PDB_REDO: constructive validation, more than just looking for errors

Exploring the sequence-function space of microbial fucosidases

Microbial α-L-fucosidases catalyse the hydrolysis of terminal α-L-fucosidic linkages and can perform transglycosylation reactions. Based on sequence identity, α-L-fucosidases are classified in glycoside hydrolases (GHs) families of the carbohydrate-active enzyme database. Here we explored the sequence-function space of GH29 fucosidases. Based on sequence similarity network (SSN) analyses, 15 GH29 α-L-fucosidases were selected for functional characterisation. HPAEC-PAD and LC-FD-MS/MS analyses revealed substrate and linkage specificities for α1,2, α1,3, α1,4 and α1,6 linked fucosylated oligosaccharides and glycoconjugates, consistent with their SSN clustering. The structural basis for the substrate specificity of GH29 fucosidase from Bifidobacterium asteroides towards α1,6 linkages and FA2G2 N-glycan was determined by X-ray crystallography and STD NMR. The capacity of GH29 fucosidases to carry out transfucosylation reactions with GlcNAc and 3FN as acceptors was evaluated by TLC combined with ESI-MS and NMR. These experimental data supported the use of SSN to further explore the GH29 sequence-function space through machine-learning models. Our lightweight protein language models could accurately allocate test sequences in their respective SSN clusters and assign 34,258 non-redundant GH29 sequences into SSN clusters. It is expected that the combination of these computational approaches will be used in the future for the identification of novel GHs with desired specificities.

Molecular glues of the regulatory ChREBP/14-3-3 complex protect beta cells from glucolipotoxicity

The Carbohydrate Response Element Binding Protein (ChREBP) is a glucose-responsive transcription factor (TF) that is characterized by two major splice isoforms (α and β). In acute hyperglycemia, both ChREBP isoforms regulate adaptive β-expansion; however, during chronic hyperglycemia and glucolipotoxicity, ChREBPβ expression surges, leading to β-cell dedifferentiation and death. 14-3-3 binding to ChREBPα results in its cytoplasmic retention and concomitant suppression of transcriptional activity, suggesting that small molecule-mediated stabilization of this protein-protein interaction (PPI) via molecular glues may represent an attractive entry for the treatment of metabolic disease. Here, we show that structure-based optimizations of a molecular glue tool compound led not only to more potent ChREBPα/14-3-3 PPI stabilizers but also for the first time cellular active compounds. In primary human β-cells, the most active compound stabilized the ChREBPα/14-3-3 interaction and thus induced cytoplasmic retention of ChREBPα, resulting in highly efficient β-cell protection from glucolipotoxicity while maintaining β-cell identity. This study may thus not only provide the basis for the development of a unique class of compounds for the treatment of Type 2 Diabetes but also showcases an alternative 'molecular glue' approach for achieving small molecule control of notoriously difficult targetable TFs.

Structural and time-resolved mechanistic investigations of protein hydrolysis by the acidic proline-specific endoprotease from Aspergillus niger

Proline-specific endoproteases have been successfully used in, for example, the in-situ degradation of gluten, the hydrolysis of bitter peptides, the reduction of haze during beer production, and the generation of peptides for mass spectroscopy and proteomics applications. Here we present the crystal structure of the extracellular proline-specific endoprotease from Aspergillus niger (AnPEP), a member of the S28 peptidase family with rarely observed true proline-specific endoprotease activity. Family S28 proteases have a conventional Ser-Asp-His catalytic triad, but their oxyanion-stabilizing hole shows a glutamic acid, an amino acid not previously observed in this role. Since these enzymes have an acidic pH optimum, the presence of a glutamic acid in the oxyanion hole may confine their activity to an acidic pH. Yet, considering the presence of the conventional catalytic triad, it is remarkable that the A. niger enzyme remains active down to pH 1.5. The determination of the primary cleavage site of cytochrome c along with molecular dynamics-assisted docking studies indicate that the active site pocket of AnPEP can accommodate a reverse turn of approximately 12 amino acids with proline at the S1 specificity pocket. Comparison with the structures of two S28-proline-specific exopeptidases reveals not only a more spacious active site cavity but also the absence of any putative binding sites for amino- and carboxyl-terminal residues as observed in the exopeptidases, explaining AnPEP's observed endoprotease activity.

First 3-D structural evidence of a native-like intertwined dimer in the acylphosphatase family

Acylphosphatase (AcP, EC 3.6.1.7) is a small model protein conformed by a ferredoxin-like fold, profoundly studied to get insights into protein folding and aggregation processes. Numerous studies focused on the aggregation and/or amyloidogenic properties of AcPs suggest the importance of edge-β-strands in the process. In this work, we present the first crystallographic structure of Escherichia coli AcP (EcoAcP), showing notable differences with the only available NMR structure for this enzyme. EcoAcP is crystalised as an intertwined dimer formed by replacing a single C-terminal β-strand between two protomers, suggesting a flexible character of the C-terminal edge of EcoAcP. Despite numerous works where AcP from different sources have been used as a model system for protein aggregation, our domain-swapped EcoAcP structure is the first 3-D structural evidence of native-like aggregated species for any AcP reported to date, providing clues on molecular determinants unleashing aggregation.

piRNA processing by a trimeric Schlafen-domain nuclease

Transposable elements are genomic parasites that expand within and spread between genomes1. PIWI proteins control transposon activity, notably in the germline2,3. These proteins recognize their targets through small RNA co-factors named PIWI-interacting RNAs (piRNAs), making piRNA biogenesis a key specificity-determining step in this crucial genome immunity system. Although the processing of piRNA precursors is an essential step in this process, many of the molecular details remain unclear. Here, we identify an endoribonuclease, precursor of 21U RNA 5'-end cleavage holoenzyme (PUCH), that initiates piRNA processing in the nematode Caenorhabditis elegans. Genetic and biochemical studies show that PUCH, a trimer of Schlafen-like-domain proteins (SLFL proteins), executes 5'-end piRNA precursor cleavage. PUCH-mediated processing strictly requires a 7-methyl-G cap (m7G-cap) and a uracil at position three. We also demonstrate how PUCH interacts with PETISCO, a complex that binds to piRNA precursors4, and that this interaction enhances piRNA production in vivo. The identification of PUCH concludes the search for the 5'-end piRNA biogenesis factor in C. elegans and uncovers a type of RNA endonuclease formed by three SLFL proteins. Mammalian Schlafen (SLFN) genes have been associated with immunity5, exposing a molecular link between immune responses in mammals and deeply conserved RNA-based mechanisms that control transposable elements.

