Experimental library screening demonstrates the successful application of computational protein design to large structural ensembles

The stability, activity, and solubility of a protein sequence are determined by a delicate balance of molecular interactions in a variety of conformational states. Even so, most computational protein design methods model sequences in the context of a single native conformation. Simulations that model the native state as an ensemble have been mostly neglected due to the lack of sufficiently powerful optimization algorithms for multistate design. Here, we have applied our multistate design algorithm to study the potential utility of various forms of input structural data for design. To facilitate a more thorough analysis, we developed new methods for the design and high-throughput stability determination of combinatorial mutation libraries based on protein design calculations. The application of these methods to the core design of a small model system produced many variants with improved thermodynamic stability and showed that multistate design methods can be readily applied to large structural ensembles. We found that exhaustive screening of our designed libraries helped to clarify several sources of simulation error that would have otherwise been difficult to ascertain. Interestingly, the lack of correlation between our simulated and experimentally measured stability values shows clearly that a design procedure need not reproduce experimental data exactly to achieve success. This surprising result suggests potentially fruitful directions for the improvement of computational protein design technology

Mimicry by asx- and ST-turns of the four main types of β-turn in proteins

Hydrogen-bonded β-turns in proteins occur in four categories: type I (the most common), type II, type II’, and type I’. Asx-turns resemble β-turns, in that both have an NH. . .OC hydrogen bond forming a ring of 10 atoms. Serine and threonine side chains also commonly form hydrogen-bonded turns, here called ST-turns. Asx-turns and ST-turns can be categorized into four classes, based on side chain rotamers and the conformation of the central turn residue, which are geometrically equivalent to the four types of β-turns. We propose asx- and ST-turns be named using the type I, II, I’, and II’ β-turn nomenclature. Using this, the frequency of occurrence of both asx- and ST-turns is: type II’ > type I > type II > type I’, whereas for β-turns it is type I > type II > type I’ > type II’. Almost all type II asx-turns occur as a recently described three residue feature named an asx-nest