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10.1093/nar/gkab977 http://scihub22266oqcxt.onion/10.1093/nar/gkab977 34761257!8689960!34761257     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Nucleic+Acids+Res 2022 ; 50 (D1): D858-D866 Nephropedia Template TP {{tp|p=34761257|t=2022. SCoV2-MD: a database for the dynamics of the SARS-CoV-2 proteome and variant impact predictions |pdf=|usr=}}{{34761257}} gab.com Text SCoV2-MD: a database for the dynamics of the SARS-CoV-2 proteome and variant impact predictions JO: Nucleic Acids Res http://www.kidney.de/pget.php?&tw=1&pmid=34761257 #FOAvip SCoV2-MD (www.scov2-md.org) is a new online resource that systematically organizes atomistic simulations of the SARS-CoV-2 proteome. The database includes simulations produced by leading groups using molecular dynamics (MD) methods to investigate the structure-dynamics-function relationships of viral proteins. SCoV2-MD cross-references the molecular data with the pandemic evolution by tracking all available variants sequenced during the pandemic and deposited in the GISAID resource. SCoV2-MD enables the interactive analysis of the deposited trajectories through a web interface, which enables users to search by viral protein, isolate, phylogenetic attributes, or specific point mutation. Each mutation can then be analyzed interactively combining static (e.g. a variety of amino acid substitution penalties) and dynamic (time-dependent data derived from the dynamics of the local geometry) scores. Dynamic scores can be computed on the basis of nine non-covalent interaction types, including steric properties, solvent accessibility, hydrogen bonding, and other types of chemical interactions. Where available, experimental data such as antibody escape and change in binding affinities from deep mutational scanning experiments are also made available. All metrics can be combined to build predefined or custom scores to interrogate the impact of evolving variants on protein structure and function. Twit Text FOAVip SCoV2-MD: a database for the dynamics of the SARS-CoV-2 proteome and variant impact predictions ????Nucleic Acids Res http://www.kidney.de/pget.php?&tw=1&pmid=34761257 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34761257 #FOAvip English Wikipedia <ref>{{Cite pmid|34761257}}</ref> SCoV2-MD: a database for the dynamics of the SARS-CoV-2 proteome and variant impact predictions #MMPMID34761257 Torrens-Fontanals M; Peralta-Garcia A; Talarico C; Guixa-Gonzalez R; Giorgino T; Selent J Nucleic Acids Res 2022[Jan]; 50 (D1): D858-D866 PMID34761257show ga SCoV2-MD (www.scov2-md.org) is a new online resource that systematically organizes atomistic simulations of the SARS-CoV-2 proteome. The database includes simulations produced by leading groups using molecular dynamics (MD) methods to investigate the structure-dynamics-function relationships of viral proteins. SCoV2-MD cross-references the molecular data with the pandemic evolution by tracking all available variants sequenced during the pandemic and deposited in the GISAID resource. SCoV2-MD enables the interactive analysis of the deposited trajectories through a web interface, which enables users to search by viral protein, isolate, phylogenetic attributes, or specific point mutation. Each mutation can then be analyzed interactively combining static (e.g. a variety of amino acid substitution penalties) and dynamic (time-dependent data derived from the dynamics of the local geometry) scores. Dynamic scores can be computed on the basis of nine non-covalent interaction types, including steric properties, solvent accessibility, hydrogen bonding, and other types of chemical interactions. Where available, experimental data such as antibody escape and change in binding affinities from deep mutational scanning experiments are also made available. All metrics can be combined to build predefined or custom scores to interrogate the impact of evolving variants on protein structure and function. |*Databases, Genetic[MESH] |*Molecular Dynamics Simulation[MESH] |*Software[MESH] |COVID-19/*virology[MESH] |Evolution, Molecular[MESH] |Gene Expression Regulation, Viral[MESH] |Genome, Viral[MESH] |Humans[MESH] |Hydrogen Bonding[MESH] |Internet[MESH] |Models, Molecular[MESH] |Phylogeny[MESH] |Point Mutation[MESH] |Protein Binding[MESH] |Protein Interaction Mapping[MESH] |SARS-CoV-2/*genetics/growth & development/metabolism/pathogenicity[MESH] |Structure-Activity Relationship[MESH]SCoV2-MD: a database for the dynamics of the SARS-CoV-2 proteome and v(epmc).pdf DeepDyve Pubget Overpricing