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.     

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.     

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.     

Simultaneous modeling of multiple loops in proteins.

The most reliable methods for predicting protein structure are by way of homologous extension, using structural information from a closely related protein, or by "threading" through a set of predefined protein folds ("inverse folding"). Both sets of methods provide a model for the core of the protein--the structurally conserved secondary structures. Due to the large variability both in sequence and size of the loops that connect these secondary structures, they generally cannot be modeled using these techniques. Loop-closure algorithms are aimed at predicting loop structures, given their end-to-end distance. Various such algorithms have been described, and all have been tested by predicting the structure of a single loop in a known protein. In this paper we propose a method, which is based on the bond-scaling-relaxation loop-closure algorithm, for simultaneously predicting the structures of multiple loops, and demonstrate that, for two spatially close loops, simultaneous closure invariably leads to more accurate predictions than sequential closure. The accuracy of the predictions obtained for pairs of loops in the size range of 5-7 residues each is comparable to that obtained by other methods, when predicting the structures of single loops: the RMS deviations from the native conformations of various test cases modeled are approximately 0.6-1.7 A for backbone atoms and 1.1-3.3 A for all-atoms.     

De novo enzyme design using Rosetta3

The Rosetta de novo enzyme design protocol has been used to design enzyme catalysts for a variety of chemical reactions, and in principle can be applied to any arbitrary chemical reaction of interest. The process has four stages: 1) choice of a catalytic mechanism and corresponding minimal model active site, 2) identification of sites in a set of scaffold proteins where this minimal active site can be realized, 3) optimization of the identities of the surrounding residues for stabilizing interactions with the transition state and primary catalytic residues, and 4) evaluation and ranking the resulting designed sequences. Stages two through four of this process can be carried out with the Rosetta package, while stage one needs to be done externally. Here, we demonstrate how to carry out the Rosetta enzyme design protocol from start to end in detail using for illustration the triosephosphate isomerase reaction.     

Antibodies as a model system for comparative model refinement

Predicting the conformations of loops is a critical aspect of protein comparative (homology) modeling. Despite considerable advances in developing loop prediction algorithms, refining loops in homology models remains challenging. In this work, we use antibodies as a model system to investigate strategies for more robustly predicting loop conformations when the protein model contains errors in the conformations of side chains and protein backbone surrounding the loop in question. Specifically, our test system consists of partial models of antibodies in which the “scaffold” (i.e., the portion other than the complementarity determining region, CDR, loops) retains native backbone conformation, whereas the CDR loops are predicted using a combination of knowledge‐based modeling (H1, H2, L1, L2, and L3) and ab initio loop prediction (H3). H3 is the most variable of the CDRs. Using a previously published method, a test set of 10 shorter H3 loops (5–7 residues) are predicted to an average backbone (N? Cα? C? O) RMSD of 2.7 Å while 11 longer loops (8–9 residues) are predicted to 5.1 Å, thus recapitulating the difficulties in refining loops in models. By contrast, in control calculations predicting the same loops in crystal structures, the same method reconstructs the loops to an average of 0.5 and 1.4 Å for the shorter and longer loops, respectively. We modify the loop prediction method to improve the ability to sample near‐native loop conformations in the models, primarily by reducing the sensitivity of the sampling to the loop surroundings, and allowing the other CDR loops to optimize with the H3 loop. The new method improves the average accuracy significantly to 1.3 Å RMSD and 3.1 Å RMSD for the shorter and longer loops, respectively. Finally, we present results predicting 8–10 residue loops within complete comparative models of five nonantibody proteins. While anecdotal, these mixed, full‐model results suggest our approach is a promising step toward more accurately predicting loops in homology models. Furthermore, while significant challenges remain, our method is a potentially useful tool for predicting antibody structures based on a known Fv scaffold. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Induced-fit Mechanism for Prolyl Endopeptidase

Prolyl peptidases cleave proteins at proline residues and are of importance for cancer, neurological function, and type II diabetes. Prolyl endopeptidase (PEP) cleaves neuropeptides and is a drug target for neuropsychiatric diseases such as post-traumatic stress disorder, depression, and schizophrenia. Previous structural analyses showing little differences between native and substrate-bound structures have suggested a lock-and-key catalytic mechanism. We now directly demonstrate from seven structures of Aeromonus punctata PEP that the mechanism is instead induced fit: the native enzyme exists in a conformationally flexible opened state with a large interdomain opening between the β-propeller and α/β-hydrolase domains; addition of substrate to preformed native crystals induces a large scale conformational change into a closed state with induced-fit adjustments of the active site, and inhibition of this conformational change prevents substrate binding. Absolute sequence conservation among 28 orthologs of residues at the active site and critical residues at the interdomain interface indicates that this mechanism is conserved in all PEPs. This finding has immediate implications for the use of conformationally targeted drug design to improve specificity of inhibition against this family of proline-specific serine proteases.     

