Quantitative imaging biomarkers are becoming usual in oncology for assessing therapy response. The harmonization of image quantitation reporting has become of utmost importance due to the multi-center trials increase. The NEMA image quality test is often considered for the evaluation of quantitation and is more accurate with a radioactive solid phantom that reduces variability. The goal of this project is to determine the level of variability among imaging centers if acquisition and imaging protocol parameters are left to the center’s preference while all other parameters are fixed including the scanner type.68Ge solid resin was imaged in five clinical sites throughout Europe. Sites reconstructed data with OSEM and BSREM algorithms applying the sites’ clinical parameters. Images were analyzed according with the NEMA-NU2-2012 standard using the manufacturer-provided NEMA tools to calculate contrast recovery (CR) and background variability (BV) for each sphere and the lung error (LE) estimation. In addition, a 18F-filled NEMA-IQ phantom was also evaluated to obtain a gauge for variability among centers when the sites were provided with identical specific instructions for acquisition and reconstruction protocol .A NEMA-IQ phantom filled with radioactive 68Ge solid phantom showed no statistical differences among different sites, proving a very good reproducibility among the PET center models even if dispersion of data is higher with OSEM compared to BSREM. Furthermore, BSREM shows better CR and comparable BV, while LE is slightly reduced. Two centers exhibit significant differences in CR and BV values for the 18F NEMA NU2-2012 experiments; these outlier results are explained.The data using the The same PET system type from the various sites produced similar quantitative results, despite allowing each site to choose their clinical protocols with no restriction on data acquisition and reconstruction parameters. BSREM leads to lower dispersion of quantitative data among different sites. A solid radioactive phantom may be recommended to qualify the sites to perform quantitative imaging. The current clinical trend is to use PET/CT as a quantitative biomarker in oncology for assessing the reliable evaluation of lesion’s uptake changes over time. The standardized uptake value (SUV) is still the standard quantitative index in positron emission tomography (PET), but new surrogates are now reported as references like response criteria in solid tumors (PERCIST) , metabolFor all these new quantitative indexes, long-term accuracy and reproducibility are mandatory , 4. NeveChauvie et al.  clearly Encouraged by the above evidence, we aimed in this research to evaluate the relevance of mixing quantitative results coming from multisite PET exams among European facilities involved in a multi-center clinical trial. The QUICK project (Quantitation Unified Intercomparison Control Kit) was launched with the purpose of evaluating the impact of clinical protocol differences over scanner introduced variability. We realize the variability introduced with different scanner types is the ultimate goal for such a comparison, but we focus on protocol variability impact first as the initial step to understand the larger picture.With the purpose of understanding the impact of different scanner operators, the same acquisitions and reconstructions were done on each site using the QUICK phantom. This step was followed with a series of acquisitions and reconstructions using local setup preferences as well as the site’s recommendations for clinical reconstruction.The final statistical analysis of all data provided by the sites was expected to point out the impact of sites’ clinical practice on absolute quantitation in terms of contrast recovery, background variability, and lung error.Results obtained using optimized protocols should be compared within the different participating sites to evaluate the global achievable accuracy of the multi-center clinical trials.In summary, the aim of this study was to estimate the global statistical multi-center quantitation accuracy taking into account the discrepancies between participating PET facilities, using a solid phantom with fixed and accurately known activities and volumes.The auxiliary aim of this collaborative work was to evaluate the impact of BSREM reconstruction on quantitation reliability, which is a unique feature of GE’s D-IQ PET-CT scanner selected for this multi-center study.All the participating sites were equipped with a GE Discovery IQ PET/CT system, which is a state-of-the-art bismuth germanate (BGO) PET. It offers very high sensitivity and, associated with a new regularization algorithm (BSREM) named Q.Clear , raises The acquisitions were performed by medical physicists on fully calibrated PET/CT scanners.In order to evaluate quantitation performance, the NEMA-defined parameters contrast recovery (CR) and background variability (BV) were collected and analyzed –15.β) is directly correlated with CR and BV. Consequently, it is relevant to this study to keep track of the site’s preference in β value selection. This penalty term provides level of regularization based on the difference between neighboring voxels as well as their sum.In the BSREM reconstruction algorithm, the noise penalty function strength named “Beta ” (68Ge phantom (QUICK phantom) based on IEC61675/NEMA Body IQ phantom geometry and activity concentrations was manufactured for this study allowing a better identification of the eventual causes of quantitative discrepancies among the participating sites.A solid In order to avoid discrepancies related to data analysis in each participating site, it was decided to use the built-in software provided by GE Healthcare and available on operating console to perform NEMA NU-2 2012 image quality test.18F-FDG phantom from seventeen different sites across Europe were combined. Each of the participating sites followed the manufacturer-provided protocol conducting three acquisitions with the IEC61675/NEMA NU2-2012 PET Image Quality Body Phantom. This phantom is a torso-like cavity containing 6 hollow spheres  surrounding a lung insert. The phantom was filled on each site with an 18F-FDG solution of approximately 53 MBq at the start of acquisition  in a line source in the scatter-fraction phantom.18F-FDG phantom tests, are listed in Table The acquisition and reconstruction parameters for the NEMA procedure, followed during the 68Ge)  were made of cold resin (non-radioactive) and the four smallest ones with 68Ge resin at a concentration of 25.2 kBq/mL. The background activity concentration was at 6.36 kBq/mL so that the ratio of spheres to background was 3.96:1. Contrary to the NEMA NU2-2012 image quality test, there was no out-of-field activity during the acquisitions to avoid any unexpected effect of external source positioning.FiveGe) Fig. b that waThe five centers involved in the QUICK phantom acquisition are identified in this paper as QUICK sites 1–5.The data acquisition involved 5 measurements per day for a span of 5 days to account for the effect of the Poisson statistics and variability in phantom positioning, respectively. Thus, a dataset of 25 images have been used