Mining electron density for functionally relevant protein polysterism in crystal structures

Changes in Active Site Loop Conformation Relate to the Transition toward a Novel Enzymatic Activity

Enzymatic promiscuity, the ability of enzymes to catalyze multiple, distinct chemical reactions, has been well documented and is hypothesized to be a major driver of the emergence of new enzymatic functions. Yet, the molecular mechanisms involved in the transition from one activity to another remain debated and elusive. Here, we evaluated the redesign of the active site binding cleft of lactonase SsoPox using structure-based design and combinatorial libraries. We created variants with largely improved catalytic abilities against phosphotriesters, the best ones being >1000-fold better compared to the wild-type enzyme. The observed shifts in activity specificity are large, and some variants completely lost their initial activity. The selected combinations of mutations have considerably reshaped the active site cavity via side chain changes but mostly through large rearrangements of the active site loops and changes to their conformations, as revealed by a suite of crystal structures. This suggests that a specific active site loop configuration is critical to the lactonase activity. Interestingly, analysis of high-resolution structures hints at the potential role of conformational sampling and its directionality in defining the enzyme activity profile.

Synergism between x-ray crystallography and NMR residual dipolar couplings in characterizing protein dynamics

The important role of structural dynamics in protein function is widely recognized. Thermal or B-factors and their anisotropy, seen in x-ray analysis of protein structures, report on the presence of atomic coordinate heterogeneity that can be attributed to motion. However, their quantitative evaluation in terms of protein dynamics by x-ray ensemble refinement remains challenging. NMR spectroscopy provides quantitative information on the amplitudes and time scales of motional processes. Unfortunately, with a few exceptions, the NMR data do not provide direct insights into the atomic details of dynamic trajectories. Residual dipolar couplings, measured by solution NMR, are very precise parameters reporting on the time-averaged bond-vector orientations and may offer the opportunity to derive correctly weighted dynamic ensembles of structures for cases where multiple high-resolution x-ray structures are available. Applications to the SARS-CoV-2 main protease, Mpro, and ubiquitin highlight this complementarity of NMR and crystallography for quantitative assessment of internal motions.

Changes in Active Site Loop Conformation Relate to the Transition toward a Novel Enzymatic Activity

Enzymatic promiscuity, the ability of enzymes to catalyze multiple, distinct chemical reactions, has been well documented and is hypothesized to be a major driver for the emergence of new enzymatic functions. Yet, the molecular mechanisms involved in the transition from one activity to another remain debated and elusive. Here, we evaluated the redesign of the active site binding cleft of the lactonase SsoPox using structure-based design and combinatorial libraries. We created variants with largely improved catalytic abilities against phosphotriesters, the best ones being > 1,000-fold better compared to the wild-type enzyme. The observed shifts in activity specificity are large, ~1,000,000-fold and beyond, since some variants completely lost their initial activity. The selected combinations of mutations have considerably reshaped the active site cavity via side chain changes but mostly through large rearrangements of the active site loops, as revealed by a suite of crystal structures. This suggests that specific active site loop configuration is critical to the lactonase activity. Interestingly, analysis of high-resolution structures hints at the potential role of conformational sampling and its directionality in defining an enzyme activity profile.

Ensemble-function relationships to dissect mechanisms of enzyme catalysis

Decades of structure-function studies have established our current extensive understanding of enzymes. However, traditional structural models are snapshots of broader conformational ensembles of interchanging states. We demonstrate the need for conformational ensembles to understand function, using the enzyme ketosteroid isomerase (KSI) as an example. Comparison of prior KSI cryogenic x-ray structures suggested deleterious mutational effects from a misaligned oxyanion hole catalytic residue. However, ensemble information from room-temperature x-ray crystallography, combined with functional studies, excluded this model. Ensemble-function analyses can deconvolute effects from altering the probability of occupying a state (P-effects) and changing the reactivity of each state (k-effects); our ensemble-function analyses revealed functional effects arising from weakened oxyanion hole hydrogen bonding and substrate repositioning within the active site. Ensemble-function studies will have an integral role in understanding enzymes and in meeting the future goals of a predictive understanding of enzyme catalysis and engineering new enzymes.

