J.S. Fraser

Hidden alternative structures of proline isomerase essential for catalysis.

A long-standing challenge is to understand at the atomic level how protein dynamics contribute to enzyme catalysis. X-ray crystallography can provide snapshots of conformational substates sampled during enzymatic reactions, while NMR relaxation methods reveal the rates of interconversion between substates and the corresponding relative populations. However, these current methods cannot simultaneously reveal the detailed atomic structures of the rare states and rationalize the finding that intrinsic motions in the free enzyme occur on a timescale similar to the catalytic turnover rate. Here we introduce dual strategies of ambient-temperature X-ray crystallographic data collection and automated electron-density sampling to structurally unravel interconverting substates of the human proline isomerase, cyclophilin A (CYPA, also known as PPIA). A conservative mutation outside the active site was designed to stabilize features of the previously hidden minor conformation. This mutation not only inverts the equilibrium between the substates, but also causes large, parallel reductions in the conformational interconversion rates and the catalytic rate. These studies introduce crystallographic approaches to define functional minor protein conformations and, in combination with NMR analysis of the enzyme dynamics in solution, show how collective motions directly contribute to the catalytic power of an enzyme.

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.

EMRinger: side chain–directed model and map validation for 3D cryo-electron microscopy

Advances in high-resolution cryo-electron microscopy (cryo-EM) require the development of validation metrics to independently assess map quality and model geometry. We report EMRinger, a tool that assesses the precise fitting of an atomic model into the map during refinement and shows how radiation damage alters scattering from negatively charged amino acids. EMRinger (https://github.com/fraser-lab/EMRinger) will be useful for monitoring progress in resolving and modeling high-resolution features in cryo-EM.

Integrative, dynamic structural biology at atomic resolution[mdash]it's about time

Biomolecules adopt a dynamic ensemble of conformations, each with the potential to interact with binding partners or perform the chemical reactions required for a multitude of cellular functions. Recent advances in X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy and other techniques are helping us realize the dream of seeing—in atomic detail—how different parts of biomolecules shift between functional substates using concerted motions. Integrative structural biology has advanced our understanding of the formation of large macromolecular complexes and how their components interact in assemblies by leveraging data from many low-resolution methods. Here, we review the growing opportunities for integrative, dynamic structural biology at the atomic scale, contending there is increasing synergistic potential between X-ray crystallography, NMR and computer simulations to reveal a structural basis for protein conformational dynamics at high resolution.

Automated electron-density sampling reveals widespread conformational polymorphism in proteins

Although proteins populate large structural ensembles, X‐ray diffraction data are traditionally interpreted using a single model. To search for evidence of alternate conformers, we developed a program, Ringer, which systematically samples electron density around the dihedral angles of protein side chains. In a diverse set of 402 structures, Ringer identified weak, nonrandom electron‐density features that suggest of the presence of hidden, lowly populated conformations for >18% of uniquely modeled residues. Although these peaks occur at electron‐density levels traditionally regarded as noise, statistically significant (P < 10−5) enrichment of peaks at successive rotameric χ angles validates the assignment of these features as unmodeled conformations. Weak electron density corresponding to alternate rotamers also was detected in an accurate electron density map free of model bias. Ringer analysis of the high‐resolution structures of free and peptide‐bound calmodulin identified shifts in ensembles and connected the alternate conformations to ligand recognition. These results show that the signal in high‐resolution electron density maps extends below the traditional 1 σ cutoff, and crystalline proteins are more polymorphic than current crystallographic models. Ringer provides an objective, systematic method to identify previously undiscovered alternate conformations that can mediate protein folding and function.

Discovery and characterization of gut microbiota decarboxylases that can produce the neurotransmitter tryptamine.

Several recent studies describe the influence of the gut microbiota on host brain and behavior. However, the mechanisms responsible for microbiota-nervous system interactions are largely unknown. Using a combination of genetics, biochemistry, and crystallography, we identify and characterize two phylogenetically distinct enzymes found in the human microbiome that decarboxylate tryptophan to form the β-arylamine neurotransmitter tryptamine. Although this enzymatic activity is exceedingly rare among bacteria more broadly, analysis of the Human Microbiome Project data demonstrate that at least 10% of the human population harbors at least one bacterium encoding a tryptophan decarboxylase in their gut community. Our results uncover a previously unrecognized enzymatic activity that can give rise to host-modulatory compounds and suggests a potential direct mechanism by which gut microbiota can influence host physiology, including behavior.

