Kemp elimination catalysts by computational enzyme design

Jiang L., Althoff E.A., Clemente F.R., Doyle L., Röthlisberger D., Zanghellini A., Gallaher J.L., Betker J.L., Tanaka F., Barbas C.F., Hilvert D., Houk K.N., Stoddard B.L., Baker D.

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.

Seelig B., Szostak J.W.

New enzymatic activities can be evolved de novo (that is, without the need for prior mechanistic information) by using mRNA-display. Functional proteins were selected for from an in vitro translated protein library of high complexity and it was possible to isolate novel RNA ligases that exhibited rate enhancements of more than two million-fold. Enzymes are exceptional catalysts that facilitate a wide variety of reactions under mild conditions, achieving high rate-enhancements with excellent chemo-, regio- and stereoselectivities. There is considerable interest in developing new enzymes for the synthesis of chemicals and pharmaceuticals1,2,3 and as tools for molecular biology. Methods have been developed for modifying and improving existing enzymes through screening, selection and directed evolution4,5. However, the design and evolution of truly novel enzymes has relied on extensive knowledge of the mechanism of the reaction6,7,8,9,10. Here we show that genuinely new enzymatic activities can be created de novo without the need for prior mechanistic information by selection from a naive protein library of very high diversity, with product formation as the sole selection criterion. We used messenger RNA display, in which proteins are covalently linked to their encoding mRNA11, to select for functional proteins from an in vitro translated protein library of >1012independent sequences without the constraints imposed by any in vivo step. This technique has been used to evolve new peptides and proteins that can bind a specific ligand12,13,14,15,16,17,18, from both random-sequence libraries12,14,15,16 and libraries based on a known protein fold17,18. We now describe the isolation of novel RNA ligases from a library that is based on a zinc finger scaffold18,19, followed by in vitro directed evolution to further optimize these enzymes. The resulting ligases exhibit multiple turnover with rate enhancements of more than two-million-fold.

Herman A., Tawfik D.S.

The directed evolution of proteins has benefited greatly from site-specific methods of diversification such as saturation mutagenesis. These techniques target diversity to a number of chosen positions that are usually non-contiguous in the protein's primary structure. However, the number of targeted positions can be large, thus leading to impractically large library size, wherein almost all library variants are inactive and the likelihood of selecting desirable properties is extremely small. We describe a versatile combinatorial method for the partial diversification of large sets of residues. Our library oligonucleotides comprise randomized codons that are flanked by wild-type sequences. Adding these oligonucleotides to an assembly PCR of wild-type gene fragments incorporates the randomized cassettes, at their target sites, into the reassembled gene. Varying the oligonucleotides concentration resulted in library variants that carry a different average number of mutated positions that comprise a random subset of the entire set of diversified codons. This method, dubbed Incorporating Synthetic Oligos via Gene Reassembly (ISOR), was used to create libraries of a cytosine-C5 methyltransferase wherein 45 individual positions were randomized. One library, containing an average of 5.6 mutated residues per gene, was selected, and mutants with wild-type-like activities isolated. We also created libraries of serum paraoxonase PON1 harboring insertions and deletions (indels) in various areas surrounding the active site. Screening these libraries yielded a range of mutants with altered substrate specificities and indicated that certain regions of this enzyme have a surprisingly high tolerance to indels.

Zanghellini A., Jiang L., Wollacott A.M., Cheng G., Meiler J., Althoff E.A., Röthlisberger D., Baker D.

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.

Meiler J., Baker D.

Protein–small molecule docking algorithms provide a means to model the structure of protein–small molecule complexes in structural detail and play an important role in drug development. In recent years the necessity of simulating protein side‐chain flexibility for an accurate prediction of the protein–small molecule interfaces has become apparent, and an increasing number of docking algorithms probe different approaches to include protein flexibility. Here we describe a new method for docking small molecules into protein binding sites employing a Monte Carlo minimization procedure in which the rigid body position and orientation of the small molecule and the protein side‐chain conformations are optimized simultaneously. The energy function comprises van der Waals (VDW) interactions, an implicit solvation model, an explicit orientation hydrogen bonding potential, and an electrostatics model. In an evaluation of the scoring function the computed energy correlated with experimental small molecule binding energy with a correlation coefficient of 0.63 across a diverse set of 229 protein– small molecule complexes. The docking method produced lowest energy models with a root mean square deviation (RMSD) smaller than 2 Å in 71 out of 100 protein–small molecule crystal structure complexes (self‐docking). In cross‐docking calculations in which both protein side‐chain and small molecule internal degrees of freedom were varied the lowest energy predictions had RMSDs less than 2 Å in 14 of 20 test cases. Proteins 2006. © 2006 Wiley‐Liss, Inc.

