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_3
Snippet: In the second protocol we started from DeepMind's AlphaFold models. Both sets of machinelearning based models were subjected to our latest molecular-dynamics based refinement protocol 9,10 to maximize model accuracy. Here we compare the resulting models with each other and with the predictions from C-I-TASSER. A particular focus is on establishing, which structural aspects are conserved based on consensus from different approaches and where signi.....
Document: In the second protocol we started from DeepMind's AlphaFold models. Both sets of machinelearning based models were subjected to our latest molecular-dynamics based refinement protocol 9,10 to maximize model accuracy. Here we compare the resulting models with each other and with the predictions from C-I-TASSER. A particular focus is on establishing, which structural aspects are conserved based on consensus from different approaches and where significant uncertainty remains in the accuracy of the computer-generated models. All of our . CC-BY-NC-ND 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.03.25.008904 doi: bioRxiv preprint predicted protein tertiary models are publicly available at https://github.com/feiglab/sars-cov-2-proteins .
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