The Rosetta All-Atom Energy Function for Macromolecular Modeling and Design

Abstract

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, REF15. 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, small molecules, carbohydrates, nucleic acids, and other macromolecules.

Extending human IgG half-life using structure-guided design

“…The Fc-FcRn interface residues and their interactions were calculated using the PISA server (http://www.ebi.ac.uk/pdbe/prot_int/pistart.html). A protein residue network was generated by representing each residue as a node in a graph; edge weights in the graph were based on the inter-residue energies calculated using Rosetta (implemented as a pyrosetta script using the Rosetta Energy Function 2015 (REF2015) 54 score function). A network was generated using the NetworkX package in python, and these networks were visualized using Gephi (https://gephi.org) to identify residues that interact both directly or through the network.…”

Evaluation system and web infrastructure for the second cryo-EM model challenge

“…Both methods return global (one per model) and local (one per residue) reliability scores scaled to [0–1] range (the higher the better). ProQ3 is based on a machine learning algorithm that combines knowledge-based Rosetta energy terms (Alford et al, 2017) with comparison of predicted and observed structural features, including contacts between different atom types, secondary structure and surface accessibility, and features predicted from sequence profiles. Local, per-residue accuracy is described in terms of S-score (Gerstein and Levitt, 1998), and global accuracy is a normalized sum of the local values.…”

Parallel Evolutionary Optimization Algorithms for Peptide-Protein Docking

“…The Rosetta 3.8 [4] framework was used for full-atom complex structure representation and scoring (energy evaluation). The Rosetta all-atom force-field is a dedicated structure prediction and docking force-field.…”

“…There are a lot of statistics about degrees of freedom: neighbor-dependent Ramachandran plots [4], backbone-independent [5] and backbone-dependent [6] libraries for side-chain dihedral angles. These libraries have been used to exclude impossible conformations by creating 1-4 dimensional cumulative distribution functions that had been derived from given probability density functions.…”