for this analysis for each site. Table 18F-FDG phantom). The NEMA-IQ protocol recommended by the manufacturer does not include PSF because not all users have access to PSF, whereas a user with access to BSREM automatically includes access to PSF.In test 1, the QUICK phantom was scanned with the acquisition and reconstruction parameters recommended by the manufacturer for the standard NEMA NU2-2012 procedure  observed in the corresponding OSEM reconstruction (test 1). Increasing beta value results in smoother background (preferred by physicians) at the expense of reduced contrast recovery [In test 2, the RAW data was re-processed using the BSREM algorithm and a recovery . This avIn test 3 and test 4, each QUICK site re-processed the same RAW data using their own clinical reconstruction parameters optimized for OSEM and BSREM algorithms, respectively. For OSEM, the number of iterations for clinical reconstruction was the site’s choice as preferred by the site’s reading physicians and is a compromise between signal recovery and background noise level. The number of iterations for BSREM (25 iterations) is selected by the manufacturer until convergence is reached as intrinsically established by the BSREM algorithm , scan time, and acquisition matrix) and re-processed with clinically optimized OSEM and BSREM algorithms already used in test 3 and test 4, respectively.Detailed acquisition and reconstruction parameters for each test are shown in Table 68Ge activity over time to meet the NEMA NU2-2012 (test 1 to test 4) or to meet the clinical protocol (test 5 and test 6) count requirements.In each site, the acquisition time for the QUICK phantom was adjusted to compensate for the decay of For a consistent analysis, all the datasets were analyzed by each site using the automated GE NEMA image quality analysis software available on the operating console: CR and BV for each sphere in the phantom were calculated using each reconstruction method. Similarly, the LE was also determined using each reconstructed method. These variables are defined in the NEMA standards publication NU2-2012 image quality test .The results of the NEMA NU2-2012 image quality test, in terms of CR, BV, and LE, are presented in Fig. As expected, the majority of participating centers obtained similar results, and only two centers (QUICK Site 4 and QUICK site 5) showed unexpected data.Excluding these 2 centers, the CR values range from 30.8–43.6 to 63.7–77.2 from the smallest to the largest of the hot spheres, respectively. For the cold spheres (28 mm and 37 mm), the same parameter ranges from 65.7–75.4 to 73–79.1.The results of the six QUICK phantom tests, as average and standard deviation of acquisitions among all QUICK sites, are shown in Table 18F-filled NEMA-IQ phantoms, scanned and imaged following same protocols across sites, is larger than the one from a 68Ge filled phantom where each site was allowed to select the acquisition and reconstruction protocols. The main goal of limiting to a single scanner type (D-IQ from GE) was to control all other parameters in this comparison except for the imaging protocol selection between sites. This conclusion is further supported by the small variability observed when same imaging protocol is used with the QUICK phantom.The most often recommended procedure to evaluate the quantitation variability among PET facilities is to perform acquisitions and reconstruction of a fillable image quality phantom using the local setting of parameters and to extract quantitative data from resulting images. Following suit, the first part of this project showed that the variability introduced in the filling of the In this study, we have tried to assess and demonstrate the possibility of performing quantitative multisite clinical trials in PET using QUICK phantom. In addition, we also made an effort to understand the impact and potential causes of discrepancies among different sites if any.In order to avoid additional possible causes of discrepancies, we decided to extract quantitative data using the automatic processing available on the scanner’s console.18FDG phantom, despite having detailed directions for filling and imaging of the phantom. Their results can be explained by placing a larger than prescribed ratio of activity concentration between spheres and background (QUICK site 5) and too high activity in the background above the NEMA prescribed value (QUICK site 4).As mentioned above, two centers of the 17 sites (QUICK site 4 and QUICK site 5) showed unexpected data from the 18F-FDG fillable phantom due to a different level of experience of the operators . A solid radioactive phantom filled with 68Ge can be used to avoid such errors [These results clearly demonstrate the possible issues when trying to compare systems using h errors , and theResults of the standard NEMA test using the QUICK phantom support this assessment by showing more consistent results.β value (25) was intended to produce comparable background variability in the BSREM images with respect to OSEM images. This selection was not optimal, particularly for smaller ROIs , BSREM algorithm reduces the CR variability among sites when compared with the OSEM algorithm. This result supports the use of BSREM as the preferred protocol in a multi-center clinical trial regardless of the site-specific beta value. This may reduce the variability introduced by patient size and body habitus .Logistical challenges in transporting the QUICK phantom from site to site , resulted in delays of sites performing the measurements. Hence, each site performed the measurements with different total activity of the phantom. We compensated the decaying activity through longer acquisition times. However, it should be noticed that the acquisition conditions are not fully equivalent as the ratio of true events to random events does not remain constant with changing activity.The QUICK project was designed as a phantom study for comparing reconstruction protocols and selection of parameters. Hence, it does not take into account other parameters like dose calibrator, injected activity, serum glucose level, and post-injection time. To minimize variability of these parameters, multi-center participants must meet accreditation requirements that should include, for instance, the use of traceable sources for calibration of their dose calibrator, and similar patient preparation , 19.This study demonstrates the variability introduced by using different imaging protocols is smaller than the variability introduced by the operator when a NEMA-IQ phantom is handled and imaged by different sites following identical protocols. In turn, this demonstrates that the use of phantoms like the NEMA-IQ phantom for multi-center evolution of protocols is unreliable.BSREM algorithm reduces the variability of contrast recovery in PET images compared to the OSEM algorithm in different clinical acquisition conditions and reconstruction parameters across multiple centers. In the future, we plan to study the impact of the patient’s preparation on the variability of these measurements and to evaluate if harmonization of the injected dose is a necessary requirement for this kind of comparison studies.


