Protein engineering, chemical biology, and synthetic biology would benefit from toolkits of peptide and protein components that could be exchanged reliably between systems while maintaining their structural and functional integrity. Ideally, such components should be highly defined and predictable in all respects of sequence, structure, stability, interactions, and function. To establish one such toolkit, here we present a basis set of de novo designed α-helical coiled-coil peptides that adopt defined and well-characterized parallel dimeric, trimeric, and tetrameric states. The designs are based on sequence-to-structure relationships both from the literature and analysis of a database of known coiled-coil X-ray crystal structures. These give foreground sequences to specify the targeted oligomer state. A key feature of the design process is that sequence positions outside of these sites are considered non-essential for structural specificity; as such, they are referred to as the background, are kept non-descript, and are available for mutation as required later. Synthetic peptides were characterized in solution by circular-dichroism spectroscopy and analytical ultracentrifugation, and their structures were determined by X-ray crystallography. Intriguingly, a hitherto widely used empirical rule-of-thumb for coiled-coil dimer specification does not hold in the designed system. However, the desired oligomeric state is achieved by database-informed redesign of that particular foreground and confirmed experimentally. We envisage that the basis set will be of use in directing and controlling protein assembly, with potential applications in chemical and synthetic biology. To help with such endeavors, we introduce Pcomp, an on-line registry of peptide components for protein-design and synthetic-biology applications.
The design of new proteins that expand the repertoire of natural protein structures represents a formidable challenge. Success in this area would increase understanding of protein structure, and present new scaffolds that could be exploited in biotechnology and synthetic biology. Here we describe the design, characterisation and X-ray crystal structure of a new coiled-coil protein. The de novo sequence forms a stand-alone, parallel, 6-helix bundle with a channel running through it. Although lined exclusively by hydrophobic leucine and isoleucine side chains, the 6 Å channel is permeable to water. One layer of leucine residues within the channel is mutable accepting polar aspartic acid (Asp) and histidine (His) side chains, and leading to subdivision and organization of solvent within the lumen. Moreover, these mutants can be combined to form a stable and unique (Asp-His)3 heterohexamer. These new structures provide a basis for engineering de novo proteins with new functions.
Motivation: The ability to accurately model protein structures at the atomistic level underpins efforts to understand protein folding, to engineer natural proteins predictably and to design proteins de novo. Homology-based methods are well established and produce impressive results. However, these are limited to structures presented by and resolved for natural proteins. Addressing this problem more widely and deriving truly ab initio models requires mathematical descriptions for protein folds; the means to decorate these with natural, engineered or de novo sequences; and methods to score the resulting models.Results: We present CCBuilder, a web-based application that tackles the problem for a defined but large class of protein structure, the α-helical coiled coils. CCBuilder generates coiled-coil backbones, builds side chains onto these frameworks and provides a range of metrics to measure the quality of the models. Its straightforward graphical user interface provides broad functionality that allows users to build and assess models, in which helix geometry, coiled-coil architecture and topology and protein sequence can be varied rapidly. We demonstrate the utility of CCBuilder by assembling models for 653 coiled-coil structures from the PDB, which cover >96% of the known coiled-coil types, and by generating models for rarer and de novo coiled-coil structures.Availability and implementation: CCBuilder is freely available, without registration, at http://coiledcoils.chm.bris.ac.uk/app/cc_builder/Contact: D.N.Woolfson@bristol.ac.uk or Chris.Wood@bristol.ac.uk
Nature presents various protein fibers that bridge the nanometer to micrometer regimes. These structures provide inspiration for the de novo design of biomimetic assemblies, both to address difficulties in studying and understanding natural systems, and to provide routes to new biomaterials with potential applications in nanotechnology and medicine. We have designed a self-assembling fiber system, the SAFs, in which two small α-helical peptides are programmed to form a dimeric coiled coil and assemble in a controlled manner. The resulting fibers are tens of nm wide and tens of μm long, and, therefore, comprise millions of peptides to give gigadalton supramolecular structures. Here, we describe the structure of the SAFs determined to approximately 8 Å resolution using cryotransmission electron microscopy. Individual micrographs show clear ultrastructure that allowed direct interpretation of the packing of individual α-helices within the fibers, and the construction of a 3D electron density map. Furthermore, a model was derived using the cryotransmission electron microscopy data and side chains taken from a 2.3 Å X-ray crystal structure of a peptide building block incapable of forming fibers. This was validated using singleparticle analysis techniques, and was stable in prolonged molecular-dynamics simulation, confirming its structural viability. The level of self-assembly and self-organization in the SAFs is unprecedented for a designed peptide-based material, particularly for a system of considerably reduced complexity compared with natural proteins. This structural insight is a unique high-resolution description of how α-helical fibrils pack into larger protein fibers, and provides a basis for the design and engineering of future biomaterials.fibrous proteins | protein design | helical reconstruction | X-ray crystallography
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