A Single-Point Mutation in d-Arginine Dehydrogenase Unlocks a Transient Conformational State Resulting in Altered Cofactor Reactivity

Proteins are inherently dynamic, and proper enzyme function relies on conformational flexibility. In this study, we demonstrated how an active site residue changes an enzyme's reactivity by modulating fluctuations between conformational states. Replacement of tyrosine 249 (Y249) with phenylalanine in the active site of the flavin-dependent d-arginine dehydrogenase yielded an enzyme with both an active yellow FAD (Y249F-y) and an inactive chemically modified green FAD, identified as 6-OH-FAD (Y249F-g) through various spectroscopic techniques. Structural investigation of Y249F-g and Y249F-y variants by comparison to the wild-type enzyme showed no differences in the overall protein structure and fold. A closer observation of the active site of the Y249F-y enzyme revealed an alternative conformation for some active site residues and the flavin cofactor. Molecular dynamics simulations probed the alternate conformations observed in the Y249F-y enzyme structure and showed that the enzyme variant with FAD samples a metastable conformational state, not available to the wild-type enzyme. Hybrid quantum/molecular mechanical calculations identified differences in flavin electronics between the wild type and the alternate conformation of the Y249F-y enzyme. The computational studies further indicated that the alternate conformation in the Y249F-y enzyme is responsible for the higher spin density at the C6 atom of flavin, which is consistent with the formation of 6-OH-FAD in the variant enzyme. The observations in this study are consistent with an alternate conformational space that results in fine-tuning the microenvironment around a versatile cofactor playing a critical role in enzyme function.

Instrumentation and experimental procedures for robust collection of X-ray diffraction data from protein crystals across physiological temperatures

Traditional X-ray diffraction data collected at cryo-temperatures have delivered invaluable insights into the three-dimensional structures of proteins, providing the backbone of structure-function studies. While cryo-cooling mitigates radiation damage, cryo-temperatures can alter protein conformational ensembles and solvent structure. Furthermore, conformational ensembles underlie protein function and energetics, and recent advances in room-temperature X-ray crystallography have delivered conformational heterogeneity information that can be directly related to biological function. Given this capability, the next challenge is to develop a robust and broadly applicable method to collect single-crystal X-ray diffraction data at and above room temperature. This challenge is addressed herein. The approach described provides complete diffraction data sets with total collection times as short as ∼5 s from single protein crystals, dramatically increasing the quantity of data that can be collected within allocated synchrotron beam time. Its applicability was demonstrated by collecting 1.09-1.54 Å resolution data over a temperature range of 293-363 K for proteinase K, thaumatin and lysozyme crystals at BL14-1 at the Stanford Synchrotron Radiation Lightsource. The analyses presented here indicate that the diffraction data are of high quality and do not suffer from excessive dehydration or radiation damage.

A chemical interpretation of protein electron density maps in the worldwide protein data bank

High-quality three-dimensional structural data is of great value for the functional interpretation of biomacromolecules, especially proteins; however, structural quality varies greatly across the entries in the worldwide Protein Data Bank (wwPDB). Since 2008, the wwPDB has required the inclusion of structure factors with the deposition of x-ray crystallographic structures to support the independent evaluation of structures with respect to the underlying experimental data used to derive those structures. However, interpreting the discrepancies between the structural model and its underlying electron density data is difficult, since derived sigma-scaled electron density maps use arbitrary electron density units which are inconsistent between maps from different wwPDB entries. Therefore, we have developed a method that converts electron density values from sigma-scaled electron density maps into units of electrons. With this conversion, we have developed new methods that can evaluate specific regions of an x-ray crystallographic structure with respect to a physicochemical interpretation of its corresponding electron density map. We have systematically compared all deposited x-ray crystallographic protein models in the wwPDB with their underlying electron density maps, if available, and characterized the electron density in terms of expected numbers of electrons based on the structural model. The methods generated coherent evaluation metrics throughout all PDB entries with associated electron density data, which are consistent with visualization software that would normally be used for manual quality assessment. To our knowledge, this is the first attempt to derive units of electrons directly from electron density maps without the aid of the underlying structure factors. These new metrics are biochemically-informative and can be extremely useful for filtering out low-quality structural regions from inclusion into systematic analyses that span large numbers of PDB entries. Furthermore, these new metrics will improve the ability of non-crystallographers to evaluate regions of interest within PDB entries, since only the PDB structure and the associated electron density maps are needed. These new methods are available as a well-documented Python package on GitHub and the Python Package Index under a modified Clear BSD open source license.

A mechanistic view of enzyme evolution

New enzyme functions often evolve through the recruitment and optimization of latent promiscuous activities. How do mutations alter the molecular architecture of enzymes to enhance their activities? Can we infer general mechanisms that are common to most enzymes, or does each enzyme require a unique optimization process? The ability to predict the location and type of mutations necessary to enhance an enzyme's activity is critical to protein engineering and rational design. In this review, via the detailed examination of recent studies that have shed new light on the molecular changes underlying the optimization of enzyme function, we provide a mechanistic perspective of enzyme evolution. We first present a global survey of the prevalence of activity-enhancing mutations and their distribution within protein structures. We then delve into the molecular solutions that mediate functional optimization, specifically highlighting several common mechanisms that have been observed across multiple examples. As distinct protein sequences encounter different evolutionary bottlenecks, different mechanisms are likely to emerge along evolutionary trajectories toward improved function. Identifying the specific mechanism(s) that need to be improved upon, and tailoring our engineering efforts to each sequence, may considerably improve our chances to succeed in generating highly efficient catalysts in the future.

Conformational sampling and kinetics changes across a non-Arrhenius break point in the enzyme thermolysin

Numerous studies have suggested a significant role that protein dynamics play in optimizing enzyme catalysis, and changes in conformational sampling offer a window to explore this role. Thermolysin from Bacillus thermoproteolyticus rokko, which is a heat-stable zinc metalloproteinase, serves here as a model system to study changes of protein function and conformational sampling across a temperature range of 16-36 °C. The temperature dependence of kinetics of thermolysin showed a biphasic transition at 26 °C that points to potential conformational and dynamic differences across this temperature. The non-Arrhenius behavior observed resembled results from previous studies of a thermophilic alcohol dehydrogenase enzyme, which also indicated a biphasic transition at ambient temperatures. To explore the non-Arrhenius behavior of thermolysin, room temperature crystallography was applied to characterize structural changes in a temperature range across the biphasic transition temperature. The alternate conformation of side chain fitting to electron density of a group of residues showed a higher variability in the temperature range from 26 to 29 °C, which indicated a change in conformational sampling that correlated with the non-Arrhenius break point.

ACMS: a database of alternate conformations found in the atoms of main and side chains of protein structures

Proteins are usually dynamic biological macromolecules, thereby exhibiting a large number of conformational ensembles which influence the association with their neighbours and interacting partners. Most of the side-chain atoms and a few main-chain atoms of the high-resolution crystal structures deposited in the Protein Data Bank adopt alternate conformations. This kind of conformational behaviour prompted the authors to explore the relationship, if any, between the alternate conformations and the function of the protein molecule. Thus, a knowledge base of the alternate conformations of the main- and side-chain atoms of protein structures has been developed. It provides a detailed description of the alternate conformations of various residues for more than 60 000 high-resolution crystal structures. The proposed knowledge base is very user friendly and has various flexible options. The knowledge base will be updated periodically and can be accessed at http://iris.physics.iisc.ac.in/acms.

The role of protein dynamics in the evolution of new enzyme function

Enzymes must be ordered to allow the stabilization of transition states by their active sites, yet dynamic enough to adopt alternative conformations suited to other steps in their catalytic cycles. The biophysical principles that determine how specific protein dynamics evolve and how remote mutations affect catalytic activity are poorly understood. Here we examine a 'molecular fossil record' that was recently obtained during the laboratory evolution of a phosphotriesterase from Pseudomonas diminuta to an arylesterase. Analysis of the structures and dynamics of nine protein variants along this trajectory, and three rationally designed variants, reveals cycles of structural destabilization and repair, evolutionary pressure to 'freeze out' unproductive motions and sampling of distinct conformations with specific catalytic properties in bi-functional intermediates. This work establishes that changes to the conformational landscapes of proteins are an essential aspect of molecular evolution and that change in function can be achieved through enrichment of preexisting conformational sub-states.

Mapping the Accessible Conformational Landscape of an Insect Carboxylesterase Using Conformational Ensemble Analysis and Kinetic Crystallography

The proper function of enzymes often depends upon their efficient interconversion between particular conformational sub-states on a free-energy landscape. Experimentally characterizing these sub-states is challenging, which has limited our understanding of the role of protein dynamics in many enzymes. Here, we have used a combination of kinetic crystallography and detailed analysis of crystallographic protein ensembles to map the accessible conformational landscape of an insect carboxylesterase (LcαE7) as it traverses all steps in its catalytic cycle. LcαE7 is of special interest because of its evolving role in organophosphate insecticide resistance. Our results reveal that a dynamically coupled network of residues extends from the substrate-binding site to a surface loop. Interestingly, the coupling of this network that is apparent in the apoenzyme appears to be reduced in the phosphorylated enzyme intermediate. Altogether, the results of this work highlight the importance of protein dynamics to enzyme function and the evolution of new activity.