Angelica pubescens. The pharmacological value of CBN is well demonstrated, especially in the prevention of several cancers and analgesic activity. A striking therapeutic target for arterial thrombosis is inhibition of platelet activation because platelet activation significantly contributes to these diseases. The current study examined the influence of CBN on human platelet activation in vitro and vascular thrombotic formation in vivo.Columbianadin (CBN) is one of the main coumarin constituents isolated from Aggregometry, immunoblotting, immunoprecipitation, confocal microscopic analysis, fibrin clot retraction, and thrombogenic animals were used in this study.2+]i) mobilization, and P-selectin expression. It also inhibited the phosphorylation of phospholipase C (PLC)γ2, protein kinase C (PKC), Akt (protein kinase B), and mitogen-activated protein kinases  in collagen-activated platelets. Neither SQ22536, an adenylate cyclase inhibitor, nor ODQ, a guanylate cyclase inhibitor, reversed the CBN-mediated inhibition of platelet aggregation. CBN had no significant effect in triggering vasodilator-stimulated phosphoprotein phosphorylation. Moreover, it markedly hindered integrin αIIbβ3 activation by interfering with the binding of PAC-1; nevertheless, it had no influences on integrin αIIbβ3-mediated outside-in signaling such as adhesion number and spreading area of platelets on immobilized fibrinogen as well as thrombin-stimulated fibrin clot retraction. Additionally, CBN did not attenuate FITC-triflavin binding or phosphorylation of proteins, such as integrin β3, Src, and focal adhesion kinase, in platelets spreading on immobilized fibrinogen. In experimental mice, CBN increased the occlusion time of thrombotic platelet plug formation.CBN markedly inhibited platelet aggregation in washed human platelets stimulated only by collagen, but was not effective in platelets stimulated by other agonists such as thrombin, arachidonic acid, and U46619. CBN evidently inhibited ATP release, intracellular ([CaThis study demonstrated that CBN exhibits an exceptional activity against platelet activation through inhibition of the PLCγ2-PKC cascade, subsequently suppressing the activation of Akt and ERKs/JNKs and influencing platelet aggregation. Consequently, this work provides solid evidence and considers that CBN has the potential to serve as a therapeutic agent for the treatment of thromboembolic disorders. DAG activates the PKC-inducing pleckstrin phosphorylation (47 kD protein) and ATP release in activated platelets; IP3 elevates calcium influx  to produce two important secondary messengers, diacylglycerol (DAG) and inositol trisphosphate -mediated inhibition of collagen-induced platelet aggregation, respectively. Neither ODQ nor SQ22536 significantly reversed CBN (80 μM)-mediated inhibition of platelet aggregation. Furthermore, both NTG (10 μM) and PGE1 (1 μM) obviously stimulated VASP phosphorylation, whereas CBN (60 and 80 μM) had no effects on cyclic nucleotide formation. Platelet aggregation is dependent on fibrinogen-integrin αIIbβ3 interaction; nevertheless, integrin αIIbβ3 inactivation can lead to disaggregation of aggregated platelets i through Ca2+ uptake into the dense tubular system, which suppresses the activation of PLC/PKC signaling. In this study, neither SQ22536 nor ODQ significantly reversed the CBN-mediated inhibitory response, and CBN had no effects on VASP phosphorylation. Therefore, the CBN-mediated inhibition of platelet activation is independent of the intracellular cyclic nucleotides/VASP pathway.Elevation of cyclic nucleotides, such as cyclic AMP and cyclic GMP, in platelets activates their respective protein kinase A and protein kinase G. This modulates platelet activation by phosphorylating intracellular protein substrates, such as VASP, which are involved in the inhibition of platelet aggregation and platelet adhesion . IncreasIIbβ3 binding belongs to a major component of activated platelets. Integrin αIIbβ3 undergoes conformational changes upon activation, generating a unique and specific ligand-binding site for the fibrinogen, von Willebrand factor, and fibronectin i, followed by integrin αIIbβ3 inside-out signaling and inhibition of platelet aggregation.This study revealed a novel role of CBN in the inhibition of platelet activation in humans, suggesting that it can be used for potential therapeutic or prophylactic applications. The outcome of this study may provide a new insight into the role of CBN in human platelet activation because it significantly inhibited platelet activation by hindering the PLCγ2-PKC cascade and subsequently, suppressed the activation of Akt and ERKs/JNKs. These changes decrease the release, such as [Ca


Elevated serum IgE levels are associated with allergic disorders, parasitosis and specific immunologic abnormalities. In addition, epidemiological and mechanistic evidence indicates an association between IgE-mediated immune surveillance and protection from tumour growth. Intriguingly, recent studies reveal a correlation between IgE deficiency and increased malignancy risk. This is the first review discussing IgE levels and links to pathological conditions, with special focus on the potential clinical significance of ultra-low serum IgE levels and risk of malignancy. In this Position Paper we discuss: (a) the utility of measuring total IgE levels in the management of allergies, parasitosis, and immunodeficiencies, (b) factors that may influence serum IgE levels, (c) IgE as a marker of different disorders, and d) the relationship between ultra-low IgE levels and malignancy susceptibility. While elevated serum IgE is generally associated with allergic/atopic conditions, very low or absent IgE may hamper anti-tumour surveillance, indicating the importance of a balanced IgE-mediated immune function. Ultra-low IgE may prove to be an unexpected biomarker for cancer risk. Nevertheless, given the early stage of investigations conducted mostly in patients with diseases that influence IgE levels, in-depth mechanistic studies and stratification of malignancy risk based on associated demographic, immunological and clinical co-factors are warranted. Elevated IgE is a robust biomarker in atopy, allergy and parasitic infestations, but the implications of ultra-low IgE levels are not understood.Epidemiologic analyses and in vitro and in vivo studies indicate that natural IgE has a surveillance function in cancer, and recombinant anti-cancer IgE is under investigation in a human trial.IgE immunodeficiency correlates with a significantly elevated risk of malignancy development, prompting the need for further research to evaluate ultra-low IgE levels as a new biomarker