti-cancer drugs, revealing disparities in drug efficacy on tumor emboli integrity and dispersion including inter-cluster space within the emboli. Intravital optical imaging, coupled with quantitative analysis of dispersion characteristics of the tumor emboli implanted in the murine model over 5-6 days, demonstrated a diffuse spread reminiscent of observations in IBC patients. Furthermore, immunohistochemistry staining showed marked Ki67, CD45, F4-80 revealing a proliferative tumor microenvironment with high levels of macrophage infiltration. Conclusions: As of now specific targeted therapies for IBC patients remain elusive. Our culture platform for tumor emboli, when combined with advanced imaging techniques both in vitro and in vivo and traditional approaches like immunohistochemistry and genomic evaluation, forms a powerful toolkit for assessing the phenotype and dispersion characteristics of this unique pathological feature in IBC. This preclinical model offers crucial insights, potentially paving the way for precision medicine strategies in the treatment of this understudied cancer. Funding in part from American Cancer Society Mission Boost MBG-20-141-01-MBG grant (GRD), Department of Defense W81XWH-20-1-0153 (GRD), Duke Consortium for Inflammatory Breast Cancer Education (AB, CW, RE). Citation Format: Dorababu Sannareddy, Theresa Charity, Alexandra Bennion, Caroline Way, Edwin Yu, Ralph Erdmann, Gregory M Palmer, Gayathri R Devi. A Tumor Emboli Platform for Morphometric Analysis, Drug screening and for Intravital Optical Imaging in a Murine Model to Simulate Clinicopathological Features of Inflammatory Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-27-02.

A pipeline for senolytics.

There is intense interest in identifying compounds that selectively kill senescent cells, termed senolytics, for ameliorating age-related comorbidities. However, screening for senolytic compounds currently relies on primary cells or cell lines where senescence is induced in vitro. Given the complexity of senescent cells across tissues and diseases, this approach may not target the senescent cells that develop under specific conditions in vivo. In this issue of the JCI, Lee et al. describe a pipeline for high-throughput drug screening of senolytic compounds where senescence was induced in vivo and identify the HSP90 inhibitor XL888 as a candidate senolytic to treat idiopathic pulmonary fibrosis.

Screening and separation of natural anticancer active ingredients related to phospholipase C.

Based on the specific binding of drug molecules to cell membrane receptors, a screening and separation method for active compounds of natural products was established by combining phospholipase C (PLC) sensitized hollow fiber microscreening by a solvent seal with high-performance liquid chromatography technology. In the process, the factors affecting the screening were optimized. Under the optimal screening conditions, we screened honokiol (HK), magnolol (MG), negative control drug carbamazepine, and positive control drug amentoflavone, the repeatability of the method was tested. The PLC activity was determined before and after the screening. Experimental results showed that the sensitization factors of PLC of HK and MG were 61.0 and 48.5, respectively, and amentoflavone was 15.0, carbamazepine could not bind to PLC. Moreover, the molecular docking results were consistent with this measurement, indicating that HK and MG could be combined with PLC, and they were potential interacting components with PLC. This method used organic solvent to seal the PLC greatly ensuring the activity, so this method had the advantage of integrating separation, and purification with screening, it not only exhibited good reproducibility and high sensitivity but was also suitable for screening the active components in natural products by various targets in vitro.

Phytochemical screening and antimicrobial activities of Guizotia abyssinica L. leaf and flower extracts

Sustainable agricultural systems demand less or no use of synthetic chemicals, which have various adverse effects on the environment and human health. In this context, studies on phytochemicals with antimicrobial and antioxidant properties hold great promise to suppress plant diseases and, thereby, reducing the application of synthetic chemical pesticides. Such an alternative approach requires screening and identification of bioactive compounds from various plant species. In the present study, Guizotia abyssinica L., an oilseed crop plant that usually requires less water with no pesticide inputs to grow, was screened for its potential antioxidant and antimicrobial phytochemicals. The methanolic and aqueous extracts of leaves and flowers of G. abyssinica were tested for their polyphenol content (total phenols and flavonoids) and antioxidant potential. The antioxidant and free radical scavenging activities of both methanolic and aqueous extracts were higher in comparison to many previously reported plant extracts. Furthermore, leaf extracts of G. abyssinica have shown slightly higher antioxidant activity than flower extracts. In vitro antimicrobial studies confirmed the inhibitory effect of methanolic extracts of leaves and flowers against phytopathogens like Xanthomonas oryzae RR24, Fusarium sp. and Alternaria sp. The chemical nature and composition of these crude extracts were analyzed by Fourier Transform Infrared Spectroscopy (FTIR) and Gas Chromatography Mass Spectrometry (GC-MS). Approximately, 29 bioactive compounds detected in GC-MS were predicted to have antimicrobial activity. Based on our results, we conclude that the extracts derived from G. abyssinica have demonstrated remarkable efficacy in inhibiting the proliferation of phytopathogens, thus exhibiting immense potential in promoting sustainable agricultural practices.

