Homology-based loop modeling yields more complete crystallographic protein structures

JBP1 and JBP3 have conserved structures but different affinity to base-J

Base-J (β-D-glucopyranosyloxymethyluracil) is an unusual kinetoplastid-specific DNA modification, recognized by base-J containing DNA (J-DNA) binding proteins JBP1 and JBP3. Recognition of J-DNA by both JBP1 and JBP3 takes place by a conserved J-DNA binding domain (JDBD). Here we show that JDBD-JBP3 has about 1,000-fold weaker affinity to base-J than JDBD-JBP1 and discriminates between J-DNA and unmodified DNA with a factor ∼5, whereas JDBD-JBP1 discriminates with a factor ∼10,000. Comparison of the crystal structures of JDBD-JBP3 we present here, with that of the previously characterized JDBD-JBP1, shows a flexible α5-helix that lacks a positively charged patch in JBP3. Mutations removing this positive charge in JDBD-JBP1, resulted in decreased binding affinity relative to wild-type JDBD-JBP1, indicating this patch is involved in DNA binding. We suggest that the α5-helix might rearrange upon JBP1 binding to J-DNA stabilizing the complex. This work contributes to our understanding of how JBPs bind to this unique DNA modification, which may contribute to identifying potential drug targets to end the base-J dependent parasite life cycle.

Identifying and avoiding radiation damage in macromolecular crystallography

Radiation damage remains one of the major impediments to accurate structure solution in macromolecular crystallography. The artefacts of radiation damage can manifest as structural changes that result in incorrect biological interpretations being drawn from a model, they can reduce the resolution to which data can be collected and they can even prevent structure solution entirely. In this article, we discuss how to identify and mitigate against the effects of radiation damage at each stage in the macromolecular crystal structure-solution pipeline.

Caskin2 is a novel talin- and Abi1-binding protein that promotes cell motility

Talin (herein referring collectively to talin 1 and 2) couples the actomyosin cytoskeleton to integrins and transmits tension to the extracellular matrix. Talin also interacts with numerous additional proteins capable of modulating the actin-integrin linkage and thus downstream mechanosignaling cascades. Here, we demonstrate that the scaffold protein Caskin2 interacts directly with the R8 domain of talin through its C-terminal LD motif. Caskin2 also associates with the WAVE regulatory complex to promote cell migration in an Abi1-dependent manner. Furthermore, we demonstrate that the Caskin2-Abi1 interaction is regulated by growth factor-induced phosphorylation of Caskin2 on serine 878. In MCF7 and UACC893 cells, which contain an amplification of CASKIN2, Caskin2 localizes in plasma membrane-associated plaques and around focal adhesions in cortical microtubule stabilization complexes. Taken together, our results identify Caskin2 as a novel talin-binding protein that might not only connect integrin-mediated adhesion to actin polymerization but could also play a role in crosstalk between integrins and microtubules.

AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination

Artificial intelligence-based protein structure prediction methods such as AlphaFold have revolutionized structural biology. The accuracies of these predictions vary, however, and they do not take into account ligands, covalent modifications or other environmental factors. Here, we evaluate how well AlphaFold predictions can be expected to describe the structure of a protein by comparing predictions directly with experimental crystallographic maps. In many cases, AlphaFold predictions matched experimental maps remarkably closely. In other cases, even very high-confidence predictions differed from experimental maps on a global scale through distortion and domain orientation, and on a local scale in backbone and side-chain conformation. We suggest considering AlphaFold predictions as exceptionally useful hypotheses. We further suggest that it is important to consider the confidence in prediction when interpreting AlphaFold predictions and to carry out experimental structure determination to verify structural details, particularly those that involve interactions not included in the prediction.

