Synthesis and dopaminergic properties of some exo- and endo-2-aminobenzonorbornenes designed as rigid analogs of dopamine

Burn, P.; Crooks, Peter A.; Heatley, Frank; Costall, B.; Naylor, R.J.; Nohria, Virinder

doi:10.1021/jm00346a007

Cited by 15 publications

(3 citation statements)

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“…Three examples are shown in Fig. 3 b each of which is based on structures from four publications [ 41 – 52 ]. The basis for the use of these data as a benchmark for structural similarity is the assumption that structural similarity decreases relative to a reference molecule as one moves from one paper to another through co-occurring molecules, given the size of chemical space and the nature of a random walk.…”

Section: Resultsmentioning

confidence: 99%

Comparing structural fingerprints using a literature-based similarity benchmark

O’Boyle¹,

Sayle²

2016

J Cheminform

184

132

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BackgroundThe concept of molecular similarity is one of the central ideas in cheminformatics, despite the fact that it is ill-defined and rather difficult to assess objectively. Here we propose a practical definition of molecular similarity in the context of drug discovery: molecules A and B are similar if a medicinal chemist would be likely to synthesise and test them around the same time as part of the same medicinal chemistry program. The attraction of such a definition is that it matches one of the key uses of similarity measures in early-stage drug discovery. If we make the assumption that molecules in the same compound activity table in a medicinal chemistry paper were considered similar by the authors of the paper, we can create a dataset of similar molecules from the medicinal chemistry literature. Furthermore, molecules with decreasing levels of similarity to a reference can be found by either ordering molecules in an activity table by their activity, or by considering activity tables in different papers which have at least one molecule in common.ResultsUsing this procedure with activity data from ChEMBL, we have created two benchmark datasets for structural similarity that can be used to guide the development of improved measures. Compared to similar results from a virtual screen, these benchmarks are an order of magnitude more sensitive to differences between fingerprints both because of their size and because they avoid loss of statistical power due to the use of mean scores or ranks. We measure the performance of 28 different fingerprints on the benchmark sets and compare the results to those from the Riniker and Landrum (J Cheminf 5:26, 2013. doi:10.1186/1758-2946-5-26) ligand-based virtual screening benchmark.ConclusionsExtended-connectivity fingerprints of diameter 4 and 6 are among the best performing fingerprints when ranking diverse structures by similarity, as is the topological torsion fingerprint. However, when ranking very close analogues, the atom pair fingerprint outperforms the others tested. When ranking diverse structures or carrying out a virtual screen, we find that the performance of the ECFP fingerprints significantly improves if the bit-vector length is increased from 1024 to 16,384.Graphical abstractAn example series from one of the benchmark datasets. Each fingerprint is assessed on its ability to reproduce a specific series order.Electronic supplementary materialThe online version of this article (doi:10.1186/s13321-016-0148-0) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

Comparing structural fingerprints using a literature-based similarity benchmark

O’Boyle¹,

Sayle²

2016

J Cheminform

184

132

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“…37 6,7-ADTN is a highly potent antagonist for dopamine receptors (IC 50 = 1.7 nM). 38 Because of high potency of these two hit compounds for other targets, further structural modifications will be needed to increase their specificity and potency for NTMT1.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

“…CGP 74514A (NCGC00015229, Figure ) and 6,7-ADTN (NCGC00015291, Figure ) are two validated hits after removal of three promiscuous compounds, such as the alkylating agent iodoacetamide (NCGC00015548), intraplate control SCH-202676 (NCGC00162335), and an inorganic dye ruthenium red (NCGC00162333). , CGP 74514A is a cell-permeable and selective inhibitor of cyclin-dependent kinase 1 (CDK1)/cyclin B (IC 50 = 31 nM) . 6,7-ADTN is a highly potent antagonist for dopamine receptors (IC 50 = 1.7 nM) . Because of high potency of these two hit compounds for other targets, further structural modifications will be needed to increase their specificity and potency for NTMT1.…”

Section: Results and Discussionmentioning

confidence: 99%

Optimization of High-Throughput Methyltransferase Assays for the Discovery of Small Molecule Inhibitors

et al. 2020

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Methyltransferases (MTases) play diverse roles in cellular processes. Aberrant methylation levels have been implicated in many diseases, indicating the need for the identification and development of small molecule inhibitors for each MTase. Specific inhibitors can serve as probes to investigate the function and validate therapeutic potential for the respective MTase. High-throughput screening (HTS) is a powerful method to identify initial hits for further optimization. Here, we report the development of a fluorescence-based MTase assay and compare this format with the recently developed MTase-Glo luminescence assay for application in HTS. Using protein N-terminal methyltransferase 1 (NTMT1) as a model system, we miniaturized to 1536-well quantitative HTS format. Through a pilot screen of 1428 pharmacologically active compounds and subsequent validation, we discovered that MTase-Glo produced lower false positive rates than the fluorescence-based MTase assay. Nevertheless, both assays displayed robust performance along with low reagent requirements and can potentially be employed as general HTS formats for the discovery of inhibitors for any MTase.

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