in oncology.This Position Paper was prepared by the EAACI Task Force (TF) for AllergoOncology, an expert panel of immunologists, allergists, physicians, biochemists and epidemiologists. In the first meeting, topics were identified and prior to the second workshop, a PubMed literature search of specific topics was conducted by individual TF members. The compiled manuscript was extensively revised by the second workshop attendees to obtain consensus on text, tables and figures. Although no evidence-based recommendations were made, due to the limited number of published studies on IgE deficiency, future directions were discussed. The manuscript was recirculated for review to all TF members, compiled and again recirculated for complete consensus. The final manuscript was read and approved by all authors and represents an expert consensus opinion with recommendations summarized in the “Published peer reviewed studies in English were identified from PubMed. The following key words were used in the search strategy:  AND  AND (IgE OR IgE deficiency). References published within the 2000-2019 timeframe that had not been otherwise identified in the initial search were added where relevant. We reviewed approximately 250 published studies relevant to this paper.Immunoglobulin E (IgE) was isolated in 1968 and recognized as the immunoglobulin isotype involved in allergic reactions . ThousanAllergic diseases, which are widespread throughout the world, are driven by a T helper 2 (Th2) immune response to allergens, resulting in production of Th2 cytokines and class-switching to IgE. Th2 responses are actually thought to have originally evolved to control extra‐cellular parasites. Nearly one-third of the global population has some type of helminth infection which triggers an immune response characterized by elevated Th2 cytokines, IgE and eosinophilia . Many quRecently, another new role of IgE in tumour immune surveillance has been suggested by many epidemiological studies and in vitro and in vivo studies in murine models –11. In hMost of the initial epidemiological studies assessed the association between self-reported allergies and malignancy, which may produce different types of biases. However, once it was recognized that the IgE molecule might be the link between allergies and cancer, different population studies began to examine the association between total or allergen-specific IgE levels and cancer incidence. For example, results from a large Swedish cohort demonstrated an inverse correlation between elevated specific IgE and overall cancer risk, specifically for melanoma, breast and gynaecological cancers . AnotherElevated IgE (often referred to high and very high serum IgE levels) is commonly considered a serum signature for allergic/atopic conditions , 28. In Total serum IgE of 100–120 kU/L is typically considered the normal upper limit in adults , althougWhile research has focused primarily on elevated IgE serum levels, the evidence presented in this Position Paper indicates that investigating the consequences of IgE deficiency J recombination in B cell precursors, and by somatic hypermutation (SHM) in the Ig variable (V) domains and class switch recombination (CSR) in mature B cells. CSR to IgE requires IL-4 or IL-13 during cognate interactions between CD40-ligand (CD40L) on the Th2 cell and CD40 on B cells, or T cell-independent (TI) stimulation of polyclonal IgE through homologues of CD40L and CD40 in mucosal tissues .There are two types of IgE receptors, high (FcεRI) and low (FcεRII) affinity, that are well described in the literature. In addition, soluble isoforms of IgE Fc receptors (sFcεR) have been described and may form a serum sink for IgE, preventing loading of IgE to surface-expressed FcεRI. In allergic reactions, this may be part of the negative feedback loop that can shut down allergic responses by inhibiting surface binding of IgE and preventing cellular sensitization . On the a personal and/or familial tendency, usually in childhood or adolescence, to become sensitized and produce IgE antibodies in response to ordinary exposures to allergens, usually proteins. As a consequence, these persons can develop typical symptoms of asthma, rhinoconjunctivitis, or eczemas” . So. So83]. Elevated IgE levels may be also found in patients with IgG4-related disease. A total IgE > 480 IU/mL at diagnosis distinguished patients with IgG4-related disease from control subjects with 86% specificity, while IgE > 380 IU/mL identified patients with disease relapse with 88% specificity . ContrasIn addition to patients with selective IgE deficiency , ultra-low IgE levels may also be found in patients with common variable immunodeficiency (CVID) , hyper-ID. farinae were ex- or current smokers [A wide variety of factors affect allergy development and may therefore influence IgE levels Table . In a no smokers  and high smokers . Among a smokers . In the  smokers .Table 4OTotal serum IgE may be influenced by medications Table . OmalizuDupilumab, a fully-humanized monoclonal antibody targeting the interleukin-4 receptor α (IL-4Rα) subunit, which is approved for the treatment of asthma, atopic dermatitis and chronic rhinosinusitis with nasal polyps, decreases serum total IgE levels by a mean of 50% at 16 weeks compared with baseline . The impCorticosteroids are used to control different allergic disorders. Since IgE is a biomarker of “allergies”, one would expect that corticosteroids would decrease IgE levels. However, the decrease in IgE does not occur since corticosteroids polarize the immune system towards a Th2 predominance by suppressing IFN-γ  and inducing IL-12 production , as well as by increasing IgE production by enhancing the expression of CD40 ligand .Allergen immunotherapy induces an initial increase in serum specific and total IgE, followed by a gradual decrease over months or years of treatment .A higher proportion of patients with chronic urticaria (34%) have total IgE > 175 IU/mL compared with controls  and multDifferent antigenic targets of IgE have been described in several medical conditions, including systemic lupus, bullous pemphigoid, pemphigus vulgaris, autoimmune uveitis, rheumatoid arthritis, multiple sclerosis, autoimmune pancreatitis, which led to the new research field of IgE-mediated autoimmunity . HoweverLastly, significant experimental evidence points to the role of vitamin D as a regulator of various immune pathways, and hypovitaminosis D might be associated with elevated total IgE levels and a higher rate of different allergic disorders .Different mechanisms, about how microbiota may influence and regulate the innate and adaptive immune responses with emphasis on the Th2 pathway, have