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Record W2148920724 · doi:10.1105/tpc.113.113183

Comparing the Calcium Binding Abilities of Two Soybean Calmodulins: Towards Understanding the Divergent Nature of Plant Calmodulins

2013· article· en· W2148920724 on OpenAlexaff
Jessica L. Gifford, Mostafa Jamshidiha, Jianhua Mo, H. Ishida, H. J. Vogel

Bibliographic record

VenueThe Plant Cell · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Micronutrient Interactions and Effects
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsCalmodulinBiologyCalciumGene isoformBiochemistryBiophysicsDissociation constantReceptorChemistryGeneEnzyme

Abstract

fetched live from OpenAlex

The discovery that plants contain multiple calmodulin (CaM) isoforms of variable sequence identity to animal CaM suggested an additional level of sophistication in the intracellular role of calcium regulation in plants. Past research has focused on the ability of conserved or divergent plant CaM isoforms to activate both mammalian and plant protein targets. At present, however, not much is known about how these isoforms respond to the signal of an increased cytosolic calcium concentration. Here, using isothermal titration calorimetry and NMR spectroscopy, we investigated the calcium binding properties of a conserved (CaM1) and a divergent (CaM4) CaM isoform from soybean (Glycine max). Both isoforms bind calcium with a semisequential pathway that favors the calcium binding EF-hands of the C-terminal lobe over those of the N-terminal lobe. From the measured dissociation constants, CaM4 binds calcium with a threefold greater affinity than CaM1 (K(d,Ca,mean) of 5.0 versus 14.9 μM) but has a significantly reduced selectivity against the chemically similar magnesium cation that binds preferentially to EF-hand I of both isoforms. The implications of a potential magnesium/calcium competition on the activation of CaM1 and CaM4 are discussed in context with their ability to respond to stimulus-specific calcium signatures and their known physiological roles.

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)0.000
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 score0.263
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.059
GPT teacher head0.234
Teacher spread0.175 · 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

Citations33
Published2013
Admission routes1
Has abstractyes

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