Specificity in Computational Protein Design

James J. Havranek

doi:10.1074/jbc.r110.157685

Abstract

A long-standing goal of computational protein design is to create proteins similar to those found in Nature. One motivation is to harness the exquisite functional capabilities of proteins for our own purposes. The extent of similarity between designed and natural proteins also reports on how faithfully our models represent the selective pressures that determine protein sequences. As the field of protein design shifts emphasis from reproducing native-like protein structure to function, it has become important that these models treat the notion of specificity in molecular interactions. Although specificity may, in some cases, be achieved by optimization of a desired protein in isolation, methods have been developed to address directly the desire for proteins that exhibit specific functions and interactions.

Highlights

Specificity in Computational Protein Design*As the field of protein design shifts emphasis from reproducing native-like protein structure to function, it has become important that these models treat the notion of specificity in molecular interactions
The field of computational protein design pursues two goals
I describe the biological parallels for the functional specificity we seek to encode in the protocols of protein design, describe techniques for achieving specificity both with and without explicit multistate design, and discuss recent algorithmic advances likely to advance the field in the near future

Summary

Specificity in Computational Protein Design*

As the field of protein design shifts emphasis from reproducing native-like protein structure to function, it has become important that these models treat the notion of specificity in molecular interactions. The second goal emphasizes scientific, rather than engineering, aims This goal is concerned with the models that serve as input for the process: we desire a quantitative description of the principles that influence the selection of natural proteins. The extent to which designed proteins resemble natural proteins serves to evaluate how well our models simulate the selective pressures for natural proteins This minireview is concerned with efforts to endow designed proteins with the specificity observed in naturally occurring proteins. I describe the biological parallels for the functional specificity we seek to encode in the protocols of protein design, describe techniques for achieving specificity both with and without explicit multistate design, and discuss recent algorithmic advances likely to advance the field in the near future

Natural Exemplars for Biomolecular Specificity

Specificity without Negative Design

Models for Specificity in Computational Protein Design

Explicit Specificity via Multistate Design

Insights from Multistate Design

Future Directions

Conclusions