Neutron crystallographic refinement with REFMAC5 from the CCP4 suite

Hydrogen (H) atoms are abundant in macromolecules and often play critical roles in enzyme catalysis, ligand-recognition processes and protein-protein interactions. However, their direct visualization by diffraction techniques is challenging. Macromolecular X-ray crystallography affords the localization of only the most ordered H atoms at (sub-)atomic resolution (around 1.2 Å or higher). However, many H atoms of biochemical significance remain undetectable by this method. In contrast, neutron diffraction methods enable the visualization of most H atoms, typically in the form of deuterium (2H) atoms, at much more common resolution values (better than 2.5 Å). Thus, neutron crystallography, although technically demanding, is often the method of choice when direct information on protonation states is sought. REFMAC5 from the Collaborative Computational Project No. 4 (CCP4) is a program for the refinement of macromolecular models against X-ray crystallographic and cryo-EM data. This contribution describes its extension to include the refinement of structural models obtained from neutron crystallographic data. Stereochemical restraints with accurate bond distances between H atoms and their parent atom nuclei are now part of the CCP4 Monomer Library, the source of prior chemical information used in the refinement. One new feature for neutron data analysis in REFMAC5 is refinement of the protium/deuterium (1H/2H) fraction. This parameter describes the relative 1H/2H contribution to neutron scattering for hydrogen isotopes. The newly developed REFMAC5 algorithms were tested by performing the (re-)refinement of several entries available in the PDB and of one novel structure (FutA) using either (i) neutron data only or (ii) neutron data supplemented by external restraints to a reference X-ray crystallographic structure. Re-refinement with REFMAC5 afforded models characterized by R-factor values that are consistent with, and in some cases better than, the originally deposited values. The use of external reference structure restraints during refinement has been observed to be a valuable strategy, especially for structures at medium-low resolution.

Analysis and validation of overall N-glycan conformation in Privateer

The oligosaccharides in N-glycosylation provide key structural and functional contributions to a glycoprotein. These contributions are dependent on the composition and overall conformation of the glycans. The Privateer software allows structural biologists to evaluate and improve the atomic structures of carbohydrates, including N-glycans; this software has recently been extended to check glycan composition through the use of glycomics data. Here, a broadening of the scope of the software to analyse and validate the overall conformation of N-glycans is presented, focusing on a newly compiled set of glycosidic linkage torsional preferences harvested from a curated set of glycoprotein models.

IDPConformerGenerator: A Flexible Software Suite for Sampling the Conformational Space of Disordered Protein States

The power of structural information for informing biological mechanisms is clear for stable folded macromolecules, but similar structure-function insight is more difficult to obtain for highly dynamic systems such as intrinsically disordered proteins (IDPs) which must be described as structural ensembles. Here, we present IDPConformerGenerator, a flexible, modular open-source software platform for generating large and diverse ensembles of disordered protein states that builds conformers that obey geometric, steric, and other physical restraints on the input sequence. IDPConformerGenerator samples backbone phi (φ), psi (ψ), and omega (ω) torsion angles of relevant sequence fragments from loops and secondary structure elements extracted from folded protein structures in the RCSB Protein Data Bank and builds side chains from robust Monte Carlo algorithms using expanded rotamer libraries. IDPConformerGenerator has many user-defined options enabling variable fractional sampling of secondary structures, supports Bayesian models for assessing the agreement of IDP ensembles for consistency with experimental data, and introduces a machine learning approach to transform between internal and Cartesian coordinates with reduced error. IDPConformerGenerator will facilitate the characterization of disordered proteins to ultimately provide structural insights into these states that have key biological functions.

Phytochemical drug discovery for COVID-19 using high-resolution computational docking and machine learning assisted binder prediction

The COVID-19 pandemic has resulted in millions of deaths around the world. Multiple vaccines are in use, but there are many underserved locations that do not have adequate access to them. Variants may emerge that are highly resistant to existing vaccines, and therefore cheap and readily obtainable therapeutics are needed. Phytochemicals, or plant chemicals, can possibly be such therapeutics. Phytochemicals can be used in a polypharmacological approach, where multiple viral proteins are inhibited and escape mutations are made less likely. Finding the right phytochemicals for viral protein inhibition is challenging, but in-silico screening methods can make this a more tractable problem. In this study, we screen a wide range of natural drug products against a comprehensive set of SARS-CoV-2 proteins using a high-resolution computational workflow. This workflow consists of a structure-based virtual screening (SBVS), where an initial phytochemical library was docked against all selected protein structures. Subsequently, ligand-based virtual screening (LBVS) was employed, where chemical features of 34 lead compounds obtained from the SBVS were used to predict 53 lead compounds from a larger phytochemical library via supervised learning. A computational docking validation of the 53 predicted leads obtained from LBVS revealed that 28 of them elicit strong binding interactions with SARS-CoV-2 proteins. Thus, the inclusion of LBVS resulted in a 4-fold increase in the lead discovery rate. Of the total 62 leads, 18 showed promising pharmacokinetic properties in a computational ADME screening. Collectively, this study demonstrates the advantage of incorporating machine learning elements into a virtual screening workflow.Communicated by Ramaswamy H. Sarma.

