Automated scaffold selection for enzyme design

A major goal of computational protein design is the construction of novel functions on existing protein scaffolds. There the first question is which scaffold is suitable for a specific reaction. Given a set of catalytic residues and their spatial arrangement, one wants to identify a protein scaffold that can host this active site. Here, we present an algorithm called ScaffoldSelection that is able to rapidly search large sets of protein structures for potential attachment sites of an enzymatic motif. The method consists of two steps; it first identifies pairs of backbone positions in pocket‐like regions. Then, it combines these to complete attachment sites using a graph theoretical approach. Identified matches are assessed for their ability to accommodate the substrate or transition state. A representative set of structures from the Protein Data Bank (～3500) was searched for backbone geometries that support the catalytic residues for 12 chemical reactions. Recapitulation of native active site geometries is used as a benchmark for the performance of the program. The native motif is identified in all 12 test cases, ranking it in the top percentile in 5 out of 12. The algorithm is fast and efficient, although dependent on the complexity of the motif. Comparisons to other methods show that ScaffoldSelection performs equally well in terms of accuracy and far better in terms of speed. Thus, ScaffoldSelection will aid future computational protein design experiments by preselecting protein scaffolds that are suitable for a specific reaction type and the introduction of a predefined amino acid motif. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

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 ∼ 2600 s^− 1 M^− 1 and an ∼ 10⁶-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.     

Optimization of reorganization energy drives evolution of the designed Kemp eliminase KE07

Understanding enzymatic evolution is essential to engineer enzymes with improved activities or to generate enzymes with tailor-made activities. The computationally designed Kemp eliminase KE07 carries out an unnatural reaction by converting of 5-nitrobenzisoxazole to cyanophenol, but its catalytic efficiency is significantly lower than those of natural enzymes. Three series of designed Kemp eliminases (KE07, KE70, KE59) were shown to be evolvable with considerable improvement in catalytic efficiency. Here we use the KE07 enzyme as a model system to reveal those forces, which govern enzymatic evolution and elucidate the key factors for improving activity. We applied the Empirical Valence Bond (EVB) method to construct the free energy pathway of the reaction in the original KE07 design and the evolved R7 1/3H variant. We analyzed catalytic effect of residues and demonstrated that not all mutations in evolution are favorable for activity. In contrast to the small decrease in the activation barrier, in vitro evolution significantly reduced the reorganization energy. We developed an algorithm to evaluate group contributions to the reorganization energy and used this approach to screen for KE07 variants with potential for improvement. We aimed to identify those mutations that facilitate enzymatic evolution, but might not directly increase catalytic efficiency. Computational results in accord with experimental data show that all mutations, which appear during in vitro evolution were either neutral or favorable for the reorganization energy. These results underscore that distant mutations can also play role in optimizing efficiency via their contribution to the reorganization energy. Exploiting this principle could be a promising strategy for computer-aided enzyme design. This article is part of a Special Issue entitled: The emerging dynamic view of proteins: Protein plasticity in allostery, evolution and self-assembly.     

Dewetting transitions in protein cavities

In a previous analysis of the solvation of protein active sites, a drying transition was observed in the narrow hydrophobic binding cavity of Cox‐2. With the use of a crude metric that often seems able to discriminate those protein cavities that dry from those that do not, we made an extensive search of the PDB, and identified five other proteins that, in molecular dynamics simulations, undergo drying transitions in their active sites. Because such cavities need not desolvate before binding hydrophobic ligands they often exhibit very large binding affinities. This article gives evidence that drying in protein cavities is not unique to Cox‐2. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Using a library of structural templates to recognise catalytic sites and explore their evolution in homologous families

Catalytic site structure is normally highly conserved between distantly related enzymes. As a consequence, templates representing catalytic sites have the potential to succeed at function prediction in cases where methods based on sequence or overall structure fail. There are many methods for searching protein structures for matches to structural templates, but few validated template libraries to use with these methods. We present a library of structural templates representing catalytic sites, based on information from the scientific literature. Furthermore, we analyse homologous template families to discover the diversity within families and the utility of templates for active site recognition. Templates representing the catalytic sites of homologous proteins mostly differ by less than 1A root mean square deviation, even when the sequence similarity between the two proteins is low. Within these sets of homologues there is usually no discernible relationship between catalytic site structure similarity and sequence similarity. Because of this structural conservation of catalytic sites, the templates can discriminate between matches to related proteins and random matches with over 85% sensitivity and predictive accuracy. Templates based on protein backbone positions are more discriminating than those based on side-chain atoms. These analyses show encouraging prospects for prediction of functional sites in structural genomics structures of unknown function, and will be of use in analyses of convergent evolution and exploring relationships between active site geometry and chemistry. The template library can be queried via a web server at and is available for download.     

