Assessment of enzyme active site positioning and tests of catalytic mechanisms through X-ray–derived conformational ensembles

How enzymes achieve their enormous rate enhancements remains a central question in biology, and our understanding to date has impacted drug development, influenced enzyme design, and deepened our appreciation of evolutionary processes. While enzymes position catalytic and reactant groups in active sites, physics requires that atoms undergo constant motion. Numerous proposals have invoked positioning or motions as central for enzyme function, but a scarcity of experimental data has limited our understanding of positioning and motion, their relative importance, and their changes through the enzyme’s reaction cycle. To examine positioning and motions and test catalytic proposals, we collected “room temperature” X-ray crystallography data for Pseudomonas putida ketosteroid isomerase (KSI), and we obtained conformational ensembles for this and a homologous KSI from multiple PDB crystal structures. Ensemble analyses indicated limited change through KSI’s reaction cycle. Active site positioning was on the 1- to 1.5-Å scale, and was not exceptional compared to noncatalytic groups. The KSI ensembles provided evidence against catalytic proposals invoking oxyanion hole geometric discrimination between the ground state and transition state or highly precise general base positioning. Instead, increasing or decreasing positioning of KSI’s general base reduced catalysis, suggesting optimized Ångstrom-scale conformational heterogeneity that allows KSI to efficiently catalyze multiple reaction steps. Ensemble analyses of surrounding groups for WT and mutant KSIs provided insights into the forces and interactions that allow and limit active-site motions. Most generally, this ensemble perspective extends traditional structure–function relationships, providing the basis for a new era of “ensemble–function” interrogation of enzymes.

The central role of enzymes in biology is embodied in the decades of effort spent to deeply investigate the origins of their catalysis (e.g., refs. 1–6). Enzyme studies now routinely identify the active-site groups that interact with substrates and reveal their roles in binding and in facilitating chemical transformations. Nevertheless, these so-called “catalytic groups” alone, outside of the context of a folded enzyme, do not account for the enormous rate enhancements and exquisite specificities exhibited by enzymes (4). Classic proposals for enzyme catalysis have invoked the importance of positioning of active-site groups within a folded enzyme and of substrates localized and positioned by binding interactions (6–15). While these proposals universally invoke restricted motion of catalytic groups, the amount of restriction and the amount of catalysis provided by that restriction has been the subject of much discussion and debate (16–20). Conversely, it is also clear that motions are inherent to enzymes, and that conformational transitions and structural rearrangements are important for enzyme function (e.g., refs. 11 and 21–23). Considering both positioning and motions, it has been recognized that: “For catalysis, flexible but not too flexible, as well as rigid but not too rigid, is essential. Specifically, the protein must be rigid enough to maintain the required structure but flexible enough to permit atomic movements as the reaction proceeds” (3).The importance of both positioning and motions to enzyme function suggests a nuanced view of enzyme catalysis and underscores the need for direct experimental measurements of positioning and motions within enzymes.As Feynman noted, “Everything that living things do can be understood in terms of the jigglings and wigglings of atoms” (24). But simply observing motions of active-site residues does not tell us how enzymes achieve catalysis. To understand enzymes, we want to know how much an enzyme dampens and alters the motions of catalytic residues. We want to know which increases or decreases in motion increase or decrease the reaction rate and what interactions and forces are most responsible for dampening motions. With this information we may be able to better design new enzymes. Additionally, to what extent are active-site residues positioned upon folding of the enzyme, or adjusted as the reaction proceeds, and are active-site residues more precisely positioned than residues throughout an enzyme?To address fundamental questions about how enzymes function and evolve, and how to ultimately design highly efficient enzymes, we need to obtain experimental information about enzyme conformation ensembles: The distribution of enzyme states dictated by their highly complex multidimensional energy landscapes over which conformational rearrangements occur. Observations of well-resolved electron densities from X-ray diffraction data indicate positioning of residues in and around the active site, but do not provide information on the extent and nature of that positioning. Crystallographic B-factors of residues are sometimes used to infer motions, but are only indirectly related to intrinsic motion and contain contributions from additional factors, such as crystallographic order (25, 26). NMR experiments identify groups with greater motional freedom and can provide temporal information, but these experiments typically lack information about the directions and extent of these motions (27). Molecular dynamics simulations provide atomic-level models for entire systems, but we currently lack the rigorous experimental tests needed to determine whether or not computational outputs reflect actual physical behavior, which prevents firm mechanistic conclusions from being inferred (28, 29).Two X-ray crystallographic approaches have recently emerged that can provide experimentally-derived conformational ensemble information: High-sequence similarity Protein Data Bank (PDB) structural ensembles (referred to as “pseudoensembles” herein) (30, 31) and multiconformer models from X-ray data obtained at temperatures above the protein’s glass transition (referred to as “room temperature” or ”RT” X-ray diffraction in the literature and herein) (22, 32, 33). These approaches are complementary. Pseudoensembles provide information about residues that move in concert (i.e., coupled motions) but require dozens of structures (see also SI Appendix, Supplementary Text 1). RT X-ray data from single crystals can provide multiconformer models, so that ensemble information about new complexes and mutants can more readily be acquired, but do not provide direct information about coupled motions. Furthermore, RT X-ray studies provide direct information about equilibrium distributions without cryocooling, which can alter and quench motions, and without assuming that different cryocooled crystals reproduce an equilibrium distribution of states (32, 34–36).Here we demonstrate consistency between these approaches and take advantage of the strengths of each: The ability to evaluate correlated side-chain rearrangements in and near the active site via pseudoensembles, and the ability to obtain new ensemble-type information of new states from single X-ray datasets at temperatures above the glass transition. Importantly, these analyses report on conformational heterogeneity and cannot give information about the timescales of motions and interconversions between states. Additionally, each traditional model within the pseudoensemble represents predominantly a single rather than average state and combining these states captures an ensemble distribution. Similarly, the alternate conformations in multiconformer models explicitly reduce bias toward average structures of multistate systems. Focusing on a model enzyme with very high-resolution data and with ligands representing steps along its reaction path has allowed us to obtain insights that would not be possible from static structures, from either ensemble approach alone or from less-extensive or lower-resolution data.We chose to investigate the enzyme ketosteroid isomerase (KSI) (Fig. 1) because of our ability to obtain high-resolution diffraction data, because of the accumulated wealth of structural and mechanistic information, and because of KSI’s use of catalytic strategies common to many enzymes. As a single-substrate enzyme, KSI allows structural information to be obtained with a bonified reactant bound. Furthermore, we obtained ensemble data for KSI from two species, which gave consistent results and allowed us to address unresolved questions from decades of KSI studies. We also used our ensembles from these KSI homologs to ask—and answer—more general questions. Our in-depth analyses of KSI bring an ensemble perspective to bear on traditional structure–function studies and provide the basis for a new era of ensemble–function studies.Open in a separate windowFig. 1.The KSI reaction. Reaction mechanism and schematic depiction of the active site (A) and its 3D organization (B) [PDB ID code 1OH0 (87)]. KSI catalyzes double bond isomerization of steroid substrates (shown for the substrate 5-androstene-3,17-dione) utilizing a general acid/base D40 (which we refer to herein as a general base, for simplicity), and an oxyanion hole composed of the side chains of Y16 and D103 (protonated); general base and oxyanion hole residues are colored in red and orange, respectively. The product in A, 4-androstene-3,17-dione, is the substrate of the reverse reaction and was used for RT X-ray crystallography herein. (C) Examples of oxyanion KSI TSAs used for the KSI TSA ensembles: Equilenin (Left) and a substituted phenolate (Right).