Sequence Characterization and Molecular Modeling of Clinically Relevant Variants of the SARS-CoV‑2 Main Protease
The SARS-CoV-2 main protease (M pro ) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for inhibitor design. However, as for any virus, SARS-CoV-2 is subject to constant neutral drift and selection pressure, with new M pro mutations arisi...
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| Published in | Biochemistry (Easton) Vol. 59; no. 39; pp. 3741 - 3756 |
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| Main Authors | , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
American Chemical Society
06.10.2020
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| Subjects | |
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| Abstract | The SARS-CoV-2 main protease (M pro ) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for inhibitor design. However, as for any virus, SARS-CoV-2 is subject to constant neutral drift and selection pressure, with new M pro mutations arising over time. Identification and structural characterization of M pro variants is thus critical for robust inhibitor design. Here we report sequence analysis, structure predictions, and molecular modeling for seventy-nine M pro variants, constituting all clinically observed mutations in this protein as of April 29, 2020. Residue substitution is widely distributed, with some tendency toward larger and more hydrophobic residues. Modeling and protein structure network analysis suggest differences in cohesion and active site flexibility, revealing patterns in viral evolution that have relevance for drug discovery. |
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| AbstractList | The SARS-CoV-2 main protease (Mpro) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for inhibitor design. However, as for any virus, SARS-CoV-2 is subject to constant neutral drift and selection pressure, with new Mpro mutations arising over time. Identification and structural characterization of Mpro variants is thus critical for robust inhibitor design. Here we report sequence analysis, structure predictions, and molecular modeling for seventy-nine Mpro variants, constituting all clinically observed mutations in this protein as of April 29, 2020. Residue substitution is widely distributed, with some tendency toward larger and more hydrophobic residues. Modeling and protein structure network analysis suggest differences in cohesion and active site flexibility, revealing patterns in viral evolution that have relevance for drug discovery.The SARS-CoV-2 main protease (Mpro) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for inhibitor design. However, as for any virus, SARS-CoV-2 is subject to constant neutral drift and selection pressure, with new Mpro mutations arising over time. Identification and structural characterization of Mpro variants is thus critical for robust inhibitor design. Here we report sequence analysis, structure predictions, and molecular modeling for seventy-nine Mpro variants, constituting all clinically observed mutations in this protein as of April 29, 2020. Residue substitution is widely distributed, with some tendency toward larger and more hydrophobic residues. Modeling and protein structure network analysis suggest differences in cohesion and active site flexibility, revealing patterns in viral evolution that have relevance for drug discovery. The SARS-CoV-2 main protease (M ) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for inhibitor design. However, as for any virus, SARS-CoV-2 is subject to constant neutral drift and selection pressure, with new M mutations arising over time. Identification and structural characterization of M variants is thus critical for