Understanding enzyme catalysis through the analysis of natural enzymes is a daunting challenge-their active sites are complex and combine numerous interactions and catalytic forces that are finely coordinated. Study of more rudimentary (wo)man-made enzymes provides a unique opportunity for better understanding of enzymatic catalysis. KE07, a computationally designed Kemp eliminase that employs a glutamate side chain as the catalytic base for the critical proton abstraction step and an apolar binding site to guide substrate binding, was optimized by seven rounds of random mutagenesis and selection, resulting in a >200-fold increase in catalytic efficiency. Here, we describe the directed evolution process in detail and the biophysical and crystallographic studies of the designed KE07 and its evolved variants. The optimization of KE07's activity to give a k(cat)/K(M) value of approximately 2600 s(-1) M(-1) and an approximately 10(6)-fold rate acceleration (k(cat)/k(uncat)) involved the incorporation of up to eight mutations. These mutations led to a marked decrease in the overall thermodynamic stability of the evolved KE07s and in the configurational stability of their active sites. We identified two primary contributions of the mutations to KE07's improved activity: (i) the introduction of new salt bridges to correct a mistake in the original design that placed a lysine for leaving-group protonation without consideration of its "quenching" interactions with the catalytic glutamate, and (ii) the tuning of the environment, the pK(a) of the catalytic base, and its interactions with the substrate through the evolution of a network of hydrogen bonds consisting of several charged residues surrounding the active site.

Repeat proteins have considerable potential for use as modular binding reagents or biomaterials in biomedical and nanotechnology applications. Here we describe a general computational method for building idealized repeats that integrates available family sequences and structural information with Rosetta de novo protein design calculations. Idealized designs from six different repeat families were generated and experimentally characterized; 80% of the proteins were expressed and soluble and more than 40% were folded and monomeric with high thermal stability. Crystal structures determined for members of three families are within 1Å root-mean-square deviation to the design models. The method provides a general approach for fast and reliable generation of stable modular repeat protein scaffolds.

Designed retroaldolases have utilized a nucleophilic lysine to promote carbon-carbon bond cleavage of β-hydroxy-ketones via a covalent Schiff base intermediate. Previous computational designs have incorporated a water molecule to facilitate formation and breakdown of the carbinolamine intermediate to give the Schiff base and to function as a general acid/base. Here we investigate an alternative active-site design in which the catalytic water molecule was replaced by the side chain of a glutamic acid. Five out of seven designs expressed solubly and exhibited catalytic efficiencies similar to previously designed retroaldolases for the conversion of 4-hydroxy-4-(6-methoxy-2-naphthyl)-2-butanone to 6-methoxy-2-naphthaldehyde and acetone. After one round of site-directed saturation mutagenesis, improved variants of the two best designs, RA114 and RA117, exhibited among the highest kcat (>10(-3)s(-1)) and kcat/KM (11-25M(-1)s(-1)) values observed for retroaldolase designs prior to comprehensive directed evolution. In both cases, the >10(5)-fold rate accelerations that were achieved are within 1-3 orders of magnitude of the rate enhancements reported for the best catalysts for related reactions, including catalytic antibodies (kcat/kuncat=10(6) to 10(8)) and an extensively evolved computational design (kcat/kuncat>10(7)). The catalytic sites, revealed by X-ray structures of optimized versions of the two active designs, are in close agreement with the design models except for the catalytic lysine in RA114. We further improved the variants by computational remodeling of the loops and yeast display selection for reactivity of the catalytic lysine with a diketone probe, obtaining an additional order of magnitude enhancement in activity with both approaches.

Computational docking of small-molecule ligands into protein receptors is an important tool for modern drug discovery. Although conformational adjustments are frequently observed between the free and ligand-bound states, the conformational flexibility of the protein is typically ignored in protein-small molecule docking programs. We previously described the program RosettaLigand, which leverages the Rosetta energy function and side-chain repacking algorithm to account for flexibility of all side chains in the binding site. Here we present extensions to RosettaLigand that incorporate full ligand flexibility as well as receptor backbone flexibility. Including receptor backbone flexibility is found to produce more correct docked complexes and to lower the average RMSD of the best-scoring docked poses relative to the rigid-backbone results. On a challenging set of retrospective and prospective cross-docking tests, we find that the top-scoring ligand pose is correctly positioned within 2 A RMSD for 64% (54/85) of cases overall.

