Open Access
A fragment-based protein interface design algorithm for symmetric assemblies
Author(s) -
Joshua Laniado,
Kyle Meador,
Todd O. Yeates
Publication year - 2021
Publication title -
protein engineering, design and selection
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.627
H-Index - 109
eISSN - 1741-0134
pISSN - 1741-0126
DOI - 10.1093/protein/gzab008
Subject(s) - computer science , protein engineering , interface (matter) , fragment (logic) , protein design , key (lock) , algorithm , protein structure , theoretical computer science , distributed computing , chemistry , biochemistry , parallel computing , computer security , bubble , maximum bubble pressure method , enzyme
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.