ArticleCombinatorial chemistry & high throughput screening2012
The applicability of molecular descriptors for designing an electrospray ionization mass spectrometry compatible library for drug discovery.
Article in Combinatorial chemistry & high throughput screening, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Quantitative method comparison in non-targeted analysis using cascade classification.Analytical and bioanalytical chemistry · 2026Article
- Development of classification models for identification of important structural features of isoform-selective histone deacetylase inhibitors (class I).Molecular diversity · 2020Article
- The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification.Environmental science and pollution research international · 2019Article
- Beyond the paradigm: Combining mass spectrometry and nuclear magnetic resonance for metabolomics.Progress in nuclear magnetic resonance spectroscopy · 2017Review
- New frontiers in metabolomics: from measurement to insight.F1000Research · 2017Review
- NMR Metabolomics Analysis of Parkinson's Disease.Current MetabolomicsArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Detecting a small molecular-weight compound by electrospray ionization mass spectrometry (ESI-MS) requires the compound to obtain a charge. Factors such as gas-phase proton affinities and analyte surface activity are correlated with a positive ESI-MS response, but unfortunately it is extremely challenging to predict from a chemical structure alone if a compound is likely to yield an observable molecular-ion peak in an ESI-MS spectrum. Thus, the design of a chemical library for an ESI-MS ligand-affinity screen is particularly daunting. Only 56.9% of the compounds from our FAST-NMR functional library [1] were detectable by ESI-MS. An analysis of ~1,600 molecular descriptors did not identify any correlation with a positive ESI-MS response that cannot be attributed to a skewed population distribution. Unfortunately, our results suggest that molecular descriptors are not a valuable approach for designing a chemical library for an MS-based ligand affinity screen.
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Registered trials
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