The ability to design stable proteins with custom-made functions is a major goal in biochemistry with practical relevance for our environment and society. Understanding and manipulating protein stability provide crucial information on the molecular determinants that modulate structure and stability, and expand the applications of de novo proteins. Since the (β/⍺)8-barrel or TIM-barrel fold is one of the most common functional scaffolds, in this work we designed a collection of stable de novo TIM barrels (DeNovoTIMs), using a computational fixed-backbone and modular approach based on improved hydrophobic packing of sTIM11, the first validated de novo TIM barrel, and subjected them to a thorough folding analysis. DeNovoTIMs navigate a region of the stability landscape previously uncharted by natural TIM barrels, with variations spanning 60 degrees in melting temperature and 22 kcal per mol in conformational stability throughout the designs. Significant non-additive or epistatic effects were observed when stabilizing mutations from different regions of the barrel were combined. The molecular basis of epistasis in DeNovoTIMs appears to be related to the extension of the hydrophobic cores. This study is an important step towards the fine-tuned modulation of protein stability by design.

We report the cocrystal structures of a computationally designed and experimentally optimized retro-aldol enzyme with covalently bound substrate analogs. The structure with a covalently bound mechanism-based inhibitor is similar to, but not identical with, the design model, with an RMSD of 1.4 Å over active-site residues and equivalent substrate atoms. As in the design model, the binding pocket orients the substrate through hydrophobic interactions with the naphthyl moiety such that the oxygen atoms analogous to the carbinolamine and β-hydroxyl oxygens are positioned near a network of bound waters. However, there are differences between the design model and the structure: the orientation of the naphthyl group and the conformation of the catalytic lysine are slightly different; the bound water network appears to be more extensive; and the bound substrate analog exhibits more conformational heterogeneity than typical native enzyme-inhibitor complexes. Alanine scanning of the active-site residues shows that both the catalytic lysine and the residues around the binding pocket for the substrate naphthyl group make critical contributions to catalysis. Mutating the set of water-coordinating residues also significantly reduces catalytic activity. The crystal structure of the enzyme with a smaller substrate analog that lacks naphthyl ring shows the catalytic lysine to be more flexible than in the naphthyl-substrate complex; increased preorganization of the active site would likely improve catalysis. The covalently bound complex structures and mutagenesis data highlight the strengths and weaknesses of the de novo enzyme design strategy.

Combinatorial sequence optimization for protein design requires libraries of discrete side-chain conformations. The discreteness of these libraries is problematic, particularly for long, polar side chains, since favorable interactions can be missed. Previously, an approach to loop remodeling where protein backbone movement is directed by side-chain rotamers predicted to form interactions previously observed in native complexes (termed "motifs") was described. Here, we show how such motif libraries can be incorporated into combinatorial sequence optimization protocols and improve native complex recapitulation. Guided by the motif rotamer searches, we made improvements to the underlying energy function, increasing recapitulation of native interactions. To further test the methods, we carried out a comprehensive experimental scan of amino acid preferences in the I-AniI protein-DNA interface and found that many positions tolerated multiple amino acids. This sequence plasticity is not observed in the computational results because of the fixed-backbone approximation of the model. We improved modeling of this diversity by introducing DNA flexibility and reducing the convergence of the simulated annealing algorithm that drives the design process. In addition to serving as a benchmark, this extensive experimental data set provides insight into the types of interactions essential to maintain the function of this potential gene therapy reagent.

Recent efforts to design de novo or redesign the sequence and structure of proteins using computational techniques have met with significant success. Most, if not all, of these computational methodologies attempt to model atomic-level interactions, and hence high-resolution structural characterization of the designed proteins is critical for evaluating the atomic-level accuracy of the underlying design force-fields. We previously used our computational protein design protocol RosettaDesign to completely redesign the sequence of the activation domain of human procarboxypeptidase A2. With 68% of the wild-type sequence changed, the designed protein, AYEdesign, is over 10 kcal/mol more stable than the wild-type protein. Here, we describe the high-resolution crystal structure and solution NMR structure of AYEdesign, which show that the experimentally determined backbone and side-chains conformations are effectively superimposable with the computational model at atomic resolution. To isolate the origins of the remarkable stabilization, we have designed and characterized a new series of procarboxypeptidase mutants that gain significant thermodynamic stability with a minimal number of mutations; one mutant gains more than 5 kcal/mol of stability over the wild-type protein with only four amino acid changes. We explore the relationship between force-field smoothing and conformational sampling by comparing the experimentally determined free energies of the overall design and these focused subsets of mutations to those predicted using modified force-fields, and both fixed and flexible backbone sampling protocols.