The importance of residue-level filtering and the Top2018 best-parts dataset of high-quality protein residues

We have curated a high-quality, "best-parts" reference dataset of about 3 million protein residues in about 15,000 PDB-format coordinate files, each containing only residues with good electron density support for a physically acceptable model conformation. The resulting prefiltered data typically contain the entire core of each chain, in quite long continuous fragments. Each reference file is a single protein chain, and the total set of files were selected for low redundancy, high resolution, good MolProbity score, and other chain-level criteria. Then each residue was critically tested for adequate local map quality to firmly support its conformation, which must also be free of serious clashes or covalent-geometry outliers. The resulting Top2018 prefiltered datasets have been released on the Zenodo online web service and are freely available for all uses under a Creative Commons license. Currently, one dataset is residue filtered on main chain plus Cβ atoms, and a second dataset is full-residue filtered; each is available at four different sequence-identity levels. Here, we illustrate both statistics and examples that show the beneficial consequences of residue-level filtering. That process is necessary because even the best of structures contain a few highly disordered local regions with poor density and low-confidence conformations that should not be included in reference data. Therefore, the open distribution of these very large, prefiltered reference datasets constitutes a notable advance for structural bioinformatics and the fields that depend upon it.

New restraints and validation approaches for nucleic acid structures in PDB-REDO

The quality of macromolecular structure models crucially depends on refinement and validation targets, which optimally describe the expected chemistry. Commonly used software for these two procedures has been designed and developed in a protein-centric manner, resulting in relatively few established features for the refinement and validation of nucleic acid-containing structure models. Here, new nucleic acid-specific approaches implemented in PDB-REDO are described, including a new restraint model using noncovalent geometries (base-pair hydrogen bonding and base-pair stacking) as refinement targets. New validation routines are also presented, including a metric for Watson-Crick base-pair geometry normality (ZbpG). Applying the PDB-REDO pipeline with the new restraint model to the whole Protein Data Bank (PDB) demonstrates an overall positive effect on the quality of nucleic acid-containing structure models. Finally, we discuss examples of improvements in the geometry of specific nucleic acid structures in the PDB. The new PDB-REDO models and pipeline are available at https://pdb-redo.eu/.

Accurate Structure Prediction for Protein Loops Based on Molecular Dynamics Simulations with RSFF2C

Protein loops, connecting the α-helices and β-strands, are involved in many important biological processes. However, due to their conformational flexibility, it is still challenging to accurately determine three-dimensional (3D) structures of long loops experimentally and computationally. Herein, we present a systematic study of the protein loop structure prediction via a total of ∼850 μs molecular dynamics (MD) simulations. For a set of 15 long (10-16 residues) and solvent-exposed loops, we first evaluated the performance of four state-of-the-art loop modeling algorithms, DaReUS-Loop, Sphinx, Rosetta-NGK, and MODELLER, on each loop, and none of them could accurately predict the structures for most loops. Then, temperature replica exchange molecular dynamics (REMD) simulations were conducted with three recent force fields, RSFF2C with TIP3P water model, CHARMM36m with CHARMM-modified TIP3P, and AMBER ff19SB with OPC. We found that our recently developed residue-specific force field RSFF2C performed the best and successfully predicted 12 out of 15 loops with a root-mean-square deviation (RMSD) < 1.5 Å. As an alternative with lower computational cost, normal MD simulations at high temperatures (380, 500, and 620 K) were investigated. Temperature-dependent performance was observed for each force field, and, for RSFF2C+TIP3P, we found that three independent 100-ns MD simulations at 500 K gave comparable results with REMD simulations. These results suggest that MD simulations, especially with enhanced sampling techniques such as replica exchange, with the RSFF2C force field could be useful for accurate loop structure prediction.