been reviewed in detail in our previous AllergoOncology Position Paper . One stuIn clinical practice, attention should be paid not only to patients with high IgE levels, but also to those with very low or absent serum IgE. IgE-deficient individuals have higher rates and risk of malignancy, and attention to this observation will close knowledge gaps with regards to questions such as: (1) Should we check serum total IgE levels in all patients? (2) Which assays should we use to monitor patients with ultra-low IgE levels and what are the ethical implications of not monitoring them? (3) What IgE levels protect from malignancies or, maybe even more importantly, which IgE titres are associated with the risk of developing cancer?Longer prospective studies are needed to delineate the exact clinical consequence of very low or absent serum IgE levels and to assess if ultra-low IgE will emerge as a clinical biomarker for malignancy susceptibility. While the anti-tumour role of IgE and the potential of IgE-based therapy begins to be recognised, the immunological mechanisms causing IgE deficiency are not yet understood. Dysregulated pathways involved in the IgE class-switching process might not only be responsible for the low serum IgE levels but perhaps also for some impaired anti-tumour activity. Based on the available data, we conclude that low IgE may be a novel, unrecognized biomarker for cancer development. However, substantial effort and interactive research by immunologists, allergists, and oncologists will be necessary to determine the exact role of IgE in malignancy susceptibility and whether there is a specific threshold for serum IgE that determines malignancy susceptibility.Box 1: Unmet needs to define very low/absent IgE as biomarker in cancerThe exact IgE level threshold that confers protection versus risk for malignancy occurrence remains to be defined.It is not yet clear whether ultra-low/undetectable serum IgE is truly a risk factor for developing malignancy, or if IgE levels are low in response to undetected cancer progression. It is possible that an aberrant and unknown immune pathway causes low IgE levels in response to malignancy.There is a need for large prospective studies as well as in vitro experiments and in vivo models to further delineate the role of ultra-low IgE as a putative biomarker for malignancy.Box 2: Pending questions in the field, future directionsIs antigen-specific and/or total serum IgE involved in cancer surveillance?Is an IgE-related immune score helpful to predict malignancy occurrence? What demographic, clinical and/or immunological factors should this score include?New genetic and genomic evaluations are needed to determine if there is a familial risk for IgE deficiency.Is the prevalence of IgE deficiency age-dependent?Should patients at risk of developing malignancy be treated with specific anti-tumour IgE or total IgE to achieve higher anti-tumour surveillance? Is passive intravenous IgE (IVIGE) or IL-4 a safe option?Box 3: Recommendations for patients with IgE deficiencyDue to current minimal information in the field, we cannot specify screening tests or establish recommendations for patients with IgE deficiency. However, with the goal of understanding the role of diminished IgE in the general population, certain clinical findings  and laboratory tests (e.g. presence of tumour markers , C-react


The MSHTS system is seldom influenced by contaminants in samples and is able to directly evaluate Aβ42 aggregation inhibitory activity of samples containing various compounds. In this study, to elucidate whether the MSHTS system could be applied to the evaluation of processed foods, we examined Aβ42 aggregation inhibitory activity of salad dressings, including soy sauces. We estimated the 50% effective concentration (EC50) from serial diluted dressings. Interestingly, all 19 commercial dressings tested showed Aβ42 aggregation inhibitory activity. It was suggested that EC50 differed by as much as 100 times between the dressings with the most (0.065 ± 0.020 v/v%) and least (6.737 ± 5.054 v/v%) inhibitory activity. The highest activity sample is traditional Japanese dressing, soy sauce. It is known that soy sauce is roughly classified into a heat-treated variety and a non-heat-treated variety. We demonstrated that non-heat-treated raw soy sauce exhibited higher Aβ42 aggregation inhibitory activity than heat-treated soy sauce. Herein, we propose that MSHTS system can be applied to processed foods.The aggregation and accumulation of amyloid β (Aβ) in the brain is a trigger of pathogenesis for Alzheimer’s disease. Previously, we developed a microliter-scale high-throughput screening (MSHTS) system for Aβ One of the problems facing an aging society is the increase of patients with dementia. While various diseases are known to cause dementia, Alzheimer’s disease (AD) in particular, accounts for the majority of cases ,2,3. FouLamiaceae such as rosemary, perilla, and lemon balm. RA is a known inhibitor of Aβ aggregation [Rosmarinic acid (RA) is a polyphenol found in abundance in plants of the regation ,13. Its regation ,15. Amonregation . Furtherregation . Hsu et regation . Thus, tregation . ThT emi42 aggregation process with a fluorescence microscope using a quantum dot (QD) nanoprobe and developed a microliter-scale high-throughput screening (MSHTS) system for Aβ42 aggregation inhibitors by applying this imaging method [42 aggregates is quantified from standard deviation (SD) value estimated from the variation in fluorescence intensity of each pixel of obtained images and the emission wavelength of QD605 does not overlap with the absorption of almost natural products [42 aggregation as EC50 values. Before, we evaluated the Aβ42 aggregation inhibitory activity of 52 spices using this method and demonstrated that the herb-based spices of the Lamiaceae family exhibited high Aβ42 aggregation inhibitory activity [42 aggregates morphology was affected with seaweed-derived polysaccharide including in boiling water extracts [42 aggregation inhibitory activity. Thus, MSHTS system is useful for quantitative evaluation of Aβ42 aggregation inhibition ability of various natural products. However, it is unclear whether MSHTS system can evaluate Aβ42 aggregation inhibitory activity in foods including various natural substances with many impurities. In this study, to elucidate whether the MSHTS system is applied to processed foods such as salad dressings, including soy sauces, we evaluated Aβ42 aggregation inhibitory activity of dressings using the MSHTS system. We found that all tested commercial dressings showed Aβ42 aggregation inhibitory activity despite there were differences in