ArticleJournal of chemical information and modeling2013
In silico enzymatic synthesis of a 400,000 compound biochemical database for nontargeted metabolomics.
Article in Journal of chemical information and modeling, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Article
- Exposome-Scale Investigation of Cl-/Br-Containing Chemicals Using High-Resolution Mass Spectrometry, Multistage Machine Learning, and Cloud Computing.Analytical chemistry · 2025Article
- Knowledge-based in silico fragmentation and annotation of mass spectra for natural products with MassKG.Computational and structural biotechnology journal · 2024Article
- Seeing the forest for the trees: Retrieving plant secondary biochemical pathways from metabolome networks.Computational and structural biotechnology journal · 2021Review
- Advancing internal exposure and physiologically-based toxicokinetic modeling for 21st-century risk assessments.Journal of exposure science & environmental epidemiology · 2019Review
- Integrating tools for non-targeted analysis research and chemical safety evaluations at the US EPA.Journal of exposure science & environmental epidemiology · 2018Review
- Identification of small molecules using accurate mass MS/MS search.Mass spectrometry reviews · 2018Review
- Cardiovascular Metabolomics.Circulation research · 2018Review
- Integrating ion mobility spectrometry into mass spectrometry-based exposome measurements: what can it add and how far can it go?Bioanalysis · 2017Article
- Searching molecular structure databases with tandem mass spectra using CSI:FingerID.Proceedings of the National Academy of Sciences of the United States of America · 2015Article
- Efficient searching and annotation of metabolic networks using chemical similarity.Bioinformatics (Oxford, England) · 2015Article
- Metabolic pathway predictions for metabolomics: a molecular structure matching approach.Journal of chemical information and modeling · 2015Article
- Analysis of phenolic and cyclic compounds in plants using derivatization techniques in combination with GC-MS-based metabolite profiling.Molecules (Basel, Switzerland) · 2015Article
- MINEs: open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics.Journal of cheminformatics · 2015Article
- Metabolomics in Endocrinology: The Way Forward.Indian journal of endocrinology and metabolismReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Current methods of structure identification in mass-spectrometry-based nontargeted metabolomics rely on matching experimentally determined features of an unknown compound to those of candidate compounds contained in biochemical databases. A major limitation of this approach is the relatively small number of compounds currently included in these databases. If the correct structure is not present in a database, it cannot be identified, and if it cannot be identified, it cannot be included in a database. Thus, there is an urgent need to augment metabolomics databases with rationally designed biochemical structures using alternative means. Here we present the In Vivo/In Silico Metabolites Database (IIMDB), a database of in silico enzymatically synthesized metabolites, to partially address this problem. The database, which is available at http://metabolomics.pharm.uconn.edu/iimdb/, includes ~23,000 known compounds (mammalian metabolites, drugs, secondary plant metabolites, and glycerophospholipids) collected from existing biochemical databases plus more than 400,000 computationally generated human phase-I and phase-II metabolites of these known compounds. IIMDB features a user-friendly web interface and a programmer-friendly RESTful web service. Ninety-five percent of the computationally generated metabolites in IIMDB were not found in any existing database. However, 21,640 were identical to compounds already listed in PubChem, HMDB, KEGG, or HumanCyc. Furthermore, the vast majority of these in silico metabolites were scored as biological using BioSM, a software program that identifies biochemical structures in chemical structure space. These results suggest that in silico biochemical synthesis represents a viable approach for significantly augmenting biochemical databases for nontargeted metabolomics applications.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.