Promiscuous recognition of MR1 drives self-reactive mucosal-associated invariant T cell responses

Mucosal-associated invariant T (MAIT) cells use canonical semi-invariant T cell receptors (TCR) to recognize microbial riboflavin precursors displayed by the antigen-presenting molecule MR1. The extent of MAIT TCR crossreactivity toward physiological, microbially unrelated antigens remains underexplored. We describe MAIT TCRs endowed with MR1-dependent reactivity to tumor and healthy cells in the absence of microbial metabolites. MAIT cells bearing TCRs crossreactive toward self are rare but commonly found within healthy donors and display T-helper-like functions in vitro. Experiments with MR1-tetramers loaded with distinct ligands revealed significant crossreactivity among MAIT TCRs both ex vivo and upon in vitro expansion. A canonical MAIT TCR was selected on the basis of extremely promiscuous MR1 recognition. Structural and molecular dynamic analyses associated promiscuity to unique TCRβ-chain features that were enriched within self-reactive MAIT cells of healthy individuals. Thus, self-reactive recognition of MR1 represents a functionally relevant indication of MAIT TCR crossreactivity, suggesting a potentially broader role of MAIT cells in immune homeostasis and diseases, beyond microbial immunosurveillance.

The CCP4 suite: integrative software for macromolecular crystallography

The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world.

In vitro selection of macrocyclic peptide inhibitors containing cyclic γ2,4-amino acids targeting the SARS-CoV-2 main protease

γ-Amino acids can play important roles in the biological activities of natural products; however, the ribosomal incorporation of γ-amino acids into peptides is challenging. Here we report how a selection campaign employing a non-canonical peptide library containing cyclic γ^2,4-amino acids resulted in the discovery of very potent inhibitors of the SARS-CoV-2 main protease (M^pro). Two kinds of cyclic γ^2,4-amino acids, cis-3-aminocyclobutane carboxylic acid (γ¹) and (1R,3S)-3-aminocyclopentane carboxylic acid (γ²), were ribosomally introduced into a library of thioether-macrocyclic peptides. One resultant potent M^pro inhibitor (half-maximal inhibitory concentration = 50 nM), GM4, comprising 13 residues with γ¹ at the fourth position, manifests a 5.2 nM dissociation constant. An M^pro:GM4 complex crystal structure reveals the intact inhibitor spans the substrate binding cleft. The γ¹ interacts with the S1' catalytic subsite and contributes to a 12-fold increase in proteolytic stability compared to its alanine-substituted variant. Knowledge of interactions between GM4 and M^pro enabled production of a variant with a 5-fold increase in potency.

Asymmetry and Ion Selectivity Properties of Bacterial Channel NaK Mutants Derived from Ionotropic Glutamate Receptors

Ionotropic glutamate receptors are ligand-gated cation channels that play essential roles in the excitatory synaptic transmission throughout the central nervous system. A number of open-pore structures of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic-acid (AMPA)-type glutamate receptors became available recently by cryo-electron microscopy (cryo-EM). These structures provide valuable insights into the conformation of the selectivity filter (SF), the part of the ion channel that determines the ion selectivity. Nonetheless, due to the moderate resolution of the cryo-EM structures, detailed information such as ion occupancy of monovalent and divalent cations as well as positioning of the side-chains in the SF is still missing. Here, in an attempt to obtain high-resolution information about glutamate receptor SFs, we incorporated partial SF sequences of the AMPA and kainate receptors into the bacterial tetrameric cation channel NaK, which served as a structural scaffold. We determined a series of X-ray structures of NaK-CDI, NaK-SDI and NaK-SELM mutants at 1.42-2.10 Å resolution, showing distinct ion occupation of different monovalent cations. Molecular dynamics (MD) simulations of NaK-CDI indicated the channel to be conductive to monovalent cations, which agrees well with our electrophysiology recordings. Moreover, previously unobserved structural asymmetry of the SF was revealed by the X-ray structures and MD simulations, implying its importance in ion non-selectivity of tetrameric cation channels.

Errors in structural biology are not the exception

During the COVID-19 pandemic, the structural biology community swung into action quickly and efficiently, and many urgent questions were solved by macromolecular structure determination. The Coronavirus Structural Task Force evaluated all structures from SARS-CoV-1 and SARS-CoV-2, but errors in measurement, data processing and modelling are present beyond these structures and throughout the structures deposited in the Protein Data Bank. Identifying them is only the first step; in order to minimize the impact that errors have in structural biology, error culture needs to change. It should be emphasized that the atomic model which is published is an interpretation of the measurement. Furthermore, risks should be minimized by addressing issues early and by investigating the source of a given problem, so that it may be avoided in the future. If we as a community can do this, it will greatly benefit experimental structural biologists as well as downstream users who are using structural models to deduce new biological and medical answers in the future.

Alkyne Derivatives of SARS-CoV-2 Main Protease Inhibitors Including Nirmatrelvir Inhibit by Reacting Covalently with the Nucleophilic Cysteine

Nirmatrelvir (PF-07321332) is a nitrile-bearing small-molecule inhibitor that, in combination with ritonavir, is used to treat infections by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Nirmatrelvir interrupts the viral life cycle by inhibiting the SARS-CoV-2 main protease (Mpro), which is essential for processing viral polyproteins into functional nonstructural proteins. We report studies which reveal that derivatives of nirmatrelvir and other Mpro inhibitors with a nonactivated terminal alkyne group positioned similarly to the electrophilic nitrile of nirmatrelvir can efficiently inhibit isolated Mpro and SARS-CoV-2 replication in cells. Mass spectrometric and crystallographic evidence shows that the alkyne derivatives inhibit Mpro by apparent irreversible covalent reactions with the active site cysteine (Cys145), while the analogous nitriles react reversibly. The results highlight the potential for irreversible covalent inhibition of Mpro and other nucleophilic cysteine proteases by alkynes, which, in contrast to nitriles, can be functionalized at their terminal position to optimize inhibition and selectivity, as well as pharmacodynamic and pharmacokinetic properties.

