Exposing Hidden Alternative Backbone Conformations in X-ray Crystallography Using qFit

Comprehensive encoding of conformational and compositional protein structural ensembles through the mmCIF data structure

In the folded state, biomolecules exchange between multiple conformational states crucial for their function. However, most structural models derived from experiments and computational predictions only encode a single state. To represent biomolecules accurately, we must move towards modeling and predicting structural ensembles. Information about structural ensembles exists within experimental data from X-ray crystallography and cryo-electron microscopy. Although new tools are available to detect conformational and compositional heterogeneity within these ensembles, the legacy PDB data structure does not robustly encapsulate this complexity. We propose modifications to the macromolecular crystallographic information file (mmCIF) to improve the representation and interrelation of conformational and compositional heterogeneity. These modifications will enable the capture of macromolecular ensembles in a human and machine-interpretable way, potentially catalyzing breakthroughs for ensemble-function predictions, analogous to the achievements of AlphaFold with single-structure prediction.

Automated multiconformer model building for X-ray crystallography and cryo-EM

In their folded state, biomolecules exchange between multiple conformational states that are crucial for their function. Traditional structural biology methods, such as X-ray crystallography and cryogenic electron microscopy (cryo-EM), produce density maps that are ensemble averages, reflecting molecules in various conformations. Yet, most models derived from these maps explicitly represent only a single conformation, overlooking the complexity of biomolecular structures. To accurately reflect the diversity of biomolecular forms, there is a pressing need to shift toward modeling structural ensembles that mirror the experimental data. However, the challenge of distinguishing signal from noise complicates manual efforts to create these models. In response, we introduce the latest enhancements to qFit, an automated computational strategy designed to incorporate protein conformational heterogeneity into models built into density maps. These algorithmic improvements in qFit are substantiated by superior Rfree and geometry metrics across a wide range of proteins. Importantly, unlike more complex multicopy ensemble models, the multiconformer models produced by qFit can be manually modified in most major model building software (e.g., Coot) and fit can be further improved by refinement using standard pipelines (e.g., Phenix, Refmac, Buster). By reducing the barrier of creating multiconformer models, qFit can foster the development of new hypotheses about the relationship between macromolecular conformational dynamics and function.

Uncovering Protein Ensembles: Automated Multiconformer Model Building for X-ray Crystallography and Cryo-EM

In their folded state, biomolecules exchange between multiple conformational states that are crucial for their function. Traditional structural biology methods, such as X-ray crystallography and cryogenic electron microscopy (cryo-EM), produce density maps that are ensemble averages, reflecting molecules in various conformations. Yet, most models derived from these maps explicitly represent only a single conformation, overlooking the complexity of biomolecular structures. To accurately reflect the diversity of biomolecular forms, there is a pressing need to shift towards modeling structural ensembles that mirror the experimental data. However, the challenge of distinguishing signal from noise complicates manual efforts to create these models. In response, we introduce the latest enhancements to qFit, an automated computational strategy designed to incorporate protein conformational heterogeneity into models built into density maps. These algorithmic improvements in qFit are substantiated by superior R f r e e and geometry metrics across a wide range of proteins. Importantly, unlike more complex multicopy ensemble models, the multiconformer models produced by qFit can be manually modified in most major model building software (e.g. Coot) and fit can be further improved by refinement using standard pipelines (e.g. Phenix, Refmac, Buster). By reducing the barrier of creating multiconformer models, qFit can foster the development of new hypotheses about the relationship between macromolecular conformational dynamics and function.

Alternate conformations found in protein structures implies biological functions: A case study using cyclophilin A

Protein dynamics linked to numerous biomolecular functions, such as ligand binding, allosteric regulation, and catalysis, must be better understood at the atomic level. Reactive atoms of key residues drive a repertoire of biomolecular functions by flipping between alternate conformations or conformational substates, seldom found in protein structures. Probing such sparsely sampled alternate conformations would provide mechanistic insight into many biological functions. We are therefore interested in evaluating the instance of amino acids adopted alternate conformations, either in backbone or side-chain atoms or in both. Accordingly, over 70000 protein structures appear to contain alternate conformations only 'A' and 'B' for any atom, particularly the instance of amino acids that adopted alternate conformations are more for Arg, Cys, Met, and Ser than others. The resulting protein structure analysis depicts that amino acids with alternate conformations are mainly found in the helical and β-regions and are often seen in high-resolution X-ray crystal structures. Furthermore, a case study on human cyclophilin A (CypA) was performed to explain the pre-existing intrinsic dynamics of catalytically critical residues from the CypA and how such intrinsic dynamics perturbed upon Ser99Thr mutation using molecular dynamics simulations on the ns-μs timescale. Simulation results demonstrated that the Ser99Thr mutation had impaired the alternate conformations or the catalytically productive micro-environment of Phe113, mimicking the experimentally observed perturbation captured by X-ray crystallography. In brief, a deeper comprehension of alternate conformations adopted by the amino acids may shed light on the interplay between protein structure, dynamics, and function.

Design of Efficient Artificial Enzymes Using Crystallographically Enhanced Conformational Sampling

The ability to create efficient artificial enzymes for any chemical reaction is of great interest. Here, we describe a computational design method for increasing the catalytic efficiency of de novo enzymes by several orders of magnitude without relying on directed evolution and high-throughput screening. Using structural ensembles generated from dynamics-based refinement against X-ray diffraction data collected from crystals of Kemp eliminases HG3 (kcat/KM 125 M-1 s-1) and KE70 (kcat/KM 57 M-1 s-1), we design from each enzyme ≤10 sequences predicted to catalyze this reaction more efficiently. The most active designs display kcat/KM values improved by 100-250-fold, comparable to mutants obtained after screening thousands of variants in multiple rounds of directed evolution. Crystal structures show excellent agreement with computational models, with catalytic contacts present as designed and transition-state root-mean-square deviations of ≤0.65 Å. Our work shows how ensemble-based design can generate efficient artificial enzymes by exploiting the true conformational ensemble to design improved active sites.

High-resolution double vision of the allosteric phosphatase PTP1B

Protein tyrosine phosphatase 1B (PTP1B) plays important roles in cellular homeostasis and is a highly validated therapeutic target for multiple human ailments, including diabetes, obesity and breast cancer. However, much remains to be learned about how conformational changes may convey information through the structure of PTP1B to enable allosteric regulation by ligands or functional responses to mutations. High-resolution X-ray crystallography can offer unique windows into protein conformational ensembles, but comparison of even high-resolution structures is often complicated by differences between data sets, including non-isomorphism. Here, the highest resolution crystal structure of apo wild-type (WT) PTP1B to date is presented out of a total of ∼350 PTP1B structures in the PDB. This structure is in a crystal form that is rare for PTP1B, with two unique copies of the protein that exhibit distinct patterns of conformational heterogeneity, allowing a controlled comparison of local disorder across the two chains within the same asymmetric unit. The conformational differences between these chains are interrogated in the apo structure and between several recently reported high-resolution ligand-bound structures. Electron-density maps in a high-resolution structure of a recently reported activating double mutant are also examined, and unmodeled alternate conformations in the mutant structure are discovered that coincide with regions of enhanced conformational heterogeneity in the new WT structure. These results validate the notion that these mutations operate by enhancing local dynamics, and suggest a latent susceptibility to such changes in the WT enzyme. Together, these new data and analysis provide a detailed view of the conformational ensemble of PTP1B and highlight the utility of high-resolution crystallography for elucidating conformational heterogeneity with potential relevance for function.