Molecular Dynamics Simulations of Channelrhodopsin Chimera, C1C2

Molecular dynamics (MD) simulations have been successfully used for modeling dynamic behavior of biologically relevant systems, such as ion channels in representative environments to decode protein structure-function relationships. Protocol presented here describes steps for generating input files and modeling a monomer of transmembrane cation channel, channelrhodopsin chimera (C1C2), in representative environment of 1,2-dioleoyl-sn-glycero-3-phosphatidylcholine (DOPC) planar lipid bilayer, TIP3P water and ions (Na+ and Cl-) using molecular dynamics package NAMD, molecular graphics/analysis tool VMD, and other relevant tools. MD simulations of C1C2 were performed at 303.15 K and in constant particle number, isothermal-isobaric (NpT) ensemble. The results of modeling have helped understand how key interactions in the center of the C1C2 channel contribute to channel gating and subsequent solvent transport across the membrane.

LAHMA: structure analysis through local annotation of homology-matched amino acids

Comparison of homologous structure models is a key step in analyzing protein structure. With a wealth of homologous structures, comparison becomes a tedious process, and often only a small (user-biased) selection of data is used. A multitude of structural superposition algorithms are then typically used to visualize the structures together in 3D and to compare them. Here, the Local Annotation of Homology-Matched Amino acids (LAHMA) website (https://lahma.pdb-redo.eu) is presented, which compares any structure model with all of its close homologs from the PDB-REDO databank. LAHMA displays structural features in sequence space, allowing users to uncover differences between homologous structure models that can be analyzed for their relevance to chemistry or biology. LAHMA visualizes numerous structural features, also allowing one-click comparison of structure-quality plots (for example the Ramachandran plot) and `in-browser' structural visualization of 3D models.

Real-space quantum-based refinement for cryo-EM: Q|R#3

Electron cryo-microscopy (cryo-EM) is rapidly becoming a major competitor to X-ray crystallography, especially for large structures that are difficult or impossible to crystallize. While recent spectacular technological improvements have led to significantly higher resolution three-dimensional reconstructions, the average quality of cryo-EM maps is still at the low-resolution end of the range compared with crystallography. A long-standing challenge for atomic model refinement has been the production of stereochemically meaningful models for this resolution regime. Here, it is demonstrated that including accurate model geometry restraints derived from ab initio quantum-chemical calculations (HF-D3/6-31G) can improve the refinement of an example structure (chain A of PDB entry 3j63). The robustness of the procedure is tested for additional structures with up to 7000 atoms (PDB entry 3a5x and chain C of PDB entry 5fn5) using the less expensive semi-empirical (GFN1-xTB) model. The necessary algorithms enabling real-space quantum refinement have been implemented in the latest version of qr.refine and are described here.

A Global Ramachandran Score Identifies Protein Structures with Unlikely Stereochemistry

Ramachandran plots report the distribution of the (ϕ, ψ) torsion angles of the protein backbone and are one of the best quality metrics of experimental structure models. Typically, validation software reports the number of residues belonging to "outlier," "allowed," and "favored" regions. While "zero unexplained outliers" can be considered the current "gold standard," this can be misleading if deviations from expected distributions are not considered. We revisited the Ramachandran Z score (Rama-Z), a quality metric introduced more than two decades ago but underutilized. We describe a reimplementation of the Rama-Z score in the Computational Crystallography Toolbox along with an algorithm to estimate its uncertainty for individual models; final implementations are available in Phenix and PDB-REDO. We discuss the interpretation of the Rama-Z score and advocate including it in the validation reports provided by the Protein Data Bank. We also advocate reporting it alongside the outlier/allowed/favored counts in structural publications.