The staphylococcal inhibitory protein SPIN binds to human myeloperoxidase with picomolar affinity but only dampens halide oxidation

The heme enzyme myeloperoxidase (MPO) is one of the key players in the neutrophil-mediated killing of invading pathogens as part of the innate immune system. MPO generates antimicrobial oxidants which indiscriminately and effectively kill phagocytosed pathogens. Staphylococcus aureus however is able to escape this fate, in part by secreting a small protein called SPIN (Staphylococcal Peroxidase Inhibitor), which specifically targets and inhibits MPO in a structurally complex manner. Here we present the first crystal structures of the complex of SPIN-aureus and a truncated version (SPIN-truncated) with mature dimeric leukocyte MPO. We unravel the contributions of the two domains to the kinetics and thermodynamics of SPIN-aureus binding to MPO by using a broad array of complementary biochemical and biophysical methods. The C-terminal "recognition" domain is shown to mediate specific binding to MPO, while interaction of the N-terminal "inhibitory" domain is guided mainly by hydrophobic effects and thus is less sequence-dependent. We found that inhibition of MPO is achieved by reducing substrate migration, but SPIN-aureus cannot completely block MPO activity. Its' effectiveness is inversely related to substrate size, with no discernible dependence on other factors. Thus, SPIN-aureus is an extremely high-affinity inhibitor and highly efficient for substrates larger than halogens. As aberrant MPO activity is implicated in a number of chronic inflammatory diseases, SPIN-aureus is the first promising protein inhibitor for specific inhibition of human MPO.

Therapeutic high affinity T cell receptor targeting a KRASG12D cancer neoantigen

Neoantigens derived from somatic mutations are specific to cancer cells and are ideal targets for cancer immunotherapy. KRAS is the most frequently mutated oncogene and drives the pathogenesis of several cancers. Here we show the identification and development of an affinity-enhanced T cell receptor (TCR) that recognizes a peptide derived from the most common KRAS mutant, KRAS^G12D, presented in the context of HLA-A*11:01. The affinity of the engineered TCR is increased by over one million-fold yet fully able to distinguish KRAS^G12D over KRAS^WT. While crystal structures reveal few discernible differences in TCR interactions with KRAS^WT versus KRAS^G12D, thermodynamic analysis and molecular dynamics simulations reveal that TCR specificity is driven by differences in indirect electrostatic interactions. The affinity enhanced TCR, fused to a humanized anti-CD3 scFv, enables selective killing of cancer cells expressing KRAS^G12D. Our work thus reveals a molecular mechanism that drives TCR selectivity and describes a soluble bispecific molecule with therapeutic potential against cancers harboring a common shared neoantigen.

Cancers often harbor mutations in genes encoding important regulatory proteins, but therapeutic targeting of these molecules proves difficult due to their high structural similarity to their non-mutated counterpart. Here authors show the engineering of T cell engaging bispecific protein able to selectively target cancer cells with a high-frequency mutation in the KRAS oncogene.

PDBx/mmCIF Ecosystem: Foundational Semantic Tools for Structural Biology

PDBx/mmCIF, Protein Data Bank Exchange (PDBx) macromolecular Crystallographic Information Framework (mmCIF), has become the data standard for structural biology. With its early roots in the domain of small-molecule crystallography, PDBx/mmCIF provides an extensible data representation that is used for deposition, archiving, remediation, and public dissemination of experimentally determined three-dimensional (3D) structures of biological macromolecules by the Worldwide Protein Data Bank (wwPDB, wwpdb.org). Extensions of PDBx/mmCIF are similarly used for computed structure models by ModelArchive (modelarchive.org), integrative/hybrid structures by PDB-Dev (pdb-dev.wwpdb.org), small angle scattering data by Small Angle Scattering Biological Data Bank SASBDB (sasbdb.org), and for models computed generated with the AlphaFold 2.0 deep learning software suite (alphafold.ebi.ac.uk). Community-driven development of PDBx/mmCIF spans three decades, involving contributions from researchers, software and methods developers in structural sciences, data repository providers, scientific publishers, and professional societies. Having a semantically rich and extensible data framework for representing a wide range of structural biology experimental and computational results, combined with expertly curated 3D biostructure data sets in public repositories, accelerates the pace of scientific discovery. Herein, we describe the architecture of the PDBx/mmCIF data standard, tools used to maintain representations of the data standard, governance, and processes by which data content standards are extended, plus community tools/software libraries available for processing and checking the integrity of PDBx/mmCIF data. Use cases exemplify how the members of the Worldwide Protein Data Bank have used PDBx/mmCIF as the foundation for its pipeline for delivering Findable, Accessible, Interoperable, and Reusable (FAIR) data to many millions of users worldwide.

Penicillin Derivatives Inhibit the SARS-CoV-2 Main Protease by Reaction with Its Nucleophilic Cysteine

The SARS-CoV-2 main protease (Mpro) is a medicinal chemistry target for COVID-19 treatment. Given the clinical efficacy of β-lactams as inhibitors of bacterial nucleophilic enzymes, they are of interest as inhibitors of viral nucleophilic serine and cysteine proteases. We describe the synthesis of penicillin derivatives which are potent Mpro inhibitors and investigate their mechanism of inhibition using mass spectrometric and crystallographic analyses. The results suggest that β-lactams have considerable potential as Mpro inhibitors via a mechanism involving reaction with the nucleophilic cysteine to form a stable acyl-enzyme complex as shown by crystallographic analysis. The results highlight the potential for inhibition of viral proteases employing nucleophilic catalysis by β-lactams and related acylating agents.

Structure-guided stabilization of pathogen-derived peptide-HLA-E complexes using non-natural amino acids conserves native TCR recognition

The nonpolymorphic class Ib molecule, HLA-E, primarily presents peptides from HLA class Ia leader peptides, providing an inhibitory signal to NK cells via CD94/NKG2 interactions. Although peptides of pathogenic origin can also be presented by HLA-E to T cells, the molecular basis underpinning their role in antigen surveillance is largely unknown. Here, we solved a co-complex crystal structure of a TCR with an HLA-E presented peptide (pHLA-E) from bacterial (Mycobacterium tuberculosis) origin, and the first TCR-pHLA-E complex with a noncanonically presented peptide from viral (HIV) origin. The structures provided a molecular foundation to develop a novel method to introduce cysteine traps using non-natural amino acid chemistry that stabilized pHLA-E complexes while maintaining native interface contacts between the TCRs and different pHLA-E complexes. These pHLA-E monomers could be used to isolate pHLA-E-specific T cells, with obvious utility for studying pHLA-E restricted T cells, and for the identification of putative therapeutic TCRs.