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.     

Reprogramming EF-hands for design of catalytically amplified lanthanide sensors

We recently reported that a computationally designed catalyst nicknamed AlleyCat facilitates C–H proton abstraction in Kemp elimination at neutral pH in a selective and calcium-dependent fashion by a factor of approximately 100,000 (Korendovych et al. in Proc. Natl. Acad. Sci. USA 108:6823, 2011). Kemp elimination produced a colored product that can be easily read out, thus making AlleyCat a catalytically amplified metal sensor for calcium. Here we report that metal-binding EF-hand motifs in AlleyCat could be redesigned to incorporate trivalent metal ions without significant loss of catalytic activity. Mutation of a single neutral residue at position 9 of each of the EF-hands to glutamate results in almost a two orders of magnitude improvement of selectivity for trivalent metal ions over calcium. Development of this new lanthanide-dependent switchable Kemp eliminase, named CuSeCat EE, provides the foundation for further selectivity improvement and broadening the scope of the repertoire of metals for sensing. A concerted effort in the design of switchable enzymes has many environmental, sensing, and metal ion tracking applications.     

Comparison of designed and randomly generated catalysts for simple chemical reactions

There has been recent success in designing enzymes for simple chemical reactions using a two-step protocol. In the first step, a geometric matching algorithm is used to identify naturally occurring protein scaffolds at which predefined idealized active sites can be realized. In the second step, the residues surrounding the transition state model are optimized to increase transition state binding affinity and to bolster the primary catalytic side chains. To improve the design methodology, we investigated how the set of solutions identified by the design calculations relate to the overall set of solutions for two different chemical reactions. Using a TIM barrel scaffold in which catalytically active Kemp eliminase and retroaldolase designs were obtained previously, we carried out activity screens of random libraries made to be compositionally similar to active designs. A small number of active catalysts were found in screens of 10(3) variants for each of the two reactions, which differ from the computational designs in that they reuse charged residues already present in the native scaffold. The results suggest that computational design considerably increases the frequency of catalyst generation for active sites involving newly introduced catalytic residues, highlighting the importance of interaction cooperativity in enzyme active sites.     

A matching algorithm for catalytic residue site selection in computational enzyme design

A loop closure-based sequential algorithm, PRODA_MATCH, was developed to match catalytic residues onto a scaffold for enzyme design in silico. The computational complexity of this algorithm is polynomial with respect to the number of active sites, the number of catalytic residues, and the maximal iteration number of cyclic coordinate descent steps. This matching algorithm is independent of a rotamer library that enables the catalytic residue to take any required conformation during the reaction coordinate. The catalytic geometric parameters defined between functional groups of transition state (TS) and the catalytic residues are continuously optimized to identify the accurate position of the TS. Pseudo-spheres are introduced for surrounding residues, which make the algorithm take binding into account as early as during the matching process. Recapitulation of native catalytic residue sites was used as a benchmark to evaluate the novel algorithm. The calculation results for the test set show that the native catalytic residue sites were successfully identified and ranked within the top 10 designs for 7 of the 10 chemical reactions. This indicates that the matching algorithm has the potential to be used for designing industrial enzymes for desired reactions.     

