Evidence map›Paper›PMID 42146451›Full record

ArticlebioRxiv : the preprint server for biology2026

Walking the Tightrope: Balancing Opposing Cooperativities as an Operating Principle in Dynein Assembly.

Douglas R Walker, Lisa Otten, Mukhtar O Idris, Brittany Lasher, Daniel M Zuckerman, Elisar J Barbar

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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

5 · Who and what money

Authors and funding

6 authors.

Douglas R WalkerDept. of Biochemistry and Biophysics, Oregon State University, Corvallis, OR, US.ORCID 0000-0002-9323-3158
Lisa OttenDept. of Biomedical Engineering, School of Medicine, Oregon Health and Science University, Portland, OR, US.ORCID 0000-0003-2561-575X
Mukhtar O IdrisDept. of Biochemistry and Biophysics, Oregon State University, Corvallis, OR, US.
Brittany LasherDept. of Biochemistry and Biophysics, Oregon State University, Corvallis, OR, US.
Daniel M ZuckermanDept. of Biomedical Engineering, School of Medicine, Oregon Health and Science University, Portland, OR, US.ORCID 0000-0001-7662-2031
Elisar J BarbarDept. of Biochemistry and Biophysics, Oregon State University, Corvallis, OR, US.

Funding

High Performance Computing and Machine Learning Infrastructure for Oregon Life SciencesS10OD034224 · OD · OREGON HEALTH & SCIENCE UNIVERSITY · PI ELLROTT, KYLE · 2023 to 2023
$2.0M
Multiscale characterization of a unique class of duplex, multivalent IDP systems-- Administrative Supplement to Support Undergraduate Summer Research ExperiencesR01GM141733 · NIGMS · OREGON HEALTH & SCIENCE UNIVERSITY · PI BARBAR, ELISAR J, ZUCKERMAN, DANIEL M · 2021 to 2024
$1.9M
NIGMS NIH HHS R01 GM141733NIH HHS S10 OD034224
6 · The paper itself

Abstract

The central region of the cytoplasmic dynein complex, comprising the intermediate chain (IC) and two light chains (LC8 and Tctex1), has eluded thorough quantitative characterization due to its participation in a highly coupled seven-state binding network. Although isothermal titration calorimetry (ITC) is the gold standard for measuring binding thermodynamics, conventional analyses are limited to simple interaction schemes because individual isotherms contain insufficient information to resolve complex reaction networks. Here, we overcome this limitation by combining extensive experimental sampling with hierarchical Bayesian inference. We collected 39 ITC isotherms spanning eight experiment types and developed a global Bayesian framework integrating multiple datasets while explicitly accounting for concentration uncertainty. Using this approach, we fit the complete dataset to a mechanistic seven-state model, estimating 190 parameters, including 12 thermodynamic parameters while marginalizing over 178 nuisance parameters. Remarkably, this strategy yields 95% confidence intervals for thermodynamic values as narrow as 0.05 kcal/mol and back-propagates to nanomolar precision in effective concentrations, even when experimental concentrations are in the hundreds of micromolar. The resulting thermodynamic landscape enables predictive modelling of assembly populations under different scenarios, including binding states inaccessible to standard ITC analyses. These results reveal previously unrecognized binding states that may play key roles in dynein cargo attachment and release. More broadly, this work reveals a form of "multi-cooperativity" governing dynein assembly and demonstrates how intensive experimentation coupled with modern statistical tools can resolve complex molecular systems beyond the reach of traditional biophysical techniques.

Indexed as

Bayesian InferenceBiological SciencesBiophysics and Computational BiologyCooperativityDyneinMultivalency

Identifiers

PMID42146451
PMCPMC13174313

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LicenceCC BY-NC-ND
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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.