Conformational Changes and Free Energies in a Proline Isomerase

Proteins are dynamic molecules and their ability to adopt alternative conformations is central to their biological function. The structural and biophysical properties of transiently and sparsely populated states are, however, difficult to study and an atomic-level description of those states is challenging. We have used enhanced-sampling all-atom, explicit-solvent molecular simulations, guided by structural information from X-ray crystallography and NMR, to describe quantitatively the transition between the major and a minor state of Cyclophilin A, thus providing new insight into how dynamics can affect enzyme function. We calculate the conformational free energy between the two states, and comparison with experiments demonstrates a surprisingly high accuracy for both the wild type protein and a mutant that traps the protein in its alternative conformation. Our results demonstrate how the combination of state-of-the-art force fields and enhanced sampling methods can provide a detailed and quantitative description of the conformational changes in proteins such as those observed in Cyclophilin A.

Predicting X-ray diffuse scattering from translation-libration-screw structural ensembles

Identifying the intramolecular motions of proteins and nucleic acids is a major challenge in macromolecular X-ray crystallography. Because Bragg diffraction describes the average positional distribution of crystalline atoms with imperfect precision, the resulting electron density can be compatible with multiple models of motion. Diffuse X-ray scattering can reduce this degeneracy by reporting on correlated atomic displacements. Although recent technological advances are increasing the potential to accurately measure diffuse scattering, computational modeling and validation tools are still needed to quantify the agreement between experimental data and different parameterizations of crystalline disorder. A new tool, phenix.diffuse, addresses this need by employing Guinier's equation to calculate diffuse scattering from Protein Data Bank (PDB)-formatted structural ensembles. As an example case, phenix.diffuse is applied to translation-libration-screw (TLS) refinement, which models rigid-body displacement for segments of the macromolecule. To enable the calculation of diffuse scattering from TLS-refined structures, phenix.tls_as_xyz builds multi-model PDB files that sample the underlying T, L and S tensors. In the glycerophosphodiesterase GpdQ, alternative TLS-group partitioning and different motional correlations between groups yield markedly dissimilar diffuse scattering maps with distinct implications for molecular mechanism and allostery. These methods demonstrate how, in principle, X-ray diffuse scattering could extend macromolecular structural refinement, validation and analysis.

Molecular dynamics simulation of triclinic lysozyme in a crystal lattice

Molecular dynamics simulations of crystals can enlighten interpretation of experimental X-ray crystallography data and elucidate structural dynamics and heterogeneity in biomolecular crystals. Furthermore, because of the direct comparison against experimental data, they can inform assessment of molecular dynamics methods and force fields. We present microsecond scale results for triclinic hen egg-white lysozyme in a supercell consisting of 12 independent unit cells using four contemporary force fields (Amber ff99SB, ff14ipq, ff14SB, and CHARMM 36) in crystalline and solvated states (for ff14SB only). We find the crystal simulations consistent across multiple runs of the same force field and robust to various solvent equilibration schemes. However, convergence is slow compared with solvent simulations. All the tested force fields reproduce experimental structural and dynamic properties well, but Amber ff14SB maintains structure and reproduces fluctuations closest to the experimental model: its average backbone structure differs from the deposited structure by 0.37Å; by contrast, the average backbone structure in solution differs from the deposited by 0.65Å. All the simulations are affected by a small progressive deterioration of the crystal lattice, presumably due to imperfect modeling of hydrogen bonding and other crystal contact interactions; this artifact is smallest in ff14SB, with average lattice positions deviating by 0.20Å from ideal. Side-chain disorder is surprisingly low with fewer than 30% of the nonglycine or alanine residues exhibiting significantly populated alternate rotamers. Our results provide helpful insight into the methodology of biomolecular crystal simulations and indicate directions for future work to obtain more accurate energy models for molecular dynamics.