The crystal structure of pyruvate decarboxylase from Kluyveromyces lactis. Implications for the substrate activation mechanism of this enzyme

The crystal structure of pyruvate decarboxylase from Kluyveromyces lactis has been determined to 2.26 A resolution. Like other yeast enzymes, Kluyveromyces lactis pyruvate decarboxylase is subject to allosteric substrate activation. Binding of substrate at a regulatory site induces catalytic activity. This process is accompanied by conformational changes and subunit rearrangements. In the nonactivated form of the corresponding enzyme from Saccharomyces cerevisiae, all active sites are solvent accessible due to the high flexibility of loop regions 106-113 and 292-301. The binding of the activator pyruvamide arrests these loops. Consequently, two of four active sites become closed. In Kluyveromyces lactis pyruvate decarboxylase, this half-side closed tetramer is present even without any activator. However, one of the loops (residues 105-113), which are flexible in nonactivated Saccharomyces cerevisiae pyruvate decarboxylase, remains flexible. Even though the tetramer assemblies of both enzyme species are different in the absence of activating agents, their substrate activation kinetics are similar. This implies an equilibrium between the open and the half-side closed state of yeast pyruvate decarboxylase tetramers. The completely open enzyme state is favoured for Saccharomyces cerevisiae pyruvate decarboxylase, whereas the half-side closed form is predominant for Kluyveromyces lactis pyruvate decarboxylase. Consequently, the structuring of the flexible loop region 105-113 seems to be the crucial step during the substrate activation process of Kluyveromyces lactis pyruvate decarboxylase.     

Modeling protein loops using a phi i + 1, psi i dimer database.

We present an automated method for modeling backbones of protein loops. The method samples a database of phi i + 1 and psi i angles constructed from a nonredundant version of the Protein Data Bank (PDB). The dihedral angles phi i + 1 and psi i completely define the backbone conformation of a dimer when standard bond lengths, bond angles, and a trans planar peptide configuration are used. For the 400 possible dimers resulting from 20 natural amino acids, a list of allowed phi i + 1, psi i pairs for each dimer is created by pooling all such pairs from the loop segments of each protein in the nonredundant version of the PDB. Starting from the N-terminus of the loop sequence, conformations are generated by assigning randomly selected pairs of phi i + 1, psi i for each dimer from the respective pool using standard bond lengths, bond angles, and a trans peptide configuration. We use this database to simulate protein loops of lengths varying from 5 to 11 amino acids in five proteins of known three-dimensional structures. Typically, 10,000-50,000 models are simulated for each protein loop and are evaluated for stereochemical consistency. Depending on the length and sequence of a given loop, 50-80% of the models generated have no stereochemical strain in the backbone atoms. We demonstrate that, when simulated loops are extended to include flanking residues from homologous segments, only very few loops from an ensemble of sterically allowed conformations orient the flanking segments consistent with the protein topology. The presence of near-native backbone conformations for loops from five different proteins suggests the completeness of the dimeric database for use in modeling loops of homologous proteins. Here, we take advantage of this observation to design a method that filters near-native loop conformations from an ensemble of sterically allowed conformations. We demonstrate that our method eliminates the need for a loop-closure algorithm and hence allows for the use of topological constraints of the homologous proteins or disulfide constraints to filter near-native loop conformations.     

Catalysing new reactions during evolution: economy of residues and mechanism

The diversity of function in some enzyme superfamilies shows that during evolution, enzymes have evolved to catalyse different reactions on the same structure scaffold. In this analysis, we examine in detail how enzymes can modify their chemistry, through a comparison of the catalytic residues and mechanisms in 27 pairs of homologous enzymes of totally different functions. We find that evolution is very economical. Enzymes retain structurally conserved residues to aid catalysis, including residues that bind catalytic metal ions and modulate cofactor chemistry. We examine the conservation of residue type and residue function in these structurally conserved residue pairs. Additionally, enzymes often retain common mechanistic steps catalyzed by structurally conserved residues. We have examined these steps in the context of their overall reactions.     

Structure and catalytic cycle of beta-1,4-galactosyltransferase

Beta-1,4-galactosyltransferase-1, a housekeeping enzyme that functions in the synthesis of glycoconjugates, has two flexible loops, one short and one long. Upon binding a metal ion and UDP-galactose, the loops change from an open to a closed conformation, repositioning residues to lock the ligands in place. Residues at the N-terminal region of the long loop form the metal-binding site and those at the C-terminal region form a helix, which becomes part of the binding site for the oligosaccharide acceptor; the remaining residues cover the bound sugar-nucleotide. After binding of the oligosaccharide acceptor and transfer of the galactose moiety, the product disaccharide unit is ejected and the enzyme returns to the open conformation, repeating the catalytic cycle.     

