What can AlphaFold do for antimicrobial amyloids?

Amyloids, protein, and peptide assemblies in various organisms are crucial in physiological and pathological processes. Their intricate structures, however, present significant challenges, limiting our understanding of their functions, regulatory mechanisms, and potential applications in biomedicine and technology. This study evaluated the AlphaFold2 ColabFold method's structure predictions for antimicrobial amyloids, using eight antimicrobial peptides (AMPs), including those with experimentally determined structures and AMPs known for their distinct amyloidogenic morphological features. Additionally, two well-known human amyloids, amyloid-ß and islet amyloid polypeptide, were included in the analysis due to their disease relevance, short sequences, and antimicrobial properties. Amyloids typically exhibit tightly mated ß-strand sheets forming a cross-ß configuration. However, certain amphipathic α-helical subunits can also form amyloid fibrils adopting a cross-α structure. Some AMPs in the study exhibited a combination of cross-α and cross-ß amyloid fibrils, adding complexity to structure prediction. The results showed that the AlphaFold2 ColabFold models favored α-helical structures in the tested amyloids, successfully predicting the presence of α-helical mated sheets and a hydrophobic core resembling the cross-α configuration. This implies that the AI-based algorithms prefer assemblies of the monomeric state, which was frequently predicted as helical, or capture an α-helical membrane-active form of toxic peptides, which is triggered upon interaction with lipid membranes.

Gram-negative outer-membrane proteins with multiple ß-barrel domains.

Outer-membrane beta barrels (OMBBs) are found in the outer membrane of gram-negative bacteria and eukaryotic organelles. OMBBs fold as antiparallel ß-sheets that close onto themselves, forming pores that traverse the membrane. Currently known structures include only one barrel, of 8 to 36 strands, per chain. The lack of multi-OMBB chains is surprising, as most OMBBs form oligomers, and some function only in this state. Using a combination of sensitive sequence comparison methods and coevolutionary analysis tools, we identify many proteins combining multiple beta barrels within a single chain; combinations that include eight-stranded barrels prevail. These multibarrels seem to be the result of independent, lineage-specific fusion and amplification events. The absence of multibarrels that are universally conserved in bacteria with an outer membrane, coupled with their frequent de novo genesis, suggests that their functions are not essential but rather beneficial in specific environments. Adjacent barrels of complementary function within the same chain may allow for functions beyond those of the individual barrels.

The copper-linked Escherichia coli AZY operon: Structure, metal binding, and a possible physiological role in copper delivery.

The Escherichia coli yobA-yebZ-yebY (AZY) operon encodes the proteins YobA, YebZ, and YebY. YobA and YebZ are homologs of the CopC periplasmic copper-binding protein and the CopD putative copper importer, respectively, whereas YebY belongs to the uncharacterized Domain of Unknown Function 2511 family. Despite numerous studies of E. coli copper homeostasis and the existence of the AZY operon in a range of bacteria, the operon's proteins and their functional roles have not been explored. In this study, we present the first biochemical and functional studies of the AZY proteins. Biochemical characterization and structural modeling indicate that YobA binds a single Cu2+ ion with high affinity. Bioinformatics analysis shows that YebY is widespread and encoded either in AZY operons or in other genetic contexts unrelated to copper homeostasis. We also determined the 1.8 Å resolution crystal structure of E. coli YebY, which closely resembles that of the lantibiotic self-resistance protein MlbQ. Two strictly conserved cysteine residues form a disulfide bond, consistent with the observed periplasmic localization of YebY. Upon treatment with reductants, YebY binds Cu+ and Cu2+ with low affinity, as demonstrated by metal-binding analysis and tryptophan fluorescence. Finally, genetic manipulations show that the AZY operon is not involved in copper tolerance or antioxidant defense. Instead, YebY and YobA are required for the activity of the copper-related NADH dehydrogenase II. These results are consistent with a potential role of the AZY operon in copper delivery to membrane proteins.

