Evidence map›Paper›PMID 23991755›Full record

ArticleJournal of chemical information and modeling2013

In silico enzymatic synthesis of a 400,000 compound biochemical database for nontargeted metabolomics.

Lochana C Menikarachchi, Dennis W Hill, Mai A Hamdalla, Ion I Mandoiu, David F Grant

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Review
  7. Review
  8. Cardiovascular Metabolomics.Circulation research · 2018
    Review
  9. Article
  10. Searching molecular structure databases with tandem mass spectra using CSI:FingerID.Proceedings of the National Academy of Sciences of the United States of America · 2015
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Metabolomics in Endocrinology: The Way Forward.Indian journal of endocrinology and metabolism
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lochana C MenikarachchiDepartment of Pharmaceutical Sciences, University of Connecticut , 69 North Eagleville Road, Storrs, Connecticut 06269, United States.
Dennis W Hill
Mai A Hamdalla
Ion I Mandoiu
David F Grant

Funding

Metabolomics Tools for BiomedicineR01GM087714 · NIGMS · UNIVERSITY OF CONNECTICUT STORRS · PI GRANT, DAVID FRANKLIN · 2010 to 2018
$3.1M
NIGMS NIH HHS 1R01GM087714NIGMS NIH HHS R01 GM087714
6 · The paper itself

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

Databases, FactualAnimalsEnzymesGlycerophospholipidsHumansInternetMetabolomicsPharmaceutical PreparationsPlantsUser-Computer InterfaceEnzymesGlycerophospholipidsPharmaceutical Preparations

Identifiers

PMID23991755
PMCPMC3819714

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.