Towards functional de novo designed proteins
Graphical abstract
Introduction
De novo protein design is said to have come of age [1]. From the early de novo proteins confirmed by high-resolution structures [2, 3, 4], the field has advanced rapidly with new scaffolds covering all-α [5,6•,7], all-β [8], and mixed-α/β and α + β structural space [9,10•,11]. In addition, side-chain constellations can be controlled exquisitely to introduce networks of hydrogen bonds throughout target structures [12], which, in turn, can improve the design and characterisation of de novo membrane proteins [13].
However, the ability to design functional de novo proteins from scratch, or to embellish existing de novo scaffolds with new functions, is still in its infancy. Herein, we use terms like ‘functional protein design’ for any stably folded de novo protein frameworks that incorporate interactions with small or large molecules, catalytic activity and so on. With notable exceptions—for example, reports of a functional ion transporter [14], a de novo designed catalytic triad [15••], and a highly efficient de novo enzyme [16••]— general design principles for functional protein design are sparse. Indeed, it may be that overoptimised de novo proteins, which are often hyperthermally stable, may not make good platforms for functional design, as it is known that dynamics play essential roles in ligand binding and catalysis [17, 18, 19].
Herein, we focus on truly de novo proteins rather than those achieved through protein engineering or redesign—that is, where functions are improved in or introduced to natural proteins. Of course, the latter have led to novel enzymes and ligand-binding proteins [20, 21, 22]. Whilst impressive, protein engineering relies on the inherent stability of natural scaffolds and their tolerance to mutation, and often uses the randomness of directed evolution to access the targeted function [23]. By contrast, de novo protein design removes the dependence on naturally evolved scaffolds, and has the potential for a deeper understanding of the contribution that every side chain makes towards the structure, stability and function of de novo proteins. Of course, this is an extremely challenging approach and its goals are ambitious.
Notable advances have also been made in introducing metal-binding and protein–protein interactions into de novo proteins (see recent reviews Refs. [24, 25, 26]). However, these pose different challenges to those laid out herein, and are only mentioned in passing in this review.
Section snippets
From minimal, through rational, to computational design
There is no single approach to protein design. However, the field can be split broadly into three different approaches (Figure 1). In minimal design binary patterns of polar (p) and hydrophobic (h) residues are used to define a target structure [27,28]. α-Helices lend themselves to this as they can be directed to fold and assemble with sequence patterns of the type hpphppp. As a result, the vast majority of work in this area has targeted four-helix bundles. Rational design goes a step further
Minimal design of functional four-helix bundles
DeGrado, Hecht and Dutton have pioneered the concepts of minimal and rational de novo protein design (reviewed extensively in Refs. [27,33,34]). In short, these combine chemical intuition about protein structure and basic sequence-to-structure relationships to deliver straightforward designed protein scaffolds (Figure 1). Key targets in these endeavours have been four-helix bundles, which involve the coalescence of amphipathic helices encoded by self-associating peptides or within single
Rational parametric design of functional assemblies
Rules-based or rational protein design and computational design do not have to be mutually exclusive (Figure 1). By incorporating design rules into computational design algorithms, the number of models that need to be built and scored can be reduced dramatically. Parametric design lends itself to this. Here, target protein folds are described mathematically with a minimal number of parameters. Not surprisingly given their simplicity and potential regularity, de novo four-helix bundles have been
Fragment-based computational design beyond protein engineering
As protein structures increase in complexity, more-sophisticated approaches are needed to access more-elaborate architectures. By harnessing the power of computers, thousands of designs can be generated and analysed in silico at scales beyond minimal and rational design. The most widespread approach is fragment-based design, which has three aspects: libraries of fragments or motifs are taken from structural databases, algorithms are developed to combine these to assemble target structures, and
Designing in function from the beginning
Most of the studies described above focus on the design of the de novo scaffold before functionalisation or improving an already established functional de novo protein. Though there are clear examples to the contrary [15••,31•,39], extant de novo designed scaffolds may not have suitable cavities or sites for every targeted function, or the post-incorporation of the necessary functional residues may prove problematic. Indeed, for natural proteins it is well documented that small changes, even
Challenges ahead
The robust and routine design of functional de novo proteins remains an unsolved problem. For instance, to our knowledge, there are no examples of tight binding of small, polar molecules by de novo proteins. The change in approach in the last few years to incorporate the functional aspect of the design at an early stage shows clear potential, which we envisage will be become more evident as design algorithms improve. However, as stated above, accessing functional de novo proteins that work on a
Conflict of interest statement
Nothing declared.
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
•• of outstanding interest
Acknowledgements
WMD, GGR and DNW were supported by a European Research Council Advanced Grant (340764). DNW is supported by the EPSRC and BBSRC through the BrisSynBio Synthetic Biology Research Centre (BB/L01386X1). DNW holds a Royal Society Wolfson Research Merit Award (WM140008). We thank Ross Anderson for providing a computational model of the C45 protein.
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