PredictProtein - Predicting Protein Structure and Function for 29 Years.

Since 1992 PredictProtein (https://predictprotein.org) is a one-stop online resource for protein sequence analysis with its main site hosted at the Luxembourg Centre for Systems Biomedicine (LCSB) and queried monthly by over 3,000 users in 2020. PredictProtein was the first Internet server for protein predictions. It pioneered combining evolutionary information and machine learning. Given a protein sequence as input, the server outputs multiple sequence alignments, predictions of protein structure in 1D and 2D (secondary structure, solvent accessibility, transmembrane segments, disordered regions, protein flexibility, and disulfide bridges) and predictions of protein function (functional effects of sequence variation or point mutations, Gene Ontology (GO) terms, subcellular localization, and protein-, RNA-, and DNA binding). PredictProtein's infrastructure has moved to the LCSB increasing throughput; the use of MMseqs2 sequence search reduced runtime five-fold (apparently without lowering performance of prediction methods); user interface elements improved usability, and new prediction methods were added. PredictProtein recently included predictions from deep learning embeddings (GO and secondary structure) and a method for the prediction of proteins and residues binding DNA, RNA, or other proteins. PredictProtein.org aspires to provide reliable predictions to computational and experimental biologists alike. All scripts and methods are freely available for offline execution in high-throughput settings.

On the evolution of protein-adenine binding.

Proteins' interactions with ancient ligands may reveal how molecular recognition emerged and evolved. We explore how proteins recognize adenine: a planar rigid fragment found in the most common and ancient ligands. We have developed a computational pipeline that extracts protein-adenine complexes from the Protein Data Bank, structurally superimposes their adenine fragments, and detects the hydrogen bonds mediating the interaction. Our analysis extends the known motifs of protein-adenine interactions in the Watson-Crick edge of adenine and shows that all of adenine's edges may contribute to molecular recognition. We further show that, on the proteins' side, binding is often mediated by specific amino acid segments ("themes") that recur across different proteins, such that different proteins use the same themes when binding the same adenine-containing ligands. We identify numerous proteins that feature these themes and are thus likely to bind adenine-containing ligands. Our analysis suggests that adenine binding has emerged multiple times in evolution.

An angular motion of a conserved four-helix bundle facilitates alternating access transport in the TtNapA and EcNhaA transporters.

There is ongoing debate regarding the mechanism through which cation/proton antiporters (CPAs), like Thermus thermophilus NapA (TtNapA) and Escherichia coli NapA (EcNhaA), alternate between their outward- and inward-facing conformations in the membrane. CPAs comprise two domains, and it is unclear whether the transition is driven by their rocking-bundle or elevator motion with respect to each other. Here we address this question using metadynamics simulations of TtNapA, where we bias conformational sampling along two axes characterizing the two proposed mechanisms: angular and translational motions, respectively. By applying the bias potential for the two axes simultaneously, as well as to the angular, but not the translational, axis alone, we manage to reproduce each of the two known states of TtNapA when starting from the opposite state, in support of the rocking-bundle mechanism as the driver of conformational change. Next, starting from the inward-facing conformation of EcNhaA, we sample what could be its long-sought-after outward-facing conformation and verify it using cross-linking experiments.

Identification and Analysis of Fungal-Specific Regions in the Aspergillus fumigatus Cu Exporter CrpA That Are Essential for Cu Resistance but Not for Virulence.

