Protocols for Molecular Modeling with Rosetta3 and RosettaScripts

Abstract

Previously, we published an article providing an overview of the Rosetta suite of biomacromolecular modeling software and a series of step-by-step tutorials [Kaufmann, K. W., et al. (2010) Biochemistry 49, 2987–2998]. The overwhelming positive response to this publication we received motivates us to here share the next iteration of these tutorials that feature de novo folding, comparative modeling, loop construction, protein docking, small molecule docking, and protein design. This updated and expanded set of tutorials is needed, as since 2010 Rosetta has been fully redesigned into an object-oriented protein modeling program Rosetta3. Notable improvements include a substantially improved energy function, an XML-like language termed “RosettaScripts” for flexibly specifying modeling task, new analysis tools, the addition of the TopologyBroker to control conformational sampling, and support for multiple templates in comparative modeling. Rosetta’s ability to model systems with symmetric proteins, membrane proteins, noncanonical amino acids, and RNA has also been greatly expanded and improved.

Structural basis of ligand binding modes at the neuropeptide Y Y1 receptor

“…Top models from a given docking round were used to seed the next round of docking in which the peptide was extended. Fragment picking was performed using the fragment_picker application within Rosetta 26 . Secondary structure during fragment picking was guided by the NMR chemical shift data.…”

“…4). A number of key Y 1 R/NPY contacts identified by the mutagenesis studies were used to guide NPY docking in Rosetta 26 with the final models being filtered against the NMR data to generate a final ensemble that best represents the combined data. The NPY-bound model reveals a relatively flat binding pose of NPY to Y 1 R with the C-terminal tetrapeptide R33-Y36, identified as a random coil/β-strand structure in NMR, penetrating into the binding pocket (Fig.…”

Computational Prediction of the Heterodimeric and Higher-Order Structure of gpE1/gpE2 Envelope Glycoproteins Encoded by Hepatitis C Virus

“…Fragments were then assembled by a Monte Carlo fragment insertion protocol, which favors insertions leading to geometries with good scores. Low-resolution models were first built by using a centroid energy function, which were later refined by using an all-atom energy function (27). A total of 100,000 models were generated, and the lowest-scoring models were subsequently clustered.…”

“…Side-chain conformations are optimized by using the Dunbrack rotamer library (26). Rosetta can accurately predict structures of small, globular, soluble proteins or of small simple membrane proteins containing up to 100 residues (27). Moreover, during modeling in Rosetta, known portions of a structure can be held rigid while extensions are folded, a useful feature for problems such as the one that we address here, where a protein has been partially crystallized.…”

“…When using Rosetta ab initio modeling, a model is selected based on the scoring of multiple decoys, and this selection process can be further assisted by available experimental structural data (27). Here, we make use of knowledge of the residues on both E1 and E2 needed for binding to the AR4A and AR5A antibodies (18); that is, structural models in which amino acids implicated in the epitopes for these antibodies were positioned very distant from each other were discounted.…”