Bridging the gaps in design methodologies by evolutionary optimization of the stability and proficiency of designed Kemp eliminase KE59.

Computational design is a test of our understanding of enzyme catalysis and a means of engineering novel, tailor-made enzymes. While the de novo computational design of catalytically efficient enzymes remains a challenge, designed enzymes may comprise unique starting points for further optimization by directed evolution. Directed evolution of two computationally designed Kemp eliminases, KE07 and KE70, led to low to moderately efficient enzymes (k(cat)/K(m) values of ≤ 5 10(4) M(-1)s(-1)). Here we describe the optimization of a third design, KE59. Although KE59 was the most catalytically efficient Kemp eliminase from this design series (by k(cat)/K(m), and by catalyzing the elimination of nonactivated benzisoxazoles), its impaired stability prevented its evolutionary optimization. To boost KE59's evolvability, stabilizing consensus mutations were included in the libraries throughout the directed evolution process. The libraries were also screened with less activated substrates. Sixteen rounds of mutation and selection led to > 2,000-fold increase in catalytic efficiency, mainly via higher k(cat) values. The best KE59 variants exhibited k(cat)/K(m) values up to 0.6 10(6) M(-1)s(-1), and k(cat)/k(uncat) values of ≤ 10(7) almost regardless of substrate reactivity. Biochemical, structural, and molecular dynamics (MD) simulation studies provided insights regarding the optimization of KE59. Overall, the directed evolution of three different designed Kemp eliminases, KE07, KE70, and KE59, demonstrates that computational designs are highly evolvable and can be optimized to high catalytic efficiencies.

Kemp elimination catalysts by computational enzyme design.

The design of new enzymes for reactions not catalysed by naturally occurring biocatalysts is a challenge for protein engineering and is a critical test of our understanding of enzyme catalysis. Here we describe the computational design of eight enzymes that use two different catalytic motifs to catalyse the Kemp elimination-a model reaction for proton transfer from carbon-with measured rate enhancements of up to 10(5) and multiple turnovers. Mutational analysis confirms that catalysis depends on the computationally designed active sites, and a high-resolution crystal structure suggests that the designs have close to atomic accuracy. Application of in vitro evolution to enhance the computational designs produced a >200-fold increase in k(cat)/K(m) (k(cat)/K(m) of 2,600 M(-1)s(-1) and k(cat)/k(uncat) of >10(6)). These results demonstrate the power of combining computational protein design with directed evolution for creating new enzymes, and we anticipate the creation of a wide range of useful new catalysts in the future.

Catalytic mechanism and performance of computationally designed enzymes for Kemp elimination.

A series of enzymes for Kemp elimination of 5-nitrobenzisoxazole has been recently designed and tested. In conjunction with the design process, extensive computational analyses were carried out to evaluate the potential performance of four of the designs, as presented here. The enzyme-catalyzed reactions were modeled using mixed quantum and molecular mechanics (QM/MM) calculations in the context of Monte Carlo (MC) statistical mechanics simulations. Free-energy perturbation (FEP) calculations were used to characterize the free-energy surfaces for the catalyzed reactions as well as for reference processes in water. The simulations yielded detailed information about the catalytic mechanisms, activation barriers, and structural evolution of the active sites over the course of the reactions. The catalytic mechanism for the designed enzymes KE07, KE10(V131N), and KE15 was found to be concerted with proton transfer, generally more advanced in the transition state than breaking of the isoxazolyl N-O bond. On the basis of the free-energy results, all three enzymes were anticipated to be active. Ideas for further improvement of the enzyme designs also emerged. On the technical side, the synergy of parallel QM/MM and experimental efforts in the design of artificial enzymes is well illustrated.

New algorithms and an in silico benchmark for computational enzyme design.

The creation of novel enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Here we describe two new algorithms for enzyme design that employ hashing techniques to allow searching through large numbers of protein scaffolds for optimal catalytic site placement. We also describe an in silico benchmark, based on the recapitulation of the active sites of native enzymes, that allows rapid evaluation and testing of enzyme design methodologies. In the benchmark test, which consists of designing sites for each of 10 different chemical reactions in backbone scaffolds derived from 10 enzymes catalyzing the reactions, the new methods succeed in identifying the native site in the native scaffold and ranking it within the top five designs for six of the 10 reactions. The new methods can be directly applied to the design of new enzymes, and the benchmark provides a powerful in silico test for guiding improvements in computational enzyme design.