The opportunistic fungus Aspergillus fumigatus is the primary invasive mold pathogen in humans, and is responsible for an estimated 200,000 yearly deaths worldwide. Most fatalities occur in immunocompromised patients who lack the cellular and humoral defenses necessary to halt the pathogen's advance, primarily in the lungs. One of the cellular responses used by macrophages to counteract fungal infection is the accumulation of high phagolysosomal Cu levels to destroy ingested pathogens. A. fumigatus responds by activating high expression levels of crpA, which encodes a Cu+ P-type ATPase that actively transports excess Cu from the cytoplasm to the extracellular environment. In this study, we used a bioinformatics approach to identify two fungal-unique regions in CrpA that we studied by deletion/replacement, subcellular localization, Cu sensitivity in vitro, killing by mouse alveolar macrophages, and virulence in a mouse model of invasive pulmonary aspergillosis. Deletion of CrpA fungal-unique amino acids 1-211 containing two N-terminal Cu-binding sites, moderately increased Cu-sensitivity but did not affect expression or localization to the endoplasmic reticulum (ER) and cell surface. Replacement of CrpA fungal-unique amino acids 542-556 consisting of an intracellular loop between the second and third transmembrane helices resulted in ER retention of the protein and strongly increased Cu-sensitivity. Deleting CrpA N-terminal amino acids 1-211 or replacing amino acids 542-556 also increased sensitivity to killing by mouse alveolar macrophages. Surprisingly, the two mutations did not affect virulence in a mouse model of infection, suggesting that even weak Cu-efflux activity by mutated CrpA preserves fungal virulence.

The Sigma-1 receptor is an ER-localized type II membrane protein.

The Sigma-1 receptor (S1R) is a transmembrane protein with important roles in cellular homeostasis in normal physiology and in disease. Especially in neurodegenerative diseases, S1R activation has been shown to provide neuroprotection by modulating calcium signaling, mitochondrial function and reducing endoplasmic reticulum (ER) stress. S1R missense mutations are one of the causes of the neurodegenerative Amyotrophic Lateral Sclerosis and distal hereditary motor neuronopathies. Although the S1R has been studied intensively, basic aspects remain controversial, such as S1R topology and whether it reaches the plasma membrane. To address these questions, we have undertaken several approaches. C-terminal tagging with a small biotin-acceptor peptide and BirA biotinylation in cells suggested a type II membrane orientation (cytosolic N-terminus). However, N-terminal tagging gave an equal probability for both possible orientations. This might explain conflicting reports in the literature, as tags may affect the protein topology. Therefore, we studied untagged S1R using a protease protection assay and a glycosylation mapping approach, introducing N-glycosylation sites. Both methods provided unambiguous results showing that the S1R is a type II membrane protein with a short cytosolic N-terminal tail. Assessments of glycan processing, surface fluorescence-activated cell sorting, and cell surface biotinylation indicated ER retention, with insignificant exit to the plasma membrane, in the absence or presence of S1R agonists or of ER stress. These findings may have important implications for S1R-based therapeutic approaches.

Titratable transmembrane residues and a hydrophobic plug are essential for manganese import via the Bacillus anthracis ABC transporter MntBC-A.

All extant life forms require trace transition metals (e.g., Fe2/3+, Cu1/2+, and Mn2+) to survive. However, as these are environmentally scarce, organisms have evolved sophisticated metal uptake machineries. In bacteria, high-affinity import of transition metals is predominantly mediated by ABC transporters. During bacterial infection, sequestration of metal by the host further limits the availability of these ions, and accordingly, bacterial ABC transporters (importers) of metals are key virulence determinants. However, the structure-function relationships of these metal transporters have not been fully elucidated. Here, we used metal-sensitivity assays, advanced structural modeling, and enzymatic assays to study the ABC transporter MntBC-A, a virulence determinant of the bacterial human pathogen Bacillus anthracis. We find that despite its broad metal-recognition profile, MntBC-A imports only manganese, whereas zinc can function as a high-affinity inhibitor of MntBC-A. Computational analysis shows that the transmembrane metal permeation pathway is lined with six titratable residues that can coordinate the positively charged metal, and mutagenesis studies show that they are essential for manganese transport. Modeling suggests that access to these titratable residues is blocked by a ladder of hydrophobic residues, and ATP-driven conformational changes open and close this hydrophobic seal to permit metal binding and release. The conservation of this arrangement of titratable and hydrophobic residues among ABC transporters of transition metals suggests a common mechanism. These findings advance our understanding of transmembrane metal recognition and permeation and may aid the design and development of novel antibacterial agents.

