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.     

A computational method for design of connected catalytic networks in proteins

Computational design of new active sites has generally proceeded by geometrically defining interactions between the reaction transition state(s) and surrounding side‐chain functional groups which maximize transition‐state stabilization, and then searching for sites in protein scaffolds where the specified side‐chain–transition‐state interactions can be realized. A limitation of this approach is that the interactions between the side chains themselves are not constrained. An extensive connected hydrogen bond network involving the catalytic residues was observed in a designed retroaldolase following directed evolution. Such connected networks could increase catalytic activity by preorganizing active site residues in catalytically competent orientations, and enabling concerted interactions between side chains during catalysis, for example, proton shuffling. We developed a method for designing active sites in which the catalytic side chains, in addition to making interactions with the transition state, are also involved in extensive hydrogen bond networks. Because of the added constraint of hydrogen‐bond connectivity between the catalytic side chains, to find solutions, a wider range of interactions between these side chains and the transition state must be considered. Our new method starts from a ChemDraw‐like two‐dimensional representation of the transition state with hydrogen‐bond donors, acceptors, and covalent interaction sites indicated, and all placements of side‐chain functional groups that make the indicated interactions with the transition state, and are fully connected in a single hydrogen‐bond network are systematically enumerated. The RosettaMatch method can then be used to identify realizations of these fully‐connected active sites in protein scaffolds. The method generates many fully‐connected active site solutions for a set of model reactions that are promising starting points for the design of fully‐preorganized enzyme catalysts.     

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.     

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.     

New algorithms and an in silico benchmark for computational enzyme design

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

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.     

A fast loop-closure algorithm to accelerate residue matching in computational enzyme design

Constructing an active site on an inert scaffold is still a challenge in chemical biology. Herein, we describe the incorporation of a Newton-direction-based fast loop-closure algorithm for catalytic residue matching into our enzyme design program ProdaMatch. This was developed to determine the sites and geometries of the catalytic residues as well as the position of the transition state with high accuracy in order to satisfy the geometric constraints on the interactions between catalytic residues and the transition state. Loop-closure results for 64,827 initial loops derived from 21 loops in the test set showed that 99.51 % of the initial loops closed to within 0.05 Å in fewer than 400 iteration steps, while the large majority of the initial loops closed within 100 iteration steps. The revised version of ProdaMatch containing the novel loop-closure algorithm identified all native matches for ten scaffolds in the native active-site recapitulation test. Its high speed and accuracy when matching catalytic residues with a scaffold make this version of ProdaMatch potentially useful for scaffold selection through the incorporation of more complex theoretical enzyme models which may yield higher initial activities in de novo enzyme design.     

Robust design and optimization of retroaldol enzymes

Enzyme catalysts of a retroaldol reaction have been generated by computational design using a motif that combines a lysine in a nonpolar environment with water-mediated stabilization of the carbinolamine hydroxyl and β-hydroxyl groups. Here, we show that the design process is robust and repeatable, with 33 new active designs constructed on 13 different protein scaffold backbones. The initial activities are not high but are increased through site-directed mutagenesis and laboratory evolution. Mutational data highlight areas for improvement in design. Different designed catalysts give different borohydride-reduced reaction intermediates, suggesting a distribution of properties of the designed enzymes that may be further explored and exploited.     

How similar are enzyme active site geometries derived from quantum mechanical theozymes to crystal structures of enzyme‐inhibitor complexes? Implications for enzyme design

Quantum mechanical optimizations of theoretical enzymes (theozymes), which are predicted catalytic arrays of biological functionalities stabilizing a transition state, have been carried out for a set of nine diverse enzyme active sites. For each enzyme, the theozyme for the rate-determining transition state plus the catalytic groups modeled by side-chain mimics was optimized using B3LYP/6-31G(d) or, in one case, HF/3-21G(d) quantum mechanical calculations. To determine if the theozyme can reproduce the natural evolutionary catalytic geometry, the positions of optimized catalytic atoms, i.e., covalent, partial covalent, or stabilizing interactions with transition state atoms, are compared to the positions of the atoms in the X-ray crystal structure with a bound inhibitor. These structure comparisons are contrasted to computed substrate-active site structures surrounded by the same theozyme residues. The theozyme/transition structure is shown to predict geometries of active sites with an average RMSD of 0.64 A from the crystal structure, while the RMSD for the bound intermediate complexes are significantly higher at 1.42 A. The implications for computational enzyme design are discussed.     