robust inhibitor design. Here we report sequence analysis, structure predictions, and molecular modeling for seventy-nine M variants, constituting all clinically observed mutations in this protein as of April 29, 2020. Residue substitution is widely distributed, with some tendency toward larger and more hydrophobic residues. Modeling and protein structure network analysis suggest differences in cohesion and active site flexibility, revealing patterns in viral evolution that have relevance for drug discovery. The SARS-CoV-2 main protease (Mᵖʳᵒ) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for inhibitor design. However, as for any virus, SARS-CoV-2 is subject to constant neutral drift and selection pressure, with new Mᵖʳᵒ mutations arising over time. Identification and structural characterization of Mᵖʳᵒ variants is thus critical for robust inhibitor design. Here we report sequence analysis, structure predictions, and molecular modeling for seventy-nine Mᵖʳᵒ variants, constituting all clinically observed mutations in this protein as of April 29, 2020. Residue substitution is widely distributed, with some tendency toward larger and more hydrophobic residues. Modeling and protein structure network analysis suggest differences in cohesion and active site flexibility, revealing patterns in viral evolution that have relevance for drug discovery. The SARS-CoV-2 main protease (M pro ) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for inhibitor design. However, as for any virus, SARS-CoV-2 is subject to constant neutral drift and selection pressure, with new M pro mutations arising over time. Identification and structural characterization of M pro variants is thus critical for robust inhibitor design. Here we report sequence analysis, structure predictions, and molecular modeling for seventy-nine M pro variants, constituting all clinically observed mutations in this protein as of April 29, 2020. Residue substitution is widely distributed, with some tendency toward larger and more hydrophobic residues. Modeling and protein structure network analysis suggest differences in cohesion and active site flexibility, revealing patterns in viral evolution that have relevance for drug discovery. The SARS-CoV-2 main protease (M pro ) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for inhibitor design. However, as for any virus, SARS-CoV-2 is subject to constant neutral drift and selection pressure, with new M pro mutations arising over time. Identification and structural characterization of M pro variants is thus critical for robust inhibitor design. Here we report sequence analysis, structure predictions, and molecular modeling for seventy-nine M pro variants, constituting all clinically observed mutations in this protein as of April 29, 2020. Residue substitution is widely distributed, with some tendency toward larger and more hydrophobic residues. Modeling and protein structure network analysis suggest differences in cohesion and active site flexibility, revealing patterns in viral evolution that have relevance for drug discovery. |
| Author | Farahmand, Vesta Takahashi, Gemma R Zhuang, Shannon Diessner, Elizabeth M Crosby, Marquise G Cross, Thomas J Martin, Rachel W Butts, Carter T |
| AuthorAffiliation | Department of Chemistry California Institute for Telecommunications and Information Technology Departments of Sociology, Statistics, Computer Science, and Electrical Engineering and Computer Science Department of Molecular Biology and Biochemistry |