Design of efficient artificial enzymes using crystallographically-enhanced conformational sampling

The ability to create efficient artificial enzymes for any chemical reaction is of great interest. Here, we describe a computational design method for increasing catalytic efficiency of de novo enzymes to a level comparable to their natural counterparts without relying on directed evolution. Using structural ensembles generated from dynamics-based refinement against X-ray diffraction data collected from crystals of Kemp eliminases HG3 (kcat/KM 125 M-1 s-1) and KE70 (kcat/KM 57 M-1 s-1), we design from each enzyme ≤10 sequences predicted to catalyze this reaction more efficiently. The most active designs display kcat/KM values improved by 100-250-fold, comparable to mutants obtained after screening thousands of variants in multiple rounds of directed evolution. Crystal structures show excellent agreement with computational models. Our work shows how computational design can generate efficient artificial enzymes by exploiting the true conformational ensemble to more effectively stabilize the transition state.

Modeling diffuse scattering with simple, physically interpretable models

Diffuse scattering has long been proposed to probe protein dynamics relevant for biological function, and more recently, as a tool to aid structure determination. Despite recent advances in measuring and modeling this signal, the field has not been able to routinely use experimental diffuse scattering for either application. A persistent challenge has been to devise models that are sophisticated enough to robustly reproduce experimental diffuse features but remain readily interpretable from the standpoint of structural biology. This chapter presents eryx, a suite of computational tools to evaluate the primary models of disorder that have been used to analyze protein diffuse scattering. By facilitating comparative modeling, eryx aims to provide insights into the physical origins of this signal and help identify the sources of disorder that are critical for reproducing experimental features. This framework also lays the groundwork for the development of more advanced models that integrate different types of disorder without loss of interpretability.

Refinement of multiconformer ensemble models from multi-temperature X-ray diffraction data

Conformational ensembles underlie all protein functions. Thus, acquiring atomic-level ensemble models that accurately represent conformational heterogeneity is vital to deepen our understanding of how proteins work. Modeling ensemble information from X-ray diffraction data has been challenging, as traditional cryo-crystallography restricts conformational variability while minimizing radiation damage. Recent advances have enabled the collection of high quality diffraction data at ambient temperatures, revealing innate conformational heterogeneity and temperature-driven changes. Here, we used diffraction datasets for Proteinase K collected at temperatures ranging from 313 to 363 K to provide a tutorial for the refinement of multiconformer ensemble models. Integrating automated sampling and refinement tools with manual adjustments, we obtained multiconformer models that describe alternative backbone and sidechain conformations, their relative occupancies, and interconnections between conformers. Our models revealed extensive and diverse conformational changes across temperature, including increased bound peptide ligand occupancies, different Ca2+ binding site configurations and altered rotameric distributions. These insights emphasize the value and need for multiconformer model refinement to extract ensemble information from diffraction data and to understand ensemble-function relationships.

PyInteraph2 and PyInKnife2 to Analyze Networks in Protein Structural Ensembles

Due to the complex nature of noncovalent interactions and their long-range effects, analyzing protein conformations using network theory can be enlightening. Protein Structure Networks (PSNs) provide a convenient formalism to study protein structures in relation to essential properties such as key residues for structural stability, allosteric communication, and the effects of modifications of the protein. PSNs can be defined according to very different principles, and the available tools have limitations in input formats, supported models, and version control. Other outstanding problems are related to the definition of network cutoffs and the assessment of the stability of the network properties. The protein science community could benefit from a common framework to carry out these analyses and make them easier to reproduce, reuse, and evaluate. We here provide two open-source software packages, PyInteraph2 and PyInKnife2, to implement and analyze PSNs in a reproducible and documented manner. PyInteraph2 interfaces with multiple formats for protein ensembles and incorporates different network models with the possibility of integrating them into a macronetwork and performing various downstream analyses, including hubs, connected components, and several other centrality measures, and visualizes the networks or further analyzes them thanks to compatibility with Cytoscape.PyInKnife2 that supports the network models implemented in PyInteraph2. It employs a jackknife resampling approach to estimate the convergence of network properties and streamline the selection of distance cutoffs. We foresee that the modular structure of the code and the supported version control system will promote the transition to a community-driven effort, boost reproducibility, and establish common protocols in the PSN field. As developers, we will guarantee the introduction of new functionalities and maintenance, assistance, and training of new contributors.

Emerging Time-Resolved X-Ray Diffraction Approaches for Protein Dynamics

Proteins guide the flows of information, energy, and matter that make life possible by accelerating transport and chemical reactions, by allosterically modulating these reactions, and by forming dynamic supramolecular assemblies. In these roles, conformational change underlies functional transitions. Time-resolved X-ray diffraction methods characterize these transitions either by directly triggering sequences of functionally important motions or, more broadly, by capturing the motions of which proteins are capable. To date, most successful have been experiments in which conformational change is triggered in light-dependent proteins. In this review, I emphasize emerging techniques that probe the dynamic basis of function in proteins lacking natively light-dependent transitions and speculate about extensions and further possibilities. In addition, I review how the weaker and more distributed signals in these data push the limits of the capabilities of analytical methods. Taken together, these new methods are beginning to establish a powerful paradigm for the study of the physics of protein function.

Refinement of Multiconformer Ensemble Models from Multi-temperature X-ray Diffraction Data

Conformational ensembles underlie all protein functions. Thus, acquiring atomic-level ensemble models that accurately represent conformational heterogeneity is vital to deepen our understanding of how proteins work. Modeling ensemble information from X-ray diffraction data has been challenging, as traditional cryo-crystallography restricts conformational variability while minimizing radiation damage. Recent advances have enabled the collection of high quality diffraction data at ambient temperatures, revealing innate conformational heterogeneity and temperature-driven changes. Here, we used diffraction datasets for Proteinase K collected at temperatures ranging from 313 to 363K to provide a tutorial for the refinement of multiconformer ensemble models. Integrating automated sampling and refinement tools with manual adjustments, we obtained multiconformer models that describe alternative backbone and sidechain conformations, their relative occupancies, and interconnections between conformers. Our models revealed extensive and diverse conformational changes across temperature, including increased bound peptide ligand occupancies, different Ca2+ binding site configurations and altered rotameric distributions. These insights emphasize the value and need for multiconformer model refinement to extract ensemble information from diffraction data and to understand ensemble-function relationships.