Fine-tuning spermidine binding modes in the putrescine binding protein PotF

A profound understanding of the molecular interactions between receptors and ligands is important throughout diverse research, such as protein design, drug discovery, or neuroscience. What determines specificity and how do proteins discriminate against similar ligands? In this study, we analyzed factors that determine binding in two homologs belonging to the well-known superfamily of periplasmic binding proteins, PotF and PotD. Building on a previously designed construct, modes of polyamine binding were swapped. This change of specificity was approached by analyzing local differences in the binding pocket as well as overall conformational changes in the protein. Throughout the study, protein variants were generated and characterized structurally and thermodynamically, leading to a specificity swap and improvement in affinity. This dataset not only enriches our knowledge applicable to rational protein design but also our results can further lay groundwork for engineering of specific biosensors as well as help to explain the adaptability of pathogenic bacteria.

Crystal structure of the pheromone Er-13 from the ciliate Euplotes raikovi, with implications for a protein-protein association model in pheromone/receptor interactions

In the ciliate Euplotes raikovi, water-borne protein pheromones promote the vegetative cell growth and mating by competitively binding as autocrine and heterologous signals to putative cell receptors represented by membrane-bound pheromone isoforms. A previously determined crystal structure of pheromone Er-1 supported a pheromone/receptor binding model in which strong protein-protein interactions result from the cooperative utilization of two distinct types of contact interfaces that arrange molecules into linear chains, and these into two-dimensional layers. We have now determined the crystal structure of a new pheromone, Er-13, isolated from cultures that are strongly mating reactive withculturessource of pheromone Er-1.The comparison between the Er-1 and Er-13 crystal structuresreinforces the fundamental of the cooperative model of pheromone/receptor binding, in that the molecules arrange into linear chains taking a rigorously alternate opposite orientation reflecting the presumed mutual orientation of pheromone and receptor molecules on the cell surface. In addition, the comparison provides two new lines of evidence for a univocal rationalization of observations on the differentbehaviourbetween the autocrine and heterologous pheromone/receptor complexes. (i) In the Er-13 crystal, chains do not form layers which thus appear to be an over-structureunique tothe Er-1 crystal, not essential for the pheromone signalling mechanisms. (ii) In both crystal structures, the intra-chain interfaces are equally derived from burying amino-acid side-chains mostly residing on helix-3 of the three-helical pheromonefold. This helix is thus identified as the key structural motif underlying the pheromone activity, in line with its tight intra- and interspecificstructuralconservation.

Structural basis of Apt48 inhibition of the BCL6 BTB domain

B cell lymphoma 6 (BCL6) is a transcriptional repressor that is deregulated in diffuse large B cell lymphoma, and the peptide aptamer, Apt48, inhibits BCL6 by an unknown mechanism. We report the crystal structure of BCL6 in complex with an Apt48 peptide, and show that Apt48 binds to a therapeutically uncharacterized region at the bottom of the BCL6 BTB domain. We show that the corepressor binding site of the BTB domain may be divided conceptually into two low-affinity, peptide-binding regions. An upper region, the lateral groove, binds peptides in robust three-dimensional conformations, whereas a lower binding site is permissive to less-specific interactions. We show that, even with little sequence specificity, the interactions of the lower region are required for the high-affinity binding of the SMRT corepressor and other peptides to the BTB domain. This has relevance for the design of new BCL6 inhibitors and for understanding the evolution of corepressor interactions with the BTB domain.

Cryo-EM single-particle structure refinement and map calculation using Servalcat

In 2020, cryo-EM single-particle analysis achieved true atomic resolution thanks to technological developments in hardware and software. The number of high-resolution reconstructions continues to grow, increasing the importance of the accurate determination of atomic coordinates. Here, a new Python package and program called Servalcat is presented that is designed to facilitate atomic model refinement. Servalcat implements a refinement pipeline using the program REFMAC5 from the CCP4 package. After the refinement, Servalcat calculates a weighted Fo - Fc difference map, which is derived from Bayesian statistics. This map helps manual and automatic model building in real space, as is common practice in crystallography. The Fo - Fc map helps in the visualization of weak features including hydrogen densities. Although hydrogen densities are weak, they are stronger than in the electron-density maps produced by X-ray crystallography, and some H atoms are even visible at ∼1.8 Å resolution. Servalcat also facilitates atomic model refinement under symmetry constraints. If point-group symmetry has been applied to the map during reconstruction, the asymmetric unit model is refined with the appropriate symmetry constraints.

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/.

Structural basis of PETISCO complex assembly during piRNA biogenesis in C. elegans

In this study, Perez-Borrajero et al. set out to characterize PETISCO architecture and its interaction with RNA, together with its effector proteins TOST-1 and PID-1. Using biochemical and structural biology approaches, the authors found that PETISCO forms a dimer of tetramers, in which dimerization is mediated by both PID-3 and ERH-2. Crystal structures of the PID- 3/TOFU-6 and ERH-2/PID-3 subcomplexes reveal insights into PETISCO assembly, function, and subcellular localization. Using NMR spectroscopy, the authors also characterize the mutually exclusive interplay of ERH-2 with the two effector proteins TOST-1 and PID-1.

Piwi-interacting RNAs (piRNAs) constitute a class of small RNAs that bind PIWI proteins and are essential to repress transposable elements in the animal germline, thereby promoting genome stability and maintaining fertility. C. elegans piRNAs (21U RNAs) are transcribed individually from minigenes as precursors that require 5′ and 3′ processing. This process depends on the PETISCO complex, consisting of four proteins: IFE-3, TOFU-6, PID-3, and ERH-2. We used biochemical and structural biology approaches to characterize the PETISCO architecture and its interaction with RNA, together with its effector proteins TOST-1 and PID-1. These two proteins define different PETISCO functions: PID-1 governs 21U processing, whereas TOST-1 links PETISCO to an unknown process essential for early embryogenesis. Here, we show that PETISCO forms an octameric assembly with each subunit present in two copies. Determination of structures of the TOFU-6/PID-3 and PID-3/ERH-2 subcomplexes, supported by in vivo studies of subunit interaction mutants, allows us to propose a model for the formation of the TOFU-6/PID-3/ERH-2 core complex and its functionality in germ cells and early embryos. Using NMR spectroscopy, we demonstrate that TOST-1 and PID-1 bind to a common surface on ERH-2, located opposite its PID-3 binding site, explaining how PETISCO can mediate different cellular roles.

