Evidence map›Paper›PMID 38745462›Full record

ArticleOpen biology2024

Automated optimization of the solubility of a hyper-stable α-amylase.

Montader Ali, Matthew Greenig, Marc Oeller, Misha Atkinson, Xing Xu, Pietro Sormanni

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Open biology, 2024. 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
–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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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.

Montader AliYusuf Hamied Department of Chemistry, University of Cambridge , Cambridge CB2 1EW, UK.ORCID 0009-0004-9022-3896
Matthew GreenigYusuf Hamied Department of Chemistry, University of Cambridge , Cambridge CB2 1EW, UK.
Marc OellerYusuf Hamied Department of Chemistry, University of Cambridge , Cambridge CB2 1EW, UK.
Misha AtkinsonYusuf Hamied Department of Chemistry, University of Cambridge , Cambridge CB2 1EW, UK.
Xing XuYusuf Hamied Department of Chemistry, University of Cambridge , Cambridge CB2 1EW, UK.
Pietro SormanniYusuf Hamied Department of Chemistry, University of Cambridge , Cambridge CB2 1EW, UK.ORCID 0000-0002-6228-2221

Funding

Royal Society URF\R1\201461
6 · The paper itself

Abstract

Most successes in computational protein engineering to date have focused on enhancing one biophysical trait, while multi-trait optimization remains a challenge. Different biophysical properties are often conflicting, as mutations that improve one tend to worsen the others. In this study, we explored the potential of an automated computational design strategy, called CamSol Combination, to optimize solubility and stability of enzymes without affecting their activity. Specifically, we focus on

Indexed as

alpha-AmylasesBacterial ProteinsEnzyme StabilityProtein EngineeringSolubilityAlgorithmsBacillus licheniformisModels, MolecularMutationalpha-AmylasesBacterial Proteinsenzyme optimizationprotein designprotein solubility

Identifiers

PMID38745462
PMCPMC11293438

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.