Chica R.A., Doucet N., Pelletier J.N.

Many research groups successfully rely on whole-gene random mutagenesis and recombination approaches for the directed evolution of enzymes. Recent advances in enzyme engineering have used a combination of these random methods of directed evolution with elements of rational enzyme modification to successfully by-pass certain limitations of both directed evolution and rational design. Semi-rational approaches that target multiple, specific residues to mutate on the basis of prior structural or functional knowledge create 'smart' libraries that are more likely to yield positive results. Efficient sampling of mutations likely to affect enzyme function has been conducted both experimentally and, on a much greater scale, computationally, with remarkable improvements in substrate selectivity and specificity and in the de novo design of enzyme activities within scaffolds of known structure.

Varadarajan N., Gam J., Olsen M.J., Georgiou G., Iverson B.L.

The exquisite selectivity and catalytic activity of enzymes have been shaped by the effects of positive and negative selection pressure during the course of evolution. In contrast, enzyme variants engineered by using in vitro screening techniques to accept novel substrates typically display a higher degree of catalytic promiscuity and lower total turnover in comparison with their natural counterparts. Using bacterial display and multiparameter flow cytometry, we have developed a novel methodology for emulating positive and negative selective pressure in vitro for the isolation of enzyme variants with reactivity for desired novel substrates, while simultaneously excluding those with reactivity toward undesired substrates. Screening of a large library of random mutants of the Escherichia coli endopeptidase OmpT led to the isolation of an enzyme variant, 1.3.19, that cleaved an Ala–Arg peptide bond instead of the Arg–Arg bond preferred by the WT enzyme. Variant 1.3.19 exhibited greater than three million-fold selectivity (-Ala–Arg-/-Arg–Arg-) and a catalytic efficiency for Ala–Arg cleavage that is the same as that displayed by the parent for the preferred substrate, Arg–Arg. A single amino acid Ser223Arg substitution was shown to recapitulate completely the unique catalytic properties of the 1.3.19 variant. These results can be explained by proposing that this mutation acts to “swap” the P 1 Arg side chain normally found in WT substrate peptides with the 223Arg side chain in the S 1 subsite of OmpT.

Studier F.W.

Inducible expression systems in which T7 RNA polymerase transcribes coding sequences cloned under control of a T7lac promoter efficiently produce a wide variety of proteins in Escherichia coli. Investigation of factors that affect stability, growth, and induction of T7 expression strains in shaking vessels led to the recognition that sporadic, unintended induction of expression in complex media, previously reported by others, is almost certainly caused by small amounts of lactose. Glucose prevents induction by lactose by well-studied mechanisms. Amino acids also inhibit induction by lactose during log-phase growth, and high rates of aeration inhibit induction at low lactose concentrations. These observations, and metabolic balancing of pH, allowed development of reliable non-inducing and auto-inducing media in which batch cultures grow to high densities. Expression strains grown to saturation in non-inducing media retain plasmid and remain fully viable for weeks in the refrigerator, making it easy to prepare many freezer stocks in parallel and use working stocks for an extended period. Auto-induction allows efficient screening of many clones in parallel for expression and solubility, as cultures have only to be inoculated and grown to saturation, and yields of target protein are typically several-fold higher than obtained by conventional IPTG induction. Auto-inducing media have been developed for labeling proteins with selenomethionine, 15N or 13C, and for production of target proteins by arabinose induction of T7 RNA polymerase from the pBAD promoter in BL21-AI. Selenomethionine labeling was equally efficient in the commonly used methionine auxotroph B834(DE3) (found to be metE) or the prototroph BL21(DE3).

Debler E.W., Ito S., Seebeck F.P., Heine A., Hilvert D., Wilson I.A.

Antibody 34E4 catalyzes the conversion of benzisoxazoles to salicylonitriles with high rates and multiple turnovers. The crystal structure of its complex with the benzimidazolium hapten at 2.5-Å resolution shows that a combination of hydrogen bonding, π stacking, and van der Waals interactions is exploited to position both the base, Glu H50 , and the substrate for efficient proton transfer. Suboptimal placement of the catalytic carboxylate, as observed in the 2.8-Å structure of the Glu H50 Asp variant, results in substantially reduced catalytic efficiency. In addition to imposing high positional order on the transition state, the antibody pocket provides a highly structured microenvironment for the reaction in which the carboxylate base is activated through partial desolvation, and the highly polarizable transition state is stabilized by dispersion interactions with the aromatic residue Trp L91 and solvation of the leaving group oxygen by external water. The enzyme-like efficiency of general base catalysis in this system directly reflects the original hapten design, in which a charged guanidinium moiety was strategically used to elicit an accurately positioned functional group in an appropriate reaction environment and suggests that even larger catalytic effects may be achievable by extending this approach to the induction of acid-base pairs capable of bifunctional catalysis.

