Canvass: A Crowd-Sourced, Natural-Product Screening Library for Exploring Biological Space

Natural products and their derivatives continue to be wellsprings of nascent therapeutic potential. However, many laboratories have limited resources for biological evaluation, leaving their previously isolated or synthesized compounds largely or completely untested. To address this issue, the Canvass library of natural products was assembled, in collaboration with academic and industry researchers, for quantitative high-throughput screening (qHTS) across a diverse set of cell-based and biochemical assays. Characterization of the library in terms of physicochemical properties, structural diversity, and similarity to compounds in publicly available libraries indicates that the Canvass library contains many structural elements in common with approved drugs. The assay data generated were analyzed using a variety of quality control metrics, and the resultant assay profiles were explored using statistical methods, such as clustering and compound promiscuity analyses. Individual compounds were then sorted by structural class and activity profiles. Differential behavior based on these classifications, as well as noteworthy activities, are outlined herein. One such highlight is the activity of (−)-2(S)-cathafoline, which was found to stabilize calcium levels in the endoplasmic reticulum. The workflow described here illustrates a pilot effort to broadly survey the biological potential of natural products by utilizing the power of automation and high-throughput screening

Canvass: a crowd-sourced, natural-product screening library for exploring biological space

NCATS thanks Dingyin Tao for assistance with compound characterization. This research was supported by the Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health (NIH). R.B.A. acknowledges support from NSF (CHE-1665145) and NIH (GM126221). M.K.B. acknowledges support from NIH (5R01GM110131). N.Z.B. thanks support from NIGMS, NIH (R01GM114061). J.K.C. acknowledges support from NSF (CHE-1665331). J.C. acknowledges support from the Fogarty International Center, NIH (TW009872). P.A.C. acknowledges support from the National Cancer Institute (NCI), NIH (R01 CA158275), and the NIH/National Institute of Aging (P01 AG012411). N.K.G. acknowledges support from NSF (CHE-1464898). B.C.G. thanks the support of NSF (RUI: 213569), the Camille and Henry Dreyfus Foundation, and the Arnold and Mabel Beckman Foundation. C.C.H. thanks the start-up funds from the Scripps Institution of Oceanography for support. J.N.J. acknowledges support from NIH (GM 063557, GM 084333). A.D.K. thanks the support from NCI, NIH (P01CA125066). D.G.I.K. acknowledges support from the National Center for Complementary and Integrative Health (1 R01 AT008088) and the Fogarty International Center, NIH (U01 TW00313), and gratefully acknowledges courtesies extended by the Government of Madagascar (Ministere des Eaux et Forets). O.K. thanks NIH (R01GM071779) for financial support. T.J.M. acknowledges support from NIH (GM116952). S.M. acknowledges support from NIH (DA045884-01, DA046487-01, AA026949-01), the Office of the Assistant Secretary of Defense for Health Affairs through the Peer Reviewed Medical Research Program (W81XWH-17-1-0256), and NCI, NIH, through a Cancer Center Support Grant (P30 CA008748). K.N.M. thanks the California Department of Food and Agriculture Pierce's Disease and Glassy Winged Sharpshooter Board for support. B.T.M. thanks Michael Mullowney for his contribution in the isolation, elucidation, and submission of the compounds in this work. P.N. acknowledges support from NIH (R01 GM111476). L.E.O. acknowledges support from NIH (R01-HL25854, R01-GM30859, R0-1-NS-12389). L.E.B., J.K.S., and J.A.P. thank the NIH (R35 GM-118173, R24 GM-111625) for research support. F.R. thanks the American Lebanese Syrian Associated Charities (ALSAC) for financial support. I.S. thanks the University of Oklahoma Startup funds for support. J.T.S. acknowledges support from ACS PRF (53767-ND1) and NSF (CHE-1414298), and thanks Drs. Kellan N. Lamb and Michael J. Di Maso for their synthetic contribution. B.S. acknowledges support from NIH (CA78747, CA106150, GM114353, GM115575). W.S. acknowledges support from NIGMS, NIH (R15GM116032, P30 GM103450), and thanks the University of Arkansas for startup funds and the Arkansas Biosciences Institute (ABI) for seed money. C.R.J.S. acknowledges support from NIH (R01GM121656). D.S.T. thanks the support of NIH (T32 CA062948-Gudas) and PhRMA Foundation to A.L.V., NIH (P41 GM076267) to D.S.T., and CCSG NIH (P30 CA008748) to C.B. Thompson. R.E.T. acknowledges support from NIGMS, NIH (GM129465). R.J.T. thanks the American Cancer Society (RSG-12-253-01-CDD) and NSF (CHE1361173) for support. D.A.V. thanks the Camille and Henry Dreyfus Foundation, the National Science Foundation (CHE-0353662, CHE-1005253, and CHE-1725142), the Beckman Foundation, the Sherman Fairchild Foundation, the John Stauffer Charitable Trust, and the Christian Scholars Foundation for support. J.W. acknowledges support from the American Cancer Society through the Research Scholar Grant (RSG-13-011-01-CDD). W.M.W.acknowledges support from NIGMS, NIH (GM119426), and NSF (CHE1755698). A.Z. acknowledges support from NSF (CHE-1463819). (Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health (NIH); CHE-1665145 - NSF; CHE-1665331 - NSF; CHE-1464898 - NSF; RUI: 213569 - NSF; CHE-1414298 - NSF; CHE1361173 - NSF; CHE1755698 - NSF; CHE-1463819 - NSF; GM126221 - NIH; 5R01GM110131 - NIH; GM 063557 - NIH; GM 084333 - NIH; R01GM071779 - NIH; GM116952 - NIH; DA045884-01 - NIH; DA046487-01 - NIH; AA026949-01 - NIH; R01 GM111476 - NIH; R01-HL25854 - NIH; R01-GM30859 - NIH; R0-1-NS-12389 - NIH; R35 GM-118173 - NIH; R24 GM-111625 - NIH; CA78747 - NIH; CA106150 - NIH; GM114353 - NIH; GM115575 - NIH; R01GM121656 - NIH; T32 CA062948-Gudas - NIH; P41 GM076267 - NIH; R01GM114061 - NIGMS, NIH; R15GM116032 - NIGMS, NIH; P30 GM103450 - NIGMS, NIH; GM129465 - NIGMS, NIH; GM119426 - NIGMS, NIH; TW009872 - Fogarty International Center, NIH; U01 TW00313 - Fogarty International Center, NIH; R01 CA158275 - National Cancer Institute (NCI), NIH; P01 AG012411 - NIH/National Institute of Aging; Camille and Henry Dreyfus Foundation; Arnold and Mabel Beckman Foundation; Scripps Institution of Oceanography; P01CA125066 - NCI, NIH; 1 R01 AT008088 - National Center for Complementary and Integrative Health; W81XWH-17-1-0256 - Office of the Assistant Secretary of Defense for Health Affairs through the Peer Reviewed Medical Research Program; P30 CA008748 - NCI, NIH, through a Cancer Center Support Grant; California Department of Food and Agriculture Pierce's Disease and Glassy Winged Sharpshooter Board; American Lebanese Syrian Associated Charities (ALSAC); University of Oklahoma Startup funds; 53767-ND1 - ACS PRF; PhRMA Foundation; P30 CA008748 - CCSG NIH; RSG-12-253-01-CDD - American Cancer Society; RSG-13-011-01-CDD - American Cancer Society; CHE-0353662 - National Science Foundation; CHE-1005253 - National Science Foundation; CHE-1725142 - National Science Foundation; Beckman Foundation; Sherman Fairchild Foundation; John Stauffer Charitable Trust; Christian Scholars Foundation)Published versionSupporting documentatio

