The HADDOCK2.4 web server for integrative modeling of biomolecular complexes.

Interactions between macromolecules, such as proteins and nucleic acids, are essential for cellular functions. Experimental methods can fail to provide all the information required to fully model biomolecular complexes at atomic resolution, particularly for large and heterogeneous assemblies. Integrative computational approaches have, therefore, gained popularity, complementing traditional experimental methods in structural biology. Here, we introduce HADDOCK2.4, an integrative modeling platform, and its updated web interface ( https://wenmr.science.uu.nl/haddock2.4 ). The platform seamlessly integrates diverse experimental and theoretical data to generate high-quality models of macromolecular complexes. The user-friendly web server offers automated parameter settings, access to distributed computing resources, and pre- and post-processing steps that enhance the user experience. To present the web server's various interfaces and features, we demonstrate two different applications: (i) we predict the structure of an antibody-antigen complex by using NMR data for the antigen and knowledge of the hypervariable loops for the antibody, and (ii) we perform coarse-grained modeling of PRC1 with a nucleosome particle guided by mutagenesis and functional data. The described protocols require some basic familiarity with molecular modeling and the Linux command shell. This new version of our widely used HADDOCK web server allows structural biologists and non-experts to explore intricate macromolecular assemblies encompassing various molecule types.

Structural basis for recognition of N-formyl peptides as pathogen-associated molecular patterns.

The formyl peptide receptor 1 (FPR1) is primarily responsible for detection of short peptides bearing N-formylated methionine (fMet) that are characteristic of protein synthesis in bacteria and mitochondria. As a result, FPR1 is critical to phagocyte migration and activation in bacterial infection, tissue injury and inflammation. How FPR1 distinguishes between formyl peptides and non-formyl peptides remains elusive. Here we report cryo-EM structures of human FPR1-Gi protein complex bound to S. aureus-derived peptide fMet-Ile-Phe-Leu (fMIFL) and E. coli-derived peptide fMet-Leu-Phe (fMLF). Both structures of FPR1 adopt an active conformation and exhibit a binding pocket containing the R2015.38XXXR2055.42 (RGIIR) motif for formyl group interaction and receptor activation. This motif works together with D1063.33 for hydrogen bond formation with the N-formyl group and with fMet, a model supported by MD simulation and functional assays of mutant receptors with key residues for recognition substituted by alanine. The cryo-EM model of agonist-bound FPR1 provides a structural basis for recognition of bacteria-derived chemotactic peptides with potential applications in developing FPR1-targeting agents.

Structural basis for isoform-specific inhibition of human CTPS1.

Cytidine triphosphate synthase 1 (CTPS1) is necessary for an effective immune response, as revealed by severe immunodeficiency in CTPS1-deficient individuals [E. Martin et al], [Nature] [510], [288-292] ([2014]). CTPS1 expression is up-regulated in activated lymphocytes to expand CTP pools [E. Martin et al], [Nature] [510], [288-292] ([2014]), satisfying increased demand for nucleic acid and lipid synthesis [L. D. Fairbanks, M. Bofill, K. Ruckemann, H. A. Simmonds], [J. Biol. Chem. ] [270], [29682-29689] ([1995]). Demand for CTP in other tissues is met by the CTPS2 isoform and nucleoside salvage pathways [E. Martin et al], [Nature] [510], [288-292] ([2014]). Selective inhibition of the proliferative CTPS1 isoform is therefore desirable in the treatment of immune disorders and lymphocyte cancers, but little is known about differences in regulation of the isoforms or mechanisms of known inhibitors. We show that CTP regulates both isoforms by binding in two sites that clash with substrates. CTPS1 is less sensitive to CTP feedback inhibition, consistent with its role in increasing CTP levels in proliferation. We also characterize recently reported small-molecule inhibitors, both CTPS1 selective and nonselective. Cryo-electron microscopy (cryo-EM) structures reveal these inhibitors mimic CTP binding in one inhibitory site, where a single amino acid substitution explains selectivity for CTPS1. The inhibitors bind to CTPS assembled into large-scale filaments, which for CTPS1 normally represents a hyperactive form of the enzyme [E. M. Lynch et al], [Nat. Struct. Mol. Biol.] [24], [507-514] ([2017]). This highlights the utility of cryo-EM in drug discovery, particularly for cases in which targets form large multimeric assemblies not amenable to structure determination by other techniques. Both inhibitors also inhibit the proliferation of human primary T cells. The mechanisms of selective inhibition of CTPS1 lay the foundation for the design of immunosuppressive therapies.

Macromolecular refinement of X-ray and cryoelectron microscopy structures with Phenix/OPLS3e for improved structure and ligand quality.

