Computational protein design with backbone plasticity.

James T Macdonald,Paul S Freemont

doi:10.1042/bst20160155

Abstract

The computational algorithms used in the design of artificial proteins have become increasingly sophisticated in recent years, producing a series of remarkable successes. The most dramatic of these is the de novo design of artificial enzymes. The majority of these designs have reused naturally occurring protein structures as ‘scaffolds’ onto which novel functionality can be grafted without having to redesign the backbone structure. The incorporation of backbone flexibility into protein design is a much more computationally challenging problem due to the greatly increased search space, but promises to remove the limitations of reusing natural protein scaffolds. In this review, we outline the principles of computational protein design methods and discuss recent efforts to consider backbone plasticity in the design process.

Highlights

A variety of different strategies have been developed to engineer novel globular proteins
We have described the methodological advances in computational protein design in the past few decades
It has become clear that the incorporation of backbone flexibility is essential to fully explore sequence space and to enable more complex designs

Summary

Introduction

A variety of different strategies have been developed to engineer novel globular proteins. These fixed-backbone computational design algorithms have been extended to introduce novel functionality, such as binding sites [11], libraries of fluorescent proteins [12], and de novo designed enzymes that catalyse reactions not found in nature [13,14]. In parallel to these developments, entirely de novo proteins, consisting of mainly canonical secondary structure and minimal loops, have been created by assembling backbone fragments from known protein structures, followed by iterated sequence design using the fixed-backbone approximation and energy minimisation [15,16,17].

Results

Conclusion