Bridging Themes: Short Protein Segments Found in Different Architectures.

The vast majority of theoretically possible polypeptide chains do not fold, let alone confer function. Hence, protein evolution from preexisting building blocks has clear potential advantages over ab initio emergence from random sequences. In support of this view, sequence similarities between different proteins is generally indicative of common ancestry, and we collectively refer to such homologous sequences as "themes." At the domain level, sequence homology is routinely detected. However, short themes which are segments, or fragments of intact domains, are particularly interesting because they may provide hints about the emergence of domains, as opposed to divergence of preexisting domains, or their mixing-and-matching to form multi-domain proteins. Here we identified 525 representative short themes, comprising 20-80 residues that are unexpectedly shared between domains considered to have emerged independently. Among these "bridging themes" are ones shared between the most ancient domains, for example, Rossmann, P-loop NTPase, TIM-barrel, flavodoxin, and ferredoxin-like. We elaborate on several particularly interesting cases, where the bridging themes mediate ligand binding. Ligand binding may have contributed to the stability and the plasticity of these building blocks, and to their ability to invade preexisting domains or serve as starting points for completely new domains.

C5 conserved region of hydrophilic C-terminal part of Saccharomyces cerevisiae Nha1 antiporter determines its requirement of Erv14 COPII cargo receptor for plasma-membrane targeting.

Erv14, a conserved cargo receptor of COPII vesicles, helps the proper trafficking of many but not all transporters to the yeast plasma membrane, for example, three out of five alkali-metal-cation transporters in Saccharomyces cerevisiae. Among them, the Nha1 cation/proton antiporter, which participates in cell cation and pH homeostasis, is a large membrane protein (985 aa) possessing a long hydrophilic C-terminus (552 aa) containing six conserved regions (C1-C6) with unknown function. A short Nha1 version, lacking almost the entire C-terminus, still binds to Erv14 but does not need it to be targeted to the plasma membrane. Comparing the localization and function of ScNha1 variants shortened at its C-terminus in cells with or without Erv14 reveals that only ScNha1 versions possessing the complete C5 region are dependent on Erv14. In addition, our broad evolutionary conservation analysis of fungal Na+ /H+ antiporters identified new conserved regions in their C-termini, and our experiments newly show C5 and other, so far unknown, regions of the C-terminus, to be involved in the functionality and substrate specificity of ScNha1. Taken together, our results reveal that also relatively small hydrophilic parts of some yeast membrane proteins underlie their need to interact with the Erv14 cargo receptor.

Structure of plant photosystem I-plastocyanin complex reveals strong hydrophobic interactions.

Photosystem I is defined as plastocyanin-ferredoxin oxidoreductase. Taking advantage of genetic engineering, kinetic analyses and cryo-EM, our data provide novel mechanistic insights into binding and electron transfer between PSI and Pc. Structural data at 2.74 Šresolution reveals strong hydrophobic interactions in the plant PSI-Pc ternary complex, leading to exclusion of water molecules from PsaA-PsaB/Pc interface once the PSI-Pc complex forms. Upon oxidation of Pc, a slight tilt of bound oxidized Pc allows water molecules to accommodate the space between Pc and PSI to drive Pc dissociation. Such a scenario is consistent with the six times larger dissociation constant of oxidized as compared with reduced Pc and mechanistically explains how this molecular machine optimized electron transfer for fast turnover.

Substrate recognition and ATPase activity of the E. coli cysteine/cystine ABC transporter YecSC-FliY.