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 × 10⁴ 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 function annotation by local binding site surface similarity

Hundreds of protein crystal structures exist for proteins whose function cannot be confidently determined from sequence similarity. Surflex‐PSIM, a previously reported surface‐based protein similarity algorithm, provides an alternative method for hypothesizing function for such proteins. The method now supports fully automatic binding site detection and is fast enough to screen comprehensive databases of protein binding sites. The binding site detection methodology was validated on apo/holo cognate protein pairs, correctly identifying 91% of ligand binding sites in holo structures and 88% in apo structures where corresponding sites existed. For correctly detected apo binding sites, the cognate holo site was the most similar binding site 87% of the time. PSIM was used to screen a set of proteins that had poorly characterized functions at the time of crystallization, but were later biochemically annotated. Using a fully automated protocol, this set of 8 proteins was screened against ～60,000 ligand binding sites from the PDB. PSIM correctly identified functional matches that predated query protein biochemical annotation for five out of the eight query proteins. A panel of 12 currently unannotated proteins was also screened, resulting in a large number of statistically significant binding site matches, some of which suggest likely functions for the podorly characterized proteins. Proteins 2014; 82:679–694. © 2013 Wiley Periodicals, Inc.     

OptGraft: A computational procedure for transferring a binding site onto an existing protein scaffold

One of the many challenging tasks of protein design is the introduction of a completely new function into an existing protein scaffold. In this study, we introduce a new computational procedure OptGraft for placing a novel binding pocket onto a protein structure so as its geometry is minimally perturbed. This is accomplished by introducing a two‐level procedure where we first identify where are the most appropriate locations to graft the new binding pocket into the protein fold by minimizing the departure from a set of geometric restraints using mixed‐integer linear optimization. On identifying the suitable locations that can accommodate the new binding pocket, CHARMM energy calculations are employed to identify what mutations in the neighboring residues, if any, are needed to ensure that the minimum energy conformation of the binding pocket conserves the desired geometry. This computational framework is benchmarked against the results available in the literature for engineering a copper binding site into thioredoxin protein. Subsequently, OptGraft is used to guide the transfer of a calcium‐binding pocket from thermitase protein (PDB: 1thm) into the first domain of CD2 protein (PDB:1hng). Experimental characterization of three de novo redesigned proteins with grafted calcium‐binding centers demonstrated that they all exhibit high affinities for terbium (K_d ～ 22, 38, and 55 μM) and can selectively bind calcium over magnesium.     

Looking at enzymes from the inside out: the proximity of catalytic residues to the molecular centroid can be used for detection of active sites and enzyme-ligand interfaces

Analysis of the distances of the exposed residues in 175 enzymes from the centroids of the molecules indicates that catalytic residues are very often found among the 5% of residues closest to the enzyme centroid. This property of catalytic residues is implemented in a new prediction algorithm (named EnSite) for locating the active sites of enzymes and in a new scheme for re-ranking enzyme-ligand docking solutions. EnSite examines only 5% of the molecular surface (represented by surface dots) that is closest to the centroid, identifying continuous surface segments and ranking them by their area size. EnSite ranks the correct prediction 1-4 in 97% of the cases in a dataset of 65 monomeric enzymes (rank 1 for 89% of the cases) and in 86% of the cases in a dataset of 176 monomeric and multimeric enzymes from all six top-level enzyme classifications (rank 1 in 74% of the cases). Importantly, identification of buried or flat active sites is straightforward because EnSite "looks" at the molecular surface from the inside out. Detailed examination of the results indicates that the proximity of the catalytic residues to the centroid is a property of the functional unit, defined as the assembly of domains or chains that form the active site (in most cases the functional unit corresponds to a single whole polypeptide chain). Using the functional unit in the prediction further improves the results. The new property of active sites is also used for re-evaluating enzyme-inhibitor unbound docking results. Sorting the docking solutions by the distance of the interface to the centroid of the enzyme improves remarkably the ranks of nearly correct solutions compared to ranks based on geometric-electrostatic-hydrophobic complementarity scores.     

Evolutionary potential of (beta/alpha)8-barrels: functional promiscuity produced by single substitutions in the enolase superfamily