Natural compound screening predicts novel GSK-3 isoform-specific inhibitors

Glycogen synthase kinase-3 (GSK-3) plays important roles in the pathogenesis of cardiovascular, metabolic, neurological disorders and cancer. Isoform-specific loss of either GSK-3α or GSK-3β often provides cytoprotective effects under such clinical conditions. However, available synthetic small molecule inhibitors are relatively non-specific, and their chronic use may lead to adverse effects. Therefore, screening for natural compound inhibitors to identify the isoform-specific inhibitors may provide improved clinical utility. Here, we screened 70 natural compounds to identify novel natural GSK-3 inhibitors employing comprehensive in silico and biochemical approaches. Molecular docking and pharmacokinetics analysis identified two natural compounds Psoralidin and Rosmarinic acid as potential GSK-3 inhibitors. Specifically, Psoralidin and Rosmarinic acid exhibited the highest binding affinities for GSK-3α and GSK-3β, respectively. Consistent with in silico findings, the kinase assay-driven IC50 revealed superior inhibitory effects of Psoralidin against GSK-3α (IC50=2.26 μM) vs. GSK-3β (IC50=4.23 μM) while Rosmarinic acid was found to be more potent against GSK-3β (IC50=2.24 μM) than GSK-3α (IC50=5.14 μM). Taken together, these studies show that the identified natural compounds may serve as GSK-3 inhibitors with Psoralidin serving as a better inhibitor for GSK-3α and Rosmarinic for GSK-3β isoform, respectively. Further characterization employing in vitro and preclinical models will be required to test the utility of these compounds as GSK-3 inhibitors for cardiometabolic and neurological disorders and cancers.

Screening for Bioactive Compounds from Mulberry Leaves Combining Bio-Affinity Ultrafiltration with α-Glucosidase and Pancreatic Lipase

Screening for Bioactive Compounds from Mulberry Leaves Combining Bio-Affinity Ultrafiltration with α-Glucosidase and Pancreatic Lipase

Structure-Based Virtual Screening of Antiviral Compounds Targeting the Norovirus RdRp Protein

Background: Human noroviruses (NV) are the primary etiological organisms causing acute gastroenteritis around the world, causing severe morbidity and imposing a significant economic burden. The RNA-dependent RNA polymerase (RdRp) is essential for viral replication and could be a promising target for anti-NV therapeutics. Despite the discovery of a few NV RdRp inhibitors, the majority of these pharmaceuticals have demonstrated limited efficacy in inhibiting viral replication in cellular models.Methods: In this study, computational screening of antiviral compounds was conducted targeting the NV RdRp protein. The assessment was based on binding poses and the key residues of RdRp involved in interactions with compounds.Results: The compounds namely, Ribavirin, BMS806, Dihydromyricetin, R7935788, and LY2784544 were found to bind the RdRp protein with high affinity. Notably, these compounds displayed significantly lower binding affinities compared to the positive control, PPNDS. In addition, these compounds exhibited many RdRp protein binding residues that were also present in the PPNDS.Conclusion: The results presented here suggest that these compounds have the potential to be used as inhibitors of NV RdRp in the development of antiviral medications. Nevertheless, due to the computational nature of this study, it is imperative to do experimental validation.Keywords: Noroviruses; RdRp; Virtual screening; Antiviral Compounds

Isoquinoline alkaloids from endophytic fungus Aspergillus puniceus and their potential as inhibitors for tobacco powdery mildew

The isoquinoline alkaloids have attracted widespread attention from chemists and biologists. With the aims of screening for biological compounds produced by fungi, three new (1–3), together with four known (4–7) isoquinolines were isolated from the cigar tobacco-derived endophytic fungus Aspergillus puniceus in this study. Their structures were determined by means of HRESIMS and NMR spectroscopic studies. Interestingly, the antifungal activity test revealed that compound 5 showed high antifungal activity against G. cichoracearum (DC) (the main pathogen of tobacco powdery mildew disease) with an inhibition rate of 76.3% ± 5.0. Compared to the negative control, compounds 1–4, 6, and 7 also showed notable anti-G. cichoracearum activities with inhibition rates in the range of 38.5–56.9%. The isolation of the above isoquinolines may provide materials for the study of more potent antifungal inhibitors and contribute to an improved utilisation of cigar tobacco-derived endophytic fungi.

