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10.1073/pnas.2017525118 http://scihub22266oqcxt.onion/10.1073/pnas.2017525118 33361332!7812826!33361332     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=33361332&cmd=llinks): Failed to open stream: HTTP request failed! 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DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on CoV-related complexes |pdf=|usr=}}{{33361332}} gab.com Text DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on CoV-related complexes JO: Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=33361332 #FOAvip Information about macromolecular structure of protein complexes and related cellular and molecular mechanisms can assist the search for vaccines and drug development processes. To obtain such structural information, we present DeepTracer, a fully automated deep learning-based method for fast de novo multichain protein complex structure determination from high-resolution cryoelectron microscopy (cryo-EM) maps. We applied DeepTracer on a previously published set of 476 raw experimental cryo-EM maps and compared the results with a current state of the art method. The residue coverage increased by over 30% using DeepTracer, and the rmsd value improved from 1.29 A to 1.18 A. Additionally, we applied DeepTracer on a set of 62 coronavirus-related cryo-EM maps, among them 10 with no deposited structure available in EMDataResource. We observed an average residue match of 84% with the deposited structures and an average rmsd of 0.93 A. Additional tests with related methods further exemplify DeepTracer's competitive accuracy and efficiency of structure modeling. DeepTracer allows for exceptionally fast computations, making it possible to trace around 60,000 residues in 350 chains within only 2 h. The web service is globally accessible at https://deeptracer.uw.edu. Twit Text FOAVip DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on CoV-related complexes ????Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=33361332 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33361332 #FOAvip English Wikipedia <ref>{{Cite pmid|33361332}}</ref> DeepTracer for fast de novo cryo-EM protein structure modeling and special studies on CoV-related complexes #MMPMID33361332 Pfab J; Phan NM; Si D Proc Natl Acad Sci U S A 2021[Jan]; 118 (2): ä PMID33361332show ga Information about macromolecular structure of protein complexes and related cellular and molecular mechanisms can assist the search for vaccines and drug development processes. To obtain such structural information, we present DeepTracer, a fully automated deep learning-based method for fast de novo multichain protein complex structure determination from high-resolution cryoelectron microscopy (cryo-EM) maps. We applied DeepTracer on a previously published set of 476 raw experimental cryo-EM maps and compared the results with a current state of the art method. The residue coverage increased by over 30% using DeepTracer, and the rmsd value improved from 1.29 A to 1.18 A. Additionally, we applied DeepTracer on a set of 62 coronavirus-related cryo-EM maps, among them 10 with no deposited structure available in EMDataResource. We observed an average residue match of 84% with the deposited structures and an average rmsd of 0.93 A. Additional tests with related methods further exemplify DeepTracer's competitive accuracy and efficiency of structure modeling. DeepTracer allows for exceptionally fast computations, making it possible to trace around 60,000 residues in 350 chains within only 2 h. The web service is globally accessible at https://deeptracer.uw.edu. |*Deep Learning[MESH] |*Models, Structural[MESH] |*Molecular Structure[MESH] |Cryoelectron Microscopy[MESH] |SARS-CoV-2/*chemistry[MESH]DeepTracer for fast de novo cryo-EM protein structure modeling and spe(epmc).pdf DeepDyve Pubget Overpricing