their activities. Especially raw soy sauce showed the highest inhibitory activity among the tested samples. These results suggest that the MSHTS system is a powerful and useful tool that is expected to be applied and developed in various processed foods.Previously, we succeeded in real-time imaging of the Aβg method ,20. The products . Thus, textracts . Furtherextracts . Screeni42  and Cys-conjugated Aβ40  kits were purchased commercially. Twenty different commercially available salad dressings and soy source brands were purchased from Japanese companies  using catalog shopping in June 2016.Human Aβ2 (QdotTM 605 ITKTM Amino (PEG) Quantum dot; Q21501MP, Thermo Fisher Scientific, Waltham, MA USA) according to our previous reports [2 with 1 mM sulfo-EMCS  in PBS  for 1 h at room temperature. QDAβ concentration was determined by comparing absorbance at 350 nm to that of unlabeled QD-PEG-NH2.The QDAβ nanoprobe was prepared using QD-PEG-NH reports ,20,21,2250 values of various dressings were determined by a modified MSHTS system, as was described in our previous reports [42 in PBS containing 5% EtOH and 3% DMSO were incubated in a 1536-well plate  at 37 °C for 24 h. The QDAβ-Aβ42 aggregates that formed in each well were observed by an inverted fluorescence microscope . Standard deviation (SD) values of fluorescence intensities of 40,000 pixels (200 × 200 pixels) around the central region of each well were measured by ImageJ software Ver 1.53b (NIH). The SD values, which were approximately proportional to the amount of aggregates [The EC reports ,21,22. MAggregates in the 1536-well plate were observed by an inverted fluorescence microscope  using a 4× objective lens  equipped with a color CCD camera .Samples were deposited in 10 µL aliquots onto 200-mesh copper grids and negatively stained with 1% phosphotungstic acid at room temperature. Specimens were examined under an H-7600 TEM  at 60 kV.The ThT assay was conducted according to the method of Levine modified in our laboratory ,21. StatSDS-polyacrylamide gel electrophoresis (SDS-PAGE) was performed using standard techniques. Soy sauce and raw soy sauce were heated by block incubator at 80 °C for 60 min before electrophorese. For dialysis protocol, soy sauce and raw soy sauce were dialyzed against distilled water. Distilled were changed three times for overnight. Then, the gel was silver-stained by staining kit 42 aggregation inhibitory activity of the liquid dressings using the ThT method was difficult because the absorption wavelength of almost samples overlapped with the excitation and emission wavelengths of ThT.First, in order to assess whether 19 liquid salad dressings could be evaluated for activity by the ThT method, their absorbance spectra were measured using a Nanodrop 2000c (Thermo Fisher Scientific) . The excv/v%) was measured in three conditions; +Aβ42 and +ThT, −Aβ42 and +ThT, −Aβ42 and −ThT . The fluorescence intensity of samples C, D, and E did not show a higher value than the negative control. The color and some components of the evaluated samples may affect the ThT method by absorbing the excitation or emission of ThT. If the sample solution without Aβ42 exhibits a higher fluorescence intensity than the negative control, it is difficult to determine whether the sample solution affects ThT. Therefore, the ThT method might not accurately evaluate the Aβ42 aggregation inhibitory activity of a commercial dressing.To confirm whether the evaluation using ThT method was performed correctly, the fluorescence intensity of five samples at a high concentration  caused an inhomogeneous distribution of fluorescence intensity in images, resulting in an increased standard deviation (SD) value estimated from the variation in fluorescence intensity of each pixel in the images. Therefore, we could estimate the effects of certain aggregation inhibitors by detecting changes in the SD value. Here, we evaluated the Aβ42 aggregation inhibitory activity of 19 commercial dressings using the MSHTS system  contained plant oil while the other 16 samples were non-oil type dressings. We compared the mean value of EC50 value of non-oil and oil type  and performed a statistical analysis. There was no significant difference between non-oil type and oil type . The activity did not depend on the presence of oil, suggesting that oil in the dressing did not affect the Aβ42 aggregation inhibitory activity. Next, to confirm whether Aβ42 aggregation was inhibited by the effect of the dressing, we observed the Aβ42 aggregates at a sample concentration of 0.04 v/v% using TEM . Because the EC50 of sample A is 0.065 ± 0.020 v/v%, it was indicated that 1.8 mM NaCl is included. The NaCl concentration of the 0.4 v/v% and 0.04 v/v% solution samples is 11 mM and 1.1 mM, respectively. Therefore, the NaCl in 0.065 v/v%  soy sauce solution might not affect the formation of Aβ42 aggregates. In fact, as shown in v/v%. Especially, 0.04 v/v% of sample A inhibited the aggregation formation. These results suggest that the Aβ42 aggregation inhibitory activity by soy sauce was due to not NaCl but other components.In general, it is well known that the soy sauce contains a large amount of NaCl and that high salt concentration affects protein aggregation. In order to determine whether the Aβgregates A. We preo 200 mM B. Howeve42 aggregation inhibitory activity of raw soy sauce purchased from NIHON SYOYU KOGYO using the MSHTS system. The Aβ42 aggregation inhibitory activity of raw soy sauce was 0.0045 ± 0.0015 v/v% (Data not shown). This activity is about 15 times higher than that of soy sauce which showed the highest activity among the 19 dressings. Therefore, it is likely that the difference in the aggregation inhibitory activity of Aβ42 between soy sauce and raw soy sauce is caused by the raw material-derived protein and the microorganism-derived enzyme, which are lost by heating.As shown in 42 aggregation inhibitory activity, each sample was subjected to SDS-PAGE after heat treatment  and/or dialysis treatment and their band patterns were compared using silver staining (To examine whether proteins and/or low molecular weight compounds in soy sauce and raw soy sauce affect Aβstaining A. As rev42 aggregation inhibitory activity of soy sauce and raw soy sauce (42 aggregation inhibitory activity of soy sauce was not changed by heating. This result was consistent with the SDS-PAGE banding pattern (42 aggregation inhibitory activity of raw soy sauce was reduced by about 30 times or by about half after heat treatment and dialysis, respectively. Dialysis treatment did not affect the 100–200 kDa band that was reduced by heat treatment, i.e., the 100–200 kDa protein did not contribute to the Aβ42 