Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1101/2020.10.15.340455 http://scihub22266oqcxt.onion/10.1101/2020.10.15.340455 33083802!7574260!33083802     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=33083802&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       bioRxiv 2020 ; ? (?): ? Nephropedia Template TP {{tp|p=33083802|t=2020. Progressive and accurate assembly of multi-domain protein structures from cryo-EM density maps |pdf=|usr=}}{{33083802}} gab.com Text Progressive and accurate assembly of multi-domain protein structures from cryo-EM density maps JO: bioRxiv http://www.kidney.de/pget.php?&tw=1&pmid=33083802 #FOAvip Progress in cryo-electron microscopy (cryo-EM) has provided the potential for large-size protein structure determination. However, the solution rate for multi-domain proteins remains low due to the difficulty in modeling inter-domain orientations. We developed DEMO-EM, an automatic method to assemble multi-domain structures from cryo-EM maps through a progressive structural refinement procedure combining rigid-body domain fitting and flexible assembly simulations with deep neural network inter-domain distance profiles. The method was tested on a large-scale benchmark set of proteins containing up to twelve continuous and discontinuous domains with medium-to-low-resolution density maps, where DEMO-EM produced models with correct inter-domain orientations (TM-score >0.5) for 98% of cases and significantly outperformed the state-of-the-art methods. DEMO-EM was applied to SARS-Cov-2 coronavirus genome and generated models with average TM-score/RMSD of 0.97/1.4A to the deposited structures. These results demonstrated an efficient pipeline that enables automated and reliable large-scale multi-domain protein structure modeling with atomic-level accuracy from cryo-EM maps. Twit Text FOAVip Progressive and accurate assembly of multi-domain protein structures from cryo-EM density maps ????bioRxiv http://www.kidney.de/pget.php?&tw=1&pmid=33083802 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33083802 #FOAvip English Wikipedia <ref>{{Cite pmid|33083802}}</ref> Progressive and accurate assembly of multi-domain protein structures from cryo-EM density maps #MMPMID33083802 Zhou X; Li Y; Zhang C; Zheng W; Zhang G; Zhang Y bioRxiv 2020[Oct]; ? (?): ? PMID33083802show ga Progress in cryo-electron microscopy (cryo-EM) has provided the potential for large-size protein structure determination. However, the solution rate for multi-domain proteins remains low due to the difficulty in modeling inter-domain orientations. We developed DEMO-EM, an automatic method to assemble multi-domain structures from cryo-EM maps through a progressive structural refinement procedure combining rigid-body domain fitting and flexible assembly simulations with deep neural network inter-domain distance profiles. The method was tested on a large-scale benchmark set of proteins containing up to twelve continuous and discontinuous domains with medium-to-low-resolution density maps, where DEMO-EM produced models with correct inter-domain orientations (TM-score >0.5) for 98% of cases and significantly outperformed the state-of-the-art methods. DEMO-EM was applied to SARS-Cov-2 coronavirus genome and generated models with average TM-score/RMSD of 0.97/1.4A to the deposited structures. These results demonstrated an efficient pipeline that enables automated and reliable large-scale multi-domain protein structure modeling with atomic-level accuracy from cryo-EM maps. ?Progressive and accurate assembly of multi-domain protein structures f(epmc).pdf DeepDyve Pubget Overpricing