Biology subjects

van den Bedem, H.

Publications and source records attributed to van den Bedem, H..

10 recordsLinked to original sources

bioRxiv2024

Expanding Automated Multiconformer Ligand Modeling to Macrocycles and Fragments

Small molecule ligands exhibit a diverse range of conformations in solution. Upon binding to a target protein, this conformational diversity is reduced. However, ligands can retain some degree of conformational flexibility even when bound to a receptor. In the Protein Data Bank (PDB), a small number of ligands have been modeled with distinct alternative conformations that are supported by macromolecular X-ray crystallography density maps. However, the vast majority of structural models are fit to a single ligand conformation, potentially ignoring the underlying conformational heterogeneity present in the sample. We previously developed qFit-ligand to sample diverse ligand conformations and to select a parsimonious ensemble consistent with the density. While this approach indicated that many ligands populate alternative conformations, limitations in our sampling procedures often resulted in non-physical conformations and could not model complex ligands like macrocycles. Here, we introduce several improvements to qFit-ligand, including integrating RDKit for stochastic conformational sampling. This new sampling method greatly enriches low energy conformations of small molecules and macrocycles. We further extended qFit-ligand to identify alternative conformations in PanDDA-modified density maps from high throughput X-ray fragment screening experiments, as well as single-particle cryo-electron microscopy (cryo-EM) density maps. The new version of qFit-ligand improves fit to electron density and reduces torsional strain relative to deposited single conformer models and our prior version of qFit-ligand. These advances enhance the analysis of residual conformational heterogeneity present in ligand-bound structures, which can provide important insights for the rational design of therapeutic agents.

biophysics↗

bioRxiv2023

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 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.

biophysics↗

bioRxiv2023

Discovery of a cryptic pocket in the AI-predicted structure of PPM1D phosphatase explains the binding site and potency of its allosteric inhibitors

Virtual screening is a widely used tool for drug discovery, but its predictive power can vary dramatically depending on how much structural data is available. In the best case, crystal structures of a ligand-bound protein can help find more potent ligands. However, virtual screens tend to be less predictive when only ligand-free crystal structures are available, and even less predictive if a homology model or other predicted structure must be used. Here, we explore the possibility that this situation can be improved by better accounting for protein dynamics, as simulations started from a single structure have a reasonable chance of sampling nearby structures that are more compatible with ligand binding. As a specific example, we consider the cancer drug target PPM1D/Wip1 phosphatase, a protein that lacks crystal structures. High-throughput screens have led to the discovery of several allosteric inhibitors of PPM1D, but their binding mode remains unknown. To enable further drug discovery efforts, we assessed the predictive power of an AlphaFold-predicted structure of PPM1D and a Markov state model (MSM) built from molecular dynamics simulations initiated from that structure. Our simulations reveal a cryptic pocket at the interface between two important structural elements, the flap and hinge regions. Using deep learning to predict the pose quality of each docked compound for the active site and cryptic pocket suggests that the inhibitors strongly prefer binding to the cryptic pocket, consistent with their allosteric effect. The predicted affinities for the dynamically uncovered cryptic pocket also recapitulate the relative potencies of the compounds ({tau}b=0.70) better than the predicted affinities for the static AlphaFold-predicted structure ({tau}b=0.42). Taken together, these results suggest that targeting the cryptic pocket is a good strategy for drugging PPM1D and, more generally, that conformations selected from simulation can improve virtual screening when limited structural data is available.

biophysics↗

bioRxiv2021

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 decrease 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 NMR 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.

biophysics↗

bioRxiv2021

Reproducibility of protein X-ray diffuse scattering and potential utility for modeling atomic displacement parameters

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.

biophysics↗

bioRxiv2020

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.

biophysics↗

bioRxiv2019

Comparing serial X-ray crystallography and microcrystal electron diffraction (MicroED) as methods for routine structure determination from small macromolecular crystals

Innovative new crystallographic methods are facilitating structural studies from ever smaller crystals of biological macromolecules. In particular, serial X-ray crystallography and microcrystal electron diffraction (MicroED) have emerged as useful methods for obtaining structural information from crystals on the nanometer to micron scale. Despite the utility of these methods, their implementation can often be difficult, as they present many challenges not encountered in traditional macromolecular crystallography experiments. Here, we describe XFEL serial crystallography experiments and MicroED experiments using batch-grown microcrystals of the enzyme cyclophilin A (CypA). Our results provide a roadmap for researchers hoping to design macromolecular microcrystallography experiments, and they highlight the strengths and weaknesses of the two methods. Specifically, we focus on how the different physical conditions imposed by the sample preparation and delivery methods required for each type of experiment effect the crystal structure of the enzyme.

biophysics↗

bioRxiv2019

Cysteine modification can gate non-equilibrium conformational dynamics during enzyme catalysis

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 enzymes 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.

biochemistry↗

bioRxiv2019

Molecular recognition of M1-linked ubiquitin chains by native and phosphorylated UBAN domains

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.

biophysics↗

bioRxiv2018

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. 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.

biophysics↗