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Record W4253022805 · doi:10.21203/rs.3.rs-59611/v1

Conformation and Dynamics of the Kinase Domain Drive Subcellular Location and Activation of LRRK2.

2020· preprint· en· W4253022805 on OpenAlexfundno aff
Sven H. Schmidt, Jui‐Hung Weng, Phillip C. Aoto, Daniela Boassa, Steven Silletti, Sebastian Mathea, Junru Hu, Maximilian Wallbott, Elizabeth A. Komives, Stefan Knapp, Friedrich W. Herberg, Susan S. Taylor

Bibliographic record

VenueResearch Square · 2020
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMelanoma and MAPK Pathways
Canadian institutionsnot available
FundersNovartis PharmaNational Cancer InstituteNational Institutes of HealthMinistero dello Sviluppo EconomicoFundação de Amparo à Pesquisa do Estado de São PauloDeutsche ForschungsgemeinschaftMerck KGaAOntario Ministry of Economic Development and InnovationGenome Canada
KeywordsDynamics (music)Domain (mathematical analysis)LRRK2Subcellular localizationCell biologyKinaseComputer scienceChemistryPhysicsBiochemistryBiologyMathematicsCytoplasmGene

Abstract

fetched live from OpenAlex

Abstract Background: Leucine-Rich Repeat Kinase 2 (LRRK2) is a complex multi-domain protein where LRRK2-mutations are associated with Parkinson´s Disease (PD). To explore how pathogenic PD-mutations hijack the finely tuned activation process of LRRK2, we here used a multi-tiered approach. Methods: First, the spatial and temporal distribution of full-length LRRK2 was investigated by a real-time cell-based assay in the presence and absence of LRRK2-kinase inhibitors. In a 2nd layer we explored the consequences of PD mutations as well as removal of the N-terminal domains employing a construct containing the ROC, Cor, Kinase and WD40 domains (LRRK2RCKW). We focused on the biochemical characterization of LRRK2RCKW variants based on kinase assays using Rab8a or LRRKtide as substrates. Next, we used hydrogen-deuterium exchange mass spectrometry (HDX-MS) to map the solvent accessible regions of LRRK2RCKW in the presence and absence of the LRRK2 inhibitor MLi-2. Finally, Molecular Dynamics simulations on the kinase domain were applied to elucidate differences in breathing dynamics between wild type and mutants of the DYGψ motif. Results: Our cellular approaches revealed that the kinase inhibitors MLi-2 and rebastinib both freeze the kinase domain in a stable conformation, however, only MLi-2 resembles an active conformation and induces filament formation. LRRK2RCKW showed, regardless of the mutation it was combined with, filament formation, indicating a shielding function of the N-terminal domains. This shielding function is impaired for pathogenic mutations in full length LRRK2. LRRK2RCKW retained kinase activity similar to full-length LRRK2. HDX-MS provided a comprehensive allosteric portrait of the kinase domain and revealed how MLi-2 binding is sensed by the entire protein. Molecular Dynamics simulations suggest that, while all domains contribute to regulating kinase activity and spatial distribution, it is the highly dynamic kinase domain, driven by the DYGψ motif, that coordinates the overall domain crosstalk and serves as a regulatory hub for the intrinsic regulation of LRRK2.Conclusion: These studies confirm our hypothesis that the N-terminal scaffolding domains shield the catalytic domains in an inactive state. PD mutations, MLi-2, or Rab GTPases can all unleash the catalytic domains while the active kinase conformation, but not kinase activity, is essential for docking onto microtubules.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.305
Teacher spread0.279 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2020
Admission routes1
Has abstractyes

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