Misura K.M., Morozov A.V., Baker D.

pi-pi, Cation-pi, and hydrophobic packing interactions contribute specificity to protein folding and stability to the native state. As a step towards developing improved models of these interactions in proteins, we compare the side-chain packing arrangements in native proteins to those found in compact decoys produced by the Rosetta de novo structure prediction method. We find enrichments in the native distributions for T-shaped and parallel offset arrangements of aromatic residue pairs, in parallel stacked arrangements of cation-aromatic pairs, in parallel stacked pairs involving proline residues, and in parallel offset arrangements for aliphatic residue pairs. We then investigate the extent to which the distinctive features of native packing can be explained using Lennard-Jones and electrostatics models. Finally, we derive orientation-dependent pi-pi, cation-pi and hydrophobic interaction potentials based on the differences between the native and compact decoy distributions and investigate their efficacy for high-resolution protein structure prediction. Surprisingly, the orientation-dependent potential derived from the packing arrangements of aliphatic side-chain pairs distinguishes the native structure from compact decoys better than the orientation-dependent potentials describing pi-pi and cation-pi interactions.

Kaplan J., DeGrado W.F.

The de novo design of catalytic proteins provides a stringent test of our understanding of enzyme function, while simultaneously laying the groundwork for the design of novel catalysts. Here we describe the design of an O 2 -dependent phenol oxidase whose structure, sequence, and activity are designed from first principles. The protein catalyzes the two-electron oxidation of 4-aminophenol ( k cat / K M = 1,500 M ·1 ·min ·1 ) to the corresponding quinone monoimine by using a diiron cofactor. The catalytic efficiency is sensitive to changes of the size of a methyl group in the protein, illustrating the specificity of the design.

Hu Y., Houk K.N., Kikuchi K., Hotta K., Hilvert D.

The mechanisms by which solvents, antibodies, and albumins influence the rates of base-catalyzed reactions of benzisoxazoles have been explored theoretically. New experimental data on substituent effects and rates of reactions in several solvents, in an antibody, and in an albumin are reported. Quantum mechanical calculations were carried out for the reactions in water and acetonitrile, and docking of the transition state into a homology model of antibody 34E4 and an X-ray structure of human serum albumin was accomplished. A microenvironment made up of catalytic polar groups (glutamate in antibody 34E4 and lysine in human serum albumin) surrounded by relatively nonpolar groups is present in both catalytic proteins.

Kuhlman B., Dantas G., Ireton G.C., Varani G., Stoddard B.L., Baker D.

A major challenge of computational protein design is the creation of novel proteins with arbitrarily chosen three-dimensional structures. Here, we used a general computational strategy that iterates between sequence design and structure prediction to design a 93-residue α/β protein called Top7 with a novel sequence and topology. Top7 was found experimentally to be folded and extremely stable, and the x-ray crystal structure of Top7 is similar (root mean square deviation equals 1.2 angstroms) to the design model. The ability to design a new protein fold makes possible the exploration of the large regions of the protein universe not yet observed in nature.

Dantas G., Kuhlman B., Callender D., Wong M., Baker D.

A previously developed computer program for protein design, RosettaDesign, was used to predict low free energy sequences for nine naturally occurring protein backbones. RosettaDesign had no knowledge of the naturally occurring sequences and on average 65% of the residues in the designed sequences differ from wild-type. Synthetic genes for ten completely redesigned proteins were generated, and the proteins were expressed, purified, and then characterized using circular dichroism, chemical and temperature denaturation and NMR experiments. Although high-resolution structures have not yet been determined, eight of these proteins appear to be folded and their circular dichroism spectra are similar to those of their wild-type counterparts. Six of the proteins have stabilities equal to or up to 7kcal/mol greater than their wild-type counterparts, and four of the proteins have NMR spectra consistent with a well-packed, rigid structure. These encouraging results indicate that the computational protein design methods can, with significant reliability, identify amino acid sequences compatible with a target protein backbone.

Cesaro-Tadic S., Lagos D., Honegger A., Rickard J.H., Partridge L.J., Blackburn G.M., Plückthun A.