Comparison of Compound Administration Methods in Biochemical Assays: Effects on Apparent Compound Potency Using Either Assay Ready Compound Plates or Pin tool Delivered Compounds

Compound sample preparation and delivery is one of the most critical steps in high-throughput screening (HTS) campaigns. Historically, several methods of compound delivery to assays have been used for HTS, including pre-diluted intermediate dilution plates, “assay-ready plates” (ARP) using either pre-plated dried compound films or nanoliter DMSO spots of compounds, as well as pin tool delivered compounds. We and others have observed differences in apparent compound potency depending on the compound delivery method. To quantitatively measure compound potency differences due to the chosen delivery methods, we conducted a controlled study using a validated biochemical luciferase assay and compared potencies when compounds were delivered in either ARP (using acoustic dispensed nanoliter spots) or by pin tool. Here we compare hit rates, confirmation rates, false positive, and false negative rates between the two delivery methods using the luciferase assay. We compared polystyrene (PS) and cyclic olefin copolymer (COC) plates using both delivery methods and examined whether ARP cold stored at 4°C were superior to those stored frozen at -20°C. The data show that pin tool delivery results in more confirmed hits than pre-plated compounds, resulting in a lower false negative rate, but that this effect is minimized through the use of COC plates and by obtaining plates “just-in-time” from 4°C cold storage. We also confirmed that the choice of compound delivery method to the assay has an effect on the apparent IC50s of some compounds that confirmed in all methods. Overall, this report impacts the way HTS campaigns are utilizing assay-ready compound plates in our department

