Biology subjects

Walker, D. R.

Publications and source records attributed to Walker, D. R..

4 recordsLinked to original sources

bioRxiv2025

Weak Motifs, Strong Complex: KANK1 Uses Cooperative Multivalency with the Hub-Protein LC8 to Bridge Cytoskeletal Complexes

The cortically anchored adaptor KANK1 organizes microtubules at focal adhesions through a long, intrinsically disordered linker (L2), yet how this linker spans the [~]35-50 nm membrane-microtubule gap is unclear. Here, we combine in-cell, biochemical, and biophysical assays, predictions of motif interaction and multivalent assembly using AlphaFold, and structural analysis by electron microscopy to show that the hub protein LC8, which binds more than 100 clients, converts the intrinsically disordered 600 amino acid L2 into an elongated, multivalent, rod-like assembly. In contrast, isolated motif peptides fail to bind LC8 at physiologically relevant concentrations, indicating that strong complex formation arises from cooperativity among multiple weak sites. These results establish LC8 as a molecular switch that rigidifies and extends KANK1 L2 via distributed weak motifs and short linkers. This interaction produces compositionally homogeneous yet conformationally adaptable rods, long enough to bridge the membrane-microtubule gap, resolving the paradox. This work expands the LC8 binding repertoire, reveals design principles for multivalent assembly, and suggests a generalizable strategy for tuning length, rigidity, and flexibility in large protein architectures.

biophysics↗

bioRxiv2025

Negative Cooperativity in a Polybivalent Complex Allows the Prevalence of a Partial Bound State.

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. Significance StatementLarge, complex mechanistic processes have remained difficult to fully characterize, which limits interpretability of the underlying biology. We utilize a large dataset of 39 complementary experiments to fully characterize a seven-state system using Bayesian inference. This process achieves impressively precise fits with 0.05 kcal/mol width confidence intervals. The high precision enables assessment of simultaneous positive and negative cooperativity in the assembly of the dynein intermediate chain with its light-chain partners. Simulation of state populations suggests that this balancing cooperativity is finely tuned to allow access to a half-bound state which has been previously inaccessible quantitatively. Our approach is broadly applicable and supports an emerging principle of molecular regulation--negative cooperativity as a strategy for tuning responsiveness and dynamic control.

biophysics↗

bioRxiv2025

Improving parameter inference by resolving Bayesian prior ambiguity via multi-dataset analysis: Application to isothermal titration calorimetry

Isothermal titration calorimetry (ITC) is a powerful technique for probing biomolecular interactions. However, accurate determination of binding parameters--such as enthalpy and free energy--as well as associated uncertainties can be hindered by noise and concentration variability. Notably, the mathematical ambiguity surrounding analyte concentrations in standard binding models intrinsically limits the precision with which binding parameters, particularly binding enthalpies, can be determined. Here, we present a Bayesian pipeline that resolves this ambiguity by combining two key strategies: simultaneous analysis of multiple ITC datasets and a hierarchical Bayesian treatment of analyte concentration priors. This dual approach not only lifts the degeneracy inherent in single-dataset studies but also removes an ambiguity typically present in Bayesian analysis by self-consistently refining concentration estimates, ensuring optimal joint inference of binding parameters and concentrations. Using modern Monte Carlo techniques enables our pipeline to provide robust posterior sampling for more than 10 datasets and 40 total parameters. We validate the approach with synthetic ITC datasets for single- and multi-site binding models and apply it to experimental data, including 14 datasets for 1:1 binding of Mg(II) to the chelator EDTA and multiple datasets of the hub protein LC8 with diverse binding partners. This work serves as a foundation for improving the precision of binding constants using multiple ITC datasets, while providing a systematic framework for assessing the reliability of experimental concentration estimates, paving the way for more accurate biomolecular interaction studies.

biophysics↗

bioRxiv2024

Heterotrimeric Collagen Helix with High Specificity of Assembly Results in a Rapid Rate of Folding

The most abundant natural collagens form heterotrimeric triple helices. Synthetic mimics of collagen heterotrimers have been found to fold slowly, even compared to the already slow rates of homotrimeric helices. These prolonged folding rates are not understood and have not been studied. This work compares three heterotrimeric collagen mimics stabilities, specificities and folding rates. One of these was designed through a computational-assisted approach, resulting in a well-controlled composition and register, in addition to providing increased amino acid diversity and excellent specificity. The crystal structure of this heterotrimer elucidates the composition, register and geometry of pairwise cation-{pi} and axial and lateral salt bridges. Complementary experimental methods of circular dichroism and NMR suggest the folding paradigm is frustrated by unproductive, competing heterotrimer species and these species must completely unwind to the monomeric state before refolding into the thermodynamically favored assembly. This collagen heterotrimer, which displays the best reported thermal specificity, was also found to fold much faster (hours vs days) than comparable, well-designed systems. The heterotrimeric collagen folding rate was observed to be both concentration and temperature-independent, suggesting a complex, multi-step mechanism. These results suggest heterotrimer folding kinetics are dominated by frustration of the energy landscape caused by competing triple helices.

biophysics↗