This report describes the selection of highly efficient antibody catalysts by combining chemical selection from a synthetic library with directed in vitro protein evolution. Evolution started from a naive antibody library displayed on phage made from fully synthetic, antibody-encoding genes (the Human Combinatorial Antibody Library; HuCAL-scFv). HuCAL-scFv was screened by direct selection for catalytic antibodies exhibiting phosphatase turnover. The substrate used was an aryl phosphate, which is spontaneously transformed into an electrophilic trapping reagent after cleavage. Chemical selection identified an efficient biocatalyst that then served as a template for error-prone PCR (epPCR) to generate randomized repertoires that were subjected to further selection cycles. The resulting superior catalysts displayed cumulative mutations throughout the protein sequence; the ten-fold improvement of their catalytic proficiencies (>1010 M−1) resulted from increased kcat values, thus demonstrating direct selection for turnover. The strategy described here makes the search for new catalysts independent of the immune system and the antibody framework.

Liu S., Liu Z.

Penner M., Klein O.J., Gantz M., Nintzel F.E., Prowald A., Boss S., Barker P., Dupree P., Hollfelder F.

Gutierrez-Rus L.I., Vos E., Pantoja-Uceda D., Hoffka G., Gutierrez-Cardenas J., Ortega-Muñoz M., Risso V.A., Jimenez M.A., Kamerlin S.C., Sanchez-Ruiz J.M.

Xu X., Wei W., Zhou Y., Liu J., Gao C., Hu G., Li X., Wen J., Liu L., Wu J., Song W.

Ding Y., Zhang S., Kong X., Hess H., Zhang Y.

AbstractEvolutionary constraints significantly limit the diversity of naturally occurring enzymes, thereby reducing the sequence repertoire available for enzyme discovery and engineering. Recent breakthroughs in protein structure prediction and de novo design, powered by artificial intelligence, now enable to create enzymes with desired functions without solely relying on traditional genome mining. Here, a computational strategy is demonstrated for creating new‐to‐nature polyethylene terephthalate hydrolases (PET hydrolases) by leveraging the known catalytic mechanisms and implementing multiple deep learning algorithms and molecular computations. This strategy includes the extraction of functional motifs from a template enzyme (here leaf‐branch compost cutinase, LCC, is used), regeneration of new protein sequences, computational screening, experimental validation, and sequence refinement. PET hydrolytic activity is successfully replicated with designer enzymes that are at least 30% shorter in sequence length than LCC. Among them, RsPETase1 stands out due to its robust expressibility. It exhibits comparable catalytic efficiency (kcat/Km) to LCC and considerable thermostability with a melting temperature of 56 °C, despite sharing only 34% sequence similarity with LCC. This work suggests that enzyme diversity can be expanded by recapitulating functional motifs with computationally built protein scaffolds, thus generating opportunities to acquire highly active and robust enzymes that do not exist in nature.

Lei Y., Yagi K., Sugita Y.

Shao Q., Hollenbeak A.C., Jiang Y., Ran X., Bachmann B.O., Yang Z.J.

Albanese K.I., Barbe S., Tagami S., Woolfson D.N., Schiex T.

Zarifi N., Asthana P., Doustmohammadi H., Klaus C., Sanchez J., Hunt S.E., Rakotoharisoa R.V., Osuna S., Fraser J.S., Chica R.A.

AbstractThe role of amino-acid residues distant from an enzyme’s active site in facilitating the complete catalytic cycle—including substrate binding, chemical transformation, and product release— remains poorly understood. Here, we investigate how distal mutations promote the catalytic cycle by engineering mutants of three de novo Kemp eliminases containing either active-site or distal mutations identified through directed evolution. Kinetic analyses, X-ray crystallography, and molecular dynamics simulations reveal that while active-site mutations create preorganized catalytic sites for efficient chemical transformation, distal mutations enhance catalysis by facilitating substrate binding and product release through tuning structural dynamics to widen the active-site entrance and reorganize surface loops. These distinct contributions work synergistically to improve overall activity, demonstrating that a well-organized active site, though necessary, is not sufficient for optimal catalysis. Our findings reveal critical roles that distal residues play in shaping the catalytic cycle to enhance efficiency, yielding valuable insights for enzyme design.

Романюк С.І., Комісаренко С.В.

