Evidence map›Paper›PMID 30087931›Full record

ArticleACS omega2018

SynPharm: A Guide to PHARMACOLOGY Database Tool for Designing Drug Control into Engineered Proteins.

Sam M Ireland, Christopher Southan, Alazne Dominguez-Monedero, Simon D Harding, Joanna L Sharman, Jamie A Davies

Open access · goldAbstract read
In one paragraph

Article in ACS omega, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 43% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

6 authors at 1 institution in 1 country.

Sam M IrelandCentre for Discovery Brain Sciences, Deanery for Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, U.K.
Christopher SouthanCentre for Discovery Brain Sciences, Deanery for Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, U.K.
Alazne Dominguez-MonederoCentre for Discovery Brain Sciences, Deanery for Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, U.K.
Simon D HardingCentre for Discovery Brain Sciences, Deanery for Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, U.K.
Joanna L SharmanCentre for Discovery Brain Sciences, Deanery for Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, U.K.
Jamie A DaviesCentre for Discovery Brain Sciences, Deanery for Biomedical Sciences, University of Edinburgh, Edinburgh EH8 9XD, U.K.
MRC Centre for Regenerative Medicine · GB

Funding

Biotechnology and Biological Sciences Research Council BB/M018040/1Wellcome Trust
6 · The paper itself

Abstract

A major challenge in synthetic biology, particularly for mammalian systems, is the inclusion of adequate external control for the synthetic system activities. Control at the transcriptional level can be achieved by adaptation of bacterial repressor-operator systems (e.g., TetR), but altering the activity of a protein by controlling transcription is indirect and for longer half-life mRNAs, decreasing activity this way can be inconveniently slow. Where possible, direct modulation of protein activity by soluble ligands has many advantages, including rapid action. Decades of drug discovery and pharmacological research have uncovered detailed information on the interactions between large numbers of small molecules and their primary protein targets (as well as off-target secondary interactions), many of which have been well studied in mammals, including humans. In principle, this accumulated knowledge would be a powerful resource for synthetic biology. Here, we present SynPharm, a tool that draws together information from the pharmacological database GtoPdb and the structural database, PDB, to help synthetic biologists identify ligand-binding domains of natural proteins. Consequently, as sequence cassettes, these may be suitable for building into engineered proteins to confer small-molecule modulation on them. The tool has ancillary utilities which include assessing contact changes among different ligands in the same protein, predicting possible effects of genetic variants on binding residues, and insights into ligand cross-reactivity among species.

Identifiers

PMID30087931
PMCPMC6068591
OpenAlexW2883626007

What OpenQuestion holds

Textmetadata
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.