Domain interactions in the Fab fragment: a comparative evaluation of the single-chain Fv and Fab format engineered with variable domains of different stability.

Recombinant antibody fragments, most notably Fab and scFv, have become important tools in research, diagnostics and therapy. Since different recombinant antibody formats exist, it is crucial to understand the difference in their respective biophysical properties. We assessed the potential stability benefits of changing the scFv into the Fab format, the influence of the variable domains on the stability of the Fab fragment, and the influence of the interchain disulfide bond in the Fab fragment. To analyze domain interactions, the Fab fragment was broken down into its individual domains, several two-domain assemblies and one three-domain assembly. The equilibrium denaturation properties of these constructs were then compared to those of the Fab fragment. It was found that mutual stabilization occurred across the VH/VL and the CH1/CL interface, whereas the direct interaction between the V) and the CL domain had no influence on the stability of either domain. This observation can be explained by the different interfaces used for interaction. In contrast, the whole CH1CL and VHVL unit showed significant mutual stabilization, indicating a high degree of cooperation between the VH/VL and CH1/CL interface. The interchain disulfide bond in the Fab fragment plays an essential role in this stabilization. In addition to the effects of domain association on the thermodynamic (equilibrium) stability, Fab fragments differ from scFv fragments of similar equilibrium stability by having a very slow unfolding rate. This kinetic stabilization may increase significantly the resistance of Fab fragments against short time exposure to adverse conditions.

An antibody library for stabilizing and crystallizing membrane proteins - selecting binders to the citrate carrier CitS.

Co-crystallization of membrane proteins with antibody fragments may emerge as a general tool to facilitate crystal growth and improve crystal quality. The bound antibody fragment enlarges the hydrophilic part of the mostly hydrophobic membrane protein, thereby increasing the interaction area for possible protein-protein contacts in the crystal. Additionally, it may restrain flexible parts or lock the membrane protein in a defined conformational state. For successful co-crystallization trials, the antibody fragments must be stable in detergents during the extended period of crystal growth and must be easily produced in amounts necessary for crystallography. Therefore, we constructed a library of antibody Fab fragments from a framework subset of the HuCAL GOLD library (Morphosys, Munich, Germany). By combining the most stable and well expressed frameworks, V(H)3 and V(kappa)3, with the further stabilizing constant domains, a Fab library with the desired properties was obtained in a standard phage display format. As a proof of principle, we selected binders with phage display against the detergent-solubilized citrate transporter CitS of Klebsiella pneumoniae. We describe efficient methods for the immobilization of the membrane protein during selection, for ELISA screening, and for BIAcore evaluation. We demonstrate that the selected Fab fragments form stable complexes with native CitS and recognize conformational epitopes with affinities in the low nanomolar range.

Computational design of novel enzymes without cofactors.

In this review we present a recently developed computational method to design de novo enzymes. Starting from the three-dimensional arrangement of the transition state structure and the catalytic side chains around it (theozyme), RosettaMatch identifies successful placements of the theozyme into protein scaffolds. Subsequently, RosettaEnzDes (for EnzymeDesign) redesigns the active site around the theozyme for binding and stabilization of the transition state and the catalytic residues. The resulting computationally designed enzymes are expressed and experimentally tested for catalytic activity.

Optimization of the in-silico-designed kemp eliminase KE70 by computational design and directed evolution.

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.

Evaluation and ranking of enzyme designs.

