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Record W2725648605 · doi:10.1002/pro.3218

The structure of <i>Plasmodium falciparum</i> 3D7_0606800 reveals a bi‐lobed architecture that supports re‐annotation as a Venus Flytrap protein

2017· article· en· W2725648605 on OpenAlexafffund
Michelle Parker, Raghavendran Ramaswamy, Kyle Van Gordon, Cameron J. Powell, Jürgen Bosch, Martin J. Boulanger

Bibliographic record

VenueProtein Science · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsUniversity of Victoria
FundersCanadian Institutes of Health Research
KeywordsPlasmodium falciparumVenusComputational biologyBiologyBotanyCell biologyPhysicsChemistryAstrobiologyMalariaImmunology

Abstract

fetched live from OpenAlex

Plasmodium falciparum, the causative agent of malaria, employs a diverse array of surface displayed proteins to promote dissemination and establish infection in the human host. Of these, Pf3D7_0606800 is highly immunogenic and has been designated a potential top 10 candidate for inclusion in a multicomponent malarial vaccine. The role of Pf3D7_0606800 in parasite biology, however, is unknown and its characterization has been complicated by a lack of sequence identity with proteins of known structure or function. Towards elucidating Pf3D7_0606800 function, we determined its structure to a resolution of 2.35 Å using selenium single wavelength anomalous dispersion. A bi-lobed architecture displays the core structural hallmarks of Venus Flytrap (VFT) proteins prompting us to re-annotate Pf3D7_0606800 as PfVFT1. Structural analysis further revealed an extended inter-lobe groove that, when interrogated by molecular docking, appears well suited to bind peptide-based ligands. Collectively, our structural characterization of the highly antigenic P. falciparum surface protein PfVFT1 provides intriguing functional insight and establishes a structural template that could prove valuable for malaria vaccine engineering studies.

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)0.001
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 score0.021
Threshold uncertainty score0.847

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.268
Teacher spread0.254 · 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

Citations3
Published2017
Admission routes2
Has abstractyes

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