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.

Riboswitches control gene expression through ligand-dependent structural rearrangements of the sensing aptamer domain. However, we found that the Bacillus cereus fluoride riboswitch aptamer adopts identical tertiary structures in solution with and without ligand. Using chemical exchange saturation transfer (CEST) NMR spectroscopy, we revealed that the structured ligand-free aptamer transiently accesses a low-populated (~1%) and short-lived (~3 ms) excited conformational state that unravels a conserved ‘linchpin’ base pair to signal transcription termination. Upon fluoride binding, this highly localized fleeting process is allosterically suppressed to activate transcription. We demonstrated that this mechanism confers effective fluoride-dependent gene activation over a wide range of transcription rates, which is essential for robust toxicity response across diverse cellular conditions. These results unveil a novel switching mechanism that employs ligand-dependent suppression of an aptamer excited state to coordinate regulatory conformational transitions rather than adopting distinct aptamer ground-state tertiary architectures, exemplifying a new mode of ligand-dependent RNA regulation.

Primordial sequence signatures in modern proteins imply ancestral origins tracing back to simple peptides. Although short peptides seldom adopt unique folds, metal ions might have templated their assembly into higher-order structures in early evolution and imparted useful chemical reactivity. Recapitulating such a biogenetic scenario, we have combined design and laboratory evolution to transform a zinc-binding peptide into a globular enzyme capable of accelerating ester cleavage with exacting enantiospecificity and high catalytic efficiency (kcat/KM~ 106M−1s−1). The simultaneous optimization of structure and function in a naïve peptide scaffold not only illustrates a plausible enzyme evolutionary pathway from the distant past to the present but also proffers exciting future opportunities for enzyme design and engineering.

The rise of antibiotic resistance calls for new therapeutics targeting resistance factors such as the New Delhi metallo-β-lactamase 1 (NDM-1), a bacterial enzyme that degrades β-lactam antibiotics. We present structure-guided computational methods for designing peptide macrocycles built from mixtures of l- and d-amino acids that are able to bind to and inhibit targets of therapeutic interest. Our methods explicitly consider the propensity of a peptide to favor a binding-competent conformation, which we found to predict rank order of experimentally observed IC50 values across seven designed NDM-1- inhibiting peptides. We were able to determine X-ray crystal structures of three of the designed inhibitors in complex with NDM-1, and in all three the conformation of the peptide is very close to the computationally designed model. In two of the three structures, the binding mode with NDM-1 is also very similar to the design model, while in the third, we observed an alternative binding mode likely arising from internal symmetry in the shape of the design combined with flexibility of the target. Although challenges remain in robustly predicting target backbone changes, binding mode, and the effects of mutations on binding affinity, our methods for designing ordered, binding-competent macrocycles should have broad applicability to a wide range of therapeutic targets.

We have developed a set of protocols in the molecular modeling program Rosetta for performing requirement-driven protein design. First, the user specifies a set of structural features that need to be present in the designed protein. These requirements can be general (e.g., "create a protein with five helices"), or they can be very specific and require the correct placement of a set of amino acids to bind a ligand. Next, a large set of protein models are generated that satisfy the design requirements. The models are built using a method that we recently introduced into Rosetta, called SEWING, that rapidly assembles novel protein backbones by combining pieces of naturally occurring proteins. In the last step of the process, rotamer-based sequence optimization and backbone refinement are performed with Rosetta, and a variety of quality metrics are used to pick sequences for experimental characterization. Here we describe the input files and user options needed to run SEWING and perform requirement-driven design and provide detailed instructions for two specific applications of the process: the design of new structural elements at a protein-protein interface and the design of ligand binding sites.