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Record W4396927795 · doi:10.1002/pro.5021

Protein purification via consecutive histidine–polyphosphate interaction

2024· article· en· W4396927795 on OpenAlexafffund
Zihao Zhou, Jin Jin, Xu Deng, Zongchao Jia

Bibliographic record

VenueProtein Science · 2024
Typearticle
Languageen
FieldMedicine
TopicCoagulation, Bradykinin, Polyphosphates, and Angioedema
Canadian institutionsQueen's University
FundersDistinguished Young Scholar Foundation of Hunan ProvinceNatural Science Foundation for Distinguished Young Scholars of Hunan ProvinceCystic Fibrosis Canada
KeywordsNitrilotriacetic acidHistidinePolyphosphateChemistryTandem affinity purificationProtein purificationAffinity chromatographyBiochemistryChromatographyChelationRecombinant DNACombinatorial chemistryFLAG-tagAmino acidOrganic chemistryFusion proteinEnzyme

Abstract

fetched live from OpenAlex

While nickel-nitrilotriacetic acid (Ni-NTA) has greatly advanced recombinant protein purification, its limitations, including nonspecific binding and partial purification for certain proteins, highlight the necessity for additional purification such as size exclusion and ion exchange chromatography. However, specialized equipment such as FPLC is typically needed but not often available in many laboratories. Here, we show a novel method utilizing polyphosphate (polyP) for purifying proteins with histidine repeats via non-covalent interactions. Our study demonstrates that immobilized polyP efficiently binds to histidine-tagged proteins across a pH range of 5.5-7.5, maintaining binding efficacy even in the presence of reducing agent DTT and chelating agent EDTA. We carried out experiments of purifying various proteins from cell lysates and fractions post-Ni-NTA. Our results demonstrate that polyP resin is capable of further purification post-Ni-NTA without the need for specialized equipment and without compromising protein activity. This cost-effective and convenient method offers a viable approach as a complementary approach to Ni-NTA.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.306
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueProtein ScienceSame topicCoagulation, Bradykinin, Polyphosphates, and AngioedemaFrench-language works237,207