aggregation inhibitory activity of raw soy sauce. The heat treatment after dialysis decreased Aβ42 aggregation inhibitory activity by about 440 times, which was consistent with the SDS-PAGE result in which many bands were reduced (42 aggregation inhibitor found in soy sauce and raw soy sauce is a low molecular weight compound that is removed by dialysis and a protein that is thermally denatured by heat treatment at 80 °C for 60 min. Since the Aβ42 aggregation inhibitory activity of raw soy sauce was greatly reduced after heat treatment, the proteins found in raw soy sauce are considered to be particularly important for the inhibition of Aβ42 aggregation.Next, using the MSHTS system, we assessed whether heating and dialysis treatment would affect the Aβoy sauce B. Furthe reduced A, lane 842 aggregation inhibitory activity. The main raw materials of soy sauce, soy, and wheat, are decomposed into amino acids, peptides and saccharides in the manufacturing process. It is known that soybeans have many physiologically active ingredients such as soy protein and isoflavone [In general, proteins and peptides are denatured by heating, then lose their physiological activity. It is possible that the presence or absence of heat treatment in the fermentation process may be involved in the physiological activity of dressings such as soy sauce, which contains Aβoflavone ,26,27, soflavone . Genisteoflavone . It was oflavone ,29 Furthoflavone ,31,32. W42 aggregation inhibitory activity of 19 commercial liquid dressings using the MSHTS system. All tested dressings exhibited Aβ42 aggregation inhibitory activity, suggesting that the MSHTS system can be applied to processed food containing various impurities. Japanese traditional liquid dressings, soy sauce, exhibited the highest inhibitory activity. However, these findings are limited to in vitro conditions. The physiological activity of the dressings should be clarified through animal experiments, taking into account dynamics such as intestinal absorption and metabolism, particularly the permeability of the blood-brain barrier. Although there is a strong demand for functional food products that help maintain and improve brain function, it is not realistic to subject all food products to animal testing. We are confident that we can progress quickly to a second screening stage such as animal testing by using the MSHTS system as a first screening tool to discover food materials with high Aβ42 aggregation inhibitory activity. Recently, we confirmed that aggregation of various amyloid proteins Aβ42, tau, and α-synuclein could be visualized using nonlabelled QD and succeeded in the evaluation of aggregation inhibitory activity of RA [In this work, we evaluated Aβty of RA . MSHTS sty of RA  and non-


The 2019 emergence of, SARS-CoV-2 has tragically taken an immense toll on human life and far reaching impacts on society. There is a need to identify effective antivirals with diverse mechanisms of action in order to accelerate preclinical development. This study focused on five of the most established drug target proteins for direct acting small molecule antivirals: Nsp5 Main Protease, Nsp12 RNA-dependent RNA polymerase, Nsp13 Helicase, Nsp16 2’-O methyltransferase and the S2 subunit of the Spike protein. A workflow of solvent mapping and free energy calculations was used to identify and characterize favorable small-molecule binding sites for an aromatic pharmacophore (benzene). After identifying the most favorable sites, calculated ligand efficiencies were compared utilizing computational fragment screening. The most favorable sites overall were located on Nsp12 and Nsp16, whereas the most favorable sites for Nsp13 and S2 Spike had comparatively lower ligand efficiencies relative to Nsp12 and Nsp16. Utilizing fragment screening on numerous possible sites on Nsp13 helicase, we identified a favorable allosteric site on the N-terminal zinc binding domain (ZBD) that may be amenable to virtual or biophysical fragment screening efforts. Recent structural studies of the Nsp12:Nsp13 replication-transcription complex experimentally corroborates ligand binding at this site, which is revealed to be a functional Nsp8:Nsp13 protein-protein interaction site in the complex. Detailed structural analysis of Nsp13 ZBD conformations show the role of induced-fit flexibility in this ligand binding site and identify which conformational states are associated with efficient ligand binding. We hope that this map of over 200 possible small-molecule binding sites for these drug targets may be of use for ongoing discovery, design, and drug repurposing efforts. This information may be used to prioritize screening efforts or aid in the process of deciphering how a screening hit may bind to a specific target protein. The societal and economic impacts of the SARS-CoV-2 virus are undeniable –4. In thCenter for Structural Genomics of Infectious Diseases (CSGID)) Studies of Nsp 4, Papin-like protease did not use the full biological assembly, but only the full-length (res:1–320) D subunit monomer of Nsp4 in complex with the peptide inhibitor VIR215 (6wx4.pdb) . SimilarThis section describes the workflow that utilized to identify the TOP25 or TOP50 possible aromatic pharmacophore (benzene) binding sites and how docking and free energy calculations are performed using CHARMM . This wobind) conformation of benzene bound to the site from molecular docking, then the TOP25 or the TOP50 aromatic pharmacophore binding sites are then sorted again, ranked by (ΔGbind) rather than by the number of C-C hydrophobic contacts (Nconts). An important limitation of this two-step procedure is that the first selection process  from a pure benzene solvent neglects consideration of physical desolvation penalties to binding from an aqueous solvent. However, after the sites are identified, in the second step aqueous desolvation is explicitly considered in the calculation of (ΔGbind). Thus, it is possible that true low energy binding sites may not be identified in the first step if a site does not satisfy the hydrophobic contact criteria.Production MD trajectories from 100–500 ps were analyzed by calculating the number of C-C hydrophobic contacts between benzene carbons and protein atom carbons using a cutoff distance of 5.4 Å , 80. In Similar MD simulations were also performed in pure water for the Nsp13 helicase (6jyt.pdb) structure . CHARMM-bind) has been previously described As shown in  on the Nth, 2020). As shown on  geometry. The next most favorable “minor” site, Site 08 (LE = 0.26) was a member of the TOP10, which was found to be a higher RMSD match (RMSD = 2.76 Å) with aromatic pharmacophore fragment ligands  such as the fragment