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Structure-based, virtual High Throughput Screening (vHTS) methods for predicting ligand activity in drug discovery are important when there are no or relatively few known compounds that interact with a therapeutic target of interest. State-of-the-art computational vHTS necessarily relies on effective methods for pose sampling and docking to generate an accurate affinity score from the docked poses. However, proteins are dynamic; in vivo, ligands bind to a conformational ensemble. In silico docking to the single conformation represented by a crystal structure can adversely affect the pose quality. Here we introduce AtomNet PoseRanker, a graph convolutional network trained to identify, and re-rank crystal-like ligand poses from a sampled ensemble of protein conformations and ligand poses. In contrast to conventional vHTS methods that incorporate receptor flexibility, a deep learning approach can internalize valid cognate and non-cognate binding modes corresponding to distinct receptor conformations. AtomNet PoseRanker significantly enriched pose quality in docking to cognate and non-cognate receptors of the PDBbind v2019 dataset. Improved pose rankings that better represent experimentally observed ligand binding modes improve hit rates in vHTS campaigns, and thereby advance computational drug discovery, especially for novel therapeutic targets or novel binding sites.

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.Proteins are the workhorses of our cells. They are large molecules that ‘fold’ into specific, often highly complex, three-dimensional configurations. These structures are not static, but rather dynamic and flexible. In other words, proteins can shift between different three-dimensional shapes to perform their tasks within the cell. To perform their roles, many proteins have to bind to small molecule ligands. Many ligands are drugs, which means that their effectiveness depends on their ability to bind to and impact the proteins involved in the disease they are treating. When a ligand binds to a protein, it can reshape the protein. For example, certain conformations of the protein, which were difficult for the protein to be in on its own, may become more stable when the ligand binds. Additionally, upon ligand binding, some parts of the protein may move relative to each other. Previous studies have shown that these movements can affect the interaction between ligand and protein. However, these studies only examined a small number of proteins. Therefore, Wankowicz et al. set out to determine, in greater detail, what happens to protein flexibility upon ligand binding. First, a pipeline was created to model alternative configurations of the protein both with and without ligands attached. These models measured flexibility within protein structures. The models revealed that when ligands bind to proteins, the flexibility of different regions of the protein changes – and does so in a consistent way. Proteins that become more rigid in the region interacting with their ligands become less rigid in other, distant regions, and vice versa. In other words, the rest of the protein is able to compensate for any changes in flexibility caused by ligand binding, which may contribute to how well a ligand binds to a protein. This study demonstrates the ability of ligands to affect the entire structure of the proteins they bind to, and therefore sheds new light on the role of proteins’ innate conformational flexibility during this process. These results will contribute to our understanding of how the ligands and proteins involved in different cellular processes interact with each other – and, potentially, how these interactions can be manipulated.

Protein structure and dynamics can be probed using X-ray crystallography. Whereas the Bragg peaks are only sensitive to the average unit-cell electron density, the signal between the Bragg peaks -- diffuse scattering -- is sensitive to spatial correlations in electron-density variations. Although diffuse scattering contains valuable information about protein dynamics, the diffuse signal is more difficult to isolate from the background compared to the Bragg signal, and the reproducibility of diffuse signal is not yet well understood. We present a systematic study of the reproducibility of diffuse scattering from isocyanide hydratase (ICH) in three different protein forms. Both replicate diffuse datasets and datasets obtained from different mutants were similar in pairwise comparisons (Pearson correlation coefficient (CC) ≥0.8). The data were processed in a manner inspired by previously published methods using custom software with modular design, enabling us to perform an analysis of various data processing choices to determine how to obtain the highest quality data as assessed using unbiased measures of symmetry and reproducibility. The diffuse data then were used to characterize atomic mobility using a liquid-like motions (LLM) model. This characterization was able to discriminate between distinct anisotropic atomic displacement parameter (ADP) models arising from different anisotropic scaling choices that agreed comparably with the Bragg data. Our results emphasize the importance of data reproducibility as a model-free measure of diffuse data quality, illustrate the ability of LLM analysis of diffuse scattering to select among alternative ADP models, and offer insights into the design of successful diffuse scattering experiments.