Deep learning identifies synergistic drug combinations for treating COVID-19

Effective treatments for COVID-19 are urgently needed. However, discovering single-agent therapies with activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been challenging. Combination therapies play an important role in antiviral therapies, due to their improved efficacy and reduced toxicity. Recent approaches have applied deep learning to identify synergistic drug combinations for diseases with vast preexisting datasets, but these are not applicable to new diseases with limited combination data, such as COVID-19. Given that drug synergy often occurs through inhibition of discrete biological targets, here we propose a neural network architecture that jointly learns drug−target interaction and drug−drug synergy. The model consists of two parts: a drug−target interaction module and a target−disease association module. This design enables the model to utilize drug−target interaction data and single-agent antiviral activity data, in addition to available drug−drug combination datasets, which may be small in nature. By incorporating additional biological information, our model performs significantly better in synergy prediction accuracy than previous methods with limited drug combination training data. We empirically validated our model predictions and discovered two drug combinations, remdesivir and reserpine as well as remdesivir and IQ-1S, which display strong antiviral SARS-CoV-2 synergy in vitro. Our approach, which was applied here to address the urgent threat of COVID-19, can be readily extended to other diseases for which a dearth of chemical−chemical combination data exists

The Toxmatrix: Chemo-Genomic Profiling Identifies Interactions That Reveal Mechanisms of Toxicity

A chemical genomics “Toxmatrix” method was developed to elucidate mechanisms of cytotoxicity using neuronal models. Quantitative high-throughput screening (qHTS) was applied to systematically screen each toxicant against a panel of 70 modulators, drugs or chemicals that act on a known target, to identify interactions that either protect or sensitize cells to each toxicant. Thirty-two toxicants were tested at 10 concentrations for cytotoxicity to SH-SY5Y human neuroblastoma cells, with results fitted to the Hill equation to determine an IC₅₀ for each toxicant. Thirty-three toxicant:modulator interactions were identified in SH-SY5Y cells for 14 toxicants, as modulators that shifted toxicant IC₅₀ values lower or higher. The target of each modulator that sensitizes cells or protects cells from a toxicant suggests a mode of toxicant action or cellular adaptation. In secondary screening, we tested modulator-toxicant pairs identified from the SH-SY5Y primary screening for interactions in three differentiated neuronal human cell lines: dSH-SY5Y, conditionally immortalized dopaminergic neurons (LUHMES), and neural stem cells. Twenty toxicant-modulator pairs showed pronounced interactions in one or several differentiated cell models. Additional testing confirmed that several modulators acted through their primary targets. For example, several chelators protected differentiated LUHMES neurons from four toxicants by chelation of divalent cations and buthionine sulphoximine sensitized cells to 6-hydroxydopamine and 4-(methylamino)­phenol hemisulfate by blocking glutathione synthesis. Such modulators that interact with multiple neurotoxicants suggest these may be vulnerable toxicity pathways in neurons. Thus, the Toxmatrix method is a systematic high-throughput approach that can identify mechanisms of toxicity and cellular adaptation

Modulation of Triple Artemisinin-Based Combination Therapy Pharmacodynamics by Plasmodium falciparum Genotype

The first-line treatments for uncomplicated Plasmodium falciparum malaria are artemisinin-based combination therapies (ACTs), consisting of an artemisinin derivative combined with a longer acting partner drug. However, the spread of P. falciparum with decreased susceptibility to artemisinin and partner drugs presents a significant challenge to malaria control efforts. To stem the spread of drug resistant parasites, novel chemotherapeutic strategies are being evaluated, including the implementation of triple artemisinin-based combination therapies (TACTs). Currently, there is limited knowledge on the pharmacodynamic and pharmacogenetic interactions of proposed TACT drug combinations. To evaluate these interactions, we established an in vitro high-throughput process for measuring the drug concentration-response to three distinct antimalarial drugs present in a TACT. Sixteen different TACT combinations were screened against 15 parasite lines from Cambodia, with a focus on parasites with differential susceptibilities to piperaquine and artemisinins. Analysis revealed drug-drug interactions unique to specific genetic backgrounds, including antagonism between piperaquine and pyronaridine associated with gene amplification of plasmepsin II/III, two aspartic proteases that localize to the parasite digestive vacuole. From this initial study, we identified parasite genotypes with decreased susceptibility to specific TACTs, as well as potential TACTs that display antagonism in a genotype-dependent manner. Our assay and analysis platform can be further leveraged to inform drug implementation decisions and evaluate next-generation TACTs

Targeting neddylation sensitizes colorectal cancer to topoisomerase I inhibitors by inactivating the DCAF13-CRL4 ubiquitin ligase complex