Phytochemical screening and GC-FID identification of bioactive compounds in n-hexane, ethylacetate and methanol fractions of methanolic leaves extract of Azanza garckeana

Azanza garckeana is a tropical African plant commonly used for food and medicine. This study was aimed at evaluating the antioxidant, phytochemicals and the bioactive compounds present in n-hexane, ethylacetate and methanol fractions of the methanolic extract of Azanza garckeana leaves. Phytochemical screening and antioxidant assayed were carried out using standard methods, while bioactive compounds were analyzed using gas chromatography-flame ionization detector (GC-FID). The phytochemical compositions revealed considerable level of tannins and saponins with moderate concentration of flavonoids and steroids in the methanol fraction; whereas n-hexane fraction also showed considerable amount of tannins followed by saponins and a low concentration of steroids. However, ethylacetate fraction had the highest yield of tannins, steroids, and terpenoids which were significantly (p < 0.05) higher than methanolic fraction and n-hexane fraction respectively. The antioxidant activity of the methanolic crude extract of A. garckeana leaves showed that the % DPPH radical scavenging activity of the crude extract increased with decreased in concentration when compared with the standard antioxidant (ascorbic acid). The result of GC-FID analysis revealed the presence of nineteen constituents in n-hexane fraction, while ethylacetate and methanol fractions each have twenty constituents. This result showed that Azanza garckeana leaves contain health-promoting bioactive compounds with potent antioxidants.

In-depth Photo-physical Properties, Characterization and Cell Imaging Applications of 2, 6-dicyanoanilines Based on Iso-phthalaldehyde and Tere-phthalaldehyde Frame

In current manuscript we have reported the interesting fluorescence properties, characterization and cell imaging applications of 2, 6-dicyanoanilines based on iso-phthalaldehyde and tere-phthalaldehyde frame. Earlier preliminary reported work was further extended to in-depth study of photo-physical properties like quantum yield, Fluorescence decay, stock shifts etc, and screening of representative compounds (1b and 2b) for use in fluorescent cell imaging applications. The 2, 6-dicyanoanilines based on iso-phthalaldehyde and tere-phthalaldehyde frame were showing very interesting photo-physical properties and promising prospectus for cell imaging applications.

Quantifying Antibody-Dependent Cellular Cytotoxicity in a Tumor Spheroid Model: Application for Drug Discovery.

Monoclonal antibody-based immunotherapy targeting tumor antigens is now a mainstay of cancer treatment. One of the clinically relevant mechanisms of action of the antibodies is antibody-dependent cellular cytotoxicity (ADCC), where the antibody binds to the cancer cells and engages the cellular component of the immune system, e.g., natural killer (NK) cells, to kill the tumor cells. The effectiveness of these therapies could be improved by identifying adjuvant compounds that increase the sensitivity of the cancer cells or the potency of the immune cells. In addition, undiscovered drug interactions in cancer patients co-medicated for previous conditions or cancer-associated symptoms may determine the success of the antibody therapy; therefore, such unwanted drug interactions need to be eliminated. With these goals in mind, we created a cancer ADCC model and describe here a simple protocol to find ADCC-modulating drugs. Since 3D models such as cancer cell spheroids are superior to 2D cultures in predicting in vivo responses of tumors to anticancer therapies, spheroid co-cultures of EGFP-expressing HER2+ JIMT-1 breast cancer cells and the NK92.CD16 cell lines were set up and induced with Trastuzumab, a monoclonal antibody clinically approved against HER2-positive breast cancer. JIMT-1 spheroids were allowed to form in cell-repellent U-bottom 96-well plates. On day 3, NK cells and Trastuzumab were added. The spheroids were then stained with Annexin V-Alexa 647 to measure apoptotic cell death, which was quantitated in the peripheral zone of the spheroids with an automated microscope. The applicability of our assay to identify ADCC-modulating molecules is demonstrated by showing that Sunitinib, a receptor tyrosine kinase inhibitor approved by the FDA against metastatic cancer, almost completely abolishes ADCC. The generation of the spheroids and image acquisition and analysis pipelines are compatible with high-throughput screening for ADCC-modulating compounds in cancer cell spheroids.