Fucosidases from the human gut symbiont Ruminococcus gnavus

The availability and repartition of fucosylated glycans within the gastrointestinal tract contributes to the adaptation of gut bacteria species to ecological niches. To access this source of nutrients, gut bacteria encode α-l-fucosidases (fucosidases) which catalyze the hydrolysis of terminal α-l-fucosidic linkages. We determined the substrate and linkage specificities of fucosidases from the human gut symbiont Ruminococcus gnavus. Sequence similarity network identified strain-specific fucosidases in R. gnavus ATCC 29149 and E1 strains that were further validated enzymatically against a range of defined oligosaccharides and glycoconjugates. Using a combination of glycan microarrays, mass spectrometry, isothermal titration calorimetry, crystallographic and saturation transfer difference NMR approaches, we identified a fucosidase with the capacity to recognize sialic acid-terminated fucosylated glycans (sialyl Lewis X/A epitopes) and hydrolyze α1–3/4 fucosyl linkages in these substrates without the need to remove sialic acid. Molecular dynamics simulation and docking showed that 3′-Sialyl Lewis X (sLeX) could be accommodated within the binding site of the enzyme. This specificity may contribute to the adaptation of R. gnavus strains to the infant and adult gut and has potential applications in diagnostic glycomic assays for diabetes and certain cancers.

The use of local structural similarity of distant homologues for crystallographic model building from a molecular-replacement solution

The performance of automated protein model building usually decreases with resolution, mainly owing to the lower information content of the experimental data. This calls for a more elaborate use of the available structural information about macromolecules. Here, a new method is presented that uses structural homologues to improve the quality of protein models automatically constructed using ARP/wARP. The method uses local structural similarity between deposited models and the model being built, and results in longer main-chain fragments that in turn can be more reliably docked to the protein sequence. The application of the homology-based model extension method to the example of a CFA synthase at 2.7 Å resolution resulted in a more complete model with almost all of the residues correctly built and docked to the sequence. The method was also evaluated on 1493 molecular-replacement solutions at a resolution of 4.0 Å and better that were submitted to the ARP/wARP web service for model building. A significant improvement in the completeness and sequence coverage of the built models has been observed.

Including crystallographic symmetry in quantum-based refinement: Q|R#2

Three-dimensional structure models refined using low-resolution data from crystallographic or electron cryo-microscopy experiments can benefit from high-quality restraints derived from quantum-chemical methods. However, nonperiodic atom-centered quantum-chemistry codes do not inherently account for nearest-neighbor interactions of crystallographic symmetry-related copies in a satisfactory way. Here, these nearest-neighbor effects have been included in the model by expanding to a super-cell and then truncating the super-cell to only include residues from neighboring cells that are interacting with the asymmetric unit. In this way, the fragmentation approach can adequately and efficiently include nearest-neighbor effects. It has previously been shown that a moderately sized X-ray structure can be treated using quantum methods if a fragmentation approach is applied. In this study, a target protein (PDB entry 4gif) was partitioned into a number of large fragments. The use of large fragments (typically hundreds of atoms) is tractable when a GPU-based package such as TeraChem is employed or cheaper (semi-empirical) methods are used. The QM calculations were run at the HF-D3/6-31G level. The models refined using a recently developed semi-empirical method (GFN2-xTB) were compared and contrasted. To validate the refinement procedure for a non-P1 structure, a standard set of crystallographic metrics were used. The robustness of the implementation is shown by refining 13 additional protein models across multiple space groups and a summary of the refinement metrics is presented.

Elucidation of a sialic acid metabolism pathway in mucus-foraging Ruminococcus gnavus unravels mechanisms of bacterial adaptation to the gut