With the advent of the resolution revolution in cryoelectron microscopy (cryo-EM), low-resolution refinement is common, and likewise increases the need for a reliable force field. Here, we report on the incorporation of the OPLS3e force field with the VSGB2.1 solvation model in the structure determination package Phenix. Our results show significantly improved structure quality and reduced ligand strain at lower resolution for X-ray refinement. For refinement of cryo-EM-based structures, we find comparable quality structures, goodness-of-fit, and reduced ligand strain. We also show how structure quality and ligand strain are related to the map-model cross-correlation as a function of data weight, and how that can detect overfitting. Signs of overfitting are found in over half of our cryo-EM dataset, which can be remedied by a re-refinement at a lower data weight. Finally, a start-to-end script for refining structures with Phenix/OPLS3e is available in the Schrödinger 2020-3 distribution.

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.

Synthetic group A streptogramin antibiotics that overcome Vat resistance.

Natural products serve as chemical blueprints for most antibiotics in clinical use. The evolutionary process by which these molecules arise is inherently accompanied by the co-evolution of resistance mechanisms that shorten the clinical lifetime of any given class of antibiotics1. Virginiamycin acetyltransferase (Vat) enzymes are resistance proteins that provide protection against streptogramins2, potent antibiotics against Gram-positive bacteria that inhibit the bacterial ribosome3. Owing to the challenge of selectively modifying the chemically complex, 23-membered macrocyclic scaffold of group A streptogramins, analogues that overcome the resistance conferred by Vat enzymes have not been previously developed2. Here we report the design, synthesis, and antibacterial evaluation of group A streptogramin antibiotics with extensive structural variability. Using cryo-electron microscopy and forcefield-based refinement, we characterize the binding of eight analogues to the bacterial ribosome at high resolution, revealing binding interactions that extend into the peptidyl tRNA-binding site and towards synergistic binders that occupy the nascent peptide exit tunnel. One of these analogues has excellent activity against several streptogramin-resistant strains of Staphylococcus aureus, exhibits decreased rates of acetylation in vitro, and is effective at lowering bacterial load in a mouse model of infection. Our results demonstrate that the combination of rational design and modular chemical synthesis can revitalize classes of antibiotics that are limited by naturally arising resistance mechanisms.

GemSpot: A Pipeline for Robust Modeling of Ligands into Cryo-EM Maps.

Producing an accurate atomic model of biomolecule-ligand interactions from maps generated by cryoelectron microscopy (cryo-EM) often presents challenges inherent to the methodology and the dynamic nature of ligand binding. Here, we present GemSpot, an automated pipeline of computational chemistry methods that take into account EM map potentials, quantum mechanics energy calculations, and water molecule site prediction to generate candidate poses and provide a measure of the degree of confidence. The pipeline is validated through several published cryo-EM structures of complexes in different resolution ranges and various types of ligands. In all cases, at least one identified pose produced both excellent interactions with the target and agreement with the map. GemSpot will be valuable for the robust identification of ligand poses and drug discovery efforts through cryo-EM.

Protein-Protein Modeling Using Cryo-EM Restraints.

Recent improvements in cryo-electron microscopy (cryo-EM) in the past few years are now allowing to observe molecular complexes at atomic resolution. As a consequence, numerous structures derived from cryo-EM are now available in the Protein Data Bank. However, if for some complexes atomic resolution is reached, this is not true for all. This is also the case in cryo-electron tomography where the achievable resolution is still limited. Furthermore the resolution in a cryo-EM map is not a constant, with often outer regions being of lower resolution, possibly linked to conformational variability. Although those low- to medium-resolution EM maps (or regions thereof) cannot directly provide atomic structure of large molecular complexes, they provide valuable information to model the individual components and their assembly into them. Most approaches for this kind of modeling are performing rigid fitting of the individual components into the EM density map. While this would appear an obvious option, they ignore key aspects of molecular recognition, the energetics and flexibility of the interfaces. Moreover, this often restricts the modeling to a unique source of data, the EM density map.In this chapter, we describe a protocol where an EM map is used as restraint in HADDOCK to guide the modeling process. In the first step, rigid-body fitting is performed with PowerFit in order to identify the most likely locations of the molecules into the map. These are then used as centroids to which distance restraints are defined from the center of mass of the components of the complex for the initial rigid-body docking. The EM density is then directly used as an additional restraint energy term, which can be combined with all the other types of data supported by HADDOCK. This protocol relies on the new version 2.4 of both the HADDOCK webserver and software. Preparation steps consisting of cropping the EM map and rigid-body fitting of the atomic structure are explained. Then, the EM-driven docking protocol using HADDOCK is illustrated.

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 of GM-CSF and IL-2 sequestration by the viral decoy receptor GIF.