Extension of a de novo TIM barrel with a rationally designed secondary structure element

The ability to construct novel enzymes is a major aim in de novo protein design. A popular enzyme fold for design attempts is the TIM barrel. This fold is a common topology for enzymes and can harbor many diverse reactions. The recent de novo design of a four‐fold symmetric TIM barrel provides a well understood minimal scaffold for potential enzyme designs. Here we explore opportunities to extend and diversify this scaffold by adding a short de novo helix on top of the barrel. Due to the size of the protein, we developed a design pipeline based on computational ab initio folding that solves a less complex sub‐problem focused around the helix and its vicinity and adapt it to the entire protein. We provide biochemical characterization and a high‐resolution X‐ray structure for one variant and compare it to our design model. The successful extension of this robust TIM‐barrel scaffold opens opportunities to diversify it towards more pocket like arrangements and as such can be considered a building block for future design of binding or catalytic sites.     

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.     

AutoMatch: target-binding protein design and enzyme design by automatic pinpointing potential active sites in available protein scaffolds

Proteins perform their functions mainly via active sites, whereas other parts of the proteins comprise the scaffolds, which support the active sites. One strategy for protein functional design is transplanting active sites, such as catalytic sites for enzyme or binding hot spots for protein-protein interactions, onto a new scaffold. AutoMatch is a new program designed for efficiently elucidating suitable scaffolds and potential sites on the scaffolds. Backrub motions are used to treat backbone flexibility during the design process. A step-by-step checking strategy and cluster-representation examination strategy were developed to solve the large combinatorial problem for the matching of active-site conformations. In addition, a grid-based binding energy scoring method was used to filter the solutions. An enzyme design benchmark and a protein-protein interaction design benchmark were built to test the algorithm. AutoMatch could identify the hot spots in the nonbinding protein and rank them within the top five results for 8 of 10 target-binding protein design cases. In addition, among the 15 enzymes tested, AutoMatch can identify the catalytic active sites in the apoprotein and rank them within the top five results for 13 cases. AutoMatch was also tested for screening scaffold library in designing binding proteins targeting influenza hemagglutinin, HIV gp120, and epidermal growth factor receptor kinase, respectively. AutoMatch, and the two test sets, ActApo and ActFree, are available for noncommercial applications at http://mdl.ipc.pku.edu.cn/cgi-bin/down.cgi.     

Motif‐directed redesign of enzyme specificity

Computational protein design relies on several approximations, including the use of fixed backbones and rotamers, to reduce protein design to a computationally tractable problem. However, allowing backbone and off‐rotamer flexibility leads to more accurate designs and greater conformational diversity. Exhaustive sampling of this additional conformational space is challenging, and often impossible. Here, we report a computational method that utilizes a preselected library of native interactions to direct backbone flexibility to accommodate placement of these functional contacts. Using these native interaction modules, termed motifs, improves the likelihood that the interaction can be realized, provided that suitable backbone perturbations can be identified. Furthermore, it allows a directed search of the conformational space, reducing the sampling needed to find low energy conformations. We implemented the motif‐based design algorithm in Rosetta, and tested the efficacy of this method by redesigning the substrate specificity of methionine aminopeptidase. In summary, native enzymes have evolved to catalyze a wide range of chemical reactions with extraordinary specificity. Computational enzyme design seeks to generate novel chemical activities by altering the target substrates of these existing enzymes. We have implemented a novel approach to redesign the specificity of an enzyme and demonstrated its effectiveness on a model system.     