The members of the mechanistically diverse, (beta/alpha)(8)-barrel fold-containing enolase superfamily evolved from a common progenitor but catalyze different reactions using a conserved partial reaction. The molecular pathway for natural divergent evolution of function in the superfamily is unknown. We have identified single-site mutants of the (beta/alpha)(8)-barrel domains in both the l-Ala-d/l-Glu epimerase from Escherichia coli (AEE) and the muconate lactonizing enzyme II from Pseudomonas sp. P51 (MLE II) that catalyze the o-succinylbenzoate synthase (OSBS) reaction as well as the wild-type reaction. These enzymes are members of the MLE subgroup of the superfamily, share conserved lysines on opposite sides of their active sites, but catalyze acid- and base-mediated reactions with different mechanisms. A comparison of the structures of AEE and the OSBS from E. coli was used to design the D297G mutant of AEE; the E323G mutant of MLE II was isolated from directed evolution experiments. Although neither wild-type enzyme catalyzes the OSBS reaction, both mutants complement an E. coli OSBS auxotroph and have measurable levels of OSBS activity. The analogous mutations in the D297G mutant of AEE and the E323G mutant of MLE II are each located at the end of the eighth beta-strand of the (beta/alpha)(8)-barrel and alter the ability of AEE and MLE II to bind the substrate of the OSBS reaction. The substitutions relax the substrate specificity, thereby allowing catalysis of the mechanistically diverse OSBS reaction with the assistance of the active site lysines. The generation of functionally promiscuous and mechanistically diverse enzymes via single-amino acid substitutions likely mimics the natural divergent evolution of enzymatic activities and also highlights the utility of the (beta/alpha)(8)-barrel as a scaffold for new function.     

Crystal structure of a metal-dependent phosphoesterase (YP_910028.1) from Bifidobacterium adolescentis: Computational prediction and experimental validation of phosphoesterase activity

The crystal structures of an unliganded and adenosine 5′‐monophosphate (AMP) bound, metal‐dependent phosphoesterase (YP_910028.1) from Bifidobacterium adolescentis are reported at 2.4 and 1.94 Å, respectively. Functional characterization of this enzyme was guided by computational analysis and then confirmed by experiment. The structure consists of a polymerase and histidinol phosphatase (PHP, Pfam: PF02811) domain with a second domain (residues 105‐178) inserted in the middle of the PHP sequence. The insert domain functions in binding AMP, but the precise function and substrate specificity of this domain are unknown. Initial bioinformatics analyses yielded multiple potential functional leads, with most of them suggesting DNA polymerase or DNA replication activity. Phylogenetic analysis indicated a potential DNA polymerase function that was somewhat supported by global structural comparisons identifying the closest structural match to the alpha subunit of DNA polymerase III. However, several other functional predictions, including phosphoesterase, could not be excluded. Theoretical microscopic anomalous titration curve shapes, a computational method for the prediction of active sites from protein 3D structures, identified potential reactive residues in YP_910028.1. Further analysis of the predicted active site and local comparison with its closest structure matches strongly suggested phosphoesterase activity, which was confirmed experimentally. Primer extension assays on both normal and mismatched DNA show neither extension nor degradation and provide evidence that YP_910028.1 has neither DNA polymerase activity nor DNA‐proofreading activity. These results suggest that many of the sequence neighbors previously annotated as having DNA polymerase activity may actually be misannotated. Proteins 2011. © 2011 Wiley‐Liss, Inc.     

Systematic optimization model and algorithm for binding sequence selection in computational enzyme design

A systematic optimization model for binding sequence selection in computational enzyme design was developed based on the transition state theory of enzyme catalysis and graph‐theoretical modeling. The saddle point on the free energy surface of the reaction system was represented by catalytic geometrical constraints, and the binding energy between the active site and transition state was minimized to reduce the activation energy barrier. The resulting hyperscale combinatorial optimization problem was tackled using a novel heuristic global optimization algorithm, which was inspired and tested by the protein core sequence selection problem. The sequence recapitulation tests on native active sites for two enzyme catalyzed hydrolytic reactions were applied to evaluate the predictive power of the design methodology. The results of the calculation show that most of the native binding sites can be successfully identified if the catalytic geometrical constraints and the structural motifs of the substrate are taken into account. Reliably predicting active site sequences may have significant implications for the creation of novel enzymes that are capable of catalyzing targeted chemical reactions.     

Active site titration as a tool for the evaluation of immobilization procedures of penicillin acylase

Native and immobilized preparations of penicillin acylase from Escherichia coli and Alcaligenes faecalis were studied using an active site titration technique. Knowledge of the number of active sites allowed the calculation of the average turnover rate of the enzyme in the various preparations and allowed us to quantify the contribution of irreversible inactivation of the enzyme to the loss of catalytic activity during the immobilization procedure. In most cases a loss of active sites as well as a decrease of catalytic activity per active site (turnover rate) was observed upon immobilization. Immobilization techniques affected the enzymes differently. The effect of increased loading of penicillin acylase on the average turnover rate was determined by active site titration to assess diffusion limitations in the carrier.     

Engineering of a bacterial tyrosinase for improved catalytic efficiency towards D‐tyrosine using random and site directed mutagenesis approaches

The tyrosinase gene from Ralstonia solanacearum (GenBank NP518458) was subjected to random mutagenesis resulting in tyrosinase variants (RVC10 and RV145) with up to 3.2‐fold improvement in k_cat, 5.2‐fold lower K_m and 16‐fold improvement in catalytic efficiency for D ‐tyrosine. Based on RVC10 and RV145 mutated sequences, single mutation variants were generated with all variants showing increased k_cat for D ‐tyrosine compared to the wild type (WT). All single mutation variants based on RV145 had a higher k_cat and K_m value compared to the RV145 and thus the combination of four mutations in RV145 was antagonistic for turnover, but synergistic for affinity of the enzyme for D ‐tyrosine. Single mutation variant 145_V153A exhibited the highest (6.9‐fold) improvement in k_cat and a 2.4‐fold increase in K_m compared to the WT. Two single mutation variants, C10_N322S and C10_T183I reduced the K_m up to 2.6‐fold for D ‐tyrosine but one variant 145_V153A increased the K_m 2.4‐fold compared to the WT. Homology based modeling of R. solanacearum tyrosinase showed that mutation V153A disrupts the van der Waals interactions with an α‐helix providing one of the conserved histidine residues of the active site. The k_cat and K_m values for L ‐tyrosine decreased for RV145 and RVC10 compared to the WT. RV145 exhibited a 2.1‐fold high catalytic efficiency compared to the WT which is a 7.6‐fold lower improvement compared to D ‐tyrosine. RV145 exhibited a threefold higher monophenolase:diphenolase activity ratio for D ‐tyrosine:D ‐DOPA and a 1.4‐fold higher L ‐tyrosine:L ‐DOPA activity ratio compared to the WT. Biotechnol. Bioeng. 2013; 110: 1849–1857. © 2013 Wiley Periodicals, Inc.     

Vicinity analysis: a methodology for the identification of similar protein active sites

Vicinity analysis (VA) is a new methodology developed to identify similarities between protein binding sites based on their three-dimensional structure and the chemical similarity of matching residues. The major objective is to enable searching of the Protein Data Bank (PDB) for similar sub-pockets, especially in proteins from different structural and biochemical series. Inspection of the ligands bound in these pockets should allow ligand functionality to be identified, thus suggesting novel monomers for use in library synthesis. VA has been developed initially using the ATP binding site in kinases, an important class of protein targets involved in cell signalling and growth regulation. This paper defines the VA procedure and describes matches to the phosphate binding sub-pocket of cyclin-dependent protein kinase 2 that were found by searching a small test database that has also been used to parameterise the methodology.     

Catalytic and binding poly-reactivities shared by two unrelated proteins: The potential role of promiscuity in enzyme evolution

It is generally accepted that enzymes evolved via gene duplication of existing proteins. But duplicated genes can serve as a starting point for the evolution of a new function only if the protein they encode happens to exhibit some activity towards this new function. Although the importance of such catalytic promiscuity in enzyme evolution has been proposed, little is actually known regarding how common promiscuous catalytic activities are in proteins or their origins, magnitudes, and potential contribution to the survival of an organism. Here we describe a pattern of promiscuous activities in two completely unrelated proteins-serum albumins and a catalytic antibody (aldolase antibody 38C2). Despite considerable structural dissimilarities-in the shape of the cavities and the position of catalytic lysine residues-both active sites are able to catalyze the Kemp elimination, a model reaction for proton transfer from carbon. We also show that these different active sites can bind promiscuously an array of hydrophobic negatively charged ligands. We suggest that the basic active-site features of an apolar pocket and a lysine residue can act as a primitive active site allowing these promiscuous activities to take place. We also describe, by modelling product formation at different substrate concentrations, how promiscuous activities of this kind- inefficient and rudimentary as they are-can provide a considerable selective advantage and a starting point for the evolution of new functions.