A fragment-based protein interface design algorithm for symmetric assemblies

ABSTRACT Theoretical and experimental advances in protein engineering have led to the creation of precisely defined, novel protein assemblies of great size and complexity, with diverse applications. One powerful approach involves designing a new attachment or binding interface between two simpler sy...

Full description

Saved in:
Bibliographic Details
Published inbioRxiv
Main Authors Laniado, Joshua, Meador, Kyle, Yeates, Todd O
Format Paper
LanguageEnglish
Published Cold Spring Harbor Cold Spring Harbor Laboratory Press 14.01.2021
Cold Spring Harbor Laboratory
Edition1.1
Subjects
Online AccessGet full text
ISSN2692-8205
2692-8205
DOI10.1101/2021.01.13.426605

Cover

More Information
Summary:ABSTRACT Theoretical and experimental advances in protein engineering have led to the creation of precisely defined, novel protein assemblies of great size and complexity, with diverse applications. One powerful approach involves designing a new attachment or binding interface between two simpler symmetric oligomeric protein components. The required methods of design, which present both similarities and key differences compared to problems in protein docking, remain challenging, and are not yet routine. With the aim of more fully enabling this emerging area of protein material engineering, we developed a computer program, Nanohedra, to introduce two key advances. First, we encoded in the program the construction rules (i.e. the search space parameters) that underlie all possible symmetric material constructions. Second, we developed algorithms for rapidly identifying favorable docking/interface arrangements based on tabulations of empirical patterns of known protein fragment-pair associations. As a result, the candidate poses that Nanohedra generates for subsequent amino acid interface design appear highly native-like (at the protein backbone level), while simultaneously conforming to the exacting requirements for symmetry-based assembly. A retrospective computational analysis of successful vs failed experimental studies supports the expectation that this should improve the success rate for this challenging area of protein engineering. Competing Interest Statement The authors have declared no competing interest. Footnotes * https://github.com/nanohedra/nanohedra
Bibliography:SourceType-Working Papers-1
ObjectType-Working Paper/Pre-Print-1
content type line 50
Competing Interest Statement: The authors have declared no competing interest.
ISSN:2692-8205
2692-8205
DOI:10.1101/2021.01.13.426605