| AuthorAffiliation_xml | – name: Department of Molecular Biology and Biochemistry – name: California Institute for Telecommunications and Information Technology – name: Department of Chemistry – name: Departments of Sociology, Statistics, Computer Science, and Electrical Engineering and Computer Science – name: ǁ California Institute for Telecommunications and Information Technology, UC Irvine – name: Department of Chemistry, University of California, Irvine, CA 92697-2025, USA – name: Department of Molecular Biology and Biochemistry, University of California, Irvine, CA 92697-3900, USA |
| Author_xml | – sequence: 1 givenname: Thomas J surname: Cross fullname: Cross, Thomas J organization: Department of Chemistry – sequence: 2 givenname: Gemma R surname: Takahashi fullname: Takahashi, Gemma R organization: Department of Molecular Biology and Biochemistry – sequence: 3 givenname: Elizabeth M surname: Diessner fullname: Diessner, Elizabeth M organization: California Institute for Telecommunications and Information Technology – sequence: 4 givenname: Marquise G surname: Crosby fullname: Crosby, Marquise G organization: Department of Molecular Biology and Biochemistry – sequence: 5 givenname: Vesta surname: Farahmand fullname: Farahmand, Vesta organization: Department of Chemistry – sequence: 6 givenname: Shannon surname: Zhuang fullname: Zhuang, Shannon organization: Department of Chemistry – sequence: 7 givenname: Carter T surname: Butts fullname: Butts, Carter T email: buttsc@uci.edu organization: Departments of Sociology, Statistics, Computer Science, and Electrical Engineering and Computer Science – sequence: 8 givenname: Rachel W orcidid: 0000-0001-9996-7411 surname: Martin fullname: Martin, Rachel W email: rwmartin@uci.edu organization: Department of Molecular Biology and Biochemistry |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32931703$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1007/978-1-4899-4541-9 10.1038/s41586-020-2313-x 10.1016/j.abb.2008.01.023 10.1111/j.1558-5646.1985.tb00420.x 10.1093/bioinformatics/btl461 10.1093/nar/gkh340 10.1101/2020.05.29.123190 10.1101/2020.05.15.097493 10.1039/c3dt50599e 10.1016/j.cell.2020.06.043 10.1063/1.445869 10.18637/jss.v024.i01 10.1093/bioinformatics/9.5.523 10.1093/bioinformatics/bty407 10.1002/gch2.1018 10.1017/CBO9780511815478 10.1126/sciadv.abb9153 10.1128/AAC.42.12.3218 10.2147/TCRM.S3285 10.1111/ijcp.13525 10.1074/jbc.M510745200 10.1021/ct300400x 10.1002/prot.20417 10.1056/NEJMoa2001282 10.1074/jbc.M408211200 10.1142/S0219720012500084 10.1093/molbev/msy096 10.1093/nar/13.9.3021 10.1016/S0022-2836(03)00865-9 10.3390/v11010059 10.1021/jp902377q 10.1001/jama.277.2.145 10.1101/2020.06.02.130955 10.1063/1.470648 10.18637/jss.v024.i02 10.1073/pnas.1835675100 10.1074/jbc.M311744200 10.1128/JVI.02612-07 10.1371/journal.pone.0113488 10.1074/jbc.M705240200 10.1063/1.467468 10.1039/C4MB00253A 10.1016/0022-2836(82)90515-0 10.1039/C8IB00140E 10.1142/S0219720006002016 10.1016/j.gheart.2017.01.009 10.1186/s13104-018-3221-0 10.1073/pnas.96.17.9459 10.1021/bi0490237 10.1093/nar/30.11.2515 10.1021/acs.jcim.0c00634 10.1016/j.cub.2020.03.022 10.1038/s41586-020-2012-7 10.1002/jmv.25762 10.1074/jbc.M310875200 10.1101/2020.05.04.075911 10.1002/pro.5560040109 10.1128/JVI.02680-07 10.1515/bchm3.1992.373.2.393 10.1002/jcc.20289 10.3389/fmolb.2019.00042 10.1021/ct100578z 10.3390/v11110979 10.1126/science.abb3405 10.1038/s41586-020-2008-3 10.1002/cpbi.3 10.1016/j.bbagen.2016.12.007 10.1038/s41591-020-0820-9 10.1074/jbc.M502577200 10.1101/2020.05.29.124610 10.7551/mitpress/4175.001.0001 10.1016/0378-8733(83)90028-X |
