Evidence map›Paper›PMID 38308671›Full record

ArticleApplied biochemistry and biotechnology2024

Targeting Efficient Features of Urate Oxidase to Increase Its Solubility.

Mohammad Reza Rahbar, Navid Nezafat, Mohammad Hossein Morowvat, Amir Savardashtaki, Mohammad Bagher Ghoshoon, Kamran Mehrabani-Zeinabad, Younes Ghasemi

Abstract read
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In one paragraph

Article in Applied biochemistry and biotechnology, 2024. 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
0.2field-weighted citation impact, top 47% 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, 1 citations in OpenAlex.

  1. Article
  2. 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

7 authors at 1 institution in 1 country.

Mohammad Reza RahbarPharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Navid NezafatPharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Mohammad Hossein MorowvatPharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Amir SavardashtakiDepartment of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran.
Mohammad Bagher GhoshoonPharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.
Kamran Mehrabani-ZeinabadDepartment of Biostatistics, Faculty of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
Younes GhasemiPharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran. ghasemiy@sums.ac.ir.
Shiraz University of Medical Sciences · IR

Funding

Shiraz University of Medical Sciences 15870
6 · The paper itself

Abstract

With the demand for mass production of protein drugs, solubility has become a serious issue. Extrinsic and intrinsic factors both affect this property. A homotetrameric cofactor-free urate oxidase (UOX) is not sufficiently soluble. To engineer UOX for optimum solubility, it is important to identify the most effective factor that influences solubility. The most effective feature to target for protein engineering was determined by measuring various solubility-related factors of UOX. A large library of homologous sequences was obtained from the databases. The data was reduced to six enzymes from different organisms. On the basis of various sequence- and structure-derived elements, the most and the least soluble enzymes were defined. To determine the best protein engineering target for modification, features of the most and least soluble enzymes were compared. Metabacillus fastidiosus UOX was the most soluble enzyme, while Agrobacterium globiformis UOX was the least soluble. According to the comparison-constant method, positive surface patches caused by arginine residue distribution are appropriate targets for modification. Two Arg to Ala mutations were introduced to the least soluble enzyme to test this hypothesis. These mutations significantly enhanced the mutant's solubility. While different algorithms produced conflicting results, it was difficult to determine which proteins were most and least soluble. Solubility prediction requires multiple algorithms based on these controversies. Protein surfaces should be investigated regionally rather than globally, and both sequence and structural data should be considered. Several other biotechnological products could be engineered using the data reduction and comparison-constant methods used in this study.

Indexed as

Protein EngineeringSolubilityUrate OxidaseBacterial ProteinsMutationBacterial ProteinsUrate OxidaseArginineData reductionSolubilitySurface patchesUrate oxidase

Identifiers

PMID38308671
OpenAlexW4391514781

What OpenQuestion holds

Textmetadata
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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.