Modeling with Alternate Locations in X-ray Protein Structures

In many molecular modeling applications, the standard procedure is still to handle proteins as single, rigid structures. While the importance of conformational flexibility is widely known, handling it remains challenging. Even the crystal structure of a protein usually contains variability exemplified in alternate side chain orientations or backbone segments. This conformational variability is encoded in PDB structure files by so-called alternate locations (AltLocs). Most modeling approaches either ignore AltLocs or resolve them with simple heuristics early on during structure import. We analyzed the occurrence and usage of AltLocs in the PDB and developed an algorithm to automatically handle AltLocs in PDB files enabling all structure-based methods using rigid structures to take the alternative protein conformations described by AltLocs into consideration. A respective software tool named AltLocEnumerator can be used as a structure preprocessor to easily exploit AltLocs. While the amount of data makes it difficult to show impact on a statistical level, handling AltLocs has a substantial impact on a case-by-case basis. We believe that the inspection and consideration of AltLocs is a very valuable approach in many modeling scenarios.

Temporal and spatial resolution of distal protein motions that activate hydrogen tunneling in soybean lipoxygenase

The enzyme soybean lipoxygenase (SLO) provides a prototype for deep tunneling mechanisms in hydrogen transfer catalysis. This work combines room temperature X-ray studies with extended hydrogen-deuterium exchange experiments to define a catalytically-linked, radiating cone of aliphatic side chains that connects an active site iron center of SLO to the protein-solvent interface. Employing eight variants of SLO that have been appended with a fluorescent probe at the identified surface loop, nanosecond fluorescence Stokes shifts have been measured. We report a remarkable identity of the energies of activation (Ea) for the Stokes shifts decay rates and the millisecond C-H bond cleavage step that is restricted to side chain mutants within an identified thermal network. These findings implicate a direct coupling of distal protein motions surrounding the exposed fluorescent probe to active site motions controlling catalysis. While the role of dynamics in enzyme function has been predominantly attributed to a distributed protein conformational landscape, the presented data implicate a thermally initiated, cooperative protein reorganization that occurs on a timescale faster than nanosecond and represents the enthalpic barrier to the reaction of SLO.

Obtaining anomalous and ensemble information from protein crystals from 220 K up to physiological temperatures

X-ray crystallography has been invaluable in delivering structural information about proteins. Previously, an approach has been developed that allows high-quality X-ray diffraction data to be obtained from protein crystals at and above room temperature. Here, this previous work is built on and extended by showing that high-quality anomalous signal can be obtained from single protein crystals using diffraction data collected at 220 K up to physiological temperatures. The anomalous signal can be used to directly determine the structure of a protein, i.e. to phase the data, as is routinely performed under cryoconditions. This ability is demonstrated by obtaining diffraction data from model lysozyme, thaumatin and proteinase K crystals, the anomalous signal from which allowed their structures to be solved experimentally at 7.1 keV X-ray energy and at room temperature with relatively low data redundancy. It is also demonstrated that the anomalous signal from diffraction data obtained at 310 K (37°C) can be used to solve the structure of proteinase K and to identify ordered ions. The method provides useful anomalous signal at temperatures down to 220 K, resulting in an extended crystal lifetime and increased data redundancy. Finally, we show that useful anomalous signal can be obtained at room temperature using X-rays of 12 keV energy as typically used for routine data collection, allowing this type of experiment to be carried out at widely accessible synchrotron beamline energies and enabling the simultaneous extraction of high-resolution data and anomalous signal. With the recent emphasis on obtaining conformational ensemble information for proteins, the high resolution of the data allows such ensembles to be built, while the anomalous signal allows the structure to be experimentally solved, ions to be identified, and water molecules and ions to be differentiated. Because bound metal-, phosphorus- and sulfur-containing ions all have anomalous signal, obtaining anomalous signal across temperatures and up to physiological temperatures will provide a more complete description of protein conformational ensembles, function and energetics.

Molecular-dynamics simulation methods for macromolecular crystallography

It is investigated whether molecular-dynamics (MD) simulations can be used to enhance macromolecular crystallography (MX) studies. Historically, protein crystal structures have been described using a single set of atomic coordinates. Because conformational variation is important for protein function, researchers now often build models that contain multiple structures. Methods for building such models can fail, however, in regions where the crystallographic density is difficult to interpret, for example at the protein-solvent interface. To address this limitation, a set of MD-MX methods that combine MD simulations of protein crystals with conventional modeling and refinement tools have been developed. In an application to a cyclic adenosine monophosphate-dependent protein kinase at room temperature, the procedure improved the interpretation of ambiguous density, yielding an alternative water model and a revised protein model including multiple conformations. The revised model provides mechanistic insights into the catalytic and regulatory interactions of the enzyme. The same methods may be used in other MX studies to seek mechanistic insights.

Computational analysis of protein conformational heterogeneity

In this paper, we applied the molecular dynamics (MD) simulations and used thermolysin as the system to study the overall protein dynamics and side chain dihedral angles across the Arrhenius break. Simulations were performed at a high temperature of 36 °C which is above the previously observed Arrhenius break, and the lower temperature of 20 °C which is below the Arrhenius break. We observed different protein dynamics and conformational heterogeneity of side chain dihedral angles of thermolysin at the two temperatures. Our results indicated that certain regions of thermolysin have a higher level of fluctuation at lower temperature. A temperature dependent dihedral angles were also observed at the two temperatures. The changes observed in the protein indicated key areas of temperature sensitivity within the protein.Communicated by Ramaswamy H. Sarma.

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.

Functional roles of enzyme dynamics in accelerating active site chemistry: Emerging techniques and changing concepts

With the growing acceptance of the contribution of protein conformational ensembles to enzyme catalysis and regulation, research in the field of protein dynamics has shifted toward an understanding of the atomistic properties of protein dynamical networks and the mechanisms and time scales that control such behavior. A full description of an enzymatic reaction coordinate is expected to extend beyond the active site and include site-specific networks that communicate with the protein/water interface. Advances in experimental tools for the spatial resolution of thermal activation pathways are being complemented by biophysical methods for visualizing dynamics in real time. An emerging multidimensional model integrates the impacts of bound substrate/effector on the distribution of protein substates that are in rapid equilibration near room temperature with reaction-specific protein embedded heat transfer conduits.

Evaluating the impact of X-ray damage on conformational heterogeneity in room-temperature (277 K) and cryo-cooled protein crystals

Cryo-cooling has been nearly universally adopted to mitigate X-ray damage and facilitate crystal handling in protein X-ray crystallography. However, cryo X-ray crystallographic data provide an incomplete window into the ensemble of conformations that is at the heart of protein function and energetics. Room-temperature (RT) X-ray crystallography provides accurate ensemble information, and recent developments allow conformational heterogeneity (the experimental manifestation of ensembles) to be extracted from single-crystal data. Nevertheless, high sensitivity to X-ray damage at RT raises concerns about data reliability. To systematically address this critical issue, increasingly X-ray-damaged high-resolution data sets (1.02-1.52 Å resolution) were obtained from single proteinase K, thaumatin and lysozyme crystals at RT (277 K). In each case a modest increase in conformational heterogeneity with X-ray damage was observed. Merging data with different extents of damage (as is typically carried out) had negligible effects on conformational heterogeneity until the overall diffraction intensity decayed to ∼70% of its initial value. These effects were compared with X-ray damage effects in cryo-cooled crystals by carrying out an analogous analysis of increasingly damaged proteinase K cryo data sets (0.9-1.16 Å resolution). X-ray damage-associated heterogeneity changes were found that were not observed at RT. This property renders it difficult to distinguish real from artefactual conformations and to determine the conformational response to changes in temperature. The ability to acquire reliable heterogeneity information from single crystals at RT, together with recent advances in RT data collection at accessible synchrotron beamlines, provides a strong motivation for the widespread adoption of RT X-ray crystallography to obtain conformational ensemble information.

Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon

Synonymous codons translate into chemically identical amino acids. Once considered inconsequential to the formation of the protein product, there is evidence to suggest that codon usage affects co-translational protein folding and the final structure of the expressed protein. Here we develop a method for computing and comparing codon-specific Ramachandran plots and demonstrate that the backbone dihedral angle distributions of some synonymous codons are distinguishable with statistical significance for some secondary structures. This shows that there exists a dependence between codon identity and backbone torsion of the translated amino acid. Although these findings cannot pinpoint the causal direction of this dependence, we discuss the vast biological implications should coding be shown to directly shape protein conformation and demonstrate the usefulness of this method as a tool for probing associations between codon usage and protein structure. Finally, we urge for the inclusion of exact genetic information into structural databases.

Ligand binding remodels protein side-chain conformational heterogeneity

While protein conformational heterogeneity plays an important role in many aspects of biological function, including ligand binding, its impact has been difficult to quantify. Macromolecular X-ray diffraction is commonly interpreted with a static structure, but it can provide information on both the anharmonic and harmonic contributions to conformational heterogeneity. Here, through multiconformer modeling of time- and space-averaged electron density, we measure conformational heterogeneity of 743 stringently matched pairs of crystallographic datasets that reflect unbound/apo and ligand-bound/holo states. When comparing the conformational heterogeneity of side chains, we observe that when binding site residues become more rigid upon ligand binding, distant residues tend to become more flexible, especially in non-solvent-exposed regions. Among ligand properties, we observe increased protein flexibility as the number of hydrogen bonds decreases and relative hydrophobicity increases. Across a series of 13 inhibitor-bound structures of CDK2, we find that conformational heterogeneity is correlated with inhibitor features and identify how conformational changes propagate differences in conformational heterogeneity away from the binding site. Collectively, our findings agree with models emerging from nuclear magnetic resonance studies suggesting that residual side-chain entropy can modulate affinity and point to the need to integrate both static conformational changes and conformational heterogeneity in models of ligand binding.

Best practices for time-resolved serial synchrotron crystallography

With recent developments in X-ray sources, instrumentation and data-analysis tools, time-resolved crystallographic experiments, which were originally the preserve of a few expert groups, are becoming simpler and can be carried out at more radiation sources, and are thus increasingly accessible to a growing user base. However, these experiments are just that: discrete experiments, not just `data collections'. As such, careful planning and consideration of potential pitfalls is required to enable a successful experiment. Here, some of the key factors that should be considered during the planning and execution of a time-resolved structural study are outlined, with a particular focus on synchrotron-based experiments.

Modeling a unit cell: crystallographic refinement procedure using the biomolecular MD simulation platform Amber

A procedure has been developed for the refinement of crystallographic protein structures based on the biomolecular simulation program Amber. The procedure constructs a model representing a crystal unit cell, which generally contains multiple protein molecules and is fully hydrated with TIP3P water. Periodic boundary conditions are applied to the cell in order to emulate the crystal lattice. The refinement is conducted in the form of a specially designed short molecular-dynamics run controlled by the Amber ff14SB force field and the maximum-likelihood potential that encodes the structure-factor-based restraints. The new Amber-based refinement procedure has been tested on a set of 84 protein structures. In most cases, the new procedure led to appreciably lower R free values compared with those reported in the original PDB depositions or obtained by means of the industry-standard phenix.refine program. In particular, the new method has the edge in refining low-accuracy scrambled models. It has also been successful in refining a number of molecular-replacement models, including one with an r.m.s.d. of 2.15 Å. In addition, Amber-refined structures consistently show superior MolProbity scores. The new approach offers a highly realistic representation of protein-protein interactions in the crystal, as well as of protein-water interactions. It also offers a realistic representation of protein crystal dynamics (akin to ensemble-refinement schemes). Importantly, the method fully utilizes the information from the available diffraction data, while relying on state-of-the-art molecular-dynamics modeling to assist with those elements of the structure that do not diffract well (for example mobile loops or side chains). Finally, it should be noted that the protocol employs no tunable parameters, and the calculations can be conducted in a matter of several hours on desktop computers equipped with graphical processing units or using a designated web service.

Mapping Enzyme Landscapes by Time-Resolved Crystallography with Synchrotron and X-Ray Free Electron Laser Light

Directly observing enzyme catalysis in real time at the molecular level has been a long-standing goal of structural enzymology. Time-resolved serial crystallography methods at synchrotron and X-ray free electron laser (XFEL) sources have enabled researchers to follow enzyme catalysis and other nonequilibrium events at ambient conditions with unprecedented time resolution. X-ray crystallography provides detailed information about conformational heterogeneity and protein dynamics, which is enhanced when time-resolved approaches are used. This review outlines the ways in which information about the underlying energy landscape of a protein can be extracted from X-ray crystallographic data, with an emphasis on new developments in XFEL and synchrotron time-resolved crystallography. The emerging view of enzyme catalysis afforded by these techniques can be interpreted as enzymes moving on a time-dependent energy landscape. Some consequences of this view are discussed, including the proposal that irreversible enzymes or enzymes that use covalent catalytic mechanisms may commonly exhibit catalysis-activated motions. Expected final online publication date for the Annual Review of Biophysics, Volume 51 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Improving sampling of crystallographic disorder in ensemble refinement

Ensemble refinement, the application of molecular dynamics to crystallographic refinement, explicitly models the disorder inherent in macromolecular structures. These ensemble models have been shown to produce more accurate structures than traditional single-model structures. However, suboptimal sampling of the molecular-dynamics simulation and modelling of crystallographic disorder has limited the utility of the method, and can lead to unphysical and strained models. Here, two improvements to the ensemble refinement method implemented within Phenix are presented: DEN restraints, which guide the local sampling of conformations and allow a more robust exploration of local conformational landscapes, and ECHT disorder models, which allow the selection of more physically meaningful and effective disorder models for parameterizing the continuous disorder components within a crystal. These improvements lead to more consistent and physically interpretable simulations of macromolecules in crystals, and allow structural heterogeneity and disorder to be systematically explored on different scales. The new approach is demonstrated on several case studies and the SARS-CoV-2 main protease, and demonstrates how the choice of disorder model affects the type of disorder that is sampled by the restrained molecular-dynamics simulation.

Temperature artifacts in protein structures bias ligand-binding predictions

X-ray crystallography is the gold standard to resolve conformational ensembles that are significant for protein function, ligand discovery, and computational methods development. However, relevant conformational states may be missed at common cryogenic (cryo) data-collection temperatures but can be populated at room temperature. To assess the impact of temperature on making structural and computational discoveries, we systematically investigated protein conformational changes in response to temperature and ligand binding in a structural and computational workhorse, the T4 lysozyme L99A cavity. Despite decades of work on this protein, shifting to RT reveals new global and local structural changes. These include uncovering an apo helix conformation that is hidden at cryo but relevant for ligand binding, and altered side chain and ligand conformations. To evaluate the impact of temperature-induced protein and ligand changes on the utility of structural information in computation, we evaluated how temperature can mislead computational methods that employ cryo structures for validation. We find that when comparing simulated structures just to experimental cryo structures, hidden successes and failures often go unnoticed. When using structural information in ligand binding predictions, both coarse docking and rigorous binding free energy calculations are influenced by temperature effects. The trend that cryo artifacts limit the utility of structures for computation holds across five distinct protein classes. Our results suggest caution when consulting cryogenic structural data alone, as temperature artifacts can conceal errors and prevent successful computational predictions, which can mislead the development and application of computational methods in discovering bioactive molecules.

Exploring ligand dynamics in protein crystal structures with ensemble refinement

Understanding the dynamics of ligands bound to proteins is an important task in medicinal chemistry and drug design. However, the dominant technique for determining protein-ligand structures, X-ray crystallography, does not fully account for dynamics and cannot accurately describe the movements of ligands in protein binding sites. In this article, an alternative method, ensemble refinement, is used on six protein-ligand complexes with the aim of understanding the conformational diversity of ligands in protein crystal structures. The results show that ensemble refinement sometimes indicates that the flexibility of parts of the ligand and some protein side chains is larger than that which can be described by a single conformation and atomic displacement parameters. However, since the electron-density maps are comparable and Rfree values are slightly increased, the original crystal structure is still a better model from a statistical point of view. On the other hand, it is shown that molecular-dynamics simulations and automatic generation of alternative conformations in crystallographic refinement confirm that the flexibility of these groups is larger than is observed in standard refinement. Moreover, the flexible groups in ensemble refinement coincide with groups that give high atomic displacement parameters or non-unity occupancy if optimized in standard refinement. Therefore, the conformational diversity indicated by ensemble refinement seems to be qualitatively correct, indicating that ensemble refinement can be an important complement to standard crystallographic refinement as a tool to discover which parts of crystal structures may show extensive flexibility and therefore are poorly described by a single conformation. However, the diversity of the ensembles is often exaggerated (probably partly owing to the rather poor force field employed) and the ensembles should not be trusted in detail.

A Minireview on Temperature Dependent Protein Conformational Sampling

In this minireview we discuss the role of the more subtle conformational change-protein conformational sampling and connect it to the classic relationship of protein structure and function. The theory of pre-existing functional states of protein are discussed in context of alternate protein conformational sampling. Last, we discuss how temperature, ligand binding and mutations affect the protein conformational sampling mode which is linked to the protein function regulation. The review includes several protein systems that showed temperature dependent protein conformational sampling. We also specifically included two enzyme systems, thermophilic alcohol dehydrogenase (ht-ADH) and thermolysin which we previously studied when discussing temperature dependent protein conformational sampling.

Structural insights into protein folding, stability and activity using in vivo perdeuteration of hen egg-white lysozyme

This structural and biophysical study exploited a method of perdeuterating hen egg-white lysozyme based on the expression of insoluble protein in Escherichia coli followed by in-column chemical refolding. This allowed detailed comparisons with perdeuterated lysozyme produced in the yeast Pichia pastoris, as well as with unlabelled lysozyme. Both perdeuterated variants exhibit reduced thermal stability and enzymatic activity in comparison with hydrogenated lysozyme. The thermal stability of refolded perdeuterated lysozyme is 4.9°C lower than that of the perdeuterated variant expressed and secreted in yeast and 6.8°C lower than that of the hydrogenated Gallus gallus protein. However, both perdeuterated variants exhibit a comparable activity. Atomic resolution X-ray crystallographic analyses show that the differences in thermal stability and enzymatic function are correlated with refolding and deuteration effects. The hydrogen/deuterium isotope effect causes a decrease in the stability and activity of the perdeuterated analogues; this is believed to occur through a combination of changes to hydrophobicity and protein dynamics. The lower level of thermal stability of the refolded perdeuterated lysozyme is caused by the unrestrained Asn103 peptide-plane flip during the unfolded state, leading to a significant increase in disorder of the Lys97-Gly104 region following subsequent refolding. An ancillary outcome of this study has been the development of an efficient and financially viable protocol that allows stable and active perdeuterated lysozyme to be more easily available for scientific applications.

Determination of amino acids that favour the αL region using Ramachandran propensity plots. Implications for α-sheet as the possible amyloid intermediate

In amyloid diseases an insoluble amyloid fibril forms via a soluble oligomeric intermediate. It is this intermediate that mediates toxicity and it has been suggested, somewhat controversially, that it has the α-sheet structure. Nests and α-strands are similar peptide motifs in that alternate residues lie in the α_R and γ_L regions of the Ramachandran plot for nests, or α_R and α_L regions for α-strands. In nests a concavity is formed by the main chain NH atoms whereas in α-strands the main chain is almost straight. Using "Ramachandran propensity plots" to focus on the α_L/γ_L region, it is shown that glycine favours γ_L (82% of amino acids are glycine), but disfavours α_L (3% are glycine). Most charged and polar amino acids favour α_L with asparagine having by far the highest propensity. Thus, glycine favours nests but, contrary to common expectation, should not favour α-sheet. By contrast most charged or polar amino acids should favour α-sheet by their propensity for the α_L conformation, which is more discriminating amongst amino acids than the α_R conformation. Thus, these results suggest the composition of sequences that favour α-sheet formation and point towards effective prediction of α-sheet from sequence.

