Industrial scale high-throughput screening delivers multiple fast acting macrofilaricides

Clare, Rachel H.; Bardelle, Catherine; Harper, Paul Robert; Hong, W. David; Börjesson, Ulf; Johnston, Kelly L.; Collier, Matthew; Myhill, Laura J.; Cassidy, Andrew; Plant, Darren; Plant, Helen; Clark, Roger; Cook, Darren; Steven, Andrew; Archer, John; McGillan, Paul; Charoensutthivarakul, Sitthivut; Bibby, Jaclyn; Sharma, Raman; Nixon, Gemma L.; Slatko, Barton E.; Cantin, Lindsey; Wu, Bo; Turner, Joseph D.; Ford, Louise; Rich, Kirsty; Wigglesworth, Mark; Berry, Neil G.; O’Neill, Paul M.; Taylor, Mark J.; Ward, Stephen A.

doi:10.1038/s41467-018-07826-2

Cited by 97 publications

(59 citation statements)

References 38 publications

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“…The output from the screening activity described has identified novel chemical starting points from the AstraZeneca compound collection, resulting in the identification of five series of novel fast-acting macrofilaricides, 23 allowing for the potential of an improved medication against both LF and onchocerciasis. These starting points for discovery will form the basis of future publications specifically addressing the discovery process from hit through to leads and optimized drug candidates.…”

Section: Resultsmentioning

confidence: 99%

“…The C6/36 ( w AlbB) cell line used in this screen has been described previously. 2,7,20–23 In brief this mosquito ( Aedes albopictus )-derived cell line is stably infected with Wolbachia pipientis ( w AlbB). For use in the screen, cells were cultured in Leibovitz medium (Life Technologies, Loughborough, UK) supplemented with 20% fetal bovine serum (FBS; Fisher Scientific, Loughborough, UK), 2% tryptose phosphate broth (Sigma-Aldrich, Poole, UK), 1% nonessential amino acids (Sigma-Aldrich), and 1% penicillin-streptomycin (Sigma-Aldrich) at 26 °C, without additional CO 2 .…”

Section: Methodsmentioning

confidence: 99%

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Development of a High-Throughput Cytometric Screen to Identify Anti-Wolbachia Compounds: The Power of Public–Private Partnership

et al. 2019

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The Anti- Wolbachia (A·WOL) consortium at the Liverpool School of Tropical Medicine (LSTM) has partnered with the Global High-Throughput Screening (HTS) Centre at AstraZeneca to create the first anthelmintic HTS for neglected tropical diseases (NTDs). The A·WOL consortium aims to identify novel macrofilaricidal drugs targeting the essential bacterial symbiont ( Wolbachia) of the filarial nematodes causing onchocerciasis and lymphatic filariasis. Working in collaboration, we have validated a robust high-throughput assay capable of identifying compounds that selectively kill Wolbachia over the host insect cell. We describe the development and validation process of this complex, phenotypic high-throughput assay and provide an overview of the primary outputs from screening the AstraZeneca library of 1.3 million compounds.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Development of a High-Throughput Cytometric Screen to Identify Anti-Wolbachia Compounds: The Power of Public–Private Partnership

et al. 2019

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“…HTS has been productive in drug design [ 204 , 205 ], but the method is time and resource intensive [ 206 ] and expensive [ 206 ] because of the numerous molecules to be examined (~100 million) [ 207 ]. Furthermore, the success rate is only estimated to be at ~50% [ 204 , 208 ].…”

Section: Nmr Methods For Drug Discovery and Drug Developmentmentioning

confidence: 99%

NMR as a “Gold Standard” Method in Drug Design and Discovery

et al. 2020

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Studying disease models at the molecular level is vital for drug development in order to improve treatment and prevent a wide range of human pathologies. Microbial infections are still a major challenge because pathogens rapidly and continually evolve developing drug resistance. Cancer cells also change genetically, and current therapeutic techniques may be (or may become) ineffective in many cases. The pathology of many neurological diseases remains an enigma, and the exact etiology and underlying mechanisms are still largely unknown. Viral infections spread and develop much more quickly than does the corresponding research needed to prevent and combat these infections; the present and most relevant outbreak of SARS-CoV-2, which originated in Wuhan, China, illustrates the critical and immediate need to improve drug design and development techniques. Modern day drug discovery is a time-consuming, expensive process. Each new drug takes in excess of 10 years to develop and costs on average more than a billion US dollars. This demonstrates the need of a complete redesign or novel strategies. Nuclear Magnetic Resonance (NMR) has played a critical role in drug discovery ever since its introduction several decades ago. In just three decades, NMR has become a “gold standard” platform technology in medical and pharmacology studies. In this review, we present the major applications of NMR spectroscopy in medical drug discovery and development. The basic concepts, theories, and applications of the most commonly used NMR techniques are presented. We also summarize the advantages and limitations of the primary NMR methods in drug development.

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“…Ultimately, however, validating a new candidate target for therapeutic intervention requires development of a chemical probe to explore the consequences of pharmacological manipulation of this target ( 3 ). In recent years, this step has typically been carried out by using high-throughput screening (HTS) ( 4 ) as a starting point for subsequent medicinal chemistry optimization; with improvements in automation, it has become feasible to screen libraries that exceed a million compounds ( 5 ).…”

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confidence: 99%

Machine learning classification can reduce false positives in structure-based virtual screening

Adeshina

Deeds

Karanicolas

2020

Proc. Natl. Acad. Sci. U.S.A.

131

120

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With the recent explosion in the size of libraries available for screening, virtual screening is positioned to assume a more prominent role in early drug discovery’s search for active chemical matter. In typical virtual screens, however, only about 12% of the top-scoring compounds actually show activity when tested in biochemical assays. We argue that most scoring functions used for this task have been developed with insufficient thoughtfulness into the datasets on which they are trained and tested, leading to overly simplistic models and/or overtraining. These problems are compounded in the literature because studies reporting new scoring methods have not validated their models prospectively within the same study. Here, we report a strategy for building a training dataset (D-COID) that aims to generate highly compelling decoy complexes that are individually matched to available active complexes. Using this dataset, we train a general-purpose classifier for virtual screening (vScreenML) that is built on the XGBoost framework. In retrospective benchmarks, our classifier shows outstanding performance relative to other scoring functions. In a prospective context, nearly all candidate inhibitors from a screen against acetylcholinesterase show detectable activity; beyond this, 10 of 23 compounds have IC50 better than 50 μM. Without any medicinal chemistry optimization, the most potent hit has IC50 280 nM, corresponding to Ki of 173 nM. These results support using the D-COID strategy for training classifiers in other computational biology tasks, and for vScreenML in virtual screening campaigns against other protein targets. Both D-COID and vScreenML are freely distributed to facilitate such efforts.

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Industrial scale high-throughput screening delivers multiple fast acting macrofilaricides

Cited by 97 publications

References 38 publications

Development of a High-Throughput Cytometric Screen to Identify Anti-Wolbachia Compounds: The Power of Public–Private Partnership

Development of a High-Throughput Cytometric Screen to Identify Anti-Wolbachia Compounds: The Power of Public–Private Partnership

NMR as a “Gold Standard” Method in Drug Design and Discovery

Machine learning classification can reduce false positives in structure-based virtual screening

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