Covalent bicyclization of protein complexes yields durable quaternary structures.

Proteins are essential biomolecules and central to biotechnological applications. In many cases, assembly into higher-order structures is a prerequisite for protein function. Under conditions relevant for applications, protein integrity is often challenged, resulting in disassembly, aggregation, and loss of function. The stabilization of quaternary structure has proven challenging, particularly for trimeric and higher-order complexes, given the complexity of involved inter- and intramolecular interaction networks. Here, we describe the chemical bicyclization of homotrimeric protein complexes, thereby increasing protein resistance toward thermal and chemical stress. This approach involves the structure-based selection of cross-linking sites, their variation to cysteine, and a subsequent reaction with a triselectrophilic agent to form a protein assembly with bicyclic topology. Besides overall increased stability, we observe resistance toward aggregation and greatly prolonged shelf life. This bicyclization strategy gives rise to unprecedented protein chain topologies and can enable new biotechnological and biomedical applications.

Of problems and opportunities-How to treat and how to not treat crystallographic fragment screening data.

In their recent commentary in Protein Science, Jaskolski et al. analyzed three randomly picked diffraction data sets from fragment-screening group depositions from the PDB and, based on that, they claimed that such data are principally problematic. We demonstrate here that if such data are treated properly, none of the proclaimed criticisms persist.

Experiences From Developing Software for Large X-Ray Crystallography-Driven Protein-Ligand Studies.

The throughput of macromolecular X-ray crystallography experiments has surged over the last decade. This remarkable gain in efficiency has been facilitated by increases in the availability of high-intensity X-ray beams, (ultra)fast detectors and high degrees of automation. These developments have in turn spurred the development of several dedicated centers for crystal-based fragment screening which enable the preparation and collection of hundreds of single-crystal diffraction datasets per day. Crystal structures of target proteins in complex with small-molecule ligands are of immense importance for structure-based drug design (SBDD) and their rapid turnover is a prerequisite for accelerated development cycles. While the experimental part of the process is well defined and has by now been established at several synchrotron sites, it is noticeable that software and algorithmic aspects have received far less attention, as well as the implications of new methodologies on established paradigms for structure determination, analysis, and visualization. We will review three key areas of development of large-scale protein-ligand studies. First, we will look into new software developments for batch data processing, followed by a discussion of the methodological changes in the analysis, modeling, refinement and deposition of structures for SBDD, and the changes in mindset that these new methods require, both on the side of depositors and users of macromolecular models. Finally, we will highlight key new developments for the presentation and analysis of the collections of structures that these experiments produce, and provide an outlook for future developments.

Mechanistic insights into the C55-P targeting lipopeptide antibiotics revealed by structure-activity studies and high-resolution crystal structures.

The continued rise of antibiotic resistance is a global concern that threatens to undermine many aspects of modern medical practice. Key to addressing this threat is the discovery and development of new antibiotics that operate by unexploited modes of action. The so-called calcium-dependent lipopeptide antibiotics (CDAs) are an important emerging class of natural products that provides a source of new antibiotic agents rich in structural and mechanistic diversity. Notable in this regard is the subset of CDAs comprising the laspartomycins and amphomycins/friulimicins that specifically target the bacterial cell wall precursor undecaprenyl phosphate (C55-P). In this study we describe the design and synthesis of new C55-P-targeting CDAs with structural features drawn from both the laspartomycin and amphomycin/friulimicin classes. Assessment of these lipopeptides revealed previously unknown and surprisingly subtle structural features that are required for antibacterial activity. High-resolution crystal structures further indicate that the amphomycin/friulimicin-like lipopeptides adopt a unique crystal packing that governs their interaction with C55-P and provides an explanation for their antibacterial effect. In addition, live-cell microscopy studies provide further insights into the biological activity of the C55-P targeting CDAs highlighting their unique mechanism of action relative to the clinically used CDA daptomycin.

Improving sampling of crystallographic disorder in ensemble refinement.

Ensemble refinement, the application of molecular dynamics to crystallographic refinement, explicitly models the disorder inherent in macromolecular structures. These ensemble models have been shown to produce more accurate structures than traditional single-model structures. However, suboptimal sampling of the molecular-dynamics simulation and modelling of crystallographic disorder has limited the utility of the method, and can lead to unphysical and strained models. Here, two improvements to the ensemble refinement method implemented within Phenix are presented: DEN restraints, which guide the local sampling of conformations and allow a more robust exploration of local conformational landscapes, and ECHT disorder models, which allow the selection of more physically meaningful and effective disorder models for parameterizing the continuous disorder components within a crystal. These improvements lead to more consistent and physically interpretable simulations of macromolecules in crystals, and allow structural heterogeneity and disorder to be systematically explored on different scales. The new approach is demonstrated on several case studies and the SARS-CoV-2 main protease, and demonstrates how the choice of disorder model affects the type of disorder that is sampled by the restrained molecular-dynamics simulation.

