Over the past decade, the Rosetta biomolecular modeling suite has informed diverse biological questions and engineering challenges ranging from interpretation of low-resolution structural data to design of nanomaterials, protein therapeutics, and vaccines. Central to Rosetta's success is the energy function: a model parameterized from small molecule and X-ray crystal structure data used to approximate the energy associated with each biomolecule conformation. This paper describes the mathematical models and physical concepts that underlie the latest Rosetta energy function, beta_nov15. Applying these concepts, we explain how to use Rosetta energies to identify and analyze the features of biomolecular models. Finally, we discuss the latest advances in the energy function that extend capabilities from soluble proteins to also include membrane proteins, peptides containing non-canonical amino acids, carbohydrates, nucleic acids, and other macromolecules.

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.

Mutations are central to evolution, providing the genetic variation upon which selection acts. A mutation’s effect on the suitability of a gene to perform a particular function (gene fitness) can be positive, negative, or neutral. Knowledge of the distribution of fitness effects (DFE) of mutations is fundamental for understanding evolutionary dynamics, molecular-level genetic variation, complex genetic disease, the accumulation of deleterious mutations, and the molecular clock. We present comprehensive DFEs for point and codon mutants of the Escherichia coli TEM-1 β-lactamase gene and missense mutations in the TEM-1 protein. These DFEs provide insight into the inherent benefits of the genetic code’s architecture, support for the hypothesis that mRNA stability dictates codon usage at the beginning of genes, an extensive framework for understanding protein mutational tolerance, and evidence that mutational effects on protein thermodynamic stability shape the DFE. Contrary to prevailing expectations, we find that deleterious effects of mutation primarily arise from a decrease in specific protein activity and not cellular protein levels.

Elucidating how antigen exposure and selection shape the human antibody repertoire is fundamental to our understanding of B-cell immunity. We sequenced the paired heavy-and light-chain variable regions (VH and VL, respectively) from large populations of single B cells combined with computational modeling of antibody structures to evaluate sequence and structural features of human antibody repertoires at unprecedented depth. Analysis of a dataset comprising 55,000 antibody clusters from CD19− IgM-naive B cells, >120,000 antibody clusters from CD19+ antigenexperienced B cells, and >2,000 RosettaAntibody-predicted structural models across three healthy donors led to a number of key findings: (i) VH and VL gene sequences pair in a combinatorial fashion without detectable pairing restrictions at the population level; (ii) certain VH:VL gene pairs were significantly enriched or depleted in the antigen-experienced repertoire relative to the naive repertoire; (iii) antigen selection increased antibody paratope net charge and solvent-accessible surface area; and (iv) public heavy-chain third complementarity-determining region (CDR-H3) antibodies in the antigen-experienced repertoire showed signs of convergent paired light-chain genetic signatures, including shared light-chain third complementarity-determining region (CDR-L3) amino acid sequences and/or Vκ,λ-Jκ,λ genes. The data reported here address several longstanding questions regarding antibody repertoire selection and development and provide a benchmark for future repertoire-scale analyses of antibody responses to vaccination and disease.antibody | B cell | immunology | high-throughput sequencing | computational modeling E ffective antigen recognition by the humoral immune system is predicated on the somatic generation of a large antibody repertoire that encompasses the sequence and conformational diversity to respond to a highly diversified set of antigens (1-3). Upon antigen challenge, naive B cells (NBCs) expressing unmutated antibodies capable of binding antigen with an affinity sufficient to initiate B-cell receptor (BCR) signaling may be stimulated to undergo somatic hypermutation (SHM) of the antibody genes. B cells expressing higher-affinity BCRs are better equipped to compete for antigen and thus receive signals that enable their preferential proliferation and further antibody sequence diversification in additional rounds of SHM. This process generates a repertoire of somatically mutated antibodies that, at the structural level, generally display decreased conformational flexibility (4, 5), slower antigen dissociation rates, and increased binding selectivity relative to the germline repertoire.Understanding the salient features of the human antibody repertoire is critical for immunology research (6, 7). Specifically, additional information is needed regarding how a history of pathogen and environmental exposure modulates the sequence and conformational properties of naive antibodies to yield a mature antibody repertoire that confers effective protection. Hi...