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dc.contributor.authorXiao, Xingqing
dc.contributor.authorWang, Yiming
dc.contributor.authorSeroski, Dillon T.
dc.contributor.authorWong, Kong M.
dc.contributor.authorLiu, Renjie
dc.contributor.authorParavastu, Anant K.
dc.contributor.authorHudalla, Gregory A.
dc.contributor.authorHall, Carol K.
dc.date.accessioned2021-07-13T15:00:36Z
dc.date.available2021-07-13T15:00:36Z
dc.date.issued2021
dc.identifier.urihttp://hdl.handle.net/1853/64905
dc.identifier.urihttps://doi.org/10.35090/gatech/x02
dc.descriptionX. Xiao, Y. Wang, D. T. Seroski, K. M. Wong, R. Liu, A. K. Paravastu, G. A. Hudalla, C. K. Hall. De Novo Design of Peptides that Co-assemble into β-sheet Based Nanofibrils. Science Advances (2021). This readme file describes the data files and supplementary files accompanying the above publication.en_US
dc.description.abstractPeptides’ hierarchical co-assembly into nanostructures enables controllable fabrication of multicomponent biomaterials. In this work, we describe a novel computational and experimental approach to design pairs of charge-complementary peptides that selectively co-assemble into β-sheet nanofibers when mixed together, but remain unassembled when isolated separately. The key advance is a pep_tide _c_o-_a_ssembly _d_esign (PepCAD) algorithm that searches for pairs of co-assembling peptides. Six peptide pairs are identified from a pool of ~106 candidates via the PepCAD algorithm and then subjected to DMD/PRIME20 simulations to examine their co-/self-association kinetics. The five pairs that spontaneously aggregate in kinetic simulations selectively co-assemble in biophysical experiments, with four forming β-sheet nanofibers, and one forming a stable non-fibrillar aggregate. Solid-state NMR, which is applied to characterize the co-assembling pairs, suggests that the _in-silico peptides exhibit a higher degree of structural order than the previously reported CATCH(+/-) peptides.
dc.description.sponsorshipNational Science Foundation Division of Chemical, Bioengineering, Environmental and Transport Systems Grant 1743432; National Science Foundation Division of Advanced Cyberinfrastructure Grant 1548562en_US
dc.publisherGeorgia Institute of Technologyen_US
dc.rightsCreative Commons Attribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleDe Novo Design of Peptides that Co-assemble into β-sheet Based Nanofibrils Dataseten_US
dc.typeDataseten_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Chemical and Biomolecular Engineeringen_US


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Creative Commons Attribution 4.0 International
Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0 International