Macromolecular room temperature crystallography

X-ray crystallography enables detailed structural studies of proteins to understand and modulate their function. Conducting crystallographic experiments at cryogenic temperatures has practical benefits but potentially limits the identification of functionally important alternative protein conformations that can be revealed only at room temperature (RT). This review discusses practical aspects of preparing, acquiring, and analyzing X-ray crystallography data at RT to demystify preconceived impracticalities that freeze progress of routine RT data collection at synchrotron sources. Examples are presented as conceptual and experimental templates to enable the design of RT-inspired studies; they illustrate the diversity and utility of gaining novel insights into protein conformational landscapes. An integrative view of protein conformational dynamics enables opportunities to advance basic and biomedical research.

qFit 3: Protein and ligand multiconformer modeling for X-ray crystallographic and single-particle cryo-EM density maps

New X-ray crystallography and cryo-electron microscopy (cryo-EM) approaches yield vast amounts of structural data from dynamic proteins and their complexes. Modeling the full conformational ensemble can provide important biological insights, but identifying and modeling an internally consistent set of alternate conformations remains a formidable challenge. qFit efficiently automates this process by generating a parsimonious multiconformer model. We refactored qFit from a distributed application into software that runs efficiently on a small server, desktop, or laptop. We describe the new qFit 3 software and provide some examples. qFit 3 is open-source under the MIT license, and is available at https://github.com/ExcitedStates/qfit-3.0.

Discovery of allosteric binding sites by crystallographic fragment screening

Understanding allosteric regulation of proteins is fundamental to our study of protein structure and function. Moreover, allosteric binding pockets have become a major target of drug discovery efforts in recent years. However, even though the function of almost every protein can be influenced by allostery, it remains a challenge to discover, rationalise and validate putative allosteric binding pockets. This review examines how the discovery and analysis of putative allosteric binding sites have been influenced by the availability of centralised facilities for crystallographic fragment screening, along with newly developed computational methods for modelling low occupancy features. We discuss the experimental parameters required for success, and how new methods could influence the field in the future. Finally, we reflect on the general problem of how to translate these findings into actual ligand development programs.

Conformational heterogeneity of Savinase from NMR, HDX-MS and X-ray diffraction analysis

Background

Several examples have emerged of enzymes where slow conformational changes are of key importance for function and where low populated conformations in the resting enzyme resemble the conformations of intermediate states in the catalytic process. Previous work on the subtilisin protease, Savinase, from Bacillus lentus by NMR spectroscopy suggested that this enzyme undergoes slow conformational dynamics around the substrate binding site. However, the functional importance of such dynamics is unknown.

Methods

Here we have probed the conformational heterogeneity in Savinase by following the temperature dependent chemical shift changes. In addition, we have measured changes in the local stability of the enzyme when the inhibitor phenylmethylsulfonyl fluoride is bound using hydrogen-deuterium exchange mass spectrometry (HDX-MS). Finally, we have used X-ray crystallography to compare electron densities collected at cryogenic and ambient temperatures and searched for possible low populated alternative conformations in the crystals.

Results

The NMR temperature titration shows that Savinase is most flexible around the active site, but no distinct alternative states could be identified. The HDX shows that modification of Savinase with inhibitor has very little impact on the stability of hydrogen bonds and solvent accessibility of the backbone. The most pronounced structural heterogeneities detected in the diffraction data are limited to alternative side-chain rotamers and a short peptide segment that has an alternative main-chain conformation in the crystal at cryo conditions. Collectively, our data show that there is very little structural heterogeneity in the resting state of Savinase and hence that Savinase does not rely on conformational selection to drive the catalytic process.

Advances in methods for atomic resolution macromolecular structure determination

Recent technical advances have dramatically increased the power and scope of structural biology. New developments in high-resolution cryo-electron microscopy, serial X-ray crystallography, and electron diffraction have been especially transformative. Here we highlight some of the latest advances and current challenges at the frontiers of atomic resolution methods for elucidating the structures and dynamical properties of macromolecules and their complexes.

Computational Analysis of Energy Landscapes Reveals Dynamic Features That Contribute to Binding of Inhibitors to CFTR-Associated Ligand

The CFTR-associated ligand PDZ domain (CALP) binds to the cystic fibrosis transmembrane conductance regulator (CFTR) and mediates lysosomal degradation of mature CFTR. Inhibition of this interaction has been explored as a therapeutic avenue for cystic fibrosis. Previously, we reported the ensemble-based computational design of a novel peptide inhibitor of CALP, which resulted in the most binding-efficient inhibitor to date. This inhibitor, kCAL01, was designed using osprey and evinced significant biological activity in in vitro cell-based assays. Here, we report a crystal structure of kCAL01 bound to CALP and compare structural features against iCAL36, a previously developed inhibitor of CALP. We compute side-chain energy landscapes for each structure to not only enable approximation of binding thermodynamics but also reveal ensemble features that contribute to the comparatively efficient binding of kCAL01. Finally, we compare the previously reported design ensemble for kCAL01 vs the new crystal structure and show that, despite small differences between the design model and crystal structure, significant biophysical features that enhance inhibitor binding are captured in the design ensemble. This suggests not only that ensemble-based design captured thermodynamically significant features observed in vitro, but also that a design eschewing ensembles would miss the kCAL01 sequence entirely.

Liquid-like and rigid-body motions in molecular-dynamics simulations of a crystalline protein

To gain insight into crystalline protein dynamics, we performed molecular-dynamics (MD) simulations of a periodic 2 × 2 × 2 supercell of staphylococcal nuclease. We used the resulting MD trajectories to simulate X-ray diffraction and to study collective motions. The agreement of simulated X-ray diffraction with the data is comparable to previous MD simulation studies. We studied collective motions by analyzing statistically the covariance of alpha-carbon position displacements. The covariance decreases exponentially with the distance between atoms, which is consistent with a liquidlike motions (LLM) model, in which the protein behaves like a soft material. To gain finer insight into the collective motions, we examined the covariance behavior within a protein molecule (intraprotein) and between different protein molecules (interprotein). The interprotein atom pairs, which dominate the overall statistics, exhibit LLM behavior; however, the intraprotein pairs exhibit behavior that is consistent with a superposition of LLM and rigid-body motions (RBM). Our results indicate that LLM behavior of global dynamics is present in MD simulations of a protein crystal. They also show that RBM behavior is detectable in the simulations but that it is subsumed by the LLM behavior. Finally, the results provide clues about how correlated motions of atom pairs both within and across proteins might manifest in diffraction data. Overall, our findings increase our understanding of the connection between molecular motions and diffraction data and therefore advance efforts to extract information about functionally important motions from crystallography experiments.

Shining light on cysteine modification: connecting protein conformational dynamics to catalysis and regulation

Cysteine is a rare but functionally important amino acid that is often subject to covalent modification. Cysteine oxidation plays an important role in many human disease processes, and basal levels of cysteine oxidation are required for proper cellular function. Because reactive cysteine residues are typically ionized to the thiolate anion (Cys-S-), their formation of a covalent bond alters the electrostatic and steric environment of the active site. X-ray-induced photo-oxidation to sulfenic acids (Cys-SOH) can recapitulate some aspects of the changes that occur under physiological conditions. Here we propose how site-specific cysteine photo-oxidation can be used to interrogate ensuing changes in protein structure and dynamics at atomic resolution. Although this powerful approach can connect cysteine covalent modification to global protein conformational changes and function, careful biochemical validation must accompany all such studies to exclude misleading artifacts. New types of X-ray crystallography experiments and powerful computational methods are creating new opportunities to connect conformational dynamics to catalysis for the large class of systems that use covalently modified cysteine residues for catalysis or regulation.

