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Uncovering the molecular basis of kinase activity and substrate recognition with phospho-PCA
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Uncovering the molecular basis of kinase activity and substrate recognition with phospho-PCA

Changhua Yu, Edward Pao, David Van Valen
November 2025
 ·
bioRxiv
 ·
DOI 
10.1101/2025.11.07.687244
94
%
Reproducible
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It ranks in the top 1% of preprints assessed in Molecular Biology this quarter.
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Why this is interesting

By coupling phosphorylation to a yeast growth sensor, this work makes deep mechanistic kinase variant mapping possible at scale, revealing allosteric determinants of substrate specificity and opening systematic profiling across the human kinome.

QED claims analysis

Summary

Comprehensive deep mutational scanning of three Src family kinases using phospho-PCA coupled with hierarchical Bayesian modeling reveals that kinase domain variants impact substrate specificity primarily through long-range allosteric networks rather than direct binding interactions, with most specificity-determining residues located distal to the substrate interface and operating through diverse mechanisms including electrostatic remodeling, conformational biasing, and metastable state stabilization.

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Main Claim 1 –

Phospho-PCA Quantifies Kinase–Substrate Interactions via Yeast Growth

Supporting evidence

  • Phospho-PCA Recapitulates Substrate Preferences Across Kinase Classes
Main Claim 2 –

Large-Scale Functional Mapping of 15,000 Kinase Variants

Supporting evidence

  • Structural Context Governs Mutation Effects on SFK Folding Stability
  • Functional Scores Distinguish Benign from Pathogenic Clinical Variants
Main Claim 3 –

Bayesian Decomposition Separates Abundance, Activity, and Specificity Effects

Supporting evidence

  • Decomposed Activity Scores Reveal Catalytic Control Residues and GOF Variants
  • ProteinMPNN Predicts Conformation-Biased Variants with High Precision
  • V195E Stabilizes Active Kinase Conformations via Coevolving Salt Bridge
Main Claim 4 –

Distal Residues Control Substrate Specificity via Allostery

Supporting evidence

  • Lck P203R Switches Substrate Preference via HF-HG Allosteric Network
  • Lck E113H Stabilizes Nonproductive Binding by Disrupting Activation Loop
  • Lck Q65D Switches Specificity via Electrostatics and Allosteric Remodeling

Abstract

Protein kinases relay information to various cellular processes, and their dysregulation underlies numerous human diseases. Despite their importance, our understanding of how kinase domains and their variants impact protein stability, catalytic activity, and substrate recognition is incomplete. In this work, we develop the phosphorylation protein complementation assay (phospho-PCA), which enables quantitative measurements of kinase-substrate interactions by coupling them to the growth of bud-ding yeast, thereby enabling deep mutational scanning of kinase domains. When combined with deep mutational scans targeting folding stability and Bayesian modeling, phospho-PCA can disentangle the relative impact of mutations on kinase domain stability, catalytic activity, and substrate specificity. We demonstrate the accuracy and breadth of phospho-PCA, showing its applicability to both tyrosine and serine/threonine kinase domains. We then apply our method to three closely related protein kinases with distinct substrate preferences, evaluating over 15,000 kinase variants against a panel of three substrates for both catalytic activity and substrate specificity. The resulting dataset constitutes the largest and most detailed variant-to-function map assembled for this enzyme family to date, revealing numerous mutations that alter kinase activity and substrate specificity. Physics-based modeling reveals how these mutations operate through diverse mechanisms, including long-range allosteric communication, to alter both activity and substrate specificity. Given its scalability, we believe phospho-PCA can measure the functional impact of variants across the entire human kinome.

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