'All That Glitters Is Not Gold': High-Resolution Crystal Structures of Ligand-Protein Complexes Need Not Always Represent Confident Binding Poses

Our understanding of the structure–function relationships of biomolecules and thereby applying it to drug discovery programs are substantially dependent on the availability of the structural information of ligand–protein complexes. However, the correct interpretation of the electron density of a small molecule bound to a crystal structure of a macromolecule is not trivial. Our analysis involving quality assessment of ~0.28 million small molecule–protein binding site pairs derived from crystal structures corresponding to ~66,000 PDB entries indicates that the majority (65%) of the pairs might need little (54%) or no (11%) attention. Out of the remaining 35% of pairs that need attention, 11% of the pairs (including structures with high/moderate resolution) pose serious concerns. Unfortunately, most users of crystal structures lack the training to evaluate the quality of a crystal structure against its experimental data and, in general, rely on the resolution as a ‘gold standard’ quality metric. Our work aims to sensitize the non-crystallographers that resolution, which is a global quality metric, need not be an accurate indicator of local structural quality. In this article, we demonstrate the use of several freely available tools that quantify local structural quality and are easy to use from a non-crystallographer’s perspective. We further propose a few solutions for consideration by the scientific community to promote quality research in structural biology and applied areas.

FragMAXapp: crystallographic fragment-screening data-analysis and project-management system

Crystallographic fragment screening (CFS) has become one of the major techniques for screening compounds in the early stages of drug-discovery projects. Following the advances in automation and throughput at modern macromolecular crystallography beamlines, the bottleneck for CFS has shifted from collecting data to organizing and handling the analysis of such projects. The complexity that emerges from the use of multiple methods for processing and refinement and to search for ligands requires an equally sophisticated solution to summarize the output, allowing researchers to focus on the scientific questions instead of on software technicalities. FragMAXapp is the fragment-screening project-management tool designed to handle CFS projects at MAX IV Laboratory. It benefits from the powerful computing infrastructure of large-scale facilities and, as a web application, it is accessible from everywhere.

Considerations Regarding Activity Determinants of Fungal Polyphenol Oxidases Based on Mutational and Structural Studies

Polyphenol oxidases (PPOs) are an industrially relevant family of enzymes, being involved in the postharvest browning of fruits and vegetables, as well as in human melanogenesis. Their involvement lies in their ability to oxidize phenolic or polyphenolic compounds, which subsequently form pigments. The PPO family includes tyrosinases and catechol oxidases, which, in spite of their high structural similarity, exhibit different catalytic activities. Long-standing research efforts have not yet managed to decipher the structural determinants responsible for this differentiation, as every new theory is disproved by a more recent study. In the present work, we combined biochemical along with structural data in order to better understand the function of a previously characterized PPO from Thermothelomyces thermophila (TtPPO). The crystal structure of a TtPPO variant, determined at 1.55 Å resolution, represents the second known structure of an ascomycete PPO. Kinetic data for structure-guided mutants prove the implication of "gate" residue L306, residue HB1+1 (G292), and HB2+1 (Y296) in TtPPO function against various substrates. Our findings demonstrate the role of L306 in the accommodation of bulky substrates and show that residue HB1+1 is unlikely to determine monophenolase activity, as was suggested from previous studies.IMPORTANCE PPOs are enzymes of biotechnological interest. They have been extensively studied both biochemically and structurally, with a special focus on the plant-derived counterparts. Even so, explicit description of the molecular determinants of their substrate specificity is still pending. For ascomycete PPOs, only one crystal structure has been determined so far, thus limiting our knowledge on this tree branch of the family. In the present study, we report the second crystal structure of an ascomycete PPO. Combined with site-directed mutagenesis and biochemical studies, we depict the amino acids in the vicinity of the active site that affect enzyme activity and perform a detailed analysis on a variety of substrates. Our findings improve current understanding of structure-function relations of microbial PPOs, which is a prerequisite for the engineering of biocatalysts of desired properties.

Fighting viruses with computers, right now

The synergistic conjunction of various technological revolutions with the accumulated knowledge and workflows is rapidly transforming several scientific fields. Particularly, Virology can now feed from accurate physical models, polished computational tools, and massive computational power to readily integrate high-resolution structures into biological representations of unprecedented detail. That preparedness allows for the first time to get crucial information for vaccine and drug design from in-silico experiments against emerging pathogens of worldwide concern at relevant action windows. The present work reviews some of the main milestones leading to these breakthroughs in Computational Virology, providing an outlook for future developments in capacity building and accessibility to computational resources.

Representations of protein structure for exploring the conformational space: A speed-accuracy trade-off

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We compare ten structural representations, either atomistic or coarse-grained.

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Thus, ten distance-dependent statistical potentials of mean force (PMF) were built.

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The Cβ-only and Cα + Cβ representations provide the best speed–accuracy trade-off.

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Including glycines through Cα, in a Cβ-only representation, yields a higher accuracy.

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We generalize the conclusions to the total information gain (TIG) scoring function.

The recent breakthrough in the field of protein structure prediction shows the relevance of using knowledge-based based scoring functions in combination with a low-resolution 3D representation of protein macromolecules. The choice of not using all atoms is barely supported by any data in the literature, and is mostly motivated by empirical and practical reasons, such as the computational cost of assessing the numerous folds of the protein conformational space. Here, we present a comprehensive study, carried on a large and balanced benchmark of predicted protein structures, to see how different types of structural representations rank in either accuracy or calculation speed, and which ones offer the best compromise between these two criteria. We tested ten representations, including low-resolution, high-resolution, and coarse-grained approaches. We also investigated the generalization of the findings to other formalisms than the widely-used “potential of mean force” (PMF) method. Thus, we observed that representing protein structures by their β carbons—combined or not with Cα—provides the best speed–accuracy trade-off, when using a “total information gain” scoring function. For statistical PMFs, using MARTINI backbone and side-chains beads is the best option. Finally, we also demonstrated the necessity of training the reference state on all atom types, and of including the Cα atoms of glycine residues, in a Cβ-based representation.

