Evidence map›Paper›PMID 29302914›Full record

ReviewBiophysical reviews2018

Biophysical studies of protein solubility and amorphous aggregation by systematic mutational analysis and a helical polymerization model.

Yutaka Kuroda

Abstract readReview
In one paragraph

Review in Biophysical reviews, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. SoluProtMutComputational and structural biotechnology journal · 2022
    Article
  6. Review
  7. Anti-EGFR VBiomolecules · 2021
    Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. 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

1 author.

Yutaka KurodaDepartment of Biotechnology and Life Sciences, Graduate School of Engineering, Tokyo University of Agriculture and Technology, 2-24-16 Nakamachi, Koganei-shi, Tokyo, 184-8588, Japan. ykuroda@cc.tuat.ac.jp.

Funding

Japan Society for the Promotion of Science KAKENHI-21300110
6 · The paper itself

Abstract

At concentrations above solubility, a protein aggregates, most often into amorphous aggregates, and loses its function. However, unlike amyloidogenic aggregates, which are β-sheeted fibrillar aggregates often related to neurodegenerative diseases, amorphous aggregates, where proteins aggregate/oligomerize without forming specific high-order structures, are rarely the focus of biophysical studies. Hence, protein solubility with respect to amorphous aggregation remains to be fully characterized from a biophysical viewpoint. Here, I briefly describe the structural nature of proteins in amorphous aggregates before discussing systematic mutational analyses that aim to rationalize the contribution of individual amino acids to the solubility of a protein. The discussion is expected to demonstrate that protein solubility, and, accordingly, amorphous aggregation, can be understood using thermodynamic and biophysical rationales similar to those used in the study of protein stability or, more recently, amyloidogenesis. Finally, I will argue that the mathematical formalism of the helical polymerization model (HPM) proposed by Oosawa, Kasai, and Asakura's group can be readily adapted to provide a thermodynamic description of a system containing amorphous aggregates and soluble particles. The HPM and HPM-derived models imply the presence of nuclei or seeds for amorphous aggregates, similar to those hypothesized in crystallogenesis and amyloidogenesis.

Indexed as

Amorphous aggregationHelical polymerization model (HPM)Mutational analysisPrecipitationSolubilityThermodynamics analysis

Identifiers

PMID29302914
PMCPMC5899702

What OpenQuestion holds

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Registered trials

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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.