Evidence map›Paper›PMID 31494210›Full record

ReviewBiotechnology advances2019

Inverse pharmacology: Approaches and tools for introducing druggability into engineered proteins.

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

Open access · hybridAbstract readReview
In one paragraph

Review in Biotechnology advances, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.1field-weighted citation impact, top 52% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
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 3 institutions in 2 countries.

Jamie A DaviesDeanery of Biomedical Sciences, University of Edinburgh, Hugh Robson Building, George Square, Edinburgh EH8 9XB, UK. Electronic address: jamie.davies@ed.ac.uk.
Sam IrelandBiomolecular Structure & Modelling Unit, Institute of Structural and Molecular Biology, Division of Biosciences, University College London, London WC1E 6BT, UK.
Simon HardingDeanery of Biomedical Sciences, University of Edinburgh, Hugh Robson Building, George Square, Edinburgh EH8 9XB, UK.
Joanna L SharmanDeanery of Biomedical Sciences, University of Edinburgh, Hugh Robson Building, George Square, Edinburgh EH8 9XB, UK; Novo Nordisk Research Centre Oxford, Novo Nordisk Ltd, Innovation Building, Old Road Campus, Roosevelt Drive, Oxford OX3 7FZ, UK.
Christopher SouthanTW2Informatics, Göteborg 41266, Sweden.
Alazne Dominguez-MonederoDeanery of Biomedical Sciences, University of Edinburgh, Hugh Robson Building, George Square, Edinburgh EH8 9XB, UK.
University of Edinburgh · GBInstitute of Structural and Molecular Biology · GBNovo Nordisk (Finland) · FI

Funding

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

Abstract

A major feature of twenty-first century medical research is the development of therapeutic strategies that use 'biologics' (large molecules, usually engineered proteins) and living cells instead of, or as well as, the small molecules that were the basis of pharmacology in earlier eras. The high power of these techniques can bring correspondingly high risk, and therefore the need for the potential for external control. One way of exerting control on therapeutic proteins is to make them responsive to small molecules; in a clinical context, these small molecules themselves have to be safe. Conventional pharmacology has resulted in thousands of small molecules licensed for use in humans, and detailed structural data on their binding to their protein targets. In principle, these data can be used to facilitate the engineering of drug-responsive modules, taken from natural proteins, into synthetic proteins. This has been done for some years (for example, Cre-ERT2) but usually in a painstaking manner. Recently, we have developed the bioinformatic tool SynPharm to facilitate the design of drug-responsive proteins. In this review, we outline the history of the field, the design and use of the Synpharm tool, and describe our own experiences in engineering druggability into the Cpf1 effector of CRISPR gene editing.

Indexed as

Protein EngineeringBacterial ProteinsCRISPR-Cas SystemsEndonucleasesGene EditingHumansBacterial ProteinsEndonucleasesCpf1CRISPRDrugGene editingPharmaceuticalProtein engineeringStructure-functionSynthetic biology

Identifiers

PMID31494210
PMCPMC6891246
OpenAlexW2971552627

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.