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10.1080/07391102.2021.1908170 http://scihub22266oqcxt.onion/10.1080/07391102.2021.1908170 33797336!8043164!33797336     free     free     free Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Biomol+Struct+Dyn 2022 ; 40 (18): 8216-8231 Nephropedia Template TP {{tp|p=33797336|t=2022. In silico characterization of mutations circulating in SARS-CoV-2 structural proteins |pdf=|usr=}}{{33797336}} gab.com Text In silico characterization of mutations circulating in SARS-CoV-2 structural proteins JO: J Biomol Struct Dyn http://www.kidney.de/pget.php?&tw=1&pmid=33797336 #FOAvip SARS-CoV-2 has recently emerged as a pandemic that has caused more than 2.4 million deaths worldwide. Since the onset of infections, several full-length sequences of viral genome have been made available which have been used to gain insights into viral dynamics. We utilised a meta-data driven comparative analysis tool for sequences (Meta-CATS) algorithm to identify mutations in 829 SARS-CoV-2 genomes from around the world. The algorithm predicted sixty-one mutations among SARS-CoV-2 genomes. We observed that most of the mutations were concentrated around three protein coding genes viz nsp3 (non-structural protein 3), RdRp (RNA-directed RNA polymerase) and Nucleocapsid (N) proteins of SARS-CoV-2. We used various computational tools including normal mode analysis (NMA), C-alpha discrete molecular dynamics (DMD) and all-atom molecular dynamic simulations (MD) to study the effect of mutations on functionality, stability and flexibility of SARS-CoV-2 structural proteins including envelope (E), N and spike (S) proteins. PredictSNP predictor suggested that four mutations (L37H in E, R203K and P344S in N and D614G in S) out of seven were predicted to be neutral whilst the remaining ones (P13L, S197L and G204R in N) were predicted to be deleterious in nature thereby impacting protein functionality. NMA, C-alpha DMD and all-atom MD suggested some mutations to have stabilizing roles (P13L, S197L and R203K in N protein) where remaining ones were predicted to destabilize mutant protein. In summary, we identified significant mutations in SARS-CoV-2 genomes as well as used computational approaches to further characterize the possible effect of highly significant mutations on SARS-CoV-2 structural proteins.Communicated by Ramaswamy H. Sarma. Twit Text FOAVip In silico characterization of mutations circulating in SARS-CoV-2 structural proteins ????J Biomol Struct Dyn http://www.kidney.de/pget.php?&tw=1&pmid=33797336 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33797336 #FOAvip English Wikipedia <ref>{{Cite pmid|33797336}}</ref> In silico characterization of mutations circulating in SARS-CoV-2 structural proteins #MMPMID33797336 Periwal N; Rathod SB; Pal R; Sharma P; Nebhnani L; Barnwal RP; Arora P; Srivastava KR; Sood V J Biomol Struct Dyn 2022[Nov]; 40 (18): 8216-8231 PMID33797336show ga SARS-CoV-2 has recently emerged as a pandemic that has caused more than 2.4 million deaths worldwide. Since the onset of infections, several full-length sequences of viral genome have been made available which have been used to gain insights into viral dynamics. We utilised a meta-data driven comparative analysis tool for sequences (Meta-CATS) algorithm to identify mutations in 829 SARS-CoV-2 genomes from around the world. The algorithm predicted sixty-one mutations among SARS-CoV-2 genomes. We observed that most of the mutations were concentrated around three protein coding genes viz nsp3 (non-structural protein 3), RdRp (RNA-directed RNA polymerase) and Nucleocapsid (N) proteins of SARS-CoV-2. We used various computational tools including normal mode analysis (NMA), C-alpha discrete molecular dynamics (DMD) and all-atom molecular dynamic simulations (MD) to study the effect of mutations on functionality, stability and flexibility of SARS-CoV-2 structural proteins including envelope (E), N and spike (S) proteins. PredictSNP predictor suggested that four mutations (L37H in E, R203K and P344S in N and D614G in S) out of seven were predicted to be neutral whilst the remaining ones (P13L, S197L and G204R in N) were predicted to be deleterious in nature thereby impacting protein functionality. NMA, C-alpha DMD and all-atom MD suggested some mutations to have stabilizing roles (P13L, S197L and R203K in N protein) where remaining ones were predicted to destabilize mutant protein. In summary, we identified significant mutations in SARS-CoV-2 genomes as well as used computational approaches to further characterize the possible effect of highly significant mutations on SARS-CoV-2 structural proteins.Communicated by Ramaswamy H. Sarma. |*COVID-19/genetics[MESH] |*SARS-CoV-2/genetics[MESH] |Computational Biology[MESH] |Humans[MESH] |Mutant Proteins/genetics[MESH] |Mutation[MESH] |RNA-Dependent RNA Polymerase/genetics[MESH]In silico characterization of mutations circulating in SARS-CoV-2 stru(epmc).pdf DeepDyve Pubget Overpricing