Summary ParagraphProtein dynamics play an important role in enzyme catalysis1-4. Many enzymes form covalent catalytic intermediates that can alter enzyme structure and conformational dynamics5,6. How these changes in enzyme structure and dynamics facilitate passage along the reaction coordinate is a fundamental unanswered question in structural enzymology. Here, we use Mix-and-Inject Serial Femtosecond X-ray Crystallography (MISC) at an X-ray Free Electron Laser (XFEL)7-10, ambient temperature X-ray crystallography, computer simulations, and enzyme kinetics to characterize how covalent modification of the active site cysteine residue in isocyanide hydratase (ICH) alters the enzyme’s conformational ensemble throughout the catalytic cycle. With MISC, we directly observe formation of a thioimidate covalent intermediate during ICH catalysis. The intermediate exhibits changes in the active site electrostatic environment, disrupting a hydrogen bond and triggering a cascade of conformational changes in ICH. X-ray-induced formation of a cysteine-sulfenic acid at the catalytic nucleophile (Cys101-SOH) with conventional crystallography at ambient temperature induces similar conformational shifts, demonstrating that these enzyme motions result from cysteine modification. Computer simulations show how cysteine modification-gated structural changes allosterically propagate through the ICH dimer. Mutations at Gly150 that modulate helical mobility reduce ICH catalytic turnover and alter its pre-steady state kinetic behavior, establishing that helical mobility is important for ICH catalytic efficiency. Taken together, our results demonstrate the potential of mix-and-inject XFEL crystallography to capture otherwise elusive mechanistic details of enzyme catalysis and dynamics from microcrystalline samples7,11. This approach can connect conformational dynamics to function for the large class of systems that rely on covalently modified cysteine residues for catalysis or regulation, resolving long-standing questions about enzyme mechanism and functionally relevant non-equilibrium enzyme motions.

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.

Proteins exist as conformational ensembles, exchanging between substates to perform their function. Advances in experimental techniques yield unprecedented access to structural snapshots of their conformational landscape. However, computationally modeling how proteins use collective motions to transition between substates is challenging owing to a rugged landscape and large energy barriers. Here, we present a new, robotics-inspired motion planning procedure called dCC-RRT that navigates the rugged landscape between substates by introducing dynamic, interatomic constraints to modulate frustration. The constraints balance non-native contacts and flexibility, and instantaneously redirect the motion towards sterically favorable conformations. On a test set of eight proteins determined in two conformations separated by, on average, 7.5A root mean square deviation (RMSD), our pathways reduced the Cα atom RMSD to the goal conformation by 78%, outperforming peer methods. We then applied dCC-RRT to examine how collective, small-scale motions of four side-chains in the active site of cyclophilin A propagate through the protein. dCC-RRT uncovered a spatially contiguous network of residues linked by steric interactions and collective motion connecting the active site to a recently proposed, non-canonical capsid binding site 25A away, rationalizing NMR and multi-temperature crystallography experiments. In all, dCC-RRT can reveal detailed, all-atom molecular mechanisms for small and large amplitude motions. Source code and binaries are freely available at https://github.com/ExcitedStates/KGS/. This article is protected by copyright. All rights reserved.

The prevalence of neurodegenerative disorders is rapidly increasing. While Alzheimer's disease and dementia generally correlate with longer lifespans, neurodegenerative disorders like chronic traumatic encephalopathy often affect individuals at young age. Historically, the underlying disease mechanisms of these chronic disorders—the slowly changing biochemical composition during aging and the repeated, rapidly changing biomechanical environment during head impact—have been viewed as distinct events. Recent studies suggest that Alzheimer's disease and chronic traumatic encephalopathy share common degenerative pathways on the molecular and cellular levels. Here we examine this current trend and explore the molecular, cellular, tissue, and organ level mechanisms of neurodegeneration through the lens of biomedical engineering. Understanding the underlying disease mechanisms across the spatio-temporal scales of neurodegeneration provides new opportunities to modulate, slow down, and possibly revert molecular dysfunction, axonal death, tissue atrophy, and loss of brain function.

Permselective nanochannels are ubiquitous in biological systems, controlling ion transport and maintaining a potential difference across a cell surface. Surface layers (S-layers) are proteinaceous, generally charged lattices punctuated with nanoscale pores that form the outermost cell envelope component of virtually all archaea and many bacteria. Ammonia oxidizing archaea (AOA) obtain their energy exclusively from oxidizing ammonia directly below the S-layer lattice, but how the charged surfaces and nanochannels affect availability of NH4+ at the reaction site is unknown. Here, we examine the electrochemical properties of negatively charged S-layers for asymmetrically forced ion transport governed by Michaelis–Menten kinetics at ultralow concentrations. Our 3-dimensional electrodiffusion reaction simulations revealed that a negatively charged S-layer can invert the potential across the nanochannel to favor chemically forced NH4+ transport, analogous to polarity switching in nanofluidic field-effect transi...

Significance Helicobacter pylori infects nearly half of the world’s population and is the primary cause of various gastric diseases. It has evolved various virulence factors to aid its host colonization and infection, including the vacuolating cytotoxin A (VacA) that is responsible for the pathogenesis of H. pylori-related diseases. Here, we resolve multiple structures of the water-soluble VacA oligomeric assemblies using cryoelectron microscopy (cryo-EM) at near-atomic resolution. These studies suggest a model of structural changes of functional VacA hexamer needed for the pore-formation process across the membrane and highlight the capability of cryo-EM to resolve multiple structure snapshots from a single specimen at near-atomic resolution., Human gastric pathogen Helicobacter pylori (H. pylori) is the primary risk factor for gastric cancer and is one of the most prevalent carcinogenic infectious agents. Vacuolating cytotoxin A (VacA) is a key virulence factor secreted by H. pylori and induces multiple cellular responses. Although structural and functional studies of VacA have been extensively performed, the high-resolution structure of a full-length VacA protomer and the molecular basis of its oligomerization are still unknown. Here, we use cryoelectron microscopy to resolve 10 structures of VacA assemblies, including monolayer (hexamer and heptamer) and bilayer (dodecamer, tridecamer, and tetradecamer) oligomers. The models of the 88-kDa full-length VacA protomer derived from the near-atomic resolution maps are highly conserved among different oligomers and show a continuous right-handed β-helix made up of two domains with extensive domain–domain interactions. The specific interactions between adjacent protomers in the same layer stabilizing the oligomers are well resolved. For double-layer oligomers, we found short- and/or long-range hydrophobic interactions between protomers across the two layers. Our structures and other previous observations lead to a mechanistic model wherein VacA hexamer would correspond to the prepore-forming state, and the N-terminal region of VacA responsible for the membrane insertion would undergo a large conformational change to bring the hydrophobic transmembrane region to the center of the oligomer for the membrane channel formation.

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.

Although the Ub-binding domain in ABIN proteins and NEMO (UBAN) is highly conserved, UBAN-containing proteins exhibit different Ub-binding properties, resulting in their diverse biological roles. Post-translational modifications further control UBAN domain specificity for poly-Ub chains. However, precisely, how the UBAN domain structurally confers such functional diversity remains poorly understood. Here we report crystal structures of ABIN-1 alone and in complex with one or two M1-linked di-Ub chains. ABIN-1 UBAN forms a homo-dimer that provides two symmetrical Ub-binding sites on either side of the coiled-coil structure. Moreover, crystal structures of ABIN1 UBAN in complex with di-Ub chains reveal a concentration-dependency of UBAN/di-Ub binding stoichiometry. Analysis of UBAN/M1-linked di-Ub binding characteristics indicates that phosphorylated S473 in OPTN and its corresponding phospho-mimetic residue in ABIN-1 (E484) are essential for high affinity interactions with M1-linked Ub chains. Also, a phospho-mimetic mutation of A303 in NEMO, corresponding to S473 of OPTN, increases binding affinity for M1-linked Ub chains. These findings are in line with the diverse physiological roles of UBAN domains, as phosphorylation of OPTN UBAN is required to enhance its binding to Ub during mitophagy.

