Computational protein design with explicit consideration of surface hydrophobic patches

De novo protein design requires the identification of amino-acid sequences that favor the target folded conformation and are soluble in water. One strategy for promoting solubility is to disallow hydrophobic residues on the protein surface during design. However, naturally occurring proteins often have hydrophobic amino acids on their surface that contribute to protein stability via the partial burial of hydrophobic surface area or play a key role in the formation of protein-protein interactions. A less restrictive approach for surface design that is used by the modeling program Rosetta is to parameterize the energy function so that the number of hydrophobic amino acids designed on the protein surface is similar to what is observed in naturally occurring monomeric proteins. Previous studies with Rosetta have shown that this limits surface hydrophobics to the naturally occurring frequency (~28%) but that it does not prevent the formation of hydrophobic patches that are considerably larger than those observed in naturally occurring proteins. Here, we describe a new score term that explicitly detects and penalizes the formation of hydrophobic patches during computational protein design. With the new term we are able to design protein surfaces that include hydrophobic amino acids at naturally occurring frequencies, but do not have large hydrophobic patches. By adjusting the strength of the new score term the emphasis of surface redesigns can be switched between maintaining solubility and maximizing folding free energy

Alternative Computational Protocols for Supercharging Protein Surfaces for Reversible Unfolding and Retention of Stability

Bryan S. Der, Ron Jacak, Brian Kuhlman, Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of AmericaChristien Kluwe, Aleksandr E. Miklos, Andrew D. Ellington , Center for Systems and Synthetic Biology, University of Texas at Austin, Austin, Texas, United States of AmericaChristien Kluwe, Aleksandr E. Miklos, George Georgiou, Andrew D. Ellington, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, United States of AmericaAleksandr E. Miklos, Andrew D. Ellington , Applied Research Laboratories, University of Texas at Austin, Austin, Texas, United States of AmericaSergey Lyskov, Jeffrey J. Gray, Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, United States of AmericaBrian Kuhlman, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of AmericaReengineering 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.This work was supported by the Defense Advanced Research Projects Agency (HR-0011-10-1-0052 to A.E.) and the Welch Foundation (F-1654 to A.E.), the National Institutes of Health grants GM073960 (B.K.) and R01-GM073151 (J.G. and S.L.), the Rosetta Commons (S.L.), the National Science Foundation graduate research fellowship (2009070950 to B.D.), the UNC Royster Society Pogue fellowship (B.D.), and National Institutes of Health grant T32GM008570 for the UNC Program in Molecular and Cellular Biophysics. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Center for Systems and Synthetic BiologyCellular and Molecular BiologyApplied Research LaboratoriesEmail: [email protected]

The Length Dependence of the PolyQ-mediated Protein Aggregation

Polyglutamine (polyQ) repeat disorders are caused by the expansion of CAG tracts in certain genes, resulting in transcription of proteins with abnormally long polyQ inserts. When these inserts expand beyond 35-45 glutamines, affected proteins form toxic aggregates, leading to neuron death. Chymotrypsin inhibitor 2 (CI2) with an inserted glutamine repeat has previously been used to model polyQ-mediated aggregation in vitro. However, polyQ insertion lengths in these studies have been kept below the pathogenic threshold. We perform molecular dynamics simulations to study monomer folding dynamics and dimer formation in CI2-polyQ chimeras with insertion lengths of up to 80 glutamines. Our model recapitulates the experimental results of previous studies of chimeric CI2 proteins, showing high folding cooperativity of monomers as well as protein association via domain swapping. Surprisingly, for chimeras with insertion lengths above the pathogenic threshold, monomer folding cooperativity decreases and the dominant mode for dimer formation becomes interglutamine hydrogen bonding. These results support a mechanism for pathogenic polyQ-mediated aggregation, in which expanded polyQ tracts destabilize affected proteins and promote the formation of partially unfolded intermediates. These unfolded intermediates form aggregates through associations by interglutamine interactions

A Generic Program for Multistate Protein Design

Some protein design tasks cannot be modeled by the traditional single state design strategy of finding a sequence that is optimal for a single fixed backbone. Such cases require multistate design, where a single sequence is threaded onto multiple backbones (states) and evaluated for its strengths and weaknesses on each backbone. For example, to design a protein that can switch between two specific conformations, it is necessary to to find a sequence that is compatible with both backbone conformations. We present in this paper a generic implementation of multistate design that is suited for a wide range of protein design tasks and demonstrate in silico its capabilities at two design tasks: one of redesigning an obligate homodimer into an obligate heterodimer such that the new monomers would not homodimerize, and one of redesigning a promiscuous interface to bind to only a single partner and to no longer bind the rest of its partners. Both tasks contained negative design in that multistate design was asked to find sequences that would produce high energies for several of the states being modeled. Success at negative design was assessed by computationally redocking the undesired protein-pair interactions; we found that multistate design's accuracy improved as the diversity of conformations for the undesired protein-pair interactions increased. The paper concludes with a discussion of the pitfalls of negative design, which has proven considerably more challenging than positive design

ROSETTA3: An Object-Oriented Software Suite for the Simulation and Design of Macromolecules

2.1. Preserving existing functionality 54