SABER: a computational method for identifying active sites for new reactions

A software suite, SABER (Selection of Active/Binding sites for Enzyme Redesign), has been developed for the analysis of atomic geometries in protein structures, using a geometric hashing algorithm (Barker and Thornton, Bioinformatics 2003;19:1644–1649). SABER is used to explore the Protein Data Bank (PDB) to locate proteins with a specific 3D arrangement of catalytic groups to identify active sites that might be redesigned to catalyze new reactions. As a proof‐of‐principle test, SABER was used to identify enzymes that have the same catalytic group arrangement present in o‐succinyl benzoate synthase (OSBS). Among the highest‐scoring scaffolds identified by the SABER search for enzymes with the same catalytic group arrangement as OSBS were L ‐Ala D/L ‐Glu epimerase (AEE) and muconate lactonizing enzyme II (MLE), both of which have been redesigned to become effective OSBS catalysts, demonstrated by experiments. Next, we used SABER to search for naturally existing active sites in the PDB with catalytic groups similar to those present in the designed Kemp elimination enzyme KE07. From over 2000 geometric matches to the KE07 active site, SABER identified 23 matches that corresponded to residues from known active sites. The best of these matches, with a 0.28 Å catalytic atom RMSD to KE07, was then redesigned to be compatible with the Kemp elimination using RosettaDesign. We also used SABER to search for potential Kemp eliminases using a theozyme predicted to provide a greater rate acceleration than the active site of KE07, and used Rosetta to create a design based on the proteins identified.     

Second-sphere amino acids contribute to transition-state structure in bovine purine nucleoside phosphorylase

Transition-state structures of human and bovine of purine nucleoside phosphorylases differ, despite 87% homologous amino acid sequences. Human PNP (HsPNP) has a fully dissociated transition state, while that for bovine PNP (BtPNP) has early SN1 character. Crystal structures and sequence alignment indicate that the active sites of these enzymes are the same within crystallographic analysis, but residues in the second-sphere from the active sites differ significantly. Residues in BtPNP have been mutated toward HsPNP, resulting in double (Asn123Lys; Arg210Gln) and triple mutant PNPs (Val39Thr; Asn123Lys; Arg210Gln). Steady-state kinetic studies indicated unchanged catalytic activity, while pre-steady-state studies indicate that the chemical step is slower in the triple mutant. The mutant enzymes have higher affinity for inhibitors that are mimics of a late dissociative transition state. Kinetic isotope effects (KIEs) and computational chemistry were used to identify the transition-state structure of the triple mutant. Intrinsic KIEs from [1'-3H], [1'-14C], [2'-3H], [5'-3H], and [9-15N] inosines were 1.221, 1.035, 1.073, 1.062 and 1.025, respectively. The primary intrinsic [1'-14C] and [9-15N] KIEs indicate a highly dissociative SN1 transition state with low bond order to the leaving group, a transition state different from the native enzyme. The [1'-14C] KIE suggests significant nucleophilic participation at the transition state. The transition-state structure of triple mutant PNP is altered as a consequence of the amino acids in the second sphere from the catalytic site. These residues are implicated in linking the dynamic motion of the protein to formation of the transition state.     

X‐ray crystallographic validation of structure predictions used in computational design for protein stabilization

Protein engineering aimed at enhancing enzyme stability is increasingly supported by computational methods for calculation of mutant folding energies and for the design of disulfide bonds. To examine the accuracy of mutant structure predictions underlying these computational methods, crystal structures of thermostable limonene epoxide hydrolase variants obtained by computational library design were determined. Four different predicted effects indeed contributed to the obtained stabilization: (i) enhanced interactions between a flexible loop close to the N‐terminus and the rest of the protein; (ii) improved interactions at the dimer interface; (iii) removal of unsatisfied hydrogen bonding groups; and (iv) introduction of additional positively charged groups at the surface. The structures of an eightfold and an elevenfold mutant showed that most mutations introduced the intended stabilizing interactions, and side‐chain conformations were correctly predicted for 72–88% of the point mutations. However, mutations that introduced a disulfide bond in a flexible region had a larger influence on the backbone conformation than predicted. The enzyme active sites were unaltered, in agreement with the observed preservation of catalytic activities. The structures also revealed how a c‐Myc tag, which was introduced for facile detection and purification, can reduce access to the active site and thereby lower the catalytic activity. Finally, sequence analysis showed that comprehensive mutant energy calculations discovered stabilizing mutations that are not proposed by the consensus or B‐FIT methods. Proteins 2015; 83:940–951. © 2015 Wiley Periodicals, Inc.     

