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.

The E2 envelope glycoprotein is the primary target of human neutralizing antibody response against hepatitis C virus (HCV), and is thus a major focus of vaccine and immunotherapeutics efforts. There is emerging evidence that E2 is a highly complex, dynamic protein with residues across the protein that are modulating antibody recognition, local and global E2 stability, and viral escape. To comprehensively map these determinants, we performed global E2 alanine scanning with a panel of 16 human monoclonal antibodies (hmAbs), resulting in an unprecedented dataset of the effects of individual alanine substitutions across the E2 protein (355 positions) on antibody recognition. Analysis of shared energetic effects across the antibody panel identified networks of E2 residues involved in antibody recognition and local and global E2 stability, as well as predicted contacts between residues across the entire E2 protein. Further analysis of antibody binding hotspot residues defined groups of residues essential for E2 conformation and recognition for all 14 conformationally dependent E2 antibodies and subsets thereof, as well as residues that enhance antibody recognition when mutated to alanine, providing a potential route to engineer E2 vaccine immunogens. By incorporating E2 sequence variability, we found a number of E2 polymorphic sites that are responsible for loss of neutralizing antibody binding. These data and analyses provide fundamental insights into antibody recognition of E2, highlighting the dynamic and complex nature of this viral envelope glycoprotein, and can serve as a reference for development and rational design of E2-targeting vaccines and immunotherapeutics.alanine scanning | immune recognition | HCV | clustering | hotspots H epatitis C virus (HCV) infects ∼185 million of the world's population, with 3-4 million new infections each year. Infection often leads to chronic hepatitis, cirrhosis, and hepatocellular carcinoma, and is a leading reason for liver transplantation (1). Despite recently developed direct-acting antiviral agents, there is a major need for a preventive HCV vaccine, because of the high cost of treatment therapies-which limit their clinical use-a high rate of asymptomatic and untreated infected individuals (over 95% of the infected population) (2, 3), concern of viral resistance to direct-acting antiviral agents (4), and that treatment-induced cure in patients with established cirrhosis does not eliminate the risk of hepatocellular carcinoma (5).A major obstacle to HCV vaccine development efforts is the extreme diversity of the virus and its high rate of mutation, which allows it to actively evade the immune response in infected individuals. Critical to the development of an effective vaccine is the identification and characterization of conserved epitopes associated with viral neutralization. The antibody response to HCV is directed primarily against the E2 glycoprotein because E2 directly interacts with the HCV coreceptors, scavenger receptor class B type 1 (SR-B1) (6) and the tetraspan...

We present the results for CAPRI Round 46, the third joint CASP‐CAPRI protein assembly prediction challenge. The Round comprised a total of 20 targets including 14 homo‐oligomers and 6 heterocomplexes. Eight of the homo‐oligomer targets and one heterodimer comprised proteins that could be readily modeled using templates from the Protein Data Bank, often available for the full assembly. The remaining 11 targets comprised 5 homodimers, 3 heterodimers, and two higher‐order assemblies. These were more difficult to model, as their prediction mainly involved “ab‐initio” docking of subunit models derived from distantly related templates. A total of ~30 CAPRI groups, including 9 automatic servers, submitted on average ~2000 models per target. About 17 groups participated in the CAPRI scoring rounds, offered for most targets, submitting ~170 models per target. The prediction performance, measured by the fraction of models of acceptable quality or higher submitted across all predictors groups, was very good to excellent for the nine easy targets. Poorer performance was achieved by predictors for the 11 difficult targets, with medium and high quality models submitted for only 3 of these targets. A similar performance “gap” was displayed by scorer groups, highlighting yet again the unmet challenge of modeling the conformational changes of the protein components that occur upon binding or that must be accounted for in template‐based modeling. Our analysis also indicates that residues in binding interfaces were less well predicted in this set of targets than in previous Rounds, providing useful insights for directions of future improvements.