© 2016 Nature America, Inc. All rights reserved. Challenges in determining the structures of heterogeneous and dynamic protein complexes have greatly hampered past efforts to obtain a mechanistic understanding of many important biological processes. One such process is chaperone-assisted protein folding. Obtaining structural ensembles of chaperone-substrate complexes would ultimately reveal how chaperones help proteins fold into their native state. To address this problem, we devised a new structural biology approach based on X-ray crystallography, termed residual electron and anomalous density (READ). READ enabled us to visualize even sparsely populated conformations of the substrate protein immunity protein 7 (Im7) in complex with the Escherichia coli chaperone Spy, and to capture a series of snapshots depicting the various folding states of Im7 bound to Spy. The ensemble shows that Spy-associated Im7 samples conformations ranging from unfolded to partially folded to native-like states and reveals how a substrate can explore its folding landscape while being bound to a chaperone.

G protein-coupled receptors (GPCRs) act as conduits in the plasma membrane, facilitating cellular responses to physiological events by activating intracellular signal transduction pathways. Extracellular signaling molecules can induce conformational changes in GPCR, which allow it to selectively activate intracellular protein partners such as heterotrimeric protein G. However, a major unsolved problem is how GPCRs and G proteins form complexes and how their interaction results in G protein activation. Here, we show that an inactive, agonist-free β2AR:Gαs complex can collectively sample intermediate states of the receptor on an activation pathway. An in silico conformational ensemble around the inactive state manifests significant conformational coupling between structural elements implicated in G protein activation throughout the complex. While Gαs helix α5 has received much attention as a driver for nucleotide exchange, we also observe interactions between helix αN with Intra Cellular Loop 2, which can be transmitted by β1 to facilitate nucleotide exchange by disrupting a salt bridge between the P-loop and Switch I. These interactions are moderated in an active state ensemble. Collectively, our results support an alternative view of G protein activation, in which precoupling can allosterically modulate an agonist-free receptor. Subsequent selective agonist recruitment would result in collective activation of the complex. This alternative view can help us understand how distinct extracellular binding partners result in different but interdependent signaling pathways, with broad implications for GPCR drug discovery.

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 multi-temperature crystallography could therefore augment the structure-based drug design toolbox.

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Surface layers (S-layers) are two-dimensional, proteinaceous, porous lattices that form the outermost cell envelope component of virtually all archaea and many bacteria. Despite exceptional sequence diversity, S-layer proteins (SLPs) share important characteristics such as their ability to form crystalline sheets punctuated with nano-scale pores, and their propensity for charged amino acids, leading to acidic or basic isoelectric points. However, the precise function of S-layers, or the role of charged SLPs and how they relate to cellular metabolism is unknown. Nano-scale lattices affect the diffusion behavior of low-concentration solutes, even if they are significantly smaller than the pore size. Here, we offer a rationale for charged S-layer proteins in the context of the structural evolution of S-layers. Using the ammonia-oxidizing archaea (AOA) as a model for S-layer geometry, and a 2D electrodiffusion reaction computational framework to simulate diffusion and consumption of the charged solute ammonium (NH(4)(+)), we find that the characteristic length scales of nanoporous S-layers elevate the concentration of NH(4)(+) in the pseudo-periplasmic space. Our simulations suggest an evolutionary, mechanistic basis for S-layer charge and shed light on the unique ability of some AOA to oxidize ammonia in environments with nanomolar NH(4)(+) availability, with broad implications for comparisons of ecologically distinct populations.

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. We found that up to 29 % of a dataset 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 multi-temperature crystallography could therefore augment the structure-based drug design toolbox.

Motivation Non-coding ribonucleic acids (ncRNA) are functional RNA molecules that are not translated into protein. They are extremely dynamic, adopting diverse conformational substates, which enables them to modulate their interaction with a large number of other molecules. The flexibility of ncRNA provides a challenge for probing their complex 3D conformational landscape, both experimentally and computationally. Results Despite their conformational diversity, ncRNAs mostly preserve their secondary structure throughout the dynamic ensemble. Here we present a kinematics-based procedure to morph an RNA molecule between conformational substates, while avoiding inter-atomic clashes. We represent an RNA as a kinematic linkage, with fixed groups of atoms as rigid bodies and rotatable bonds as degrees of freedom. Our procedure maintains RNA secondary structure by treating hydrogen bonds between base pairs as constraints. The constraints define a lower-dimensional, secondary-structure constraint manifold in conformation space, where motions are largely governed by molecular junctions of unpaired nucleotides. On a large benchmark set, we show that our morphing procedure compares favorably to peer algorithms, and can approach goal conformations to within a low all-atom RMSD by directing fewer than 1% of its atoms. Our results suggest that molecular junctions can modulate 3D structural rearrangements, while secondary structure elements guide large parts of the molecule along the transition to the correct final conformation. Availability and Implementation The source code, binaries and data are available at https://simtk.org/home/kgs. Supplementary information Supplementary data are available at Bioinformatics online.