Sialic acid (Neu5Ac) is commonly found in terminal location of colonic mucins glycans where it is a much-coveted nutrient for gut bacteria including Ruminococcus gnavus. R. gnavus is part of the healthy gut microbiota in humans but shows a disproportionate representation in diseases. There is therefore a need in understanding the molecular mechanisms underpinning its adaptation to the gut. Previous in vitro work demonstrated that R. gnavus mucin glycan-foraging strategy is strain-dependent and associated with the expression of an intramolecular trans-sialidase releasing 2,7-anhydro-Neu5Ac instead of Neu5Ac from mucins. Here, we have unravelled the metabolism pathway of 2,7-anhydro-Neu5Ac in R. gnavus which is underpinned by the exquisite specificity of the sialic transporter for 2,7-anhydro-Neu5Ac, and by the action of an oxidoreductase converting 2,7-anhydro-Neu5Ac into Neu5Ac which then becomes substrate of a Neu5Ac-specific aldolase. Having generated a R. gnavus nan cluster deletion mutant that lost the ability to grow on sialylated substrates, we showed that in gnotobiotic mice colonised with R. gnavus wild-type and mutant strains, the fitness of the nan mutant was significantly impaired with a reduced ability to colonise the mucus layer. Overall, our study revealed a unique sialic acid pathway in bacteria, with significant implications for the spatial adaptation of mucin-foraging gut symbionts in health and disease.

Autosomal Dominant Tubulointerstitial Kidney Disease with Adult Onset due to a Novel Renin Mutation Mapping in the Mature Protein

Autosomal dominant tubulointerstitial kidney disease (ADTKD) is a genetically heterogeneous renal disorder leading to progressive loss of renal function. ADTKD-REN is due to rare mutations in renin, all localized in the protein leader peptide and affecting its co-translational insertion in the endoplasmic reticulum (ER). Through exome sequencing in an adult-onset ADTKD family we identified a new renin variant, p.L381P, mapping in the mature protein. To assess its pathogenicity, we combined genetic data, computational and predictive analysis and functional studies. The L381P substitution affects an evolutionary conserved residue, co-segregates with renal disease, is not found in population databases and is predicted to be deleterious by in silico tools and by structural modelling. Expression of the L381P variant leads to its ER retention and induction of the Unfolded Protein Response in cell models and to defective pronephros development in zebrafish. Our work shows that REN mutations outside of renin leader peptide can cause ADTKD and delineates an adult form of ADTKD-REN, a condition which has usually its onset in childhood. This has implications for the molecular diagnosis and the estimated prevalence of the disease and points at ER homeostasis as a common pathway affected in ADTKD-REN, and possibly more generally in ADTKD.

Building and rebuilding N-glycans in protein structure models

N-Glycosylation is one of the most common post-translational modifications and is implicated in, for example, protein folding and interaction with ligands and receptors. N-Glycosylation trees are complex structures of linked carbohydrate residues attached to asparagine residues. While carbohydrates are typically modeled in protein structures, they are often incomplete or have the wrong chemistry. Here, new tools are presented to automatically rebuild existing glycosylation trees, to extend them where possible, and to add new glycosylation trees if they are missing from the model. The method has been incorporated in the PDB-REDO pipeline and has been applied to build or rebuild 16 452 carbohydrate residues in 11 651 glycosylation trees in 4498 structure models, and is also available from the PDB-REDO web server. With better modeling of N-glycosylation, the biological function of this important modification can be better and more easily understood.

Characterization and structure determination of a llama-derived nanobody targeting the J-base binding protein 1

J-base binding protein 1 (JBP1) contributes to the biosynthesis and maintenance of base J (β-D-glucosylhydroxymethyluracil), a modification of thymidine confined to some protozoa. Camelid (llama) single-domain antibody fragments (nanobodies) targeting JBP1 were produced for use as crystallization chaperones. Surface plasmon resonance screening identified Nb6 as a strong binder, recognizing JBP1 with a 1:1 stoichiometry and high affinity (Kd = 30 nM). Crystallization trials of JBP1 in complex with Nb6 yielded crystals that diffracted to 1.47 Å resolution. However, the dimensions of the asymmetric unit and molecular replacement with a nanobody structure clearly showed that the crystals of the expected complex with JBP1 were of the nanobody alone. Nb6 crystallizes in space group P31 with two molecules in the asymmetric unit; its crystal structure was refined to a final resolution of 1.64 Å. Ensemble refinement suggests that in the ligand-free state one of the complementarity-determining regions (CDRs) is flexible, while the other two adopt well defined conformations.