Synchrotron Radiation as a Tool for Macromolecular X-Ray Crystallography: a XXI Century Perspective

Intense X-rays available at powerful synchrotron beamlines provide macromolecular crystallographers with an incomparable tool for investigating biological phenomena on an atomic scale. The resulting insights into the mechanism's underlying biological processes have played an essential role and shaped biomedical sciences during the last 30 years, considered the "golden age" of structural biology. In this review, we analyze selected aspects of the impact of synchrotron radiation on structural biology. Synchrotron beamlines have been used to determine over 70% of all macromolecular structures deposited into the Protein Data Bank (PDB). These structures were deposited by over 13,000 different research groups. Interestingly, despite the impressive advances in synchrotron technologies, the median resolution of macromolecular structures determined using synchrotrons has remained constant throughout the last 30 years, at about 2 Å. Similarly, the median times from the data collection to the deposition and release have not changed significantly. We describe challenges to reproducibility related to recording all relevant data and metadata during the synchrotron experiments, including diffraction images. Finally, we discuss some of the recent opinions suggesting a diminishing importance of X-ray crystallography due to impressive advances in Cryo-EM and theoretical modeling. We believe that synchrotrons of the future will increasingly evolve towards a life science center model, where X-ray crystallography, Cryo-EM, and other experimental and computational resources and knowledge are encompassed within a versatile research facility. The recent response of crystallographers to the COVID-19 pandemic suggests that X-ray crystallography conducted at synchrotron beamlines will continue to play an essential role in structural biology and drug discovery for years to come.

Detection of translational noncrystallographic symmetry in Patterson functions

Detection of translational noncrystallographic symmetry (TNCS) can be critical for success in crystallographic phasing, particularly when molecular-replacement models are poor or anomalous phasing information is weak. If the correct TNCS is detected then expected intensity factors for each reflection can be refined, so that the maximum-likelihood functions underlying molecular replacement and single-wavelength anomalous dispersion use appropriate structure-factor normalization and variance terms. Here, an analysis of a curated database of protein structures from the Protein Data Bank to investigate how TNCS manifests in the Patterson function is described. These studies informed an algorithm for the detection of TNCS, which includes a method for detecting the number of vectors involved in any commensurate modulation (the TNCS order). The algorithm generates a ranked list of possible TNCS associations in the asymmetric unit for exploration during structure solution.

A comprehensive binding study illustrates ligand recognition in the periplasmic binding protein PotF

Periplasmic binding proteins (PBPs) are ubiquitous receptors in gram-negative bacteria. They sense solutes and play key roles in nutrient uptake. Escherichia coli's putrescine receptor PotF has been reported to bind putrescine and spermidine. We reveal that several similar biogenic polyamines are recognized by PotF. Using isothermal titration calorimetry paired with X-ray crystallography of the different complexes, we unveil PotF's binding modes in detail. The binding site for PBPs is located between two lobes that undergo a large conformational change upon ligand recognition. Hence, analyzing the influence of ligands on complex formation is crucial. Therefore, we solved crystal structures of an open and closed apo state and used them as a basis for molecular dynamics simulations. In addition, we accessed structural behavior in solution for all complexes by ¹H-¹⁵N HSQC NMR spectroscopy. This combined analysis provides a robust framework for understanding ligand binding for future developments in drug design and protein engineering.

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.

Phasertng: directed acyclic graphs for crystallographic phasing

Crystallographic phasing strategies increasingly require the exploration and ranking of many hypotheses about the number, types and positions of atoms, molecules and/or molecular fragments in the unit cell, each with only a small chance of being correct. Accelerating this move has been improvements in phasing methods, which are now able to extract phase information from the placement of very small fragments of structure, from weak experimental phasing signal or from combinations of molecular replacement and experimental phasing information. Describing phasing in terms of a directed acyclic graph allows graph-management software to track and manage the path to structure solution. The crystallographic software supporting the graph data structure must be strictly modular so that nodes in the graph are efficiently generated by the encapsulated functionality. To this end, the development of new software, Phasertng, which uses directed acyclic graphs natively for input/output, has been initiated. In Phasertng, the codebase of Phaser has been rebuilt, with an emphasis on modularity, on scripting, on speed and on continuing algorithm development. As a first application of phasertng, its advantages are demonstrated in the context of phasertng.xtricorder, a tool to analyse and triage merged data in preparation for molecular replacement or experimental phasing. The description of the phasing strategy with directed acyclic graphs is a generalization that extends beyond the functionality of Phasertng, as it can incorporate results from bioinformatics and other crystallographic tools, and will facilitate multifaceted search strategies, dynamic ranking of alternative search pathways and the exploitation of machine learning to further improve phasing strategies.

On the Effect of the Various Assumptions and Approximations used in Molecular Simulations on the Properties of Bio-Molecular Systems: Overview and Perspective on Issues

Computer simulations of molecular systems enable structure-energy-function relationships of molecular processes to be described at the sub-atomic, atomic, supra-atomic or supra-molecular level and plays an increasingly important role in chemistry, biology and physics. To interpret the results of such simulations appropriately, the degree of uncertainty and potential errors affecting the calculated properties must be considered. Uncertainty and errors arise from (1) assumptions underlying the molecular model, force field and simulation algorithms, (2) approximations implicit in the interatomic interaction function (force field), or when integrating the equations of motion, (3) the chosen values of the parameters that determine the accuracy of the approximations used, and (4) the nature of the system and the property of interest. In this overview, advantages and shortcomings of assumptions and approximations commonly used when simulating bio-molecular systems are considered. What the developers of bio-molecular force fields and simulation software can do to facilitate and broaden research involving bio-molecular simulations is also discussed.

GlycoTorch Vina: Docking Designed and Tested for Glycosaminoglycans

Glycosaminoglycans (GAGs) are a family of anionic carbohydrates that play an essential role in the physiology and pathology of all eukaryotic life forms. Experimental determination of GAG-protein complexes is challenging due to their difficult isolation from biological sources, natural heterogeneity, and conformational flexibility-including possible ring puckering of sulfated iduronic acid from ¹C₄ to ²S_O conformation. To overcome these challenges, we present GlycoTorch Vina (GTV), a molecular docking tool based on the carbohydrate docking program VinaCarb (VC). Our program is unique in that it contains parameters to model ²S_O sugars while also supporting glycosidic linkages specific to GAGs. We discuss how crystallographic models of carbohydrates can be biased by the choice of refinement software and structural dictionaries. To overcome these variations, we carefully curated 12 of the best available GAG and GAG-like crystal structures (ranging from tetra- to octasaccharides or longer) obtained from the PDB-REDO server and refined using the same protocol. Both GTV and VC produced pose predictions with a mean root-mean-square deviation (RMSD) of 3.1 Å from the native crystal structure-a statistically significant improvement when compared to AutoDock Vina (4.5 Å) and the commercial software Glide (5.9 Å). Examples of how real-space correlation coefficients can be used to better assess the accuracy of docking pose predictions are given. Comparisons between statistical distributions of empirical "salt bridge" interactions, relevant to GAGs, were compared to density functional theory (DFT) studies of model salt bridges, and water-mediated salt bridges; however, there was generally a poor agreement between these data. Water bridges appear to play an important, yet poorly understood, role in the structures of GAG-protein complexes. To aid in the rapid prototyping of future pose scoring functions, we include a module that allows users to include their own torsional and nonbonded parameters.

Local and global analysis of macromolecular atomic displacement parameters

This paper describes the global and local analysis of atomic displacement parameters (ADPs) of macromolecules in X-ray crystallography. The distribution of ADPs is shown to follow the shifted inverse-gamma distribution or a mixture of these distributions. The mixture parameters are estimated using the expectation-maximization algorithm. In addition, a method for the resolution- and individual ADP-dependent local analysis of neighbouring atoms has been designed. This method facilitates the detection of mismodelled atoms, heavy-metal atoms and disordered and/or incorrectly modelled ligands. Both global and local analyses can be used to detect errors in atomic models, thus helping in the (re)building, refinement and validation of macromolecular structures. This method can also serve as an additional validation tool during PDB deposition.

Iris: Interactive all-in-one graphical validation of 3D protein model iterations

Iris validation is a Python package created to represent comprehensive per‐residue validation metrics for entire protein chains in a compact, readable and interactive view. These metrics can either be calculated by Iris, or by a third‐party program such as MolProbity. We show that those parts of a protein model requiring attention may generate ripples across the metrics on the diagram, immediately catching the modeler's attention. Iris can run as a standalone tool, or be plugged into existing structural biology software to display per‐chain model quality at a glance, with a particular emphasis on evaluating incremental changes resulting from the iterative nature of model building and refinement. Finally, the integration of Iris into the CCP4i2 graphical user interface is provided as a showcase of its pluggable design.

Segmented flow generator for serial crystallography at the European X-ray free electron laser

Serial femtosecond crystallography (SFX) with X-ray free electron lasers (XFELs) allows structure determination of membrane proteins and time-resolved crystallography. Common liquid sample delivery continuously jets the protein crystal suspension into the path of the XFEL, wasting a vast amount of sample due to the pulsed nature of all current XFEL sources. The European XFEL (EuXFEL) delivers femtosecond (fs) X-ray pulses in trains spaced 100 ms apart whereas pulses within trains are currently separated by 889 ns. Therefore, continuous sample delivery via fast jets wastes >99% of sample. Here, we introduce a microfluidic device delivering crystal laden droplets segmented with an immiscible oil reducing sample waste and demonstrate droplet injection at the EuXFEL compatible with high pressure liquid delivery of an SFX experiment. While achieving ~60% reduction in sample waste, we determine the structure of the enzyme 3-deoxy-D-manno-octulosonate-8-phosphate synthase from microcrystals delivered in droplets revealing distinct structural features not previously reported.

Structural alphabets for conformational analysis of nucleic acids available at dnatco.datmos.org

A detailed description of the dnatco.datmos.org web server implementing the universal structural alphabet of nucleic acids is presented. It is capable of processing any mmCIF- or PDB-formatted files containing DNA or RNA molecules; these can either be uploaded by the user or supplied as the wwPDB or PDB-REDO structural database access code. The web server performs an assignment of the nucleic acid conformations and presents the results for the intuitive annotation, validation, modeling and refinement of nucleic acids.

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.

Toward a Computational Ecotoxicity Assay

Thousands of anthropogenic chemicals are released into the environment each year, posing potential hazards to human and environmental health. Toxic chemicals may cause a variety of adverse health effects, triggering immediate symptoms or delayed effects over longer periods of time. It is thus crucial to develop methods that can rapidly screen and predict the toxicity of chemicals to limit the potential harmful impacts of chemical pollutants. Computational methods are being increasingly used in toxicity predictions. Here, the method of molecular docking is assessed for screening potential toxicity of a variety of xenobiotic compounds, including pesticides, pharmaceuticals, pollutants, and toxins derived from the chemical industry. The method predicts the binding energy of pollutants to a set of carefully selected receptors under the assumption that toxicity in many cases is related to interference with biochemical pathways. The strength of the applied method lies in its rapid generation of interaction maps between potential toxins and the targeted enzymes, which could quickly yield molecular-level information and insight into potential perturbation pathways, aiding in the prioritization of chemicals for further tests. Two scoring functions are compared: Autodock Vina and the machine-learning scoring function RF-Score-VS. The results are promising, although hampered by the accuracy of the scoring functions. The strengths and weaknesses of the docking protocol are discussed, as well as future directions for improving the accuracy for the purpose of toxicity predictions.

Coarse-grained (hybrid) integrative modeling of biomolecular interactions

The computational modeling field has vastly evolved over the past decades. The early developments of simplified protein systems represented a stepping stone towards establishing more efficient approaches to sample intricated conformational landscapes. Downscaling the level of resolution of biomolecules to coarser representations allows for studying protein structure, dynamics and interactions that are not accessible by classical atomistic approaches. The combination of different resolutions, namely hybrid modeling, has also been proved as an alternative when mixed levels of details are required. In this review, we provide an overview of coarse-grained/hybrid models focusing on their applicability in the modeling of biomolecular interactions. We give a detailed list of ready-to-use modeling software for studying biomolecular interactions allowing various levels of coarse-graining and provide examples of complexes determined by integrative coarse-grained/hybrid approaches in combination with experimental information.

Structure-Guided Design of a Peptide Lock for Modular Peptide Binders

Peptides play an important role in intermolecular interactions and are frequent analytes in diagnostic assays, also as unstructured, linear epitopes in whole proteins. Yet, due to the many different sequence possibilities even for short peptides, classical selection of binding proteins from a library, one at a time, is not scalable to proteomes. However, moving away from selection to a rational assembly of preselected modules binding to predefined linear epitopes would split the problem into smaller parts. These modules could then be reassembled in any desired order to bind to, in principle, arbitrary sequences, thereby circumventing any new rounds of selection. Designed Armadillo repeat proteins (dArmRPs) are modular, and they do bind elongated peptides in a modular way. Their consensus sequence carries pockets that prefer arginine and lysine. In our quest to select pockets for all amino acid side chains, we had discovered that repetitive sequences can lead to register shifts and peptide flipping during selections from libraries, hindering the selection of new binding specificities. To solve this problem, we now created an orthogonal binding specificity by a combination of grafting from β-catenin, computational design and mutual optimization of the pocket and the bound peptide. We have confirmed the design and the desired interactions by X-ray structure determination. Furthermore, we could confirm the absence of sliding in solution by a single-molecule Förster resonance energy transfer. The new pocket could be moved from the N-terminus of the protein to the middle, retaining its properties, further underlining the modularity of the system.

Computational reconstruction of atomistic protein structures from coarse-grained models

Three-dimensional protein structures, whether determined experimentally or theoretically, are often too low resolution. In this mini-review, we outline the computational methods for protein structure reconstruction from incomplete coarse-grained to all atomistic models. Typical reconstruction schemes can be divided into four major steps. Usually, the first step is reconstruction of the protein backbone chain starting from the C-alpha trace. This is followed by side-chains rebuilding based on protein backbone geometry. Subsequently, hydrogen atoms can be reconstructed. Finally, the resulting all-atom models may require structure optimization. Many methods are available to perform each of these tasks. We discuss the available tools and their potential applications in integrative modeling pipelines that can transfer coarse-grained information from computational predictions, or experiment, to all atomistic structures.

Rigid fusions of designed helical repeat binding proteins efficiently protect a binding surface from crystal contacts

Designed armadillo repeat proteins (dArmRPs) bind extended peptides in a modular way. The consensus version recognises alternating arginines and lysines, with one dipeptide per repeat. For generating new binding specificities, the rapid and robust analysis by crystallography is key. Yet, we have previously found that crystal contacts can strongly influence this analysis, by displacing the peptide and potentially distorting the overall geometry of the scaffold. Therefore, we now used protein design to minimise these effects and expand the previously described concept of shared helices to rigidly connect dArmRPs and designed ankyrin repeat proteins (DARPins), which serve as a crystallisation chaperone. To shield the peptide-binding surface from crystal contacts, we rigidly fused two DARPins to the N- and C-terminal repeat of the dArmRP and linked the two DARPins by a disulfide bond. In this ring-like structure, peptide binding, on the inside of the ring, is very regular and undistorted, highlighting the truly modular binding mode. Thus, protein design was utilised to construct a well crystallising scaffold that prevents interference from crystal contacts with peptide binding and maintains the equilibrium structure of the dArmRP. Rigid DARPin-dArmRPs fusions will also be useful when chimeric binding proteins with predefined geometries are required.

Structural analysis of biological targets by host:guest crystal lattice engineering

To overcome the laborious identification of crystallisation conditions for protein X-ray crystallography, we developed a method where the examined protein is immobilised as a guest molecule in a universal host lattice. We applied crystal engineering to create a generic crystalline host lattice under reproducible, predefined conditions and analysed the structures of target guest molecules of different size, namely two 15-mer peptides and green fluorescent protein (sfGFP). A fusion protein with an N-terminal endo-α-N-acetylgalactosaminidase (EngBF) domain and a C-terminal designed ankyrin repeat protein (DARPin) domain establishes the crystal lattice. The target is recruited into the host lattice, always in the same crystal form, through binding to the DARPin. The target structures can be determined rapidly from difference Fourier maps, whose quality depends on the size of the target and the orientation of the DARPin.

Sequence assignment for low-resolution modelling of protein crystal structures

Recent advances in automated protein model building using ARP/wARP are presented. The new methods include machine-learning-enhanced sequence assignment and loop building using a fragment database.

The performance of automated model building in crystal structure determination usually decreases with the resolution of the experimental data, and may result in fragmented models and incorrect side-chain assignment. Presented here are new methods for machine-learning-based docking of main-chain fragments to the sequence and for their sequence-independent connection using a dedicated library of protein fragments. The combined use of these new methods noticeably increases sequence coverage and reduces fragmentation of the protein models automatically built with ARP/wARP.

Structural Principles in Robo Activation and Auto-inhibition

Proper brain function requires high-precision neuronal expansion and wiring, processes controlled by the transmembrane Roundabout (Robo) receptor family and their Slit ligands. Despite their great importance, the molecular mechanism by which Robos' switch from "off" to "on" states remains unclear. Here, we report a 3.6 Å crystal structure of the intact human Robo2 ectodomain (domains D1-8). We demonstrate that Robo cis dimerization via D4 is conserved through hRobo1, 2, and 3 and the C. elegans homolog SAX-3 and is essential for SAX-3 function in vivo. The structure reveals two levels of auto-inhibition that prevent premature activation: (1) cis blocking of the D4 dimerization interface and (2) trans interactions between opposing Robo receptors that fasten the D4-blocked conformation. Complementary experiments in mouse primary neurons and C. elegans support the auto-inhibition model. These results suggest that Slit stimulation primarily drives the release of Robo auto-inhibition required for dimerization and activation.

Covalently immobilized catalase on functionalized graphene: effect on the activity, immobilization efficiency, and tetramer stability

Herein we describe, for the first time, the covalent immobilization of catalase (CAT) on functionalized graphene surfaces (G) by exploiting the azalactone chemistry for the post-functionalization of graphene-based materials. The structure, morphology and chemical composition of catalase immobilized on graphene (CAT-G) have been investigated by Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM/EDX). The biological responses such as catalytic activity, cellular uptake, internalization pathway, and the ability to protect lymphocytes from oxidative stress induced by H2O2 together with the unforeseen ability to increase the lifetime of the free catalase in solution have been deeply investigated. From our studies, it is evident that the behavior of CAT covalently linked to modified graphene depends on the CAT/G ratio that affects the secondary structure and the tetramer stability of CAT. In order to support the experimental results, we have also investigated the behaviors of two appropriately designed model systems, named CAT-surfer and CAT-skier, by molecular dynamics calculations. These in silico results parallel the experimental results proving our hypothesis that the CAT-surfer maintains the conformational flexibility needed for a biological response, whereas CAT-skier favors the dissociation of the tetramer subunits, involving the inactivation of the enzyme.