Sulfur is essential for biological processes such as amino acid biogenesis, iron-sulfur cluster formation, and redox homeostasis. To acquire sulfur-containing compounds from the environment, bacteria have evolved high-affinity uptake systems, predominant among which is the ABC transporter family. Theses membrane-embedded enzymes use the energy of ATP hydrolysis for transmembrane transport of a wide range of biomolecules against concentration gradients. Three distinct bacterial ABC import systems of sulfur-containing compounds have been identified, but the molecular details of their transport mechanism remain poorly characterized. Here we provide results from a biochemical analysis of the purified Escherichia coli YecSC-FliY cysteine/cystine import system. We found that the substrate-binding protein FliY binds l-cystine, l-cysteine, and d-cysteine with micromolar affinities. However, binding of the l- and d-enantiomers induced different conformational changes of FliY, where the l- enantiomer-substrate-binding protein complex interacted more efficiently with the YecSC transporter. YecSC had low basal ATPase activity that was moderately stimulated by apo FliY, more strongly by d-cysteine-bound FliY, and maximally by l-cysteine- or l-cystine-bound FliY. However, at high FliY concentrations, YecSC reached maximal ATPase rates independent of the presence or nature of the substrate. These results suggest that FliY exists in a conformational equilibrium between an open, unliganded form that does not bind to the YecSC transporter and closed, unliganded and closed, liganded forms that bind this transporter with variable affinities but equally stimulate its ATPase activity. These findings differ from previous observations for similar ABC transporters, highlighting the extent of mechanistic diversity in this large protein family.

Potential Antigenic Cross-reactivity Between Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Dengue Viruses.

BACKGROUND: Coronavirus disease 2019 (COVID-19) and dengue fever are difficult to distinguish given shared clinical and laboratory features. Failing to consider COVID-19 due to false-positive dengue serology can have serious implications. We aimed to assess this possible cross-reactivity. METHODS: We analyzed clinical data and serum samples from 55 individuals with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. To assess dengue serology status, we used dengue-specific antibodies by means of lateral-flow rapid test, as well as enzyme-linked immunosorbent assay (ELISA). Additionally, we tested SARS-CoV-2 serology status in patients with dengue and performed in-silico protein structural analysis to identify epitope similarities. RESULTS: Using the dengue lateral-flow rapid test we detected 12 positive cases out of the 55 (21.8%) COVID-19 patients versus zero positive cases in a control group of 70 healthy individuals (P = 2.5E-5). This includes 9 cases of positive immunoglobulin M (IgM), 2 cases of positive immunoglobulin G (IgG), and 1 case of positive IgM as well as IgG antibodies. ELISA testing for dengue was positive in 2 additional subjects using envelope protein directed antibodies. Out of 95 samples obtained from patients diagnosed with dengue before September 2019, SARS-CoV-2 serology targeting the S protein was positive/equivocal in 21 (22%) (16 IgA, 5 IgG) versus 4 positives/equivocal in 102 controls (4%) (P = 1.6E-4). Subsequent in-silico analysis revealed possible similarities between SARS-CoV-2 epitopes in the HR2 domain of the spike protein and the dengue envelope protein. CONCLUSIONS: Our findings support possible cross-reactivity between dengue virus and SARS-CoV-2, which can lead to false-positive dengue serology among COVID-19 patients and vice versa. This can have serious consequences for both patient care and public health.

A natural upper bound to the accuracy of predicting protein stability changes upon mutations.