Chemical modification with functionalized ionic liquids: a novel method to improve the enzymatic properties of Candida rugosa lipase

Chemical modification of lysine residues in Candida rugosa lipase (CRL) was carried out using five different functional ionic liquids, and about 15.4–25.0 % of the primary amino groups of lysine were modified. Enzymatic properties of the native and modified CRLs were investigated in olive oil hydrolysis reaction. Improved thermal stability, catalytic activity in organic solvents, and adaptability to temperature and pH changes were achieved compared with the native enzyme. CRL modified by [choline][H₂PO₄] showed the best results, bearing a maximum improvement of 16.7 % in terms of relative activity, 5.2-fold increase in thermostability (after incubation at 45 °C for 5 h), and 2.3-fold increase in activity in strong polar organic solvent (80 % dimethyl sulfoxide) compared with the native enzyme. The results of ultraviolet, circular dichroism and fluorescence spectroscopy suggested that the change of the secondary and tertiary structures of CRL caused by the chemical modification resulted in the enhancement of enzymatic performance. The modification of CRL with functional ionic liquids was proved to be a novel and efficient method for improving the enzymatic properties of CRL.     

Explaining an unusually fast parasitic enzyme: folate tail-binding residues dictate substrate positioning and catalysis in Cryptosporidium hominis thymidylate synthase

The essential enzyme TS-DHFR from Cryptosporidium hominis undergoes an unusually rapid rate of catalysis at the conserved TS domain, facilitated by two nonconserved residues, Ala287 and Ser290, in the folate tail-binding region. Mutation of these two residues to their conserved counterparts drastically affects multiple steps of the TS catalytic cycle. We have determined the crystal structures of all three mutants (A287F, S290G, and A287F/S290G) in complex with active site ligands dUMP and CB3717. The structural data show two effects of the mutations: an increased distance between the ligands in the active site and increased flexibility of the folate ligand in the partially open enzyme state that precedes conformational change to the active catalytic state. The latter effect is able to be rescued by the mutants containing the A287F mutation. In addition, the conserved water network of TS is altered in each of the mutants. The structural results point to a role of the folate tail-binding residues in closely positioning ChTS ligands and restricting ligand flexibility in the partially open state to allow for a rapid transition to the active closed state and enhanced rate of catalysis. These results provide an explanation on how folate tail-binding residues at one end of the active site affect long-range interactions throughout the TS active site and validate these residues as targets for species-specific drug design.     

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.     

Structure and dynamics of the G121V dihydrofolate reductase mutant: lessons from a transition-state inhibitor complex

It is well known that enzyme flexibility is critical for function. This is due to the observation that the rates of intramolecular enzyme motions are often matched to the rates of intermolecular events such as substrate binding and product release. Beyond this role in progression through the reaction cycle, it has been suggested that enzyme dynamics may also promote the chemical step itself. Dihydrofolate reductase (DHFR) is a model enzyme for which dynamics have been proposed to aid in both substrate flux and catalysis. The G121V mutant of DHFR is a well studied form that exhibits a severe reduction in the rate of hydride transfer yet there remains dispute as to whether this defect is caused by altered structure, dynamics, or both. Here we address this by presenting an NMR study of the G121V mutant bound to reduced cofactor and the transition state inhibitor, methotrexate. NMR chemical shift markers demonstrate that this form predominantly adopts the closed conformation thereby allowing us to provide the first glimpse into the dynamics of a catalytically relevant complex. Based on (15)N and (2)H NMR spin relaxation, we find that the mutant complex has modest changes in ps-ns flexibility with most affected residues residing in the distal adenosine binding domain rather than the active site. Thus, aberrant ps-ns dynamics are likely not the main contributor to the decreased catalytic rate. The most dramatic effect of the mutation involves changes in μs-ms dynamics of the F-G and Met20 loops. Whereas loop motion is quenched in the wild type transition state inhibitor complex, the F-G and Met20 loops undergo excursions from the closed conformation in the mutant complex. These excursions serve to decrease the population of conformers having the correct active site configuration, thus providing an explanation for the G121V catalytic defect.     