Increased LACTB2 Expression Regulates Oxidative Phosphorylation and mTORC1 Signaling of Colorectal Cancer.

This study aimed to investigate the mechanisms of LACTB2 in colorectal cancer (CRC). Microarrays and sequencing data of CRC were acquired from UCSC Xena, GTEx, Gene Expression Omnibus, and TCGA. Pooled analysis of the mRNA expression of LACTB2 in CRC was performed using Stata software. The protein expression of LACTB2 in CRC tissues was evaluated by immunohistochemistry. The relationship between immune cell infiltration and LACTB2 expression was investigated using CIBERSORT. The potential signaling pathways and biological mechanisms of LACTB2 were explored using GSEA, KEGG, and GO. Subsequently, further screening of small molecular compounds with potential therapeutic effects on CRC was conducted through the HERB database, followed by molecular docking studies of these compounds with the LACTB2 protein. The integration and analysis of expression data obtained from 2294 CRC samples and 1286 noncancerous colorectal samples showed that LACTB2 was highly expressed in CRC. Immunohistochemistry performed on in-house tissue samples confirmed that LACTB2 protein expression was upregulated in CRC. CIBERSORT revealed lower B cell infiltration levels in the high LACTB2 expression group than in the low expression group. GO, KEGG, and GSEA analyses showed that LACTB2 expression and genes positively correlating with it were mainly related to DNA synthesis and repair, mitochondrial translational elongation and translational termination, phosphorylation, and mTORC1 signaling. Finally, molecular docking simulations confirmed the ability of quercitin to target and bind to LACTB2. This is the first study to demonstrate that LACTB2 is upregulated in CRC. LACTB2 promotes colorectal tumorigenesis and tumor progression.

Global Health Priority Box: Discovering Flucofuron as a Promising Antikinetoplastid Compound

Leishmaniasis, produced by Leishmania spp., and Chagas disease, produced by Trypanosoma cruzi, affect millions of people around the world. The treatments for these pathologies are not entirely effective and produce some side effects. For these reasons, it is necessary to develop new therapies that are more active and less toxic for patients. Some initiatives, such as the one carried out by the Medicines for Malaria Venture, allow for the screening of a large number of compounds of different origins to find alternatives to the lack of trypanocide treatments. In this work, 240 compounds were tested from the Global Health Priority Box (80 compounds with confirmed activity against drug-resistant malaria, 80 compounds for screening against neglected and zoonotic diseases and diseases at risk of drug resistance, and 80 compounds with activity against various vector species) against Trypanosoma cruzi and Leishmania amazonensis. Flucofuron, a compound with activity against vectors and with previous activity reported against Staphylococcus spp. and Schistosoma spp., demonstrates activity against L. amazonensis and T. cruzi and produces programmed cell death in the parasites. Flucofuron seems to be a good candidate for continuing study and proving its use as a trypanocidal agent.

Cell Painting-based bioactivity prediction boosts high-throughput screening hit-rates and compound diversity

Identifying active compounds for a target is a time- and resource-intensive task in early drug discovery. Accurate bioactivity prediction using morphological profiles could streamline the process, enabling smaller, more focused compound screens. We investigate the potential of deep learning on unrefined single-concentration activity readouts and Cell Painting data, to predict compound activity across 140 diverse assays. We observe an average ROC-AUC of 0.744 ± 0.108 with 62% of assays achieving ≥0.7, 30% ≥0.8, and 7% ≥0.9. In many cases, the high prediction performance can be achieved using only brightfield images instead of multichannel fluorescence images. A comprehensive analysis shows that Cell Painting-based bioactivity prediction is robust across assay types, technologies, and target classes, with cell-based assays and kinase targets being particularly well-suited for prediction. Experimental validation confirms the enrichment of active compounds. Our findings indicate that models trained on Cell Painting data, combined with a small set of single-concentration data points, can reliably predict the activity of a compound library across diverse targets and assays while maintaining high hit rates and scaffold diversity. This approach has the potential to reduce the size of screening campaigns, saving time and resources, and enabling primary screening with more complex assays.