Defining a new nomenclature for the structures of active and inactive kinases

Protein kinases play important roles in signaling pathways and are widely studied as drug targets. Their active site exhibits remarkable structural variation as observed in the large number of available crystal structures. We have developed a clustering scheme and nomenclature to categorize and label all the observed conformations in human protein kinases. This has enabled us to clearly define the geometry of the active state and to distinguish closely related inactive states which were previously not characterized. Our classification of kinase conformations will help in better understanding the conformational dynamics of these proteins and the development of inhibitors against them.

Targeting protein kinases is an important strategy for intervention in cancer. Inhibitors are directed at the active conformation or a variety of inactive conformations. While attempts have been made to classify these conformations, a structurally rigorous catalog of states has not been achieved. The kinase activation loop is crucial for catalysis and begins with the conserved DFGmotif. This motif is observed in two major classes of conformations, DFGin—a set of active and inactive conformations where the Phe residue is in contact with the C-helix of the N-terminal lobe—and DFGout—an inactive form where Phe occupies the ATP site exposing the C-helix pocket. We have developed a clustering of kinase conformations based on the location of the Phe side chain (DFGin, DFGout, and DFGinter or intermediate) and the backbone dihedral angles of the sequence X-D-F, where X is the residue before the DFGmotif, and the DFG-Phe side-chain rotamer, utilizing a density-based clustering algorithm. We have identified eight distinct conformations and labeled them based on the Ramachandran regions (A, alpha; B, beta; L, left) of the XDF motif and the Phe rotamer (minus, plus, trans). Our clustering divides the DFGin group into six clusters including BLAminus, which contains active structures, and two common inactive forms, BLBplus and ABAminus. DFGout structures are predominantly in the BBAminus conformation, which is essentially required for binding type II inhibitors. The inactive conformations have specific features that make them unable to bind ATP, magnesium, and/or substrates. Our structurally intuitive nomenclature will aid in understanding the conformational dynamics of kinases and structure-based development of kinase drugs.

Structural and dynamical description of the enzymatic reaction of a phosphohexomutase

Enzymes are known to adopt various conformations at different points along their catalytic cycles. Here, we present a comprehensive analysis of 15 isomorphous, high resolution crystal structures of the enzyme phosphoglucomutase from the bacterium Xanthomonas citri. The protein was captured in distinct states critical to function, including enzyme-substrate, enzyme-product, and enzyme-intermediate complexes. Key residues in ligand recognition and regions undergoing conformational change are identified and correlated with the various steps of the catalytic reaction. In addition, we use principal component analysis to examine various subsets of these structures with two goals: (1) identifying sites of conformational heterogeneity through a comparison of room temperature and cryogenic structures of the apo-enzyme and (2) a priori clustering of the enzyme-ligand complexes into functionally related groups, showing sensitivity of this method to structural features difficult to detect by traditional methods. This study captures, in a single system, the structural basis of diverse substrate recognition, the subtle impact of covalent modification, and the role of ligand-induced conformational change in this representative enzyme of the α-D-phosphohexomutase superfamily.

Enhanced dynamics of conformationally heterogeneous T7 bacteriophage lysozyme native state attenuates its stability and activity

Proteins are dynamic in nature and exist in a set of equilibrium conformations on various timescale motions. The flexibility of proteins governs various biological functions, and therefore elucidation of such functional dynamics is essential. In this context, we have studied the structure–dynamics–stability–activity relationship of bacteriophage T7 lysozyme/endolysin (T7L) native-state ensemble in the pH range of 6–8. Our studies established that T7L native state is conformationally heterogeneous, as several residues of its C-terminal half are present in two conformations (major and minor) in the slow exchange time scale of nuclear magnetic resonance (NMR). Structural and dynamic studies suggested that the residues belonging to minor conformations do exhibit native-like structural and dynamic features. Furthermore, the NMR relaxation experiments unraveled that the native state is highly dynamic and the dynamic behavior is regulated by the pH, as the pH 6 conformation exhibited enhanced dynamics compared with pH 7 and 8. The stability measurements and cell-based activity studies on T7L indicated that the native protein at pH 6 is ∼2 kcal less stable and is ∼50% less active than those of pH 7 and 8. A comprehensive analysis of the T7L active site, unfolding initiation sites and the residues with altered dynamics outlined that the attenuation of stability and activity is a resultant of its enhanced dynamic properties, which, in turn, can be attributed to the protonation/deprotonation of its partially buried His residues. Our study on T7L structure–dynamics–activity paradigm could assist in engineering novel amidase-based endolysins with enhanced activity and stability over a broad pH range.

Journey to the center of the protein: allostery from multitemperature multiconformer X-ray crystallography

Proteins inherently fluctuate between conformations to perform functions in the cell. For example, they sample product-binding, transition-state-stabilizing and product-release states during catalysis, and they integrate signals from remote regions of the structure for allosteric regulation. However, there is a lack of understanding of how these dynamic processes occur at the basic atomic level. This gap can be at least partially addressed by combining variable-temperature (instead of traditional cryogenic temperature) X-ray crystallography with algorithms for modeling alternative conformations based on electron-density maps, in an approach called multitemperature multiconformer X-ray crystallography (MMX). Here, the use of MMX to reveal alternative conformations at different sites in a protein structure and to estimate the degree of energetic coupling between them is discussed. These insights can suggest testable hypotheses about allosteric mechanisms. Temperature is an easily manipulated experimental parameter, so the MMX approach is widely applicable to any protein that yields well diffracting crystals. Moreover, the general principles of MMX are extensible to other perturbations such as pH, pressure, ligand concentration etc. Future work will explore strategies for leveraging X-ray data across such perturbation series to more quantitatively measure how different parts of a protein structure are coupled to each other, and the consequences thereof for allostery and other aspects of protein function.

Biophysical Characterization of a Disabled Double Mutant of Soybean Lipoxygenase: The "Undoing" of Precise Substrate Positioning Relative to Metal Cofactor and an Identified Dynamical Network

Soybean lipoxygenase (SLO) has served as a prototype for understanding the molecular origin of enzymatic rate accelerations. The double mutant (DM) L546A/L754A is considered a dramatic outlier, due to the unprecedented size and near temperature-independence of its primary kinetic isotope effect, low catalytic efficiency, and elevated enthalpy of activation. To uncover the physical basis of these features, we herein apply three structural probes: hydrogen-deuterium exchange mass spectrometry, room-temperature X-ray crystallography and EPR spectroscopy on four SLO variants (wild-type (WT) enzyme, DM, and the two parental single mutants, L546A and L754A). DM is found to incorporate features of each parent, with the perturbation at position 546 predominantly influencing thermally activated motions that connect the active site to a protein-solvent interface, while mutation at position 754 disrupts the ligand field and solvation near the cofactor iron. However, the expanded active site in DM leads to more active site water molecules and their associated hydrogen bond network, and the individual features from L546A and L754A alone cannot explain the aggregate kinetic properties for DM. Using recently published QM/MM-derived ground-state SLO-substrate complexes for WT and DM, together with the thorough structural analyses presented herein, we propose that the impairment of DM is the combined result of a repositioning of the reactive carbon of linoleic acid substrate with regard to both the iron cofactor and a catalytically linked dynamic region of protein.

