Design of a Heterospecific, Tetrameric, 21-Residue Miniprotein with Mixed α/β Structure

Ali, Mayssam H.; Taylor, Christina; Grigoryan, Gevorg; Allen, Karen N.; Imperiali, Barbara; Keating, Amy E.

doi:10.1016/j.str.2004.12.009

Cited by 32 publications

(33 citation statements)

References 65 publications

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“…[5][6][7]17,18 There are only a small number of examples in which a protein or peptide has successfully been designed to bind a native target. 8-10 Here, we report the successful design of several new 26-residue peptides that bind to Bcl-x L .…”

Section: Discussionmentioning

confidence: 99%

Modeling Backbone Flexibility to Achieve Sequence Diversity: The Design of Novel α-Helical Ligands for Bcl-xL

Apgar

Keating

2007

Journal of Molecular Biology

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Computational protein design can be used to select sequences that are compatible with a fixedbackbone template. This strategy has been used in numerous instances to engineer novel proteins. However, the fixed-backbone assumption severely restricts the sequence space that is accessible via design. For challenging problems, such as the design of functional proteins, this may not be acceptable. In this paper, we present a method for introducing backbone flexibility into protein design calculations and apply it to the design of diverse helical BH3 ligands that bind to the anti-apoptotic protein Bcl-x L , a member of the Bcl-2 protein family. We demonstrate how normal mode analysis can be used to sample different BH3 backbones, and show that this leads to a larger and more diverse set of low-energy solutions than can be achieved using a native high-resolution Bcl-x L complex crystal structure as a template. We tested several of the designed solutions experimentally and found that this approach worked well when normal mode calculations were used to deform a native BH3 helix structure, but less well when they were used to deform an idealized helix. A subsequent round of design and testing identified a likely source of the problem as inadequate sampling of the helix pitch. In all, we tested seventeen designed BH3 peptide sequences, including several point mutants. Of these, eight bound well to Bcl-x L and four others showed weak but detectable binding. The successful designs showed a diversity of sequences that would have been difficult or impossible to achieve using only a fixed backbone. Thus, introducing backbone flexibility via normal mode analysis effectively broadened the set of sequences identified by computational design, and provided insight into positions important for binding Bcl-x L .

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Section: Discussionmentioning

confidence: 99%

Modeling Backbone Flexibility to Achieve Sequence Diversity: The Design of Novel α-Helical Ligands for Bcl-xL

Apgar

Keating

2007

Journal of Molecular Biology

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“…Although all negative-design strategies optimize the difference in computed energy between the target and competing states, different groups have used a wide range of force fields, descriptions of the unfolded state, and optimization algorithms to achieve this end (7,8,10). For our studies, we used a force field that had been empirically optimized for protein design, implicitly considered the energy of the unfolded state to be constant, and used a combination of DEE and Monte Carlo search algorithms for global optimization.…”

Section: Predicted Vs Experimental Stabilitiesmentioning

confidence: 99%

“…Protein-protein interactions have been successfully reengineered to alter binding specificity both by using and ignoring negative design (7)(8)(9)(10)(11)(12)(13)(14)(15). How is success possible in the absence of negative design?…”

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confidence: 99%

Specificity versus stability in computational protein design

Bolon

Grant

Baker

et al. 2005

Proc. Natl. Acad. Sci. U.S.A.

133

123

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Protein-protein interactions can be designed computationally by using positive strategies that maximize the stability of the desired structure and͞or by negative strategies that seek to destabilize competing states. Here, we compare the efficacy of these methods in reengineering a protein homodimer into a heterodimer. The stability-design protein (positive design only) was experimentally more stable than the specificity-design heterodimer (positive and negative design). By contrast, only the specificity-design protein assembled as a homogenous heterodimer in solution, whereas the stability-design protein formed a mixture of homodimer and heterodimer species. The experimental stabilities of the engineered proteins correlated roughly with their calculated stabilities, and the crystal structure of the specificity-design heterodimer showed most of the predicted side-chain packing interactions and a mainchain conformation indistinguishable from the wild-type structure. These results indicate that the design simulations capture important features of both stability and structure and demonstrate that negative design can be critical for attaining specificity when competing states are close in structure space.adaptor protein ͉ protein engineering ͉ SspB H ighly specific recognition lies at the core of most cellular processes. The interaction of two partner proteins in a crowded intracellular environment depends on the equilibrium stability of the complex, which is determined by affinity and concentration, but is also controlled by the competing binding of either partner to other cellular macromolecules. Efficient protein recognition requires both stability and specificity. In natural systems, both parameters are subject to evolutionary optimization. Likewise in engineered systems, stability can be targeted for maximization, and known competing states or interactions can be minimized through the use of negative design. The biophysical tradeoff between stability and specificity in molecular recognition is a fascinating problem that has important implications in the development of practical tools for synthesizing and dissecting biological systems.Focusing on stability without explicit consideration of specificity has resulted in impressive protein-engineering feats, including full-sequence design of a zinc-finger protein that folds in the absence of metal (1), introduction of catalytic activity into previously inert protein scaffolds (2, 3), and the creation of a novel protein fold (4). These successes relied on positive design only. Positive design maximizes favorable interactions in the target conformation. Negative design, by contrast, maximizes unfavorable interactions in competing states and requires modeling of each unwanted conformation (5, 6).Protein-protein interactions have been successfully reengineered to alter binding specificity both by using and ignoring negative design (7-15). How is success possible in the absence of negative design? One possibility is that most changes that optimize the stability of a targe...

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“…The folding energy is defined as the energy difference between the folded and the unfolded states: E folding = E folded − E unfolded . Although the CE can in principle be used with any energy model, we test it here with a physically meaningful but relatively simple expression similar to Hamiltonians commonly used in the design field [22]: where E vdW is the vdW interaction modeled as a 6-12 Lennard-Jones potential, E elec,wat is the total electrostatic energy (excluding intra-sidechain interactions), E solv,sc is the solvation energy of all backbone and sidechain atoms [23], and E torsion is the sidechain torsional energy. All energy terms are calculated using the CHARMM package [24] with the param19 parameters.…”

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confidence: 99%

Coarse-Graining Protein Energetics in Sequence Variables

et al. 2005

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We show that cluster expansion (CE), previously used to model solid-state materials with binary or ternary configurational disorder, can be extended to the protein design problem. We present a generalized CE framework suitable for protein studies, in which properties such as the energy can be unambiguously expanded in the amino-acid sequence space. The CE coarse-grains over nonsequence degrees of freedom (e.g., sidechain conformations) and thereby simplifies the problem of designing proteins, or predicting the compatibility of a sequence with a given structure, by many orders of magnitude. The CE is physically transparent, and can be evaluated through linear regression on the energy of training sequences. The approach is demonstrated on two distinct backbone folds. We show that good prediction accuracy is obtained with up to pairwise interactions for a coiled-coil backbone, and that triplet interactions are important in the energetics of a more globular zinc-finger backbone.

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Design of a Heterospecific, Tetrameric, 21-Residue Miniprotein with Mixed α/β Structure

Cited by 32 publications

References 65 publications

Modeling Backbone Flexibility to Achieve Sequence Diversity: The Design of Novel α-Helical Ligands for Bcl-xL

Modeling Backbone Flexibility to Achieve Sequence Diversity: The Design of Novel α-Helical Ligands for Bcl-xL

Specificity versus stability in computational protein design

Coarse-Graining Protein Energetics in Sequence Variables

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