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Record W1998213944 · doi:10.1021/ja060046d

Mapping Allostery through Equilibrium Perturbation NMR Spectroscopy

2006· article· en· W1998213944 on OpenAlexaff
Rahul Das, Mona Abu‐Abed, Giuseppe Melacini

Bibliographic record

VenueJournal of the American Chemical Society · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNMR spectroscopy and applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsChemistryNuclear magnetic resonance spectroscopyPerturbation (astronomy)SpectroscopyNuclear magnetic resonanceComputational chemistryStereochemistryQuantum mechanicsPhysics

Abstract

fetched live from OpenAlex

The understanding of allostery relies on the comparative analysis of macromolecules in their free and bound states. However, the direct free versus bound comparison is often challenging due to the instability of one of the two forms. This problem is effectively circumvented by using minor free/bound equilibrium perturbations which are tolerated without compromising sample stability. The subtle equilibrium perturbations are still able to reveal significant apo/holo differences if monitored by NMR experiments that are sensitive to minor populations within dynamic equilibria, such as NMR relaxation dispersion (NMRD) and hydrogen exchange (H/D and H/H) rates. These measurements are complementary to each other as they unmask how a ligand affects both the stable and the excited states of the free energy landscape for its protein receptor. The proposed equilibrium perturbation approach therefore significantly expands the scope of applicability of NMRD and hydrogen exchange experiments to the investigation of ligand-protein interactions, in general, unveiling allosteric "hot spot" maps for systems that have been traditionally elusive to direct free/bound comparisons.

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 score0.047
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.009
GPT teacher head0.286
Teacher spread0.278 · 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

Citations32
Published2006
Admission routes1
Has abstractyes

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