There are 20(200) possible amino-acid sequences for a 200-residue protein, of which the natural evolutionary process has sampled only an infinitesimal subset. De novo protein design explores the full sequence space, guided by the physical principles that underlie protein folding. Computational methodology has advanced to the point that a wide range of structures can be designed from scratch with atomic-level accuracy. Almost all protein engineering so far has involved the modification of naturally occurring proteins; it should now be possible to design new functional proteins from the ground up to tackle current challenges in biomedicine and nanotechnology.

The Rosetta software suite for macromolecular modeling, docking, and design is widely used in pharmaceutical, industrial, academic, non-profit, and government laboratories. Despite its broad modeling capabilities, Rosetta remains consistently among leading software suites when compared to other methods created for highly specialized protein modeling and design tasks. Developed for over two decades by a global community of over 60 laboratories, Rosetta has undergone multiple refactorings, and now comprises over three million lines of code. Here we discuss methods developed in the last five years in Rosetta, involving the latest protocols for structure prediction; protein-protein and protein-small molecule docking; protein structure and interface design; loop modeling; the incorporation of various types of experimental data; modeling of peptides, antibodies and proteins in the immune system, nucleic acids, non-standard chemistries, carbohydrates, and membrane proteins. We briefly discuss improvements to the energy function, user interfaces, and usability of the software. Rosetta is available at www.rosettacommons.org.

Gram-negative bacteria, such as Escherichia coli, frequently utilize tripartite efflux complexes in the resistance-nodulation-cell division (RND) family to expel diverse toxic compounds from the cell.1,2 The efflux system CusCBA is responsible for extruding biocidal Cu(I) and Ag(I) ions.3,4 No prior structural information was available for the heavy-metal efflux (HME) subfamily of the RND efflux pumps. Here we describe the crystal structures of the inner membrane transporter CusA in the absence and presence of bound Cu(I) or Ag(I). These CusA structures provide important new structural information about the HME sub-family of RND efflux pumps. The structures suggest that the metal binding sites, formed by a three-methionine cluster, are located within the cleft region of the periplasmic domain. Intriguingly, this cleft is closed in the apo-CusA form but open in the CusA-Cu(I) and CusA-Ag(I) structures, which directly suggests a plausible pathway for ion export. Binding of Cu(I) and Ag(I) triggers significant conformational changes in both the periplasmic and transmembrane domains. The crystal structure indicates that CusA has, in addition to the three-methionine metal binding site, four methionine pairs - three located in the transmembrane region and one in the periplasmic domain. Genetic analysis and transport assays suggest that CusA is capable of actively picking up metal ions from the cytosol, utilizing these methionine pairs/clusters to bind and export metal ions. These structures suggest a stepwise shuttle mechanism for transport between these sites.

In nature, structural specificity in DNA and proteins is encoded quite differently: in DNA, specificity arises from modular hydrogen bonds in the core of the double helix, whereas in proteins, specificity arises largely from buried hydrophobic packing complemented by irregular peripheral polar interactions. Here we describe a general approach for designing a wide range of protein homo-oligomers with specificity determined by modular arrays of central hydrogen bond networks. We use the approach to design dimers, trimers, and tetramers consisting of two concentric rings of helices, including previously not seen triangular, square, and supercoiled topologies. X-ray crystallography confirms that the structures overall, and the hydrogen bond networks in particular, are nearly identical to the design models, and the networks confer interaction specificity in vivo. The ability to design extensive hydrogen bond networks with atomic accuracy is a milestone for protein design and enables the programming of protein interaction specificity for a broad range of synthetic biology applications.