qFit-ligand Reveals Widespread Conformational Heterogeneity of Drug-Like Molecules in X-Ray Electron Density Maps

Proteins and ligands sample a conformational ensemble that governs molecular recognition, activity, and dissociation. In structure-based drug design, access to this conformational ensemble is critical to understand the balance between entropy and enthalpy in lead optimization. However, ligand conformational heterogeneity is currently severely underreported in crystal structures in the Protein Data Bank, owing in part to a lack of automated and unbiased procedures to model an ensemble of protein-ligand states into X-ray data. Here, we designed a computational method, qFit-ligand, to automatically resolve conformationally averaged ligand heterogeneity in crystal structures, and applied it to a large set of protein receptor-ligand complexes. In an analysis of the cancer related BRD4 domain, we found that up to 29% of protein crystal structures bound with drug-like molecules present evidence of unmodeled, averaged, relatively isoenergetic conformations in ligand-receptor interactions. In many retrospective cases, these alternate conformations were adventitiously exploited to guide compound design, resulting in improved potency or selectivity. Combining qFit-ligand with high-throughput screening or multitemperature crystallography could therefore augment the structure-based drug design toolbox.

Structural basis for the bi-functionality of human oxaloacetate decarboxylase FAHD1

Whereas enzymes in the fumarylacetoacetate hydrolase (FAH) superfamily catalyze several distinct chemical reactions, the structural basis for their multi-functionality remains elusive. As a well-studied example, human FAH domain-containing protein 1 (FAHD1) is a mitochondrial protein displaying both acylpyruvate hydrolase (ApH) and oxaloacetate decarboxylase (ODx) activity. As mitochondrial ODx, FAHD1 acts antagonistically to pyruvate carboxylase, a key metabolic enzyme. Despite its importance for mitochondrial function, very little is known about the catalytic mechanisms underlying FAHD1 enzymatic activities, and the architecture of its ligated active site is currently ill defined. We present crystallographic data of human FAHD1 that provide new insights into the structure of the catalytic center at high resolution, featuring a flexible 'lid'-like helical region which folds into a helical structure upon binding of the ODx inhibitor oxalate. The oxalate-driven structural transition results in the generation of a potential catalytic triad consisting of E33, H30 and an associated water molecule. In silico docking studies indicate that the substrate is further stabilized by a complex hydrogen-bond network, involving amino acids Q109 and K123, identified herein as potential key residues for FAHD1 catalytic activity. Mutation of amino acids H30, E33 and K123 each had discernible influence on the ApH and/or ODx activity of FAHD1, suggesting distinct catalytic mechanisms for both activities. The structural analysis presented here provides a defined structural map of the active site of FAHD1 and contributes to a better understanding of the FAH superfamily of enzymes.

A Multi-model Approach to Assessing Local and Global Cryo-EM Map Quality

There does not currently exist a standardized indicator of how well cryo-EM-derived models represent the density from which they were generated. We present a straightforward methodology that utilizes freely available tools to generate a suite of independent models and to evaluate their convergence in an EM density. These analyses provide both a quantitative and qualitative assessment of the precision of the models and their representation of the density, respectively, while concurrently providing a platform for assessing both global and local EM map quality. We further use standardized datasets to provide an expected deviation within a suite of models refined against EM maps reported to be at 5 Å resolution or better. Associating multiple atomic models with a deposited EM map provides a rapid and accessible reporter of convergence, a strong indicator of highly resolved molecular detail, and is an important step toward an FSC-independent assessment of map and model quality.

Predicting allostery and microbial drug resistance with molecular simulations

Beta-lactamase enzymes mediate the most common forms of gram-negative antibiotic resistance affecting clinical treatment. They also constitute an excellent model system for the difficult problem of understanding how allosteric mutations can augment catalytic activity of already-competent enzymes. Multiple allosteric mutations have been identified that alter catalytic activity or drug-resistance spectrum in class A beta lactamases, but predicting these in advance continues to be challenging. Here, we review computational techniques based on structure and/or molecular simulation to predict such mutations. Structure-based techniques have been particularly helpful in developing graph algorithms for analyzing critical residues in beta-lactamase function, while classical molecular simulation has recently shown the ability to prospectively predict allosteric mutations increasing beta-lactamase activity and drug resistance. These will ultimately achieve the greatest power when combined with simulation methods that model reactive chemistry to calculate activation free energies directly.

An expanded allosteric network in PTP1B by multitemperature crystallography, fragment screening, and covalent tethering

Allostery is an inherent feature of proteins, but it remains challenging to reveal the mechanisms by which allosteric signals propagate. A clearer understanding of this intrinsic circuitry would afford new opportunities to modulate protein function. Here, we have identified allosteric sites in protein tyrosine phosphatase 1B (PTP1B) by combining multiple-temperature X-ray crystallography experiments and structure determination from hundreds of individual small-molecule fragment soaks. New modeling approaches reveal 'hidden' low-occupancy conformational states for protein and ligands. Our results converge on allosteric sites that are conformationally coupled to the active-site WPD loop and are hotspots for fragment binding. Targeting one of these sites with covalently tethered molecules or mutations allosterically inhibits enzyme activity. Overall, this work demonstrates how the ensemble nature of macromolecular structure, revealed here by multitemperature crystallography, can elucidate allosteric mechanisms and open new doors for long-range control of protein function.

Proteins perform many important jobs in each of the cells in our bodies, such as transporting other molecules and helping chemical reactions to occur. The part of the protein directly involved in these tasks is called the active site. Other areas of the protein can communicate with the active site to switch the protein on or off. This method of control is known as allostery.

Switching proteins on and off could help us to develop treatments for certain diseases. For example, a protein called PTP1B reduces how well cells can respond to insulin. Switching this protein off could therefore help to treat diabetes. However, much like it’s hard to guess how a light switch is wired to a light bulb without seeing behind the walls, it is hard to predict which remote areas of a protein are ‘wired’ to the active site.

Keedy, Hill et al. have now used two complementary methods to examine the structure of PTP1B and find new allosteric sites. The first method captured a series of X-ray images from crystallized molecules of the protein held at different temperatures. This revealed areas of PTP1B that can move like windshield wipers to communicate with each other. The second method soaked PTP1B crystals in trays with hundreds of drug-sized molecules and assessed which sites on the protein the molecules bound to. The molecules generally bound to just a few sites of the protein. Further tests on one of these sites showed that it can communicate with the active site to turn the protein on or off.

Further work will be needed to develop drugs that could treat diabetes by binding to the newly identified allosteric sites in PTP1B. More generally, the methods developed by Keedy, Hill et al. could be used to study allostery in other important proteins.