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| References | ref9/cit9 ref45/cit45 ref3/cit3 ref27/cit27 ref81/cit81 ref63/cit63 Kowalczyk A. (ref58/cit58) 2001 ref16/cit16 ref52/cit52 ref23/cit23 ref8/cit8 ref31/cit31 ref2/cit2 Efron B. (ref56/cit56) 1993 ref77/cit77 ref71/cit71 ref37/cit37 ref20/cit20 ref48/cit48 Scholkopf B. (ref57/cit57) 2001 ref74/cit74 ref17/cit17 ref82/cit82 ref10/cit10 ref35/cit35 ref53/cit53 ref19/cit19 ref21/cit21 Eddelbuettel D. (ref60/cit60) 2017; 5 ref42/cit42 ref46/cit46 ref13/cit13 Idé J. (ref47/cit47) 2017 ref61/cit61 ref75/cit75 ref67/cit67 ref24/cit24 ref38/cit38 ref50/cit50 ref64/cit64 ref78/cit78 Van Rossum G. (ref29/cit29) 1995; 620 ref6/cit6 ref36/cit36 ref18/cit18 ref83/cit83 ref65/cit65 ref79/cit79 ref11/cit11 ref25/cit25 Saitou N. (ref34/cit34) 1987; 4 ref72/cit72 ref76/cit76 ref32/cit32 ref39/cit39 ref14/cit14 ref5/cit5 ref51/cit51 ref43/cit43 ref80/cit80 ref28/cit28 ref40/cit40 ref68/cit68 Wright E. S. (ref22/cit22) 2020 ref26/cit26 ref55/cit55 ref73/cit73 Roser M. (ref66/cit66) 2020 ref69/cit69 ref12/cit12 ref15/cit15 Kwok J. T. (ref59/cit59) 2003 ref62/cit62 ref41/cit41 Wasserman S. (ref54/cit54) 1994; 8 R Core Team (ref49/cit49) 2020 ref33/cit33 ref4/cit4 ref30/cit30 ref84/cit84 ref1/cit1 ref44/cit44 ref70/cit70 ref7/cit7 32511408 - bioRxiv. 2020 May 15 |
| References_xml | – volume-title: An Introduction to the Bootstrap year: 1993 ident: ref56/cit56 doi: 10.1007/978-1-4899-4541-9 – ident: ref65/cit65 doi: 10.1038/s41586-020-2313-x – ident: ref16/cit16 doi: 10.1016/j.abb.2008.01.023 – ident: ref31/cit31 – ident: ref35/cit35 doi: 10.1111/j.1558-5646.1985.tb00420.x – ident: ref48/cit48 doi: 10.1093/bioinformatics/btl461 – ident: ref32/cit32 doi: 10.1093/nar/gkh340 – ident: ref78/cit78 doi: 10.1101/2020.05.29.123190 – ident: ref77/cit77 doi: 10.1101/2020.05.15.097493 – ident: ref51/cit51 doi: 10.1039/c3dt50599e – ident: ref24/cit24 doi: 10.1016/j.cell.2020.06.043 – ident: ref41/cit41 doi: 10.1063/1.445869 – ident: ref44/cit44 doi: 10.18637/jss.v024.i01 – volume-title: Rpdb: Read, Write, Visualize and Manipulate PDB Files year: 2017 ident: ref47/cit47 – year: 2020 ident: ref22/cit22 publication-title: bioRxiv – ident: ref80/cit80 doi: 10.1093/bioinformatics/9.5.523 – ident: ref63/cit63 doi: 10.1093/bioinformatics/bty407 – ident: ref28/cit28 doi: 10.1002/gch2.1018 – volume: 8 volume-title: Social network analysis: methods and applications year: 1994 ident: ref54/cit54 doi: 10.1017/CBO9780511815478 – ident: ref6/cit6 doi: 10.1126/sciadv.abb9153 – ident: ref9/cit9 doi: 10.1128/AAC.42.12.3218 – ident: ref10/cit10 doi: 10.2147/TCRM.S3285 – volume: 4 start-page: 406 year: 1987 ident: ref34/cit34 publication-title: Mol. Biol. Evol. – ident: ref26/cit26 doi: 10.1111/ijcp.13525 – ident: ref20/cit20 doi: 10.1074/jbc.M510745200 – ident: ref40/cit40 doi: 10.1021/ct300400x – ident: ref72/cit72 doi: 10.1002/prot.20417 – ident: ref11/cit11 doi: 10.1056/NEJMoa2001282 – ident: ref19/cit19 doi: 10.1074/jbc.M408211200 – ident: ref50/cit50 doi: 10.1142/S0219720012500084 – volume-title: R: A Language and Environment for Statistical Computing year: 2020 ident: ref49/cit49 – ident: ref33/cit33 doi: 10.1093/molbev/msy096 – ident: ref30/cit30 doi: 10.1093/nar/13.9.3021 – ident: ref12/cit12 doi: 10.1016/S0022-2836(03)00865-9 – ident: ref7/cit7 doi: 10.3390/v11010059 – ident: ref73/cit73 doi: 10.1021/jp902377q – ident: ref8/cit8 doi: 10.1001/jama.277.2.145 – ident: ref23/cit23 doi: 10.1101/2020.06.02.130955 – ident: ref43/cit43 doi: 10.1063/1.470648 – ident: ref45/cit45 doi: 10.18637/jss.v024.i02 – ident: ref18/cit18 doi: 10.1073/pnas.1835675100 – ident: ref46/cit46 doi: 10.18637/jss.v024.i02 – ident: ref13/cit13 doi: 10.1074/jbc.M311744200 – year: 2020 ident: ref66/cit66 publication-title: Our World in Data – ident: ref17/cit17 doi: 10.1128/JVI.02612-07 – start-page: 439 volume-title: Proceedings of the 14th International Conference on Neural Information Processing Systems: Natural and Synthetic year: 2001 ident: ref58/cit58 – ident: ref81/cit81 doi: 10.1371/journal.pone.0113488 – volume: 5 start-page: