Using natural sequences and modularity to design common and novel protein topologies.
Protein design is still a challenging undertaking, often requiring multiple attempts or iterations for success. Typically, the source of failure is unclear, and scoring metrics appear similar between successful and failed cases. Nevertheless, the use of sequence statistics, modularity and symmetry from natural proteins, combined with computational design both at the coarse-grained and atomistic levels is propelling a new wave of design efforts to success. Here we highlight recent examples of design, showing how the wealth of natural protein sequence and topology data may be leveraged to reduce the search space and increase the likelihood of achieving desired outcomes.
Department of Chemistry, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1.
Aron
A
Broom
Department of Chemistry, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1.
Kyle
K
Trainor
Department of Chemistry, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1.
Duncan Ws
DW
MacKenzie
Department of Chemistry, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1. Electronic address: meiering@uwaterloo.ca.
Elizabeth M
EM
Meiering
D000595:Amino Acid Sequence; D019295:Computational Biology; D015202:Protein Engineering / Q000379:methods*; D011506:Proteins / Q000737:chemistry* / Q000235:genetics*
D011506:Proteins