Proteins exist as conformational ensembles, exchanging between substates to perform their function. Advances in experimental techniques yield unprecedented access to structural snapshots of their conformational landscape. However, computationally modeling how proteins use collective motions to transition between substates is challenging owing to a rugged landscape and large energy barriers. Here, we present a new, robotics-inspired motion planning procedure called dCC-RRT that navigates the rugged landscape between substates by introducing dynamic, interatomic constraints to modulate frustration. The constraints balance non-native contacts and flexibility, and instantaneously redirect the motion towards sterically favorable conformations. On a test set of eight proteins determined in two conformations separated by, on average, 7.5 Å root mean square deviation (RMSD), our pathways reduced the Cα atom RMSD to the goal conformation by 78%, outperforming peer methods. We then applied dCC-RRT to examine how collective, small-scale motions of four side-chains in the active site of cyclophilin A propagate through the protein. dCC-RRT uncovered a spatially contiguous network of residues linked by steric interactions and collective motion connecting the active site to a recently proposed, non-canonical capsid binding site 25 Å away, rationalizing NMR and multi-temperature crystallography experiments. In all, dCC-RRT can reveal detailed, all-atom molecular mechanisms for small and large amplitude motions. Source code and binaries are freely available at https://github.com/ExcitedStates/KGS/.

Knowledge of the molecular ecology and environmental determinants of ammonia-oxidizing organisms is critical to understanding and predicting the global nitrogen (N) and carbon cycles, but an incomplete biochemical picture hinders in vitro studies of N-cycling enzymes. Although an integrative structural and dynamic characterization at the atomic scale would advance our understanding of function tremendously, structural knowledge of key N-cycling enzymes from ecologically relevant ammonia oxidizers is unfortunately extremely limited. Here, we discuss the challenges and opportunities for examining the ecology of ammonia-oxidizing organisms, particularly uncultivated Thaumarchaeota, through (meta)genome-driven structural biology of the enzymes ammonia monooxygenase (AMO) and nitrite reductase (NirK).

The conformational variation of three different proteins as a function of dose is examined at 278 and 100 K., Protein crystallography data collection at synchrotrons is routinely carried out at cryogenic temperatures to mitigate radiation damage. Although damage still takes place at 100 K and below, the immobilization of free radicals increases the lifetime of the crystals by approximately 100-fold. Recent studies have shown that flash-cooling decreases the heterogeneity of the conformational ensemble and can hide important functional mechanisms from observation. These discoveries have motivated increasing numbers of experiments to be carried out at room temperature. However, the trade-offs between increased risk of radiation damage and increased observation of alternative conformations at room temperature relative to cryogenic temperature have not been examined. A considerable amount of effort has previously been spent studying radiation damage at cryo-temperatures, but the relevance of these studies to room temperature diffraction is not well understood. Here, the effects of radiation damage on the conformational landscapes of three different proteins (T. danielli thaumatin, hen egg-white lysozyme and human cyclo­philin A) at room (278 K) and cryogenic (100 K) temperatures are investigated. Increasingly damaged datasets were collected at each temperature, up to a maximum dose of the order of 107 Gy at 100 K and 105 Gy at 278 K. Although it was not possible to discern a clear trend between damage and multiple conformations at either temperature, it was observed that disorder, monitored by B-factor-dependent crystallographic order parameters, increased with higher absorbed dose for the three proteins at 100 K. At 278 K, however, the total increase in this disorder was only statistically significant for thaumatin. A correlation between specific radiation damage affecting side chains and the amount of disorder was not observed. This analysis suggests that elevated conformational heterogeneity in crystal structures at room temperature is observed despite radiation damage, and not as a result thereof.