Nuisance Compounds, PAINS Filters, and Dark Chemical Matter in the GSK HTS Collection

Chakravorty, Subhas J.; Chan, James; Greenwood, M. Nicole; Popa‐Burke, Ioana; Remlinger, Katja; Pickett, Stephen D.; Green, Darren V. S.; Fillmore, Martin C; Dean, Tony W.; Luengo, Juan I.; Macarrόn, Ricardo

doi:10.1177/2472555218768497

Cited by 58 publications

(58 citation statements)

References 53 publications

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“…A large range of molecular properties, predictive models for ADMET liabilities, permeability, solubility are available through GSK internal web-services, QSAR Workbench models [65] or as native Pipeline Pilot descriptors. The Task also runs GSK specific substructural filters to identify undesirable chemotypes [66]. It is a requirement of the system that the molecule generator output be processed by this Task.…”

Section: Compound Profile Filtermentioning

confidence: 99%

BRADSHAW: a system for automated molecular design

Green

Pickett

Luscombe

et al. 2019

J Comput Aided Mol Des

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This paper introduces BRADSHAW (Biological Response Analysis and Design System using an Heterogenous, Automated Workflow), a system for automated molecular design which integrates methods for chemical structure generation, experimental design, active learning and cheminformatics tools. The simple user interface is designed to facilitate access to large scale automated design whilst minimising software development required to introduce new algorithms, a critical requirement in what is a very fast moving field. The system embodies a philosophy of automation, best practice, experimental design and the use of both traditional cheminformatics and modern machine learning algorithms.

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Section: Compound Profile Filtermentioning

confidence: 99%

BRADSHAW: a system for automated molecular design

Green

Pickett

Luscombe

et al. 2019

J Comput Aided Mol Des

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“…The assay was found to be highly sensitive, specific, and robust, with a sensitivity of 100%, specificity of 99.4% (see Table S2 in the supplemental material), and Z factor value of 0.87. Next, a “nuisance” set of 1,027 compounds, selected to highlight common biochemical assay interference mechanisms (28), was tested. A good linear correlation was established between screening replicates of this compound set ( R 2 = 0.95) (see Fig.…”

Section: Resultsmentioning

confidence: 99%

Identification of Novel Trypanosoma cruzi Proteasome Inhibitors Using a Luminescence-Based High-Throughput Screening Assay

Zmuda

Sastry

Jones

et al. 2019

Antimicrob Agents Chemother

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Chagas’ disease, caused by the protozoan parasite Trypanosoma cruzi, is a potentially life-threatening condition that has become a global issue. Current treatment is limited to two medicines that require prolonged dosing and are associated with multiple side effects, which often lead to treatment discontinuation and failure. One way to address these shortcomings is through target-based drug discovery on validated T. cruzi protein targets. One such target is the proteasome, which plays a crucial role in protein degradation and turnover through chymotrypsin-, trypsin-, and caspase-like catalytic activities. In order to initiate a proteasome drug discovery program, we isolated proteasomes from T. cruzi epimastigotes and characterized their activity using a commercially available glow-like luminescence-based assay. We developed a high-throughput biochemical assay for the chymotrypsin-like activity of the T. cruzi proteasome, which was found to be sensitive, specific, and robust but prone to luminescence technology interference. To mitigate this, we also developed a counterscreen assay that identifies potential interferers at the levels of both the luciferase enzyme reporter and the mechanism responsible for a glow-like response. Interestingly, we also found that the peptide substrate for chymotrypsin-like proteasome activity was not specific and was likely partially turned over by other catalytic sites of the protein. Finally, we utilized these biochemical tools to screen 18,098 compounds, exploring diverse drug-like chemical space, which allowed us to identify 39 hits that were active in the primary screening assay and inactive in the counterscreen assay.

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“…Substructures listed in the "remove" and "extreme caution" categories of the SMARTS patterns compiled by Chakravorty et al [31]. These SMARTS patterns were compiled from a meta-analysis of existing structural filters to identify nuisance compounds and correctly identified 57% of noisy GSK compounds in the study's validation [31] 10.…”

Section: Filtering Of the Zinc20 Subset By Molecular Propertiesmentioning

confidence: 99%

BonMOLière: Small-Sized Libraries of Readily Purchasable Compounds, Optimized to Produce Genuine Hits in Biological Screens across the Protein Space

Mathai

Stork

Kirchmair

2021

IJMS

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Experimental screening of large sets of compounds against macromolecular targets is a key strategy to identify novel bioactivities. However, large-scale screening requires substantial experimental resources and is time-consuming and challenging. Therefore, small to medium-sized compound libraries with a high chance of producing genuine hits on an arbitrary protein of interest would be of great value to fields related to early drug discovery, in particular biochemical and cell research. Here, we present a computational approach that incorporates drug-likeness, predicted bioactivities, biological space coverage, and target novelty, to generate optimized compound libraries with maximized chances of producing genuine hits for a wide range of proteins. The computational approach evaluates drug-likeness with a set of established rules, predicts bioactivities with a validated, similarity-based approach, and optimizes the composition of small sets of compounds towards maximum target coverage and novelty. We found that, in comparison to the random selection of compounds for a library, our approach generates substantially improved compound sets. Quantified as the “fitness” of compound libraries, the calculated improvements ranged from +60% (for a library of 15,000 compounds) to +184% (for a library of 1000 compounds). The best of the optimized compound libraries prepared in this work are available for download as a dataset bundle (“BonMOLière”).

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Nuisance Compounds, PAINS Filters, and Dark Chemical Matter in the GSK HTS Collection

Cited by 58 publications

References 53 publications

BRADSHAW: a system for automated molecular design

BRADSHAW: a system for automated molecular design

Identification of Novel Trypanosoma cruzi Proteasome Inhibitors Using a Luminescence-Based High-Throughput Screening Assay

BonMOLière: Small-Sized Libraries of Readily Purchasable Compounds, Optimized to Produce Genuine Hits in Biological Screens across the Protein Space

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