MOTIVATION: Accurate prediction of protein stability changes upon single-site variations (ΔΔG) is important for protein design, as well as for our understanding of the mechanisms of genetic diseases. The performance of high-throughput computational methods to this end is evaluated mostly based on the Pearson correlation coefficient between predicted and observed data, assuming that the upper bound would be 1 (perfect correlation). However, the performance of these predictors can be limited by the distribution and noise of the experimental data. Here we estimate, for the first time, a theoretical upper-bound to the ΔΔG prediction performances imposed by the intrinsic structure of currently available ΔΔG data. RESULTS: Given a set of measured ΔΔG protein variations, the theoretically "best predictor" is estimated based on its similarity to another set of experimentally determined ΔΔG values. We investigate the correlation between pairs of measured ΔΔG variations, where one is used as a predictor for the other. We analytically derive an upper bound to the Pearson correlation as a function of the noise and distribution of the ΔΔG data. We also evaluate the available datasets to highlight the effect of the noise in conjunction with ΔΔG distribution. We conclude that the upper bound is a function of both uncertainty and spread of the ΔΔG values, and that with current data the best performance should be between 0.7 and 0.8, depending on the dataset used; higher Pearson correlations might be indicative of overtraining. It also follows that comparisons of predictors using different datasets are inherently misleading. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Single-molecule probing of the conformational homogeneity of the ABC transporter BtuCD.

ATP-binding cassette (ABC) transporters use the energy of ATP hydrolysis to move molecules through cellular membranes. They are directly linked to human diseases, cancer multidrug resistance, and bacterial virulence. Very little is known of the conformational dynamics of ABC transporters, especially at the single-molecule level. Here, we combine single-molecule spectroscopy and a novel molecular simulation approach to investigate the conformational dynamics of the ABC transporter BtuCD. We observe a single dominant population of molecules in each step of the transport cycle and tight coupling between conformational transitions and ligand binding. We uncover transient conformational changes that allow substrate to enter the transporter. This is followed by a 'squeezing' motion propagating from the extracellular to the intracellular side of the translocation cavity. This coordinated sequence of events provides a mechanism for the unidirectional transport of vitamin B12 by BtuCD.

Complex evolutionary footprints revealed in an analysis of reused protein segments of diverse lengths.

Proteins share similar segments with one another. Such "reused parts"-which have been successfully incorporated into other proteins-are likely to offer an evolutionary advantage over de novo evolved segments, as most of the latter will not even have the capacity to fold. To systematically explore the evolutionary traces of segment "reuse" across proteins, we developed an automated methodology that identifies reused segments from protein alignments. We search for "themes"-segments of at least 35 residues of similar sequence and structure-reused within representative sets of 15,016 domains [Evolutionary Classification of Protein Domains (ECOD) database] or 20,398 chains [Protein Data Bank (PDB)]. We observe that theme reuse is highly prevalent and that reuse is more extensive when the length threshold for identifying a theme is lower. Structural domains, the best characterized form of reuse in proteins, are just one of many complex and intertwined evolutionary traces. Others include long themes shared among a few proteins, which encompass and overlap with shorter themes that recur in numerous proteins. The observed complexity is consistent with evolution by duplication and divergence, and some of the themes might include descendants of ancestral segments. The observed recursive footprints, where the same amino acid can simultaneously participate in several intertwined themes, could be a useful concept for protein design. Data are available at http://trachel-srv.cs.haifa.ac.il/rachel/ppi/themes/.

DDGun: an untrained method for the prediction of protein stability changes upon single and multiple point variations.

BACKGROUND: Predicting the effect of single point variations on protein stability constitutes a crucial step toward understanding the relationship between protein structure and function. To this end, several methods have been developed to predict changes in the Gibbs free energy of unfolding (∆∆G) between wild type and variant proteins, using sequence and structure information. Most of the available methods however do not exhibit the anti-symmetric prediction property, which guarantees that the predicted ∆∆G value for a variation is the exact opposite of that predicted for the reverse variation, i.e., ∆∆G(A → B) = -∆∆G(B → A), where A and B are amino acids. RESULTS: Here we introduce simple anti-symmetric features, based on evolutionary information, which are combined to define an untrained method, DDGun (DDG untrained). DDGun is a simple approach based on evolutionary information that predicts the ∆∆G for single and multiple variations from sequence and structure information (DDGun3D). Our method achieves remarkable performance without any training on the experimental datasets, reaching Pearson correlation coefficients between predicted and measured ∆∆G values of ~ 0.5 and ~ 0.4 for single and multiple site variations, respectively. Surprisingly, DDGun performances are comparable with those of state of the art methods. DDGun also naturally predicts multiple site variations, thereby defining a benchmark method for both single site and multiple site predictors. DDGun is anti-symmetric by construction predicting the value of the ∆∆G of a reciprocal variation as almost equal (depending on the sequence profile) to -∆∆G of the direct variation. This is a valuable property that is missing in the majority of the methods. CONCLUSIONS: Evolutionary information alone combined in an untrained method can achieve remarkably high performances in the prediction of ∆∆G upon protein mutation. Non-trained approaches like DDGun represent a valid benchmark both for scoring the predictive power of the individual features and for assessing the learning capability of supervised methods.