e3188v1 year: 2017 ident: ref60/cit60 publication-title: PeerJ. Preprints – ident: ref21/cit21 doi: 10.1074/jbc.M705240200 – ident: ref42/cit42 doi: 10.1063/1.467468 – ident: ref82/cit82 doi: 10.1039/C4MB00253A – ident: ref67/cit67 doi: 10.1016/0022-2836(82)90515-0 – ident: ref52/cit52 doi: 10.1039/C8IB00140E – ident: ref62/cit62 doi: 10.1142/S0219720006002016 – ident: ref83/cit83 doi: 10.1016/j.gheart.2017.01.009 – ident: ref68/cit68 doi: 10.1186/s13104-018-3221-0 – ident: ref71/cit71 doi: 10.1073/pnas.96.17.9459 – ident: ref14/cit14 doi: 10.1021/bi0490237 – ident: ref69/cit69 doi: 10.1093/nar/30.11.2515 – ident: ref79/cit79 doi: 10.1021/acs.jcim.0c00634 – ident: ref5/cit5 doi: 10.1016/j.cub.2020.03.022 – ident: ref3/cit3 doi: 10.1038/s41586-020-2012-7 – ident: ref61/cit61 doi: 10.1002/jmv.25762 – ident: ref15/cit15 doi: 10.1074/jbc.M310875200 – ident: ref25/cit25 doi: 10.1101/2020.05.04.075911 – ident: ref70/cit70 doi: 10.1002/pro.5560040109 – ident: ref76/cit76 doi: 10.1128/JVI.02680-07 – ident: ref75/cit75 doi: 10.1515/bchm3.1992.373.2.393 – ident: ref39/cit39 doi: 10.1002/jcc.20289 – ident: ref84/cit84 doi: 10.3389/fmolb.2019.00042 – ident: ref38/cit38 doi: 10.1021/ct100578z – ident: ref4/cit4 doi: 10.3390/v11110979 – ident: ref36/cit36 doi: 10.1126/science.abb3405 – ident: ref1/cit1 doi: 10.1038/s41586-020-2008-3 – ident: ref37/cit37 doi: 10.1002/cpbi.3 – ident: ref55/cit55 doi: 10.1016/j.bbagen.2016.12.007 – ident: ref2/cit2 doi: 10.1038/s41591-020-0820-9 – ident: ref64/cit64 doi: 10.1038/s41586-020-2008-3 – volume: 620 volume-title: Python tutorial year: 1995 ident: ref29/cit29 – ident: ref74/cit74 doi: 10.1074/jbc.M502577200 – ident: ref27/cit27 doi: 10.1101/2020.05.29.124610 – volume-title: Learning with Kernels: Support Vector Machines Regularization, Optimization, and Beyond year: 2001 ident: ref57/cit57 doi: 10.7551/mitpress/4175.001.0001 – ident: ref53/cit53 doi: 10.1016/0378-8733(83)90028-X – volume-title: Proceedings of the Twentieth International Conference on Machine Learning (ICML-2003) year: 2003 ident: ref59/cit59 – reference: 32511408 - bioRxiv. 2020 May 15;: |
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| Snippet | The SARS-CoV-2 main protease (M pro ) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for... The SARS-CoV-2 main protease (M ) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for inhibitor... The SARS-CoV-2 main protease (Mpro) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for... The SARS-CoV-2 main protease (Mᵖʳᵒ) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for... The SARS-CoV-2 main protease (M pro ) is essential to viral replication and cleaves highly specific substrate sequences, making it an obvious target for... |
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| SubjectTerms | active sites Betacoronavirus - enzymology Betacoronavirus - genetics Catalytic Domain cohesion design Drug Discovery drugs Evolution, Molecular Humans hydrophobicity Models, Molecular molecular models Molecular Structure Mutation Phylogeny prediction Protease Inhibitors - chemistry protein structure proteinases SARS-CoV-2 selection pressure sequence analysis Sequence Analysis, Protein Viral Nonstructural Proteins - antagonists & inhibitors Viral Nonstructural Proteins - genetics virus replication viruses |
| Title | Sequence Characterization and Molecular Modeling of Clinically Relevant Variants of the SARS-CoV‑2 Main Protease |
| URI | http://dx.doi.org/10.1021/acs.biochem.0c00462 https://www.ncbi.nlm.nih.gov/pubmed/32931703 https://www.proquest.com/docview/2443518670 https://www.proquest.com/docview/2511174434 https://pubmed.ncbi.nlm.nih.gov/PMC7518256 |
| Volume | 59 |
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