Summary Dynamic instability, the stochastic switching between growth and shrinkage, is essential for microtubule function. This behavior is driven by GTP hydrolysis in the microtubule lattice, and is inhibited by anticancer agents like Taxol. We provide new insight into the mechanism of dynamic instability, based on high-resolution cryo-EM structures (4.7–5.6 Å) of dynamic microtubules and microtubules stabilized by GMPCPP or Taxol. We infer that hydrolysis leads to a compaction around the E-site nucleotide at longitudinal interfaces, as well as movement of the α–tubulin intermediate domain and H7 helix. Displacement of the C-terminal helices in both α– and β–tubulin subunits suggests an effect on interactions with binding partners that contact this region. Taxol inhibits most of these conformational changes, allosterically inducing a GMPCPP-like state. Lateral interactions are similar in all conditions we examined, suggesting that microtubule lattice stability is primarily modulated at longitudinal interfaces.

The prediction of changes in protein stability and structure resulting from single amino acid substitutions is both a fundamental test of macromolecular modeling methodology and an important current problem as high throughput sequencing reveals sequence polymorphisms at an increasing rate. In principle, given the structure of a wild-type protein and a point mutation whose effects are to be predicted, an accurate method should recapitulate both the structural changes and the change in the folding-free energy. Here, we explore the performance of protocols which sample an increasing diversity of conformations. We find that surprisingly similar performances in predicting changes in stability are achieved using protocols that involve very different amounts of conformational sampling, provided that the resolution of the force field is matched to the resolution of the sampling method. Methods involving backbone sampling can in some cases closely recapitulate the structural changes accompanying mutations but not surprisingly tend to do more harm than good in cases where structural changes are negligible. Analysis of the outliers in the stability change calculations suggests areas needing particular improvement; these include the balance between desolvation and the formation of favorable buried polar interactions, and unfolded state modeling.

We present a large-scale approach to investigate the functional consequences of sequence variation in a protein. The approach entails the display of hundreds of thousands of protein variants, moderate selection for activity, and high throughput DNA sequencing to quantify the performance of each variant. Using this strategy, we tracked the performance of >600,000 variants of a human WW domain after three and six rounds of selection by phage display for binding to its peptide ligand. Binding properties of these variants defined a high-resolution map of mutational preference across the WW domain; each position possessed unique features that could not be captured by a few representative mutations. Our approach could be applied to many in vitro or in vivo protein assays, providing a general means for understanding how protein function relates to sequence.