Metal Coordination Is Crucial for Geranylgeranyl Diphosphate Synthase-Bisphosphonate Interactions: A Crystallographic and Computational Analysis.

Geranylgeranyl diphosphate synthase (GGPPS) is a central metalloenzyme in the mevalonate pathway, crucial for the prenylation of small GTPases. As small GTPases are pivotal for cellular survival, GGPPS was highlighted as a potential target for treating human diseases, including solid and hematologic malignancies and parasitic infections. Most available GGPPS inhibitors are bisphosphonates, but the clinically available compounds demonstrate poor pharmacokinetic properties. Although the design of novel bisphosphonates with improved physicochemical properties is highly desirable, the structure of wild-type human GGPPS (hGGPPS) bound to a bisphosphonate has not been resolved. Moreover, various metal-bisphosphonate-binding stoichiometries were previously reported in structures of yeast GGPPS (yGGPPS), hampering computational drug design with metal-binding pharmacophores (MBP). In this study, we report the 2.2 Å crystal structure of hGGPPS in complex with ibandronate, clearly depicting the involvement of three Mg2+ ions in bisphosphonate-protein interactions. Using drug-binding assays and computational docking, we show that the assignment of three Mg2+ ions to the binding site of both hGGPPS and yGGPPS greatly improves the correlation between calculated binding energies and experimentally measured affinities. This work provides a structural basis for future rational design of additional MBP-harboring drugs targeting hGGPPS. SIGNIFICANCE STATEMENT: Bisphosphonates are inhibitors of geranylgeranyl diphosphate synthase (GGPPS), a metalloenzyme crucial for cell survival. Bisphosphonate binding depends on coordination by Mg2+ ions, but various Mg2+-bisphosphonate-binding stoichiometries were previously reported. In this study, we show that three Mg2+ ions are vital for drug binding and provide a structural basis for future computational design of GGPPS inhibitors.

BcXYG1, a Secreted Xyloglucanase from Botrytis cinerea, Triggers Both Cell Death and Plant Immune Responses.

In search of Botrytis cinerea cell death-inducing proteins, we found a xyloglucanase (BcXYG1) that induced strong necrosis and a resistance response in dicot plants. Expression of the BcXYG1 gene was strongly induced during the first 12 h post inoculation, and analysis of disease dynamics using PathTrack showed that a B. cinerea strain overexpressing BcXYG1 produced early local necrosis, supporting a role of BcXYG1 as an early cell death-inducing factor. The xyloglucanase activity of BcXYG1 was not necessary for the induction of necrosis and plant resistance, as a mutant of BcXYG1 lacking the xyloglucanase enzymatic activity retained both functions. Residues in two exposed loops on the surface of BcXYG1 were found to be necessary for the induction of cell death but not to induce plant resistance. Further analyses showed that BcXYG1 is apoplastic and possibly interacts with the proteins of the plant cell membrane and also that the BcXYG1 cell death-promoting signal is mediated by the leucine-rich repeat receptor-like kinases BAK1 and SOBIR1. Our findings support the role of cell death-inducing proteins in establishing the infection of necrotrophic pathogens and highlight the recognition of fungal apoplastic proteins by the plant immune system as an important mechanism of resistance against this class of pathogens.