Exploring the role of conformational heterogeneity in cis-autoproteolytic activation of ThnT

In the past decade, there have been major achievements in understanding the relationship between enzyme catalysis and protein structural plasticity. In autoprocessing systems, however, there is a sparsity of direct evidence of the role of conformational dynamics, which are complicated by their intrinsic chemical reactivity. ThnT is an autoproteolytically activated enzyme involved in the biosynthesis of the β-lactam antibiotic thienamycin. Conservative mutation of ThnT results in multiple conformational states that can be observed via X-ray crystallography, establishing ThnT as a representative and revealing system for studing how conformational dynamics control autoactivation at a molecular level. Removal of the nucleophile by mutation to Ala disrupts the population of a reactive state and causes widespread structural changes from a conformation that promotes autoproteolysis to one associated with substrate catalysis. Finer probing of the active site polysterism was achieved by EtHg derivatization of the nucleophile, which indicates the active site and a neighboring loop have coupled dynamics. Disruption of these interactions by mutagenesis precludes the ability to observe a reactive state through X-ray crystallography, and application of this insight to other autoproteolytically activated enzymes offers an explanation for the widespread crystallization of inactive states. We suggest that the N → O(S) acyl shift in cis-autoproteolysis might occur through a si-face attack, thereby unifying the fundamental chemistry of these enzymes through a common mechanism.

Automated identification of functional dynamic contact networks from X-ray crystallography

Protein function often depends on the exchange between conformational substates. Allosteric ligand binding or distal mutations can stabilize specific active site conformations and consequently alter protein function. In addition to comparing independently determined X-ray crystal structures, alternative conformations observed at low levels of electron density have the potential to provide mechanistic insights into conformational dynamics. Here, we report a new multi-conformer contact network algorithm (CONTACT) that identifies networks of conformationally heterogeneous residues directly from high-resolution X-ray crystallography data. Contact networks in Escherichia coli dihydrofolate reductase (ecDHFR) predict the long-range pattern of NMR chemical shift perturbations of an allosteric mutation. A comparison of contact networks in wild type and mutant ecDHFR suggests how mutations that alter optimized networks of coordinated motions can impair catalytic function. Thus, CONTACT-guided mutagenesis will allow the structure-dynamics-function relationship to be exploited in protein engineering and design.

Peptide crystal simulations reveal hidden dynamics

Molecular dynamics simulations of biomolecular crystals at atomic resolution have the potential to recover information on dynamics and heterogeneity hidden in X-ray diffraction data. We present here 9.6 μs of dynamics in a small helical peptide crystal with 36 independent copies of the unit cell. The average simulation structure agrees with experiment to within 0.28 Å backbone and 0.42 Å all-atom RMSD; a model refined against the average simulation density agrees with the experimental structure to within 0.20 Å backbone and 0.33 Å all-atom RMSD. The R-factor between the experimental structure factors and those derived from this unrestrained simulation is 23% to 1.0 Å resolution. The B-factors for most heavy atoms agree well with experiment (Pearson correlation of 0.90), but B-factors obtained by refinement against the average simulation density underestimate the coordinate fluctuations in the underlying simulation where the simulation samples alternate conformations. A dynamic flow of water molecules through channels within the crystal lattice is observed, yet the average water density is in remarkable agreement with experiment. A minor population of unit cells is characterized by reduced water content, 310 helical propensity and a gauche(-) side-chain rotamer for one of the valine residues. Careful examination of the experimental data suggests that transitions of the helices are a simulation artifact, although there is indeed evidence for alternate valine conformers and variable water content. This study highlights the potential for crystal simulations to detect dynamics and heterogeneity in experimental diffraction data as well as to validate computational chemistry methods.

Accessing protein conformational ensembles using room-temperature X-ray crystallography

Modern protein crystal structures are based nearly exclusively on X-ray data collected at cryogenic temperatures (generally 100 K). The cooling process is thought to introduce little bias in the functional interpretation of structural results, because cryogenic temperatures minimally perturb the overall protein backbone fold. In contrast, here we show that flash cooling biases previously hidden structural ensembles in protein crystals. By analyzing available data for 30 different proteins using new computational tools for electron-density sampling, model refinement, and molecular packing analysis, we found that crystal cryocooling remodels the conformational distributions of more than 35% of side chains and eliminates packing defects necessary for functional motions. In the signaling switch protein, H-Ras, an allosteric network consistent with fluctuations detected in solution by NMR was uncovered in the room-temperature, but not the cryogenic, electron-density maps. These results expose a bias in structural databases toward smaller, overpacked, and unrealistically unique models. Monitoring room-temperature conformational ensembles by X-ray crystallography can reveal motions crucial for catalysis, ligand binding, and allosteric regulation.