Engineering a protein–protein interface using a computationally designed library

Abstract

Computational algorithms for protein design can sample large regions of sequence space, but suffer from undersampling of conformational space and energy function inaccuracies. Experimental screening of combinatorial protein libraries avoids the need for accurate energy functions, but has limited access to vast amounts of sequence space. Here, we test if these two traditionally alternative, but potentially complementary approaches can be combined to design a variant of the ubiquitin-ligase E6AP that will bind to a nonnatural partner, the NEDD8-conjugating enzyme Ubc12. Three E6AP libraries were constructed: (i) a naive library in which all 20 amino acids were allowed at every position on the target-binding surface of E6AP (13 positions), (ii) a semidirected library that varied the same residue positions as in the naive library but disallowed mutations computationally predicted to destabilize E6AP, and (iii) a directed library that used docking and sequence optimization simulations to identify mutations predicted to be favorable for binding Ubc12. Both of the directed libraries showed >30-fold enrichment over the naive library after the first round of screening with a split-dihydrofolate reductase complementation assay and produced multiple tight binders (K d < 100 nM) after four rounds of selection. Four rounds of selection with the naive library failed to produce any binders with K d 's lower than 50 μM. These results indicate that protein design simulations can be used to create directed libraries that are enriched in tight binders and that in some cases it is sufficient to computationally screen for well-folded sequences without explicit binding calculations.computational protein design | protein engineering | Rosetta C omputational design and selection from combinatorial libraries are alternative approaches for protein engineering. In computational design, high-resolution models of protein structure are used to predict amino acid sequences that will stabilize target protein structures or complexes. Computational design has been used to stabilize protein structures and interfaces, redesign protein-binding specificities, and in a few cases build protein structures from scratch (1-4). Despite these successes, many problems in protein engineering remain very difficult for computational design: These include the design of protein-protein interactions and the creation of enzymes that compare favorably with naturally occurring enzymes (5-9). In silico ranking of designed interfaces is challenging because large free energies of desolvation have to be correctly balanced by hydrogen bonding and van der Waals interactions that are sensitive to small changes in atomic positions. As a result, there are often significant errors in calculated energies for protein-binding events. One advantage of screening or selecting from large-scale combinatorial libraries is that it does not rely on the accuracy of an energy functioneach sequence is experimentally tested for the desired functionality. Protein selection techniques such as...

Artificial proteins from combinatorial approaches

“…New combinatorial approaches will undoubtedly be combined with other strategies, and first of all, with computational design approaches, for example, to aid the design of smart libraries [4]. For example, new functional catalytic devices have been invented by computational design and catalytic sites have subsequently been improved or adapted by evolution and combinatorial strategies.…”

“…Similarly, this review is limited to projects that apply combinatorial exploration/directed evolution as a dominant part of their strategy. Computational design will not be covered here, although spectacular progress has recently also been made in this field [3,4].…”

“…Similarly, this review is limited to projects that apply combinatorial exploration/directed evolution as a dominant part of their strategy. Computational design will not be covered here, although spectacular progress has recently also been made in this field [3,4].Two lines of interest have motivated studies aimed at creating new proteins by combinatorial approaches. First: these approaches can potentially address very fundamental questions about protein evolution: how can a folded or functional protein arise from a collection of random sequences?…”

Other Applications of Combinatorial Peptide Libraries

“…Depending on the complexity and the length of the peptides in an array, overlapping sequences can be present and a higher precision can be reached. In spite of that, methods involving combinatorial peptides for the discovery of protein-protein interaction are increasingly being used and are associated with computer-assisted models to enhance the power of the identification of binding sites (Guntas et al, 2010;Katz et al, 2011).…”

Accelerated computational discovery of high-performance materials for organic photovoltaics by means of cheminformatics

“…Developments in cheminformatics have been driven by the combination of experimental high-throughput screening (the assay and analysis of more than a million chemical reactions) and with the ability to computationally predict physicochemical parameters (called descriptors). The basic strategy of this approach is to obtain these descriptors for candidate molecules, often obtained from designated candidate libraries, [72][73][74][75][76][77][78][79][80] to score their fitness with respect to a desired set of properties.…”