Dynamics of the active site loops in catalyzing aminoacylation reaction in seryl and histidyl tRNA synthetases

Aminoacylation reaction is the first step of protein biosynthesis. The catalytic reorganization at the active site of aminoacyl tRNA synthetases (aaRSs) is driven by the loop motions. There remain lacunae of understanding concerning the catalytic loop dynamics in aaRSs. We analyzed the functional loop dynamics in seryl tRNA synthetase from Methanopyrus kandleri (^mkSerRS) and histidyl tRNA synthetases from Thermus thermophilus (^ttHisRS), respectively, using molecular dynamics. Results confirm that the motif 2 loop and other active site loops are flexible spots within the catalytic domain. Catalytic residues of the loops form a network of interaction with the substrates to form a reactive state. The loops undergo transitions between closed state and open state and the relaxation of the constituent residues occurs in femtosecond to nanosecond time scale. Order parameters are higher for constituent catalytic residues which form a specific network of interaction with the substrates to form a reactive state compared to the Gly residues within the loop. The development of interaction is supported from mutation studies where the catalytic domain with mutated loop exhibits unfavorable binding energy with the substrates. During the open-close motion of the loops, the catalytic residues make relaxation by ultrafast librational motion as well as fast diffusive motion and subsequently relax rather slowly via slower diffusive motion. The Gly residues act as a hinge to facilitate the loop closing and opening by their faster relaxation behavior. The role of bound water is analyzed by comparing implicit solvent-based and explicit solvent-based simulations. Loops fail to form catalytically competent geometry in absence of water. The present result, for the first time reveals the nature of the active site loop dynamics in aaRS and their influence on catalysis.     

Identification of Histidine 303 as the Catalytic Base of Lysyl Oxidase via Site-Directed Mutagenesis

Lysyl oxidase (LOX) is a copper-dependent amine oxidase enzyme that catalyzes the formation of crosslinkages of collagen and elastin in connective tissues by oxidative deamination of lysine. Using site-directed mutagenesis, Histidine 303 has been shown to be a key residue that acts as the necessary catalytic base for this enzyme to function properly. Histidine 303 was mutated to isoleucine to remove catalytic activity and to aspartate and glutamate, respectively, in order to provide alternate residues that could act as a general base that could maintain catalytic activity. Overexpression of the H303I mutant yielded 3.9 mg of enzyme per liter of media, the H303D mutant yielded 3.3 mg of enzyme per liter of media, and the H303E mutant yielded 3.0 mg/L of media. Overexpression of wildtype LOX yielded 4.5 mg/L of media, which is a slight improvement from previous yields. Total copper incorporation for H303I was calculated to be 68% and no copper was detected for the H303D and H303E mutants. As LOX requires the self-processed cofactor lysyl tyrosyl quinone (LTQ) for activity, total LTQ content was obtained by reacting the enzyme with phenylhydrazine and using the previously reported extinction coefficient of 15.4 mM/cm. LTQ content for the wildtype enzyme was determined to be 92%, for H303I the total LTQ content was determined to be 36%, and no LTQ was detected for the H303D and H303E mutants. No catalytic activity was detected for any mutants when compared to the wildtype which has a previously reported activity of 0.11 U/mg. Comparison of excitation–emission matrices (EEM) of each of the mutants as compared to the wildtype indicate that all the mutations cause a change in the internal environment of the enzyme, albeit to varying degrees, as evidenced by the observed shifts.     

Importance of Arg-599 of β-galactosidase (Escherichia coli) as an anchor for the open conformations of Phe-601 and the active-site loop

Structural and kinetic data show that Arg-599 of β-galactosidase plays an important role in anchoring the "open" conformations of both Phe-601 and an active-site loop (residues 794-803). When alanine was substituted for Arg-599, the conformations of Phe-601 and the loop shifted towards the "closed" positions because interactions with the guanidinium side chain were lost. Also, Phe-601, the loop, and Na+, which is ligated by the backbone carbonyl of Phe-601, lost structural order, as indicated by large B-factors. IPTG, a substrate analog, restored the conformations of Phe-601 and the loop of R599A-β-galactosidase to the open state found with IPTG-complexed native enzyme and partially reinstated order. ?-Galactonolactone, a transition state analog, restored the closed conformations of R599A-β-galactosidase to those found with ?-galactonolactone-complexed native enzyme and completely re-established the order. Substrates and substrate analogs bound R599A-β-galactosidase with less affinity because the closed conformation does not allow substrate binding and extra energy is required for Phe-601 and the loop to open. In contrast, transition state analog binding, which occurs best when the loop is closed, was several-fold better. The higher energy level of the enzyme?substrate complex and the lower energy level of the first transition state means that less activation energy is needed to form the first transition state and thus the rate of the first catalytic step (k2) increased substantially. The rate of the second catalytic step (k3) decreased, likely because the covalent form is more stabilized than the second transition state when Phe-601 and the loop are closed. The importance of the guanidinium group of Arg-599 was confirmed by restoration of conformation, order, and activity by guanidinium ions.     

Structural analyses of covalent enzyme-substrate analog complexes reveal strengths and limitations of de novo enzyme 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.