Armadillo repeat proteins (ArmRPs) recognize their target peptide in extended conformation and bind, in a first approximation, two residues per repeat. Thus, they may form the basis for building a modular system, in which each repeat is complementary to a piece of the target peptide. Accordingly, preselected repeats could be assembled into specific binding proteins on demand and thereby avoid the traditional generation of every new binding molecule by an independent selection from a library. Stacked armadillo repeats, each consisting of 42 aa arranged in three α-helices, build an elongated superhelical structure. Here, we analyzed the curvature variations in natural ArmRPs and identified a repeat pair from yeast importin-α as having the optimal curvature geometry that is complementary to a peptide over its whole length. We employed a symmetric in silico design to obtain a uniform sequence for a stackable repeat while maintaining the desired curvature geometry. Computationally designed ArmRPs (dArmRPs) had to be stabilized by mutations to remove regions of higher flexibility, which were identified by molecular dynamics simulations in explicit solvent. Using an N-capping repeat from the consensus-design approach, two different crystal structures of dArmRP were determined. Although the experimental structures of dArmRP deviated from the designed curvature, the insertion of the most conserved binding pockets of natural ArmRPs onto the surface of dArmRPs resulted in binders against the expected peptide with low nanomolar affinities, similar to the binders from the consensus-design series.

Computational grafting of functional motifs onto scaffold proteins is a promising way to engineer novel proteins with pre-specified functionalities. Typically, protein grafting involves the transplantation of protein side chains from a functional motif onto structurally homologous regions of scaffold proteins. Using this approach, we previously transplanted the human immunodeficiency virus 2F5 and 4E10 epitopes onto heterologous proteins to design novel "epitope-scaffold" antigens. However, side-chain grafting is limited by the availability of scaffolds with compatible backbone for a given epitope structure and offers no route to modify backbone structure to improve mimicry or binding affinity. To address this, we report here a new and more aggressive computational method-backbone grafting of linear motifs-that transplants the backbone and side chains of linear functional motifs onto scaffold proteins. To test this method, we first used side-chain grafting to design new 2F5 epitope scaffolds with improved biophysical characteristics. We then independently transplanted the 2F5 epitope onto three of the same parent scaffolds using the newly developed backbone grafting procedure. Crystal structures of side-chain and backbone grafting designs showed close agreement with both the computational models and the desired epitope structure. In two cases, backbone grafting scaffolds bound antibody 2F5 with 30- and 9-fold higher affinity than corresponding side-chain grafting designs. These results demonstrate that flexible backbone methods for epitope grafting can significantly improve binding affinities over those achieved by fixed backbone methods alone. Backbone grafting of linear motifs is a general method to transplant functional motifs when backbone remodeling of the target scaffold is necessary.

The CS-RDC-NOE Rosetta program was used to generate the solution structure of a 27-kDa fragment of the Escherichia coli BamC protein from a limited set of NMR data. The BamC protein is a component of the essential five-protein β-barrel assembly machine in E. coli. The first 100 residues in BamC were disordered in solution. The Rosetta calculations showed that BamC₁₀₁₋₃₄₄ forms two well-defined domains connected by an ~18-residue linker, where the relative orientation of the domains was not defined. Both domains adopt a helix-grip fold previously observed in the Bet v 1 superfamily. ¹⁵N relaxation data indicated a high degree of conformational flexibility for the linker connecting the N-terminal domain and the C-terminal domain in BamC. The results here show that CS-RDC-NOE Rosetta is robust and has a high tolerance for misassigned nuclear Overhauser effect restraints, greatly simplifying NMR structure determinations.

How proteins achieve high-affinity binding to a specific protein partner while simultaneously excluding all others is a major biological problem that has important implications for protein design. We report the crystal structure of the ultra-high-affinity protein-protein complex between the endonuclease domain of colicin E2 and its cognate immunity (Im) protein, Im2 (K(d)∼10(-)(15) M), which, by comparison to previous structural and biophysical data, provides unprecedented insight into how high affinity and selectivity are achieved in this model family of protein complexes. Our study pinpoints the role of structured water molecules in conjoining hotspot residues that govern stability with residues that control selectivity. A key finding is that a single residue, which in a noncognate context massively destabilizes the complex through frustration, does not participate in specificity directly but rather acts as an organizing center for a multitude of specificity interactions across the interface, many of which are water mediated.

