Protein structure prediction by trRosetta - Nankai University

Introduction. trRosetta is an algorithm for fast and accurate protein structure prediction. It builds the protein structure based on direct energy minimizations with a restrained Rosetta. The restraints include inter-residue distance and orientation distributions, predicted by a deep neural network. Homologous templates are included in the ...

Rosetta: - University of Arizona

Rosetta predicts L which will be negative in most cases. Although this leads to some theoretical complications, negative L values give far better results (cf., Kosugi, 1999; Schaap and Leij, 1999). top of page: ROSETTA Class Average Hydraulic Parameters . The table below gives class-average values of the seven hydraulic parameters for the ...

GitHub - LatticeX-Foundation/Rosetta: A Privacy …

Rosetta is an open source project developed under the LPGLv3 license and maintained by LatticeX Foundation. Contributions from individuals and organizations are all welcome. Before beginning, please take a look at our contributing guidelines. Our project adheres to code of conduct. By participating in our community, you are expected to uphold ...

PRosettaC: Rosetta Based Modeling of PROTAC Mediated …

Proteolysis-targeting chimeras (PROTACs), which induce degradation by recruitment of an E3 ligase to a target protein, are gaining much interest as a new pharmacological modality. However, designing PROTACs is challenging. Formation of a ternary complex between the protein target, the PROTAC, and th …

ROSETTA3: an object-oriented software suite for the …

We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. Th …

The Rosetta Software | RosettaCommons

The Rosetta software suite includes algorithms for computational modeling and analysis of protein structures. It has enabled notable scientific advances in computational biology, including de novo protein design, enzyme design, ligand docking, and structure prediction of biological macromolecules and macromolecular complexes. ...