In 2008, a successful computational design procedure was reported that yielded active enzyme catalysts for the Kemp elimination. Here, we studied these proteins together with a set of previously unpublished inactive designs to determine the sources of activity or lack thereof, and to predict which of the designed structures are most likely to be catalytic. Methods that range from quantum mechanics (QM) on truncated model systems to the treatment of the full protein with ONIOM QM/MM and AMBER molecular dynamics (MD) were explored. The most effective procedure involved molecular dynamics, and a general MD protocol was established. Substantial deviations from the ideal catalytic geometries were observed for a number of designs. Penetration of water into the catalytic site and insufficient residue-packing around the active site are the main factors that can cause enzyme designs to be inactive. Where in the past, computational evaluations of designed enzymes were too time-extensive for practical considerations, it has now become feasible to rank and refine candidates computationally prior to and in conjunction with experimentation, thus markedly increasing the efficiency of the enzyme design process.

Evolutionary optimization of computationally designed enzymes: Kemp eliminases of the KE07 series.

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.

The influence of the framework core residues on the biophysical properties of immunoglobulin heavy chain variable domains.

Antibody variable domains differ considerably in stability. Single-chain Fv (scFv) fragments derived from natural repertoires frequently lack the high stability needed for therapeutic application, necessitating reengineering not only to humanize their sequence, but also to improve their biophysical properties. The human V(H)3 domain has been identified as having the best biophysical properties among human subtypes. However, complementarity determining region (CDR) grafts from highly divergent V(H) domains to huV(H)3 frequently fail to reach its superior stability. In previous experiments involving a CDR graft from a murine V(H)9 domain of very poor stability to huV(H)3, a hybrid V(H) framework was obtained which combines the lower core residues of muV(H)9 with the surface residues of huV(H)3. It resulted in a scFv with far better biophysical properties than the corresponding grafts to the consensus huV(H)3 framework. To better understand the origin of the superior properties of the hybrid framework, we constructed further hybrids, but now in the context of the consensus CDR-H1 and -H2 of the original human V(H)3 domain. The new hybrids included elements from either murine V(H)9, human V(H)1 or human V(H)5 domains. From guanidinium chloride-induced equilibrium denaturation measurements, kinetic denaturation experiments, measurements of heat-induced aggregation and comparison of soluble expression yield in Escherichia coli, we conclude that the optimal V(H) framework is CDR-dependent. The present work pinpoints structural features responsible for this dependency and helps to explain why the immune system uses more than one framework with different structural subtypes in framework 1 to optimally support widely different CDRs.

De novo computational design of retro-aldol enzymes.

The creation of enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Using new algorithms that rely on hashing techniques to construct active sites for multistep reactions, we designed retro-aldolases that use four different catalytic motifs to catalyze the breaking of a carbon-carbon bond in a nonnatural substrate. Of the 72 designs that were experimentally characterized, 32, spanning a range of protein folds, had detectable retro-aldolase activity. Designs that used an explicit water molecule to mediate proton shuffling were significantly more successful, with rate accelerations of up to four orders of magnitude and multiple turnovers, than those involving charged side-chain networks. The atomic accuracy of the design process was confirmed by the x-ray crystal structure of active designs embedded in two protein scaffolds, both of which were nearly superimposable on the design model.

In vitro selection and characterization of DARPins and Fab fragments for the co-crystallization of membrane proteins: The Na(+)-citrate symporter CitS as an example.

The determination of 3D structures of membrane proteins is still extremely difficult. The co-crystallization with specific binding proteins may be an important aid in this process, as these proteins provide rigid, hydrophilic surfaces for stable protein-protein contacts. Also, the conformational homogeneity of the membrane protein may be increased to obtain crystals suitable for high resolution structures. Here, we describe the efficient generation and characterization of Designed Ankyrin Repeat Proteins (DARPins) as specific binding molecules for membrane proteins. We used both phage display and ribosome display to select DARPins in vitro that are specific for the detergent-solubilized Na(+)-citrate symporter CitS of Klebsiella pneumoniae. Compared to classical hybridoma technology, the in vitro selection systems allow a much better control of the structural integrity of the target protein and allow the use of other protein classes in addition to recombinant antibodies. We also compared the selected DARPins to a Fab fragment previously selected by phage display and demonstrate that different epitopes are recognized, unique to each class of binding molecules. Therefore, the use of several classes of binding molecules will make suitable crystal formation and the determination of their 3D structure more likely.