The geometry of interactions between catalytic residues and their substrates

The process of deducing the catalytic mechanism of an enzyme from its structure is highly complex and requires extensive experimental work to validate a proposed mechanism. As one step towards improving the reliability of this process, we have gathered statistics describing the typical geometry of catalytic residues with regard to the substrate and one another. In order to analyse residue-substrate interactions, we have assembled a dataset of structures of enzymes of known mechanism bound to substrate, product, or a substrate analogue. Despite the challenges presented in obtaining such experimental data, we were able to include 42 enzyme structures. We have also assembled a separate dataset of catalytic residues which act upon other catalytic residues, using a set of 60 enzyme structures. For both datasets, we have extracted the distances between residues with a given catalytic function and their target moieties. The geometry of residues whose function involves the transfer or sharing of hydrogens (either with substrate or another residue) was analysed more closely. The results showed that the geometry for such productive interactions (prior to the transition state) closely resembles that seen in non-catalytic hydrogen bonds, with distances and angles in the normal expected range. Such statistics provide limits on "expected geometries" for catalytic residues, which will help to identify these residues and elucidate enzyme mechanisms.     

Understanding the transition states of phosphodiester bond cleavage: insights from heavy atom isotope effects

The nucleotides of DNA and RNA are joined by phosphodiester linkages whose synthesis and hydrolysis are catalyzed by numerous essential enzymes. Two prominent mechanisms have been proposed for RNA and protein enzyme catalyzed cleavage of phosphodiester bonds in RNA: (a) intramolecular nucleophilic attack by the 2'-hydroxyl group adjacent to the reactive phosphate; and (b) intermolecular nucleophilic attack by hydroxide, or other oxyanion. The general features of these two mechanisms have been established by physical organic chemical analyses; however, a more detailed understanding of the transition states of these reactions is emerging from recent kinetic isotope effect (KIE) studies. The recent data show interesting differences between the chemical mechanisms and transition state structures of the inter- and intramolecular reactions, as well as provide information on the impact of metal ion, acid, and base catalysis on these mechanisms. Importantly, recent nonenzymatic model studies show that interactions with divalent metal ions, an important feature of many phosphodiesterase active sites, can influence both the mechanism and transition state structure of nonenzymatic phosphodiester cleavage. Such detailed investigations are important because they mimic catalytic strategies employed by both RNA and protein phosphodiesterases, and so set the stage for explorations of enzyme-catalyzed transition states. Application of KIE analyses for this class of enzymes is just beginning, and several important technical challenges remain to be overcome. Nonetheless, such studies hold great promise since they will provide novel insights into the role of metal ions and other active site interactions.     

Novel approach of fragment-based lead discovery applied to renin inhibitors

A novel approach was conducted for fragment-based lead discovery and applied to renin inhibitors. The biochemical screening of a fragment library against renin provided the hit fragment which showed a characteristic interaction pattern with the target protein. The hit fragment bound only to the S1, S3, and S3^SP (S3 subpocket) sites without any interactions with the catalytic aspartate residues (Asp32 and Asp215 (pepsin numbering)). Prior to making chemical modifications to the hit fragment, we first identified its essential binding sites by utilizing the hit fragment’s substructures. Second, we created a new and smaller scaffold, which better occupied the identified essential S3 and S3^SP sites, by utilizing library synthesis with high-throughput chemistry. We then revisited the S1 site and efficiently explored a good building block attaching to the scaffold with library synthesis. In the library syntheses, the binding modes of each pivotal compound were determined and confirmed by X-ray crystallography and the library was strategically designed by structure-based computational approach not only to obtain a more active compound but also to obtain informative Structure Activity Relationship (SAR). As a result, we obtained a lead compound offering synthetic accessibility as well as the improved in vitro ADMET profiles. The fragments and compounds possessing a characteristic interaction pattern provided new structural insights into renin’s active site and the potential to create a new generation of renin inhibitors. In addition, we demonstrated our FBDD strategy integrating highly sensitive biochemical assay, X-ray crystallography, and high-throughput synthesis and in silico library design aimed at fragment morphing at the initial stage was effective to elucidate a pocket profile and a promising lead compound.     

Step‐by‐step design of proteins for small molecule interaction: A review on recent milestones

Protein design is the field of synthetic biology that aims at developing de novo custom‐made proteins and peptides for specific applications. Despite exploring an ambitious goal, recent computational advances in both hardware and software technologies have paved the way to high‐throughput screening and detailed design of novel folds and improved functionalities. Modern advances in the field of protein design for small molecule targeting are described in this review, organized in a step‐by‐step fashion: from the conception of a new or upgraded active binding site, to scaffold design, sequence optimization, and experimental expression of the custom protein. In each step, contemporary examples are described, and state‐of‐the‐art software is briefly explored.