Paramagnetic metal ions generate pseudocontact shifts (PCSs) in nuclear magnetic resonance spectra that are manifested as easily measurable changes in chemical shifts. Metals can be incorporated into proteins through metal binding tags, and PCS data constitute powerful long-range restraints on the positions of nuclear spins relative to the coordinate system of the magnetic susceptibility anisotropy tensor (Δχ-tensor) of the metal ion. We show that three-dimensional structures of proteins can reliably be determined using PCS data from a single metal binding site combined with backbone chemical shifts. The program PCS-ROSETTA automatically determines the Δχ-tensor and metal position from the PCS data during the structure calculations, without any prior knowledge of the protein structure. The program can determine structures accurately for proteins of up to 150 residues, offering a powerful new approach to protein structure determination that relies exclusively on readily measurable backbone chemical shifts and easily discriminates between correctly and incorrectly folded conformations.

While there has been considerable progress in designing protein-protein interactions, the design of proteins that bind polar surfaces is an unmet challenge. We describe the computational design of a protein that binds the acidic active site of hen egg lysozyme and inhibits the enzyme. The design process starts with two polar amino acids that fit deep into the enzyme active site, identifies a protein scaffold that supports these residues and is complementary in shape to the lysozyme active-site region, and finally optimizes the surrounding contact surface for high-affinity binding. Following affinity maturation, a protein designed using this method bound lysozyme with low nanomolar affinity, and a combination of NMR studies, crystallography, and knockout mutagenesis confirmed the designed binding surface and orientation. Saturation mutagenesis with selection and deep sequencing demonstrated that specific designed interactions extending well beyond the centrally grafted polar residues are critical for high-affinity binding.

What conformations do protein molecules populate in solution? Crystallography provides a high-resolution description of protein structure in the crystal environment, while NMR describes structure in solution but using less data. NMR structures display more variability, but is this because crystal contacts are absent or because of fewer data constraints? Here we report unexpected insight into this issue obtained through analysis of detailed protein energy landscapes generated by large-scale, native-enhanced sampling of conformational space with Rosetta@home for 111 protein domains. In the absence of tightly associating binding partners or ligands, the lowest-energy Rosetta models were nearly all <2.5 Å C(α)RMSD from the experimental structure; this result demonstrates that structure prediction accuracy for globular proteins is limited mainly by the ability to sample close to the native structure. While the lowest-energy models are similar to deposited structures, they are not identical; the largest deviations are most often in regions involved in ligand, quaternary, or crystal contacts. For ligand binding proteins, the low energy models may resemble the apo structures, and for oligomeric proteins, the monomeric assembly intermediates. The deviations between the low energy models and crystal structures largely disappear when landscapes are computed in the context of the crystal lattice or multimer. The computed low-energy ensembles, with tight crystal-structure-like packing in the core, but more NMR-structure-like variability in loops, may in some cases resemble the native state ensembles of proteins better than individual crystal or NMR structures, and can suggest experimentally testable hypotheses relating alternative states and structural heterogeneity to function.

Although de novo computational enzyme design has been shown to be feasible, the field is still in its infancy: the kinetic parameters of designed enzymes are still orders of magnitude lower than those of naturally occurring ones. Nonetheless, designed enzymes can be improved by directed evolution, as recently exemplified for the designed Kemp eliminase KE07. Random mutagenesis and screening resulted in variants with >200-fold higher catalytic efficiency and provided insights about features missing in the designed enzyme. Here we describe the optimization of KE70, another designed Kemp eliminase. Amino acid substitutions predicted to improve catalysis in design calculations involving extensive backbone sampling were individually tested. Those proven beneficial were combinatorially incorporated into the originally designed KE70 along with random mutations, and the resulting libraries were screened for improved eliminase activity. Nine rounds of mutation and selection resulted in >400-fold improvement in the catalytic efficiency of the original KE70 design, reflected in both higher k(cat) values and lower K(m) values, with the best variants exhibiting k(cat)/K(m) values of >5×10(4) s(-)(1) M(-1). The optimized KE70 variants were characterized structurally and biochemically, providing insights into the origins of the improvements in catalysis. Three primary contributions were identified: first, the reshaping of the active-site cavity to achieve tighter substrate binding; second, the fine-tuning of electrostatics around the catalytic His-Asp dyad; and, third, the stabilization of the active-site dyad in a conformation optimal for catalysis.

Protein-protein interactions play critical roles in biology, and computational design of interactions could be useful in a range of applications. We describe in detail a general approach to de novo design of protein interactions based on computed, energetically optimized interaction hotspots, which was recently used to produce high-affinity binders of influenza hemagglutinin. We present several alternative approaches to identify and build the key hotspot interactions within both core secondary structural elements and variable loop regions and evaluate the method's performance in natural-interface recapitulation. We show that the method generates binding surfaces that are more conformationally restricted than previous design methods, reducing opportunities for off-target interactions.