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 21 s 21 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.Naturally occurring enzymes are extraordinarily efficient catalysts 1 . They bind their substrates in a well-defined active site with precisely aligned catalytic residues to form highly active and selective catalysts for a wide range of chemical reactions under mild conditions. Nevertheless, many important synthetic reactions lack a naturally occurring enzymatic counterpart. Hence, the design of stable enzymes with new catalytic activities is of great practical interest, with potential applications in biotechnology, biomedicine and industrial processes. Furthermore, the computational design of new enzymes provides a stringent test of our understanding of how naturally occurring enzymes work. In the past several years, there has been exciting progress in designing new biocatalysts 2,3 .Here we describe the use of our recently developed computational enzyme design methodology 4 to create new enzyme catalysts for a reaction for which no naturally occurring enzyme exists: the Kemp elimination 5,6 . The reaction, shown in Fig. 1a, has been extensively studied as an activated model system for understanding the catalysis of proton abstraction from carbon-a process that is normally restricted by high activation-energy barriers 7,8 . Computational design methodThe first step in our protocol for designing new enzymes is to choose a catalytic mechanism and then to use quantum mechanical transition state calculations to create an idealized active site with protein functional groups positioned so as to maximize transition state stabilization (Fig. 1b). The key step for the Kemp elimination is deprotonation of a carbon by a general base. We chose two different catalytic bases for this purpose: first, the carboxyl group of an aspartate or glutamate side chain, and, second, the imidazole of a histidine positioned and polarized by the carboxyl group of an aspartate or glutamate (we refer to this combination as a His-Asp dyad). The two choices have complementary strengths and weaknesses. The advantage of the carboxylate...
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.
The Diels-Alder reaction is a cornerstone in organic synthesis, forming two carbon-carbon bonds and up to four new stereogenic centers in one step. No naturally occurring enzymes have been shown to catalyze bimolecular Diels-Alder reactions. We describe the de novo computational design and experimental characterization of enzymes catalyzing a bimolecular Diels-Alder reaction with high stereoselectivity and substrate specificity. X-ray crystallography confirms that the structure matches the design for the most active of the enzymes, and binding site substitutions reprogram the substrate specificity. Designed stereoselective catalysts for carbon-carbon bond forming reactions should be broadly useful in synthetic chemistry.
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.Keywords: enzyme design; protein design; active site recapitulation; protein-ligand interactions; geometric hashing Enzymes are among the most efficient, specific, and selective catalysts known. The ability to design efficient enzymes for a broad class of different reactions would be of tremendous practical interest for both science and the industry. Furthermore, the rational design of enzymes is a stringent test of our understanding of biological catalysis.There has been exciting progress in enzyme design. On the experimental side, catalytic antibodies, elicited by immunization with transition state analogs, have been shown to possess catalytic activity (Lerner et al. 1991;Hilvert 2000). More recently, several successful enzyme designs have been reported. Kaplan and DeGrado (2004) The computational methods used in enzyme site design to date, such as ORBIT from the Mayo group (Dahiyat and Mayo 1996) and Dezymer from the Hellinga group (Hellinga and Richards 1991), have primarily been used to search for catalytic site placement in one or a small number of scaffolds. In contrast, computational methods for searching for functional sites that employ geometric hashing (Russell 1998) In general, how to evaluate and optimize computational design methods for the creation of new molecules is a nontrivial problem. For robust conclusions, it is desirable to compare alternative methods and parameter choices by comparing results on a representative set of test systems. In the ''protein design cycle'' approach described by Dahiyat and Mayo (1997), alternative choices in a design method are tested by producing designs and experimentally characterizing them, and the choice is selected that produces designs with the desired properties. While this is a very powerful approach, experimentally characterizing a large number of designs for a number of different methods is slow and expensive, and therefore, it is desirable to have a faster and cheaper test. A purely in silico test for monomeric protein design developed in our group based on...
We describe the development of a method for assembling structures of multidomain proteins from structures of isolated domains. The method consists of an initial low-resolution search in which the conformational space of the domain linker is explored using the Rosetta de novo structure prediction method, followed by a high-resolution search in which all atoms are treated explicitly and backbone and side chain degrees of freedom are simultaneously optimized. The method recapitulates, often with very high accuracy, the structures of existing multidomain proteins.Keywords: domain assembly; protein-protein docking; protein structure prediction Proteins are frequently composed of multiple domains (Ponting and Russell 2002;Vogel et al. 2004) that are likely to fold independently (Shen et al. 2005). Determining the structure of multidomain complexes at atomic resolution is critical to understanding the underpinnings of much of biology (Lupas et al. 2001;Aloy and Russell 2006). While structures of single domains can be readily determined through X-ray or NMR techniques, the structures of large multipart proteins are often more difficult to elucidate (Aloy et al. 2003).There are two general approaches to predicting structures of multidomain proteins from structures of individual domains. First, the domain assembly problem may be treated as a docking problem. For example, Inbar et al. (2005) used rigid body docking methods to predict the structure of the resulting complex. A second approach to domain assembly, which we describe here, is to explicitly sample the degrees of freedom of the linker rather than the rigid body degrees of freedom of the two domains. Approached in this manner, the domain assembly problem may be viewed as an ab initio prediction problem for a relatively short amino acid sequence with preformed N-and C-terminal structures.The Rosetta protein modeling method has had success in folding small protein chains ab initio , and in protein-protein docking with flexible side chains ). Here we combine these methods to assemble structures of isolated domains into a multidomain complex. The conformation of the linker is explored, keeping the backbone of the individual domains fixed but allowing the side chains in the linker and at the domain interface to sample a full range of rotamer conformations. The lowest energy models found are often very close to the correct structure. Results and DiscussionSeventy-six two-domain proteins were culled from a nonredundant database of proteins (Berman et al. 2000), as described in Materials and Methods. These proteins contained no cofactors or ligands near the interface of the domains, as the focus was on modeling the interface Abbreviations: RMSD, root mean square deviation. Article published online ahead of print. Article and publication date are at
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