Subversion of the host immune system by viruses is often mediated by molecular decoys that sequester host proteins pivotal to mounting effective immune responses. The widespread mammalian pathogen parapox Orf virus deploys GIF, a member of the poxvirus immune evasion superfamily, to antagonize GM-CSF (granulocyte macrophage colony-stimulating factor) and IL-2 (interleukin-2), two pleiotropic cytokines of the mammalian immune system. However, structural and mechanistic insights into the unprecedented functional duality of GIF have remained elusive. Here we reveal that GIF employs a dimeric binding platform that sequesters two copies of its target cytokines with high affinity and slow dissociation kinetics to yield distinct complexes featuring mutually exclusive interaction footprints. We illustrate how GIF serves as a competitive decoy receptor by leveraging binding hotspots underlying the cognate receptor interactions of GM-CSF and IL-2, without sharing any structural similarity with the cytokine receptors. Our findings contribute to the tracing of novel molecular mimicry mechanisms employed by pathogenic viruses.

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment.

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. Proteins 2016; 84(Suppl 1):323-348. © 2016 Wiley Periodicals, Inc.

Probing a cell-embedded megadalton protein complex by DNP-supported solid-state NMR.

Studying biomolecules at atomic resolution in their native environment is the ultimate aim of structural biology. We investigated the bacterial type IV secretion system core complex (T4SScc) by cellular dynamic nuclear polarization-based solid-state nuclear magnetic resonance spectroscopy to validate a structural model previously generated by combining in vitro and in silico data. Our results indicate that T4SScc is well folded in the cellular setting, revealing protein regions that had been elusive when studied in vitro.

Integrative Modeling of Biomolecular Complexes: HADDOCKing with Cryo-Electron Microscopy Data.

Protein-protein interactions play a central role in all cellular processes. Insight into their atomic architecture is therefore of paramount importance. Cryo-electron microscopy (cryo-EM) is capable of directly imaging large macromolecular complexes. Unfortunately, the resolution is usually not sufficient for a direct atomic interpretation. To overcome this, cryo-EM data are often combined with high-resolution atomic structures. However, current computational approaches typically do not include information from other experimental sources nor a proper physico-chemical description of the interfaces. Here we describe the integration of cryo-EM data into our data-driven docking program HADDOCK and its performance on a benchmark of 17 complexes. The approach is demonstrated on five systems using experimental cryo-EM data in the range of 8.5-21 Å resolution. For several cases, cryo-EM data are integrated with additional interface information, e.g. mutagenesis and hydroxyl radical footprinting data. The resulting models have high-quality interfaces, revealing novel details of the interactions.

Modeling protein-protein complexes using the HADDOCK webserver "modeling protein complexes with HADDOCK".

Protein-protein interactions lie at the heart of most cellular processes. Determining their high-resolution structures by experimental methods is a nontrivial task, which is why complementary computational approaches have been developed over the years. To gain structural and dynamical insight on an atomic scale in these interactions, computational modeling must often be complemented by low-resolution experimental information. For this purpose, we developed the user-friendly HADDOCK webserver, the interface to our biomolecular docking program, which can make use of a variety of low-resolution data to drive the docking process. In this chapter, we explain the use of the HADDOCK webserver based on the real-life Lys48-linked di-ubiquitin case, which led to the 2BGF PDB model. We demonstrate the use of chemical shift perturbation data in combination with residual dipolar couplings and further highlight a few other cases where our software was successfully used. The HADDOCK webserver is available to the science community for free at haddock.science.uu.nl/services/HADDOCK.

IR spectroscopy of isolated neutral and protonated adenine and 9-methyladenine.

IR spectroscopy is employed to study isolated adenine and its derivative 9-methyladenine in both their neutral and protonated forms. The IR spectra of neutral adenine and 9-methyladenine are measured in a molecular beam expansion via IR-UV ion-dip spectroscopy in the 525 to 1750 cm(-1) region. For adenine, UV excitation selects the 9H tautomer to give a conformer-selective IR spectrum. For 9-methyladenine, only one tautomer exists because of the methyl substitution at the N(9) position. The experimental spectra agree closely with spectra computed for these tautomers at the B3LYP/6-311++G(df,pd) level of theory. These spectra complement previous tautomer-specific IR spectra in the hydrogen stretching range. The 9H-adenine spectrum obtained is compared to a previously recorded FTIR spectrum of adenine at 280 °C, which shows close agreement, although the 7H tautomer cannot be excluded from contributing. Protonated adenine and 9-methyladenine are generated by electrospray ionization and studied via IR multiple-photon dissociation (IRMPD) spectroscopy. Comparison of the experimental spectra with computed spectra allows identification of the protonation site, which suggests that the 1-9 tautomer is the dominant contributor to the spectra.