Автори статті аналізують Нобелівську премію з хімії 2024 р., яку було присуджено американському біохіміку та комп’ютерному біологу Девіду Бейкеру (David Baker) за «комп'ютерний дизайн білків», а також представникам компанії Google DeepMind: британському фахівцю з систем штучного інтелекту Демісу Гассабісу (Demis Hassabis) і американському хіміку та інформатику Джону Джамперу (John M. Jumper) за «прогнозування структури білка». Досягнення нобелівських лауреатів у галузі обчислювального проєктування протеїнів та прогнозування їхньої структури відкрили нову еру біохімічних і біологічних досліджень, що в поєднанні із застосуванням інструментів штучного інтелекту матиме далекосяжні наслідки для людства.

Eberhart M.E., Alexandrova A.N., Ajmera P., Bím D., Chaturvedi S.S., Vargas S., Wilson T.R.

Patat A.S., Nalbantoğlu Ö.U.

ABSTRACTProtein sequence design is a highly challenging task, aimed at discovering new proteins that are more functional and producible under laboratory conditions than their natural counterparts. Deep learning‐based approaches developed to address this problem have achieved significant success. However, these approaches often do not adequately emphasize the functional properties of proteins. In this study, we developed a heuristic optimization method to enhance key functionalities such as solubility, flexibility, and stability, while preserving the structural integrity of proteins. This method aims to reduce laboratory demands by enabling a design that is both functional and structurally sound. This approach is particularly valuable for the synthetic production of proteins with anti‐inflammatory properties and those used in gene therapy. The designed proteins were initially evaluated for their ability to preserve natural structures using recovery and confidence metrics, followed by assessments with the AlphaFold tool. Additionally, natural protein sequences were mutated using a genetic algorithm and compared with those designed by our method. The results demonstrate that the protein sequences generated by our method exhibit much greater similarity to native protein sequences and structures. The code and sequences for the designed proteins are available at https://github.com/aysenursoyturk/HMHO.

Lauko A., Pellock S.J., Sumida K.H., Anishchenko I., Juergens D., Ahern W., Jeung J., Shida A., Hunt A., Kalvet I., Norn C., Humphreys I.R., Jamieson C., Krishna R., Kipnis Y., et. al.

The design of enzymes with complex active sites that mediate multistep reactions remains an outstanding challenge. With serine hydrolases as a model system, we combined the generative capabilities of RFdiffusion with an ensemble generation method for assessing active site preorganization to design enzymes starting from minimal active site descriptions. Experimental characterization revealed catalytic efficiencies ( k cat / K m ) up to 2.2x10 5 M −1 s −1 and crystal structures that closely match the design models (Cα RMSDs < 1 Å). Selection for structural compatibility across the reaction coordinate enabled identification of new catalysts in low-throughput screens with five different folds distinct from those of natural serine hydrolases. Our de novo approach provides insight into the geometric basis of catalysis and a roadmap for designing enzymes that catalyze multistep transformations.

Chen Y., Bhattacharya S., Bergmann L., Correy G.J., Tan S., Hou K., Biel J., Lu L., Bakanas I., Polizzi N.F., Fraser J.S., DeGrado W.F.

AbstractThe evolution of proteins that bind to small molecules and catalyze chemical transformations played a central role in the emergence of life. While natural proteins have finely tuned affinity for their primary ligands, they also often have weak affinities for other molecules. These interactions serve as starting points for the evolution of new specificities and functions. Inspired by this concept, we determined the ability of a simplede novoprotein to bind a set of diverse small molecules (< 300 Da) by crystallographic fragment screening. We then used this information to design one variant that binds fluorogenic molecule and another that acts as a highly efficient Kemp eliminase enzyme. Collectively, our work illuminates how the evolution of novel protein functions can emerge from existing proteins.

Beck J., Smith B.J., Zarifi N., Freund E., Chica R.A., Hoecker B.

AbstractThe TIM barrel is the most prevalent fold in natural enzymes, supporting efficient catalysis of diverse chemical reactions. Whilede novoTIM barrels have been successfully designed, their minimalistic architectures lack the structural elements necessary for substrate binding and catalysis. Here, we present CANVAS, a computational workflow that introduces a structural lid into a minimalde novoTIM barrel to anchor catalytic residues and form an active-site pocket for enzymatic function. Starting from twode novoTIM barrels, we designed nine variants with distinct lids to form active sites for the Kemp elimination. Experimental testing identified one active variant with catalytic efficiency comparable to previously reported Kemp eliminases. Mutational analyses confirmed that the designed lid is essential for catalysis, while molecular dynamics simulations revealed the importance of lid flexibility for substrate binding. This study reports the first enzymatically activede novoTIM barrel and establishes a platform for designing enzymes from minimal protein scaffolds.