Structural Proteomics-Based Deciphering of Hydrophobic Packing Fingerprints Informing Protein Thermostability in TIM Barrels.

A tightly packed hydrophobic core, with regions composed of hydrophobic residues defined as hydrophobic clusters, is a hallmark of globular proteins. However, quantitative rules governing the formation of stable hydrophobic clusters remain unclear. This is mainly due to the exponential growth in residue combinations with the number of sites in the clusters, which makes experimental characterization of all variants highly challenging. Current physics-based energy functions and deep learning models struggle with both accuracy and interpretability when modeling the stability of hydrophobic clusters. The advent of high-accuracy protein structure prediction models has enabled structural proteomics studies with hundreds of millions of structures. The triosephosphate isomerase (TIM) barrel, among the most abundant fold architectures, has been extensively investigated in evolutionary studies and protein design. In this study, we developed the hydrophobic packing fingerprints quantitative platform, qPacking, to define five hydrophobic packing descriptors (HPDs) for hydrophobic residues (A, V, I, L, and M) and to systematically quantify the hydrophobic clusters within TIM barrels. Hydrophobic clusters in TIM barrels were predominantly located in α-β regions rather than in β-barrel regions. Compared with their nonthermophilic counterparts, thermophilic TIM barrels exhibited larger and more densely packed hydrophobic clusters, with the most pronounced differences observed in the closure regions. Evolutionary analysis indicated that selection of residues within hydrophobic clusters involved a trade-off between packing area and spatial steric constraints. Feature analysis indicated that HPDs showed distributional differences between thermophilic and nonthermophilic TIM barrels. In summary, qPacking and HPDs provided a quantitative framework for understanding and optimizing protein thermal stability.