title: Alternative computational protocols for supercharging protein surfaces for reversible unfolding and retention of stability.
abstract: Reengineering protein surfaces to exhibit high net charge, referred to as "supercharging", can improve reversibility of unfolding by preventing aggregation of partially unfolded states. Incorporation of charged side chains should be optimized while considering structural and energetic consequences, as numerous mutations and accumulation of like-charges can also destabilize the native state. A previously demonstrated approach deterministically mutates flexible polar residues (amino acids DERKNQ) with the fewest average neighboring atoms per side chain atom (AvNAPSA). Our approach uses Rosetta-based energy calculations to choose the surface mutations. Both protocols are available for use through the ROSIE web server. The automated Rosetta and AvNAPSA approaches for supercharging choose dissimilar mutations, raising an interesting division in surface charging strategy. Rosetta-supercharged variants of GFP (RscG) ranging from -11 to -61 and +7 to +58 were experimentally tested, and for comparison, we re-tested the previously developed AvNAPSA-supercharged variants of GFP (AscG) with +36 and -30 net charge. Mid-charge variants demonstrated ∼3-fold improvement in refolding with retention of stability. However, as we pushed to higher net charges, expression and soluble yield decreased, indicating that net charge or mutational load may be limiting factors. Interestingly, the two different approaches resulted in GFP variants with similar refolding properties. Our results show that there are multiple sets of residues that can be mutated to successfully supercharge a protein, and combining alternative supercharge protocols with experimental testing can be an effective approach for charge-based improvement to refolding.
authors.affiliation: Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.
authors.forename: Bryan S
authors.initials: BS
authors.lastname: Der
authors.forename: Christien
authors.initials: C
authors.lastname: Kluwe
authors.forename: Aleksandr E
authors.initials: AE
authors.lastname: Miklos
authors.forename: Ron
authors.initials: R
authors.lastname: Jacak
authors.forename: Sergey
authors.initials: S
authors.lastname: Lyskov
authors.forename: Jeffrey J
authors.initials: JJ
authors.lastname: Gray
authors.forename: George
authors.initials: G
authors.lastname: Georgiou
authors.forename: Andrew D
authors.initials: AD
authors.lastname: Ellington
authors.forename: Brian
authors.initials: B
authors.lastname: Kuhlman
mesh_terms: D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry* / Q000235:genetics; D000818:Animals; D003063:Cnidaria; D049452:Green Fluorescent Proteins / Q000737:chemistry* / Q000235:genetics; D006860:Hydrogen Bonding; D008958:Models, Molecular; D008969:Molecular Sequence Data; D009154:Mutation; D011487:Protein Conformation; D015202:Protein Engineering; D055550:Protein Stability; D058767:Protein Unfolding; D012984:Software; D055672:Static Electricity; D013816:Thermodynamics
chemical_list: D000596:Amino Acids; D049452:Green Fluorescent Proteins