Abstract Colorectal cancers (CRCs) are prevalent worldwide, yet current treatments remain inadequate. Using chemical genetic screens, we identify that co-inhibition of topoisomerase I (TOP1) and NEDD8 is synergistically cytotoxic in human CRC cells. Combination of the TOP1 inhibitor irinotecan or its bioactive metabolite SN38 with the NEDD8-activating enzyme inhibitor pevonedistat exhibits synergy in CRC patient-derived organoids and xenografts. Mechanistically, we show that pevonedistat blocks the ubiquitin/proteasome-dependent repair of TOP1 DNA-protein crosslinks (TOP1-DPCs) induced by TOP1 inhibitors and that the CUL4-RBX1 complex (CRL4) is a prominent ubiquitin ligase acting on TOP1-DPCs for proteasomal degradation upon auto-NEDD8 modification during replication. We identify DCAF13, a DDB1 and Cullin Associated Factor, as the receptor of TOP1-DPCs for CRL4. Our study not only uncovers a replication-coupled ubiquitin-proteasome pathway for the repair of TOP1-DPCs but also provides molecular and translational rationale for combining TOP1 inhibitors and pevonedistat for CRC and other types of cancers

High-throughput and targeted drug screens identify pharmacological candidates against MiT-translocation renal cell carcinoma

Abstract Background MiT-Renal Cell Carcinoma (RCC) is characterized by genomic translocations involving microphthalmia-associated transcription factor (MiT) family members TFE3, TFEB, or MITF. MiT-RCC represents a specific subtype of sporadic RCC that is predominantly seen in young patients and can present with heterogeneous histological features making diagnosis challenging. Moreover, the disease biology of this aggressive cancer is poorly understood and there is no accepted standard of care therapy for patients with advanced disease. Tumor-derived cell lines have been established from human TFE3-RCC providing useful models for preclinical studies. Methods TFE3-RCC tumor derived cell lines and their tissues of origin were characterized by IHC and gene expression analyses. An unbiased high-throughput drug screen was performed to identify novel therapeutic agents for treatment of MiT-RCC. Potential therapeutic candidates were validated in in vitro and in vivo preclinical studies. Mechanistic assays were conducted to confirm the on-target effects of drugs. Results The results of a high-throughput small molecule drug screen utilizing three TFE3-RCC tumor-derived cell lines identified five classes of agents with potential pharmacological efficacy, including inhibitors of phosphoinositide-3-kinase (PI3K) and mechanistic target of rapamycin (mTOR), and several additional agents, including the transcription inhibitor Mithramycin A. Upregulation of the cell surface marker GPNMB, a specific MiT transcriptional target, was confirmed in TFE3-RCC and evaluated as a therapeutic target using the GPNMB-targeted antibody-drug conjugate CDX-011. In vitro and in vivo preclinical studies demonstrated efficacy of the PI3K/mTOR inhibitor NVP-BGT226, Mithramycin A, and CDX-011 as potential therapeutic options for treating advanced MiT-RCC as single agents or in combination. Conclusions The results of the high-throughput drug screen and validation studies in TFE3-RCC tumor-derived cell lines have provided in vitro and in vivo preclinical data supporting the efficacy of the PI3K/mTOR inhibitor NVP-BGT226, the transcription inhibitor Mithramycin A, and GPNMB-targeted antibody-drug conjugate CDX-011 as potential therapeutic options for treating advanced MiT-RCC. The findings presented here should provide the basis for designing future clinical trials for patients with MiT-driven RCC

Canvass: A Crowd-Sourced, Natural Product Screening Library for Exploring Biological Space

Natural products and their derivatives continue to be wellsprings of nascent therapeutic potential. However, many laboratories have limited resources for biological evaluation, leaving their previously isolated or synthesized compounds largely or completely untested. To address this issue, the Canvass library of natural products was assembled, in collaboration with academic and industry researchers, for quantitative high-throughput screening (qHTS) across a diverse set of cell-based and biochemical assays. Characterization of the library in terms of physicochemical properties, structural diversity, and similarity to compounds in publicly available libraries indicates that the Canvass library contains many structural elements in common with approved drugs. The assay data generated were analyzed using a variety of quality control metrics, and the resultant assay profiles were explored using statistical methods, such as clustering and compound promiscuity analyses. Individual compounds were then sorted by structural class and activity profiles. Differential behavior based on these classifications, as well as noteworthy activities, are outlined herein. One such highlight is the activity of (–)-2(S)-cathafoline, which was found to stabilize calcium levels in the endoplasmic reticulum. The workflow described here illustrates a pilot effort to broadly survey the biological potential of natural products by utilizing the power of automation and high-throughput screening