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10.1002/prot.26176 http://scihub22266oqcxt.onion/10.1002/prot.26176 34245187!ä!34245187 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 253.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Proteins 2021 ; 89 (11): 1541-1556 Nephropedia Template TP {{tp|p=34245187|t=2021. A fast protein binding site comparison algorithm for proteome-wide protein function prediction and drug repurposing |pdf=|usr=}}{{34245187}} gab.com Text A fast protein binding site comparison algorithm for proteome-wide protein function prediction and drug repurposing JO: Proteins http://www.kidney.de/pget.php?&tw=1&pmid=34245187 #FOAvip The expansion of three-dimensional protein structures and enhanced computing power have significantly facilitated our understanding of protein sequence/structure/function relationships. A challenge in structural genomics is to predict the function of uncharacterized proteins. Protein function deconvolution based on global sequence or structural homology is impracticable when a protein relates to no other proteins with known function, and in such cases, functional relationships can be established by detecting their local ligand binding site similarity. Here, we introduce a sequence order-independent comparison algorithm, PocketShape, for structural proteome-wide exploration of protein functional site by fully considering the geometry of the backbones, orientation of the sidechains, and physiochemical properties of the pocket-lining residues. PocketShape is efficient in distinguishing similar from dissimilar ligand binding site pairs by retrieving 99.3% of the similar pairs while rejecting 100% of the dissimilar pairs on a dataset containing 1538 binding site pairs. This method successfully classifies 83 enzyme structures with diverse functions into 12 clusters, which is highly in accordance with the actual structural classification of proteins classification. PocketShape also achieves superior performances than other methods in protein profiling based on experimental data. Potential new applications for representative SARS-CoV-2 drugs Remdesivir and 11a are predicted. The high accuracy and time-efficient characteristics of PocketShape will undoubtedly make it a promising complementary tool for proteome-wide protein function inference and drug repurposing study. Twit Text FOAVip A fast protein binding site comparison algorithm for proteome-wide protein function prediction and drug repurposing ????Proteins http://www.kidney.de/pget.php?&tw=1&pmid=34245187 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34245187 #FOAvip English Wikipedia <ref>{{Cite pmid|34245187}}</ref> A fast protein binding site comparison algorithm for proteome-wide protein function prediction and drug repurposing #MMPMID34245187 Li S; Cai C; Gong J; Liu X; Li H Proteins 2021[Nov]; 89 (11): 1541-1556 PMID34245187show ga The expansion of three-dimensional protein structures and enhanced computing power have significantly facilitated our understanding of protein sequence/structure/function relationships. A challenge in structural genomics is to predict the function of uncharacterized proteins. Protein function deconvolution based on global sequence or structural homology is impracticable when a protein relates to no other proteins with known function, and in such cases, functional relationships can be established by detecting their local ligand binding site similarity. Here, we introduce a sequence order-independent comparison algorithm, PocketShape, for structural proteome-wide exploration of protein functional site by fully considering the geometry of the backbones, orientation of the sidechains, and physiochemical properties of the pocket-lining residues. PocketShape is efficient in distinguishing similar from dissimilar ligand binding site pairs by retrieving 99.3% of the similar pairs while rejecting 100% of the dissimilar pairs on a dataset containing 1538 binding site pairs. This method successfully classifies 83 enzyme structures with diverse functions into 12 clusters, which is highly in accordance with the actual structural classification of proteins classification. PocketShape also achieves superior performances than other methods in protein profiling based on experimental data. Potential new applications for representative SARS-CoV-2 drugs Remdesivir and 11a are predicted. The high accuracy and time-efficient characteristics of PocketShape will undoubtedly make it a promising complementary tool for proteome-wide protein function inference and drug repurposing study. |*Algorithms[MESH] |Adenosine Monophosphate/analogs & derivatives/chemistry/metabolism/pharmacology[MESH] |Alanine/analogs & derivatives/chemistry/metabolism/pharmacology[MESH] |Antiviral Agents/chemistry/*pharmacology[MESH] |Binding Sites[MESH] |Coronavirus 3C Proteases/chemistry/metabolism[MESH] |Databases, Protein[MESH] |Drug Repositioning/*methods[MESH] |GTP Phosphohydrolases/chemistry/metabolism[MESH] |Phosphoglycerate Mutase/chemistry/metabolism[MESH] |Proteins/chemistry/classification/*metabolism[MESH] |ROC Curve[MESH]A fast protein binding site comparison algorithm for proteome-wide pro(epmc).pdf DeepDyve Pubget Overpricing