Crystal Structures of the Tetratricopeptide Repeat Domains of Kinesin Light Chains: Insight into Cargo Recognition Mechanisms
Bibliographic record
Abstract
Kinesin-1 transports various cargos along the axon by interacting with the cargos through its light chain subunit. Kinesin light chains (KLC) utilize its tetratricopeptide repeat (TPR) domain to interact with over 10 different cargos. Despite a high sequence identity between their TPR domains (87%), KLC1 and KLC2 isoforms exhibit differential binding properties towards some cargos. We determined the structures of human KLC1 and KLC2 tetratricopeptide repeat (TPR) domains using X-ray crystallography and investigated the different mechanisms by which KLCs interact with their cargos. Using isothermal titration calorimetry, we attributed the specific interaction between KLC1 and JNK-interacting protein 1 (JIP1) cargo to residue N343 in the fourth TRP repeat. Structurally, the N343 residue is adjacent to other asparagines and lysines, creating a positively charged polar patch within the groove of the TPR domain. Whereas, KLC2 with the corresponding residue S328 did not interact with JIP1. Based on these finding, we propose that N343 of KLC1 can form "a carboxylate clamp" with its neighboring asparagine to interact with JIP1, similar to that of HSP70/HSP90 organizing protein-1's (HOP1) interaction with heat shock proteins. For the binding of cargos shared by KLC1 and KLC2, we propose a different site located within the groove but not involving N343. We further propose a third binding site on KLC1 which involves a stretch of polar residues along the inter-TPR loops that may form a network of hydrogen bonds to JIP3 and JIP4. Together, these results provide structural insights into possible mechanisms of interaction between KLC TPR domains and various cargo proteins.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".