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. Observing alternative conformations at low levels of electron density, in addition to comparison of independently determined X-ray crystal structures, can provide mechanistic insights into conformational dynamics. Here we report a new algorithm, CONTACT, that identifies contact networks of conformationally heterogeneous residues directly from high-resolution X-ray crystallography data. Contact networks determined for Escherichia coli dihydrofolate reductase (ecDHFR) predict the observed long-range pattern of NMR chemical shift perturbations of an allosteric mutation. A comparison of contact networks in wild-type and mutant ecDHFR suggests that mutations that alter optimized contact networks of coordinated motions can impair catalytic function. CONTACT-guided mutagenesis can exploit the structure-dynamics-function relationship in protein engineering and design.

From Structure to Systems: High-Resolution, Quantitative Genetic Analysis of RNA Polymerase II

RNA polymerase II (RNAPII) lies at the core of dynamic control of gene expression. Using 53 RNAPII point mutants, we generated a point mutant epistatic miniarray profile (pE-MAP) comprising ∼60,000 quantitative genetic interactions in Saccharomyces cerevisiae. This analysis enabled functional assignment of RNAPII subdomains and uncovered connections between individual regions and other protein complexes. Using splicing microarrays and mutants that alter elongation rates in vitro, we found an inverse relationship between RNAPII speed and in vivo splicing efficiency. Furthermore, the pE-MAP classified fast and slow mutants that favor upstream and downstream start site selection, respectively. The striking coordination of polymerization rate with transcription initiation and splicing suggests that transcription rate is tuned to regulate multiple gene expression steps. The pE-MAP approach provides a powerful strategy to understand other multifunctional machines at amino acid resolution.

Integrated description of protein dynamics from room-temperature X-ray crystallography and NMR.

Significance Most proteins are inherently flexible and their dynamics play a central role in their biological functions. A molecular level understanding of protein function and mechanism requires an accurate description of the atomic coordinates in both time and space. Here we show, through studies of the enzyme dihydrofolate reductase, that multiconformer models derived from room-temperature X-ray crystallographic data can be used synergistically with nuclear magnetic resonance relaxation measurements to provide a detailed description of both the amplitude and timescale of fluctuations in atomic coordinates. This hybrid approach provides a more complete description of protein dynamics than can be obtained from either method alone. The room-temperature crystallographic ensemble accurately reflects the picosecond–nanosecond motions of the protein backbone and side chains. Detailed descriptions of atomic coordinates and motions are required for an understanding of protein dynamics and their relation to molecular recognition, catalytic function, and allostery. Historically, NMR relaxation measurements have played a dominant role in the determination of the amplitudes and timescales (picosecond–nanosecond) of bond vector fluctuations, whereas high-resolution X-ray diffraction experiments can reveal the presence of and provide atomic coordinates for multiple, weakly populated substates in the protein conformational ensemble. Here we report a hybrid NMR and X-ray crystallography analysis that provides a more complete dynamic picture and a more quantitative description of the timescale and amplitude of fluctuations in atomic coordinates than is obtainable from the individual methods alone. Order parameters (S2) were calculated from single-conformer and multiconformer models fitted to room temperature and cryogenic X-ray diffraction data for dihydrofolate reductase. Backbone and side-chain order parameters derived from NMR relaxation experiments are in excellent agreement with those calculated from the room-temperature single-conformer and multiconformer models, showing that the picosecond timescale motions observed in solution occur also in the crystalline state. These motions are quenched in the crystal at cryogenic temperatures. The combination of NMR and X-ray crystallography in iterative refinement promises to provide an atomic resolution description of the alternate conformational substates that are sampled through picosecond to nanosecond timescale fluctuations of the protein structure. The method also provides insights into the structural heterogeneity of nonmethyl side chains, aromatic residues, and ligands, which are less commonly analyzed by NMR relaxation measurements.

Incorporation of protein flexibility and conformational energy penalties in docking screens to improve ligand discovery.

Proteins fluctuate between alternative conformations, which presents a challenge for ligand discovery because such flexibility is difficult to treat computationally owing to problems with conformational sampling and energy weighting. Here, we describe a flexible-docking method that samples and weights protein conformations using experimentally-derived conformations as a guide. The crystallographically refined occupancies of these conformations, which are observable in an apo receptor structure, define energy penalties for docking. In a large prospective library screen, we identified new ligands that target specific receptor conformations of a cavity in Cytochrome c Peroxidase, and we confirm both ligand pose and associated receptor conformation predictions by crystallography. The inclusion of receptor flexibility led to ligands with new chemotypes and physical properties. By exploiting experimental measures of loop and side chain flexibility, this method can be extended to the discovery of new ligands for hundreds of targets in the Protein Data Bank where similar experimental information is available.