A method for intuitively extracting macromolecular dynamics from structural disorder.

Macromolecular dynamics manifest as disorder in structure determination, which is subsequently accounted for by displacement parameters (also called temperature factors, or B-factors) or alternate conformations. Though B-factors contain detailed information about structural dynamics, they are the total of multiple sources of disorder, making them difficult to interpret and thus little-used in structural analysis. We report here an analytical approach for decomposing molecular disorder into a parsimonious hierarchical series of contributions, providing an intuitive basis for quantitative structural-dynamics analysis. We demonstrate the decomposition of disorder on example SARS-CoV-2 and STEAP4 structures, from both crystallographic and cryo-electron microscopy data, and reveal how understanding of the macromolecular disorder leads to deeper understanding of molecular motions and flexibility, and suggests hypotheses for molecular mechanisms.

Crystallographic approach to fragment-based hit discovery against Schistosoma mansoni purine nucleoside phosphorylase.

Several Schistosoma species cause Schistosomiasis, an endemic disease in 78 countries that is ranked second amongst the parasitic diseases in terms of its socioeconomic impact and human health importance. The drug recommended for treatment by the WHO is praziquantel (PZQ), but there are concerns associated with PZQ, such as the lack of information about its exact mechanism of action, its high price, its effectiveness - which is limited to the parasite's adult form - and reports of resistance. The parasites lack the de novo purine pathway, rendering them dependent on the purine salvage pathway or host purine bases for nucleotide synthesis. Thus, the Schistosoma purine salvage pathway is an attractive target for the development of necessary and selective new drugs. In this study, the purine nucleotide phosphorylase II (PNP2), a new isoform of PNP1, was submitted to a high-throughput fragment-based hit discovery using a crystallographic screening strategy. PNP2 was crystallized and crystals were soaked with 827 fragments, a subset of the Maybridge 1000 library. X-ray diffraction data was collected and structures were solved. Out of 827-screened fragments we have obtained a total of 19 fragments that show binding to PNP2. Fourteen of these fragments bind to the active site of PNP2, while five were observed in three other sites. Here we present the first fragment screening against PNP2.

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source.

In fragment-based drug discovery, hundreds or often thousands of compounds smaller than ~300 Da are tested against the protein of interest to identify chemical entities that can be developed into potent drug candidates. Since the compounds are small, interactions are weak, and the screening method must therefore be highly sensitive; moreover, structural information tends to be crucial for elaborating these hits into lead-like compounds. Therefore, protein crystallography has always been a gold-standard technique, yet historically too challenging to find widespread use as a primary screen. Initial XChem experiments were demonstrated in 2014 and then trialed with academic and industrial collaborators to validate the process. Since then, a large research effort and significant beamtime have streamlined sample preparation, developed a fragment library with rapid follow-up possibilities, automated and improved the capability of I04-1 beamline for unattended data collection, and implemented new tools for data management, analysis and hit identification. XChem is now a facility for large-scale crystallographic fragment screening, supporting the entire crystals-to-deposition process, and accessible to academic and industrial users worldwide. The peer-reviewed academic user program has been actively developed since 2016, to accommodate projects from as broad a scientific scope as possible, including well-validated as well as exploratory projects. Academic access is allocated through biannual calls for peer-reviewed proposals, and proprietary work is arranged by Diamond's Industrial Liaison group. This workflow has already been routinely applied to over a hundred targets from diverse therapeutic areas, and effectively identifies weak binders (1%-30% hit rate), which both serve as high-quality starting points for compound design and provide extensive structural information on binding sites. The resilience of the process was demonstrated by continued screening of SARS-CoV-2 targets during the COVID-19 pandemic, including a 3-week turn-around for the main protease.

Bicyclic ß-Sheet Mimetics that Target the Transcriptional Coactivator ß-Catenin and Inhibit Wnt Signaling.

Protein complexes are defined by the three-dimensional structure of participating binding partners. Knowledge about these structures can facilitate the design of peptidomimetics which have been applied for example, as inhibitors of protein-protein interactions (PPIs). Even though ß-sheets participate widely in PPIs, they have only rarely served as the basis for peptidomimetic PPI inhibitors, in particular when addressing intracellular targets. Here, we present the structure-based design of ß-sheet mimetics targeting the intracellular protein ß-catenin, a central component of the Wnt signaling pathway. Based on a protein binding partner of ß-catenin, a macrocyclic peptide was designed and its crystal structure in complex with ß-catenin obtained. Using this structure, we designed a library of bicyclic ß-sheet mimetics employing a late-stage diversification strategy. Several mimetics were identified that compete with transcription factor binding to ß-catenin and inhibit Wnt signaling in cells. The presented design strategy can support the development of inhibitors for other ß-sheet-mediated PPIs.

