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Tertiary Structural Motif Sequence Statistics Enable Facile Prediction and Design of Peptides that Bind Anti-apoptotic Bfl-1 and Mcl-1
dc.date.accessioned | 2020-04-14T19:29:40Z | |
dc.date.available | 2020-04-14T19:29:40Z | |
dc.identifier.uri | https://hdl.handle.net/1721.1/124632 | |
dc.description.abstract | © 2019 Elsevier Ltd Understanding the relationship between protein sequence and structure well enough to design new proteins with desired functions is a longstanding goal in protein science. Here, we show that recurring tertiary structural motifs (TERMs) in the PDB provide rich information for protein-peptide interaction prediction and design. TERM statistics can be used to predict peptide binding energies for Bcl-2 family proteins as accurately as widely used structure-based tools. Furthermore, design using TERM energies (dTERMen) rapidly and reliably generates high-affinity peptide binders of anti-apoptotic proteins Bfl-1 and Mcl-1 with just 15%–38% sequence identity to any known native Bcl-2 family protein ligand. High-resolution structures of four designed peptides bound to their targets provide opportunities to analyze the strengths and limitations of the computational design method. Our results support dTERMen as a powerful approach that can complement existing tools for protein engineering. | en_US |
dc.language.iso | en | |
dc.publisher | Elsevier BV | en_US |
dc.relation.isversionof | 10.1016/J.STR.2019.01.008 | en_US |
dc.rights | Creative Commons Attribution-NonCommercial-NoDerivs License | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | en_US |
dc.source | PMC | en_US |
dc.title | Tertiary Structural Motif Sequence Statistics Enable Facile Prediction and Design of Peptides that Bind Anti-apoptotic Bfl-1 and Mcl-1 | en_US |
dc.type | Article | en_US |
dc.identifier.citation | "Tertiary Structural Motif Sequence Statistics Enable Facile Prediction and Design of Peptides that Bind Anti-apoptotic Bfl-1 and Mcl-1." Structure, 27 (4). | |
dc.relation.journal | Structure | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2020-04-06T17:26:56Z | |
dspace.date.submission | 2020-04-06T17:26:58Z | |
mit.journal.volume | 27 | en_US |
mit.journal.issue | 4 | en_US |
mit.license | PUBLISHER_CC |