Evidence map›Paper›PMID 42738854›Full record

ReviewCells2026

Dynamic Protein Structure Paradox: An Integrative Framework for Endpoint-Conditioned Evidentiary Sufficiency in Structure-to-Function Claims.

Sarfaraz K Niazi

Abstract readReview
In one paragraph

Review in Cells, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Sarfaraz K NiaziCollege of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, WA 99202, USA.ORCID 0000-0002-0513-0336

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate coordinates for a represented protein state do not, by themselves, establish activity or any other condition-specific function. This article defines the Dynamic Protein Structure Paradox (DPSP) as the apparent conflict between structural accuracy and functional underdetermination and develops it as an integrative evidentiary assessment framework rather than a new theory or paradigm. The underlying problem has been longstanding, since structural genomics, function annotation, allostery, and disorder research each established that fold does not determine function and that function does not determine fold. DPSP consolidates those results into one endpoint-conditioned rule. Once a measurable endpoint is defined, it assesses four coupled dimensions: relevant-state completeness, context completeness, ensemble or kinetic dependence, and chemical dependence. A rubric rates each dimension as adequate, uncertain, or missing, and a materiality test determines which gaps influence the stated decision. The outcome is one of three mutually exclusive modes of utilization: geometry-led, conditional, or function-measured. The deliverable is a concise evidence statement delineating what the structure supports, which decisive variable remains unmeasured, and what corroboration is necessary. DPSP complements, rather than replaces, existing structural, ensemble, and computational approaches. The framework remains unvalidated, its thresholds are provisional, and the studies necessary to confirm or refute it are specified.

Indexed as

ProteinsHumansModels, MolecularProtein ConformationProtein FoldingStructure-Activity RelationshipProteinsAlphaFoldconformational ensembleevidence assessmentfunctional inferenceintrinsic disordermodel credibilityprotein structure predictionscoring rubricstructural genomicsstructure–function relationship

Identifiers

PMID42738854
PMCPMC13565516

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.