Implications for tetraspanin-enriched microdomain assembly based on structures of CD9 with EWI-F.

Tetraspanins are eukaryotic membrane proteins that contribute to a variety of signaling processes by organizing partner-receptor molecules in the plasma membrane. How tetraspanins bind and cluster partner receptors into tetraspanin-enriched microdomains is unknown. Here, we present crystal structures of the large extracellular loop of CD9 bound to nanobodies 4C8 and 4E8 and, the cryo-EM structure of 4C8-bound CD9 in complex with its partner EWI-F. CD9-EWI-F displays a tetrameric arrangement with two central EWI-F molecules, dimerized through their ectodomains, and two CD9 molecules, one bound to each EWI-F transmembrane helix through CD9-helices h3 and h4. In the crystal structures, nanobodies 4C8 and 4E8 bind CD9 at loops C and D, which is in agreement with the 4C8 conformation in the CD9-EWI-F complex. The complex varies from nearly twofold symmetric (with the two CD9 copies nearly anti-parallel) to ca. 50° bent arrangements. This flexible arrangement of CD9-EWI-F with potential CD9 homo-dimerization at either end provides a "concatenation model" for forming short linear or circular assemblies, which may explain the occurrence of tetraspanin-enriched microdomains.

Insights Into Enhanced Complement Activation by Structures of Properdin and Its Complex With the C-Terminal Domain of C3b.

Properdin enhances complement-mediated opsonization of targeted cells and particles for immune clearance. Properdin occurs as dimers, trimers and tetramers in human plasma, which recognize C3b-deposited surfaces, promote formation, and prolong the lifetime of C3bBb-enzyme complexes that convert C3 into C3b, thereby enhancing the complement-amplification loop. Here, we report crystal structures of monomerized properdin, which was produced by co-expression of separate N- and C-terminal constructs that yielded monomer-sized properdin complexes that stabilized C3bBb. Consistent with previous low-resolution X-ray and EM data, the crystal structures revealed ring-shaped arrangements that are formed by interactions between thrombospondin type-I repeat (TSR) domains 4 and 6 of one protomer interacting with the N-terminal domain (which adopts a short transforming-growth factor B binding protein-like fold) and domain TSR1 of a second protomer, respectively. Next, a structure of monomerized properdin in complex with the C-terminal domain of C3b showed that properdin-domain TSR5 binds along the C-terminal α-helix of C3b, while two loops, one from domain TSR5 and one from TSR6, extend and fold around the C3b C-terminus like stirrups. This suggests a mechanistic model in which these TSR5 and TSR6 "stirrups" bridge interactions between C3b and factor B or its fragment Bb, and thereby enhance formation of C3bB pro-convertases and stabilize C3bBb convertases. In addition, properdin TSR6 would sterically block binding of the protease factor I to C3b, thus limiting C3b proteolytic degradation. The presence of a valine instead of a third tryptophan in the canonical Trp-ladder of TSR domains in TSR4 allows a remarkable ca. 60°-domain bending motion of TSR4. Together with variable positioning of TSR2 and, putatively, TSR3, this explains the conformational flexibility required for properdin to form dimers, trimers, and tetramers. In conclusion, the results indicate that binding avidity of oligomeric properdin is needed to distinguish surface-deposited C3b molecules from soluble C3b or C3 and suggest that properdin-mediated interactions bridging C3b-B and C3b-Bb enhance affinity, thus promoting convertase formation and stabilization. These mechanisms explain the enhancement of complement-mediated opsonization of targeted cells and particle for immune clearance.

An expanded allosteric network in PTP1B by multitemperature crystallography, fragment screening, and covalent tethering.

Allostery is an inherent feature of proteins, but it remains challenging to reveal the mechanisms by which allosteric signals propagate. A clearer understanding of this intrinsic circuitry would afford new opportunities to modulate protein function. Here, we have identified allosteric sites in protein tyrosine phosphatase 1B (PTP1B) by combining multiple-temperature X-ray crystallography experiments and structure determination from hundreds of individual small-molecule fragment soaks. New modeling approaches reveal 'hidden' low-occupancy conformational states for protein and ligands. Our results converge on allosteric sites that are conformationally coupled to the active-site WPD loop and are hotspots for fragment binding. Targeting one of these sites with covalently tethered molecules or mutations allosterically inhibits enzyme activity. Overall, this work demonstrates how the ensemble nature of macromolecular structure, revealed here by multitemperature crystallography, can elucidate allosteric mechanisms and open new doors for long-range control of protein function.

