Blind variation and focused selection have made the biosphere, and they’re being used in the lab to make functional biomolecular components. The laboratory methods often go under the names of “directed evolution” and (in single-round versions) “high-throughput screening”, and they hold promise as partners for rational design in macromolecular systems engineering.
As background, here are a few papers that were published in the last year or so and are freely available:
- Ultrahigh-throughput screening in drop-based microfluidics for directed evolution. (“…compared to state-of-the-art robotic screening systems, we perform the entire assay with a 1,000-fold increase in speed and a 1-million-fold reduction in cost.”)
- Computational analysis of off-rate selection experiments to optimize affinity maturation by directed evolution. [pdf] (“…sequential selection rounds with lower stringency are favored over high-stringency selection experiments due to enhanced diversity in the selected pools.”)
- Beyond directed evolution: Darwinian selection as a tool for synthetic biology. (“…a strategy for fine-tuning of relatively complex circuits by coupling them to a master standard circuit is discussed.”)
- De novo enzymes: from computational design to mRNA display. [pdf] (“To date, several technologies have been developed to achieve this goal: namely, computational design, catalytic antibodies and mRNA display. These methods rely on different principles, trading off rational protein design against an entirely combinatorial approach of directed evolution of vast protein libraries. The aim of this article is to review and compare these methods and their potential for generating truly de novo biocatalysts.”)
Design, then refine
Methods of the sort analyzed in paper #2 select for molecules that bind a target molecule tightly (somewhere, somehow), starting with molecules that might not bind at all. A standard challenge in protein engineering, however, is a bit different: to develop tight-binding molecules that bind in a specific way — that is, in a position and orientation chosen by a designer.
This is important if one aims to develop building blocks that play specific structural or functional roles in larger macromolecular systems. (For example, engineering molecular assembly lines like polyketide- and nonribosomal-peptide synthases.)
There’s an approach for solving this problem that has recently appeared in the literature (as viewed from the computational side of the problem), but that, to the best of my knowledge, hasn’t yet been applied. It has two stages:
- In the first step, use protein design tools (for example, RosettaDesign) to design complementary interfaces having the desired alignment, choosing (by design on both sides of the interface!) surface configurations with complementary shapes, charges, patterns of hydrophobicity, etc.
- In the second step, apply screening or directed evolution methods to select for variants that bind more tightly. The expectation is that these will retain enough of the designed interactions to maintain the relative position and orientation chosen by the designer, while achieving the sort of high affinity routinely achieved by variation and selection in less well specified systems.
If a result is unsatisfactory, the next move would be to try again, keeping the preferred position and orientation of binding, but starting with a different choice of complementary surface features.