ligand shown (5ree.pdb) . Finallybind), fragment screening was used to additionally characterize these sites. The results for screening the FRAG100 library are summarized in (max = 0.34) < Site08 (LEmax = 0.29) << Site 23 (LEmax = 0.20). Thus, the results from fragment screening reinforced the same trend that was observed from pharmacophore mapping, that Site02 had the greatest ligand efficiency of these experimentally confirmed allosteric fragment binding sites.Following the identification and ranking by (ΔGrized in  and (S3 rized in . The 3 smax = 0.39), followed by the P1 site (LEmax = 0.35), and then the P3 site (LEmax = 0.33). Even though the P1 site was ranked to be slightly more favorable than the P2 site in the initial pharmacophore mapping results, this may have been due to it actually being a more exact match for an optimal group at this position. Fragment screening shows that the P2 site identified a greater number of more favorable (ΔGbind) and ligand efficient fragment hits than the P1 site. In summary, given that there was so much more structural information available the Nsp5 Mpro, our level of agreement with the existing data is encouraging and supports its use as a comparison benchmark against the other protein targets. The P1 site was selected as a reference site for screening with the larger 3,700 compound fragment screening library. We report this data below in the Nsp13 helicase section in comparison to screening the full fragment library against several Nsp13 helicase sites.Turning our attention back around to the protease active site and the major P1, P2 and P3 sites, the results from fragment screening show that the site with the greatest ligand efficiency was the P2 sites (LEThe Nsp16 is a 2’-O methyltransferase (MT) involved in 5’ cap maturation of viral RNA, which has been shown to be essential for viral replication in cell culture models for several viruses, including coronavirus strains , 95. WhiSimilar to the Nsp5 Mprot, the Nsp16 2’-O MT is a relatively smaller protein 296 residues) compared to the larger targets and the TOP25 binding sites were identified. The analysis was performed using the recent structure of the Nsp16 / Nsp10 homodimer bound in complex with sinefungin , 96. The residuesbind), it was not surprising that a specific substructure of sinefungin was found to be one of the most favorable sites within the TOP5. The sinefungin adenine group pharmacophore Site 02 (LE = 0.40) was found to be the 2nd most favorable overall site of the TOP25 and the most favorable site that maps to the structure of sinefungin. Although this result is entirely expected, it remains in sharp comparison to the sinefungin ribose pharmacophore position identified as Site 25 (LE = 0.15) which is much less favorable. Also, ribose is a poor replacement of a flat aromatic benzene pharmacophore, so it is also expected to not be very favorable. Interestingly, the most favorable overall site on Nsp 16 was, Site 01 (LE = 0.42) in a hydrophobic pocket that is directly adjacent to the sinefungin binding site formed by residues . This site is illustrated in (When the TOP25 sites were ranked by (ΔGrated in  as the cbind). The most favorable of these were Site 03 (LE = 0.32) and Site 06 (LE = 0.28), in comparison to two other less favorable PPI sites Site 12 (LE = 0.25) and Site 18 (LE = 0.23). So, as might be expected, specific PPI sites are more favorable than other so called “hot-spots.” However, all of these Nsp16 / Nsp10 dimer interface PPI sites were less favorable than the major small-molecule co-factor binding site, the sinefungin adenine group pharmacophore Site 02 (LE = 0.40), as expected. Targeting the Nsp10:Nsp16 PPI sites have been proposed for SARS-CoV-2 discovery . These results in  show thaactivity , 115 andxzl.pdb) . Thus, oMAX = 0.26) shown in (bind), but was found to have reasonable ligand efficiency with fragment screening derivatives identified from the library. Shown in (bind. However the ligand efficiencies for Nsp13 Site 01 are on the order of the P3 site (Nsp5 site 04), but not as favorable as the other two P1 (Nsp5 Site 01) and P2 sites (Nsp5 Site 05).From these results, compared to all of the other helicase sites the next most favorable was a ZBD-stalk interface allosteric Site 19 . Shown in (MAX = 0.50) was found to have the greatest ligand efficiency over the entire database. The ZBD-stalk domain interface Site 19 (LEMAX = 0.40) was actually found to have a slightly greater ligand efficiency over the entire database than Site 07 (LEMAX = 0.39) which was the most favorable site identified proximal to the ATPase active site. A conclusion from our screening data analysis is that at least two allosteric ZBD domain binding sites may be at least as favorable, or more favorable compared to the ATPase active site ATP binding site.The larger fragment library  was screened for these three most favorable sites on the helicase and the results were compared to the “reference” P1 aromatic pharmacophore site on Nsp5 Mpro Site 01 .Prior to the release of the cryoEM structure of the replication transcription complex of Nsp12:13 (discussed in the next section), based on these fragment screening results, we had hypothesized that small molecules binding to these N-terminal ZBD allosteric sites may interfere with Nsp13 helicase function either inhibiting (1) conformational change of the ZBD domain recently identified to be key in the allosteric helicase mechanism or (2) protein-protein interactions with Nsp8 forming the replication complex . The relMAX = 0.50) as shown on (The recent 3.5 Å resolution cryoEM structure (6xez.pdb) of the replication transcription complex of Nsp12 RdRp in complex with Nsp7, Nsp8 and Nsp13 shows for the first time how the Nsp12 RdRp couples with multiple copies of the Nsp13 helicase . While tshown on . Interesshown on  dependinHowever, despite the fact that the Nsp13 N-terminal ZBD domain remains relatively rigid (Cα RMSD < 1.0 Å) between multiple independent structures and in short MD simulations in explicit solvent, the independent structures of the SARS-CoV-2 structures show that small side-chain mediated conformational changes in the binding site are observed between the different structures . InteresIn comparison, targeting the exact PPI site directly may not be as thermodynamically favorable as illustrated in . Two aroa RMSD < 1.0 Å) in other furin cleavage resistant engineered constructs (6zge.pdb) of Spike [bind and the energetic ranking of sites.Our studies of the S2 segment of the Spike protein (res:711–1147) used the 3.2 Å CryoEM structure (6vxx.pdb) of the full-length SARS-CoV-2 Spike protein where the ectodomain was in the “closed” state . