Flexibility and Design: Conformational Heterogeneity along the Evolutionary Trajectory of a Redesigned Ubiquitin

VIPER: Virus Inhibition Via Peptide Engineering and Receptor Mimicry

A key step in most viral infections is the binding of a viral protein to a host receptor, leading to the virus entering the host cell. Disrupting this protein-protein interaction is an effective strategy for preventing infection and subsequent disease. Building on recent advances in computational tools for structural biology, we introduce Virus Inhibition via Peptide Engineering and Receptor Mimicry (VIPER), a novel approach for the automatic derivation and optimization of biomimetic decoy peptides that mimic binding sites of human proteins. VIPER leverages structural data from human-pathogen protein complexes, yielding peptides that can competitively inhibit viral entry by mimicking the natural receptor. We computationally validated VIPER using molecular dynamics simulations and showcased its applicability on three clinically relevant viruses, highlighting its potential to accelerate therapeutic development. With a focus on reproducibility and extensibility, VIPER can facilitate the rapid development of antiviral inhibitors by automating the design and optimization of biomimetic compounds.

Structure-Based Experimental Datasets for Benchmarking Protein Simulation Force Fields [Article v0.1]

This review article provides an overview of structurally oriented experimental datasets that can be used to benchmark protein force fields, focusing on data generated by nuclear magnetic resonance (NMR) spectroscopy and room temperature (RT) protein crystallography. We discuss what the observables are, what they tell us about structure and dynamics, what makes them useful for assessing force field accuracy, and how they can be connected to molecular dynamics simulations carried out using the force field one wishes to benchmark. We also touch on statistical issues that arise when comparing simulations with experiment. We hope this article will be particularly useful to computational researchers and trainees who develop, benchmark, or use protein force fields for molecular simulations.

Ensemble-function relationships: From qualitative to quantitative relationships between protein structure and function

Structure-function relationships are deeply rooted in modern biochemistry and structural biology and have provided the basis for our understanding of how protein structure defines function. While structure-function relationships continue to provide invaluable qualitative information, they cannot, in principle, provide the quantitative information ultimately needed to fully understand how proteins function and to make quantitative predictions about changes in activity from changes in sequence and structure. These limitations appear to arise from fundamental principles of physics, which dictate that proteins exist as interchanging ensembles of conformations, rather than as static structures that underly conventional structure-function relationships. This perspective discusses the concept of ensemble-function relationships as quantitative relationships that build on and extend traditional structure-function relationships. The concepts of free energy landscapes and conformational ensembles and their application to proteins are reviewed. The perspective summarizes a range of approaches that can provide conformational ensemble information and focuses on X-ray crystallography methods for obtaining experimental protein conformational ensembles. Focusing on enzymes as archetypes of protein function, recent literature examples are reviewed that used ensemble-function relationships to understand how protein residues contribute to function and how changes in protein sequence and structure impact activity, leading to new models and providing previously inaccessible mechanistic insights. Potential applications of conformational ensembles and ensemble-function relationships to protein design are examined. The perspective concludes with current limitations of the ensemble-function relationships and potential paths forward toward the next generation of quantitative ensemble-function models.

Ubiquitin's Conformational Heterogeneity as Discerned by Nuclear Magnetic Resonance Spectroscopy

Visualizing a protein's molecular motions has been a long standing topic of research in the biophysics community. Largely this has been done by exploiting nuclear magnetic resonance spectroscopy (NMR), and arguably no protein's molecular motions have been better characterized by NMR than that of ubiquitin (Ub), a 76 amino acid polypeptide essential in ubiquitination-a key regulatory system within cells. Herein, we discuss ubiquitin's conformational plasticity as visualized, at atomic resolution, by more than 35 years of NMR work. In our discussions we point out the differences between data acquired in vitro, ex vivo, as well as in vivo and stress the need to investigate Ub's conformational plasticity in more biologically representative backgrounds.

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.

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.

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.

Structural and functional characterization of USP47 reveals a hot spot for inhibitor design

USP47 is widely involved in tumor development, metastasis, and other processes while performing a more regulatory role in inflammatory responses, myocardial infarction, and neuronal development. In this study, we investigate the functional and biochemical properties of USP47, whereby depleting USP47 inhibited cancer cell growth in a p53-dependent manner-a phenomenon that enhances during the simultaneous knockdown of USP7. Full-length USP47 shows higher deubiquitinase activity than the catalytic domain. The crystal structures of the catalytic domain, in its free and ubiquitin-bound states, reveal that the misaligned catalytic triads, ultimately, become aligned upon ubiquitin-binding, similar to USP7, thereby becoming ready for catalysis. Yet, the composition and lengths of BL1, BL2, and BL3 of USP47 differ from those for USP7, and they contribute to the observed selectivity. Our study provides molecular details of USP47 regulation, substrate recognition, and the hotspots for drug discovery by targeting USP47.

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.

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.

C-N Bond Forming Radical Rebound Is the Enantioselectivity-Determining Step in P411-Catalyzed Enantioselective C(sp3)-H Amination: A Combined Computational and Experimental Investigation

Engineered metalloenzymes represent promising catalysts for stereoselective C-H functionalization reactions. Recently, P450 enzymes have been evolved to allow for new-to-nature intramolecular C(sp3)-H amination reactions via a nitrene transfer mechanism, giving rise to diamine derivatives with excellent enantiocontrol. To shed light on the origin of enantioselectivity, a combined computational and experimental study was carried out. Hybrid quantum mechanics/molecular mechanics calculations were performed to investigate the activation energies and enantioselectivities of both the hydrogen atom transfer (HAT) and the subsequent C-N bond forming radical rebound steps. Contrary to previously hypothesized enantioinduction mechanisms, our calculations show that the radical rebound step is enantioselectivity-determining, whereas the preceding HAT step is only moderately stereoselective. Furthermore, the selectivity in the initial HAT is ablated by rapid conformational change of the radical intermediate prior to C-N bond formation. This finding is corroborated by our experimental study using a set of enantiomerically pure, monodeuterated substrates. Furthermore, classical and ab initio molecular dynamics simulations were carried out to investigate the conformational flexibility of the carbon-centered radical intermediate. This key radical species undergoes a facile conformational change in the enzyme active site from the pro-(R) to the pro-(S) configuration, whereas the radical rebound is slower due to the spin-state change and ring strain of the cyclization process, thereby allowing stereoablative C-N bond formation. Together, these studies revealed an underappreciated enantioinduction mechanism in biocatalytic C(sp3)-H functionalizations involving radical intermediates, opening up new avenues for the development of other challenging asymmetric C(sp3)-H functionalizations.

New insights into the molecular mechanisms of glutaminase C inhibitors in cancer cells using serial room temperature crystallography

Cancer cells frequently exhibit uncoupling of the glycolytic pathway from the TCA cycle (i.e. the "Warburg effect"), and as a result, often become dependent on their ability to increase glutamine catabolism. The mitochondrial enzyme Glutaminase C (GAC) helps to satisfy this 'glutamine addiction' of cancer cells by catalyzing the hydrolysis of glutamine to glutamate, which is then converted to the TCA-cycle intermediate α-ketoglutarate. This makes GAC an intriguing drug target, and spurred the molecules derived from bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl)ethyl sulfide (the so-called BPTES-class of allosteric GAC inhibitors), including CB-839, which is currently in clinal trials. However, none of the drugs targeting GAC are yet approved for cancer treatment and their mechanism of action is not well understood. Here, we shed new light on the underlying basis for the differential potencies exhibited by members of the BPTES/CB-839 family of compounds, which could not previously be explained with standard cryo-cooled X-ray crystal structures of GAC bound to CB-839 or its analogs. Using an emerging technique known as serial room temperature crystallography, we were able to observe clear differences between the binding conformations of inhibitors with significantly different potencies. We also developed a computational model to further elucidate the molecular basis of differential inhibitor potency. We then corroborated the results from our modeling efforts using recently established fluorescence assays that directly read out inhibitor binding to GAC. Together, these findings should aid in future design of more potent GAC inhibitors with better clinical outlook.

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.

Ensemble-based enzyme design can recapitulate the effects of laboratory directed evolution in silico

The creation of artificial enzymes is a key objective of computational protein design. Although de novo enzymes have been successfully designed, these exhibit low catalytic efficiencies, requiring directed evolution to improve activity. Here, we use room-temperature X-ray crystallography to study changes in the conformational ensemble during evolution of the designed Kemp eliminase HG3 (k_cat/K_M 146 M⁻¹s⁻¹). We observe that catalytic residues are increasingly rigidified, the active site becomes better pre-organized, and its entrance is widened. Based on these observations, we engineer HG4, an efficient biocatalyst (k_cat/K_M 103,000 M⁻¹s⁻¹) containing key first and second-shell mutations found during evolution. HG4 structures reveal that its active site is pre-organized and rigidified for efficient catalysis. Our results show how directed evolution circumvents challenges inherent to enzyme design by shifting conformational ensembles to favor catalytically-productive sub-states, and suggest improvements to the design methodology that incorporate ensemble modeling of crystallographic data.

Kemp eliminases are artificial enzymes that catalyze the concerted deprotonation and ring-opening of benzisoxazoles. Here, the authors use room-temperature X-ray crystallography to investigate changes to the conformational ensemble of the Kemp eliminase HG3 along a directed evolutionary trajectory, and develop an experimentally guided, ensemble-based computational enzyme design procedure.

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.

Origin of conformational dynamics in a globular protein

Protein structures are dynamic, undergoing motions that can play a vital role in function. However, the link between primary sequence and conformational dynamics remains poorly understood. Here, we studied how conformational dynamics can arise in a globular protein by evaluating the impact of individual core-residue substitutions in DANCER-3, a streptococcal protein G domain β1 variant that we previously designed to undergo a specific mode of conformational exchange that has never been observed in the wild-type protein. Using a combination of solution NMR experiments and molecular dynamics simulations, we demonstrate that only two mutations are necessary to create this conformational exchange, and that these mutations work synergistically, with one destabilizing the native structure and the other allowing two new conformational states to be accessed on the energy landscape. Overall, our results show how dynamics can appear in a stable globular fold, a critical step in the molecular evolution of dynamics-linked functions.

Temperature-jump solution X-ray scattering reveals distinct motions in a dynamic enzyme

Correlated motions of proteins are critical to function, but these features are difficult to resolve using traditional structure determination techniques. Time-resolved X-ray methods hold promise for addressing this challenge, but have relied on the exploitation of exotic protein photoactivity, and are therefore not generalizable. Temperature jumps, through thermal excitation of the solvent, have been utilized to study protein dynamics using spectroscopic techniques, but their implementation in X-ray scattering experiments has been limited. Here, we perform temperature-jump small- and wide-angle X-ray scattering measurements on a dynamic enzyme, cyclophilin A, demonstrating that these experiments are able to capture functional intramolecular protein dynamics on the microsecond timescale. We show that cyclophilin A displays rich dynamics following a temperature jump, and use the resulting time-resolved signal to assess the kinetics of conformational changes. Two relaxation processes are resolved: a fast process is related to surface loop motions, and a slower process is related to motions in the core of the protein that are critical for catalytic turnover.

Room Temperature X-Ray Crystallography Reveals Conformational Heterogeneity of Engineered Proteins

In this issue of Structure, Biel et al. (2017) present multi-conformer analyses from room temperature X-ray data of two ubiquitin phage display variants binding deubiquitinase USP7. The first contains core mutations. The second matured variant contains additional surface mutations. Alternate conformations detected in the core mutant were removed by maturation.

Directed Evolution Mimics Allosteric Activation by Stepwise Tuning of the Conformational Ensemble

Allosteric enzymes contain a wealth of catalytic diversity that remains distinctly underutilized for biocatalysis. Tryptophan synthase is a model allosteric system and a valuable enzyme for the synthesis of noncanonical amino acids (ncAA). Previously, we evolved the β-subunit from Pyrococcus furiosus, PfTrpB, for ncAA synthase activity in the absence of its native partner protein PfTrpA. However, the precise mechanism by which mutation activated TrpB to afford a stand-alone catalyst remained enigmatic. Here, we show that directed evolution caused a gradual change in the rate-limiting step of the catalytic cycle. Concomitantly, the steady-state distribution of the intermediates shifts to favor covalently bound Trp adducts, which have increased thermodynamic stability. The biochemical properties of these evolved, stand-alone TrpBs converge on those induced in the native system by allosteric activation. High-resolution crystal structures of the wild-type enzyme, an intermediate in the lineage, and the final variant, encompassing five distinct chemical states, show that activating mutations have only minor structural effects on their immediate environment. Instead, mutation stabilizes the large-scale motion of a subdomain to favor an otherwise transiently populated closed conformational state. This increase in stability enabled the first structural description of Trp covalently bound in a catalytically active TrpB, confirming key features of catalysis. These data combine to show that sophisticated models of allostery are not a prerequisite to recapitulating its complex effects via directed evolution, opening the way to engineering stand-alone versions of diverse allosteric enzymes.

A Comprehensive Analysis of Anion-Quadrupole Interactions in Protein Structures

The edgewise interactions of anions with phenylalanine (Phe) aromatic rings in proteins, known as anion-quadrupole interactions, have been well studied. However, the anion-quadrupole interactions of the tyrosine (Tyr) and tryptophan (Trp) rings have been less well studied, probably because these have been considered weaker than interactions of anions hydrogen bonded to Trp/Tyr side chains. Distinguishing such hydrogen bonding interactions, we comprehensively surveyed the edgewise interactions of certain anions (aspartate, glutamate, and phosphate) with Trp, Tyr, and Phe rings in high-resolution, nonredundant protein single chains and interfaces (protein-protein, DNA/RNA-protein, and membrane-protein). Trp/Tyr anion-quadrupole interactions are common, with Trp showing the highest propensity and average interaction energy for this type of interaction. The energy of an anion-quadrupole interaction (-15.0 to 0.0 kcal/mol, based on quantum mechanical calculations) depends not only on the interaction geometry but also on the ring atom. The phosphate anions at DNA/RNA-protein interfaces interact with aromatic residues with energies comparable to that of aspartate/glutamate anion-quadrupole interactions. At DNA-protein interfaces, the frequency of aromatic ring participation in anion-quadrupole interactions is comparable to that of positive charge participation in salt bridges, suggesting an underappreciated role for anion-quadrupole interactions at DNA-protein (or membrane-protein) interfaces. Although less frequent than salt bridges in single-chain proteins, we observed highly conserved anion-quadrupole interactions in the structures of remote homologues, and evolutionary covariance-based residue contact score predictions suggest that conserved anion-quadrupole interacting pairs, like salt bridges, contribute to polypeptide folding, stability, and recognition.