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10.1073/pnas.1607178113 http://scihub22266oqcxt.onion/10.1073/pnas.1607178113 C5127300!5127300!27810958     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Proc+Natl+Acad+Sci+U+S+A 2016 ; 113 (47): E7438-47 Nephropedia Template TP {{tp|p=27810958|t=2016. Tertiary alphabet for the observable protein structural universe |pdf=|usr=}}{{27810958}} gab.com Text Tertiary alphabet for the observable protein structural universe JO: Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=27810958 #FOAvip Proteins fold into intricate 3D structures, determined by their amino acid sequences. Different proteins can fold into drastically different structures, and the space of all possible structures appears hopelessly complex. However, this is precisely the space that needs to be described to understand how sequence encodes structure. In this paper, we decompose the set of known protein structures into standard reusable building blocks, which we call tertiary structural motifs (TERMs). Strikingly, we find that only ?600 TERMs describe 50% of the known protein structural universe at sub-Angstrom resolution. Furthermore, we find the natural utilization of TERMs gives us a means of uncovering sequence?structure relationships. These insights can be harnessed for protein structure prediction, protein design, and other applications. Twit Text FOAVip Tertiary alphabet for the observable protein structural universe ????Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=27810958 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27810958 #FOAvip English Wikipedia <ref>{{Cite pmid|27810958}}</ref> Tertiary alphabet for the observable protein structural universe #MMPMID27810958 Mackenzie CO; Zhou J; Grigoryan G Proc Natl Acad Sci U S A 2016[Nov]; 113 (47): E7438-47 PMID27810958show ga Proteins fold into intricate 3D structures, determined by their amino acid sequences. Different proteins can fold into drastically different structures, and the space of all possible structures appears hopelessly complex. However, this is precisely the space that needs to be described to understand how sequence encodes structure. In this paper, we decompose the set of known protein structures into standard reusable building blocks, which we call tertiary structural motifs (TERMs). Strikingly, we find that only ?600 TERMs describe 50% of the known protein structural universe at sub-Angstrom resolution. Furthermore, we find the natural utilization of TERMs gives us a means of uncovering sequence?structure relationships. These insights can be harnessed for protein structure prediction, protein design, and other applications. äTertiary alphabet for the observable protein structural universe (epmc).pdf DeepDyve Pubget Overpricing