A multi-crystal method for extracting obscured crystallographic states from conventionally uninterpretable electron density.

In macromolecular crystallography, the rigorous detection of changed states (for example, ligand binding) is difficult unless signal is strong. Ambiguous ('weak' or 'noisy') density is experimentally common, since molecular states are generally only fractionally present in the crystal. Existing methodologies focus on generating maximally accurate maps whereby minor states become discernible; in practice, such map interpretation is disappointingly subjective, time-consuming and methodologically unsound. Here we report the PanDDA method, which automatically reveals clear electron density for the changed state-even from inaccurate maps-by subtracting a proportion of the confounding 'ground state'; changed states are objectively identified from statistical analysis of density distributions. The method is completely general, implying new best practice for all changed-state studies, including the routine collection of multiple ground-state crystals. More generally, these results demonstrate: the incompleteness of atomic models; that single data sets contain insufficient information to model them fully; and that accuracy requires further map-deconvolution approaches.

Partial-occupancy binders identified by the Pan-Dataset Density Analysis method offer new chemical opportunities and reveal cryptic binding sites.

Crystallographic fragment screening uses low molecular weight compounds to probe the protein surface and although individual protein-fragment interactions are high quality, fragments commonly bind at low occupancy, historically making identification difficult. However, our new Pan-Dataset Density Analysis method readily identifies binders missed by conventional analysis: for fragment screening data of lysine-specific demethylase 4D (KDM4D), the hit rate increased from 0.9% to 10.6%. Previously unidentified fragments reveal multiple binding sites and demonstrate: the versatility of crystallographic fragment screening; that surprisingly large conformational changes are possible in crystals; and that low crystallographic occupancy does not by itself reflect a protein-ligand complex's significance.

Gentle, fast and effective crystal soaking by acoustic dispensing.

The steady expansion in the capacity of modern beamlines for high-throughput data collection, enabled by increasing X-ray brightness, capacity of robotics and detector speeds, has pushed the bottleneck upstream towards sample preparation. Even in ligand-binding studies using crystal soaking, the experiment best able to exploit beamline capacity, a primary limitation is the need for gentle and nontrivial soaking regimens such as stepwise concentration increases, even for robust and well characterized crystals. Here, the use of acoustic droplet ejection for the soaking of protein crystals with small molecules is described, and it is shown that it is both gentle on crystals and allows very high throughput, with 1000 unique soaks easily performed in under 10 min. In addition to having very low compound consumption (tens of nanolitres per sample), the positional precision of acoustic droplet ejection enables the targeted placement of the compound/solvent away from crystals and towards drop edges, allowing gradual diffusion of solvent across the drop. This ensures both an improvement in the reproducibility of X-ray diffraction and increased solvent tolerance of the crystals, thus enabling higher effective compound-soaking concentrations. The technique is detailed here with examples from the protein target JMJD2D, a histone lysine demethylase with roles in cancer and the focus of active structure-based drug-design efforts.

Proper modelling of ligand binding requires an ensemble of bound and unbound states.

Although noncovalent binding by small molecules cannot be assumed a priori to be stoichiometric in the crystal lattice, occupancy refinement of ligands is often avoided by convention. Occupancies tend to be set to unity, requiring the occupancy error to be modelled by the B factors, and residual weak density around the ligand is necessarily attributed to `disorder'. Where occupancy refinement is performed, the complementary, superposed unbound state is rarely modelled. Here, it is shown that superior accuracy is achieved by modelling the ligand as partially occupied and superposed on a ligand-free `ground-state' model. Explicit incorporation of this model of the crystal, obtained from a reference data set, allows constrained occupancy refinement with minimal fear of overfitting. Better representation of the crystal also leads to more meaningful refined atomic parameters such as the B factor, allowing more insight into dynamics in the crystal. An outline of an approach for algorithmically generating ensemble models of crystals is presented, assuming that data sets representing the ground state are available. The applicability of various electron-density metrics to the validation of the resulting models is assessed, and it is concluded that ensemble models consistently score better than the corresponding single-state models. Furthermore, it appears that ignoring the superposed ground state becomes the dominant source of model error, locally, once the overall model is accurate enough; modelling the local ground state properly is then more meaningful than correcting all remaining model errors globally, especially for low-occupancy ligands. Implications for the simultaneous refinement of B factors and occupancies, and for future evaluation of the limits of the approach, in particular its behaviour at lower data resolution, are discussed.