Evidence map›Paper›PMID 25659145›Full record

ArticlePloS one2015

UFSRAT: Ultra-fast Shape Recognition with Atom Types--the discovery of novel bioactive small molecular scaffolds for FKBP12 and 11βHSD1.

Steven Shave, Elizabeth A Blackburn, Jillian Adie, Douglas R Houston, Manfred Auer, Scott P Webster, Paul Taylor, Malcolm D Walkinshaw

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.9field-weighted citation impact, top 9% of its field
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

9 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
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  4. Article
  5. Article
  6. Review
  7. Virtual screening applications in short-chain dehydrogenase/reductase research.The Journal of steroid biochemistry and molecular biology · 2017
    Review
  8. Article
  9. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Steven ShaveCentre for Translational and Chemical Biology, University of Edinburgh, Edinburgh, United Kingdom.
Elizabeth A BlackburnCentre for Translational and Chemical Biology, University of Edinburgh, Edinburgh, United Kingdom.
Jillian AdieCentre for Translational and Chemical Biology, University of Edinburgh, Edinburgh, United Kingdom.
Douglas R HoustonCentre for Translational and Chemical Biology, University of Edinburgh, Edinburgh, United Kingdom.
Manfred AuerCentre for Translational and Chemical Biology, University of Edinburgh, Edinburgh, United Kingdom.
Scott P WebsterUniversity/BHF Centre for Cardiovascular Science, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom.
Paul TaylorCentre for Translational and Chemical Biology, University of Edinburgh, Edinburgh, United Kingdom.
Malcolm D WalkinshawCentre for Translational and Chemical Biology, University of Edinburgh, Edinburgh, United Kingdom.
University of Edinburgh · GB

Funding

Biotechnology and Biological Sciences Research CouncilMedical Research Council MC_G0802522Wellcome Trust 095831Wellcome Trust 101527/Z/13/Z
6 · The paper itself

Abstract

motivationUsing molecular similarity to discover bioactive small molecules with novel chemical scaffolds can be computationally demanding. We describe Ultra-fast Shape Recognition with Atom Types (UFSRAT), an efficient algorithm that considers both the 3D distribution (shape) and electrostatics of atoms to score and retrieve molecules capable of making similar interactions to those of the supplied query.

resultsComputational optimization and pre-calculation of molecular descriptors enables a query molecule to be run against a database containing 3.8 million molecules and results returned in under 10 seconds on modest hardware. UFSRAT has been used in pipelines to identify bioactive molecules for two clinically relevant drug targets; FK506-Binding Protein 12 and 11β-hydroxysteroid dehydrogenase type 1. In the case of FK506-Binding Protein 12, UFSRAT was used as the first step in a structure-based virtual screening pipeline, yielding many actives, of which the most active shows a KD, app of 281 µM and contains a substructure present in the query compound. Success was also achieved running solely the UFSRAT technique to identify new actives for 11β-hydroxysteroid dehydrogenase type 1, for which the most active displays an IC50 of 67 nM in a cell based assay and contains a substructure radically different to the query. This demonstrates the valuable ability of the UFSRAT algorithm to perform scaffold hops. AVAILABILITY AND IMPLEMENTATION: A web-based implementation of the algorithm is freely available at http://opus.bch.ed.ac.uk/ufsrat/.

Indexed as

11-beta-Hydroxysteroid Dehydrogenase Type 1AlgorithmsComputer SimulationEnzyme InhibitorsMolecular Docking SimulationTacrolimus Binding Protein 1AHEK293 CellsHumans11-beta-Hydroxysteroid Dehydrogenase Type 1Enzyme InhibitorsTacrolimus Binding Protein 1A

Identifiers

PMID25659145
PMCPMC4319890
OpenAlexW2046944485

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.