Author: Lim Heo; Michael Feig
Title: Modeling of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Proteins by Machine Learning and Physics-Based Refinement Document date: 2020_3_28
ID: 9qv11m4f_15
Snippet: We applied the trRosetta method to generate inter-residue distance predictions and to build initial models for further refinement. The original machine-learning trRosetta pipeline was modified to be applied to multiple domain proteins. We iteratively searched sequences and predicted inter-residue distances where contact information was not enough to build a model until all the residues could be built or there was no contact information update. We.....
Document: We applied the trRosetta method to generate inter-residue distance predictions and to build initial models for further refinement. The original machine-learning trRosetta pipeline was modified to be applied to multiple domain proteins. We iteratively searched sequences and predicted inter-residue distances where contact information was not enough to build a model until all the residues could be built or there was no contact information update. We built 10 models for each protein, and the lowest energy structure was selected for the following refinement step.
Search related documents:
Co phrase search for related documents- contact information and model build: 1
- domain protein and energy structure: 1, 2, 3, 4
- domain protein and multiple domain protein: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16
- domain protein and sequence search: 1
- energy structure and low energy structure: 1, 2
- energy structure and sequence search: 1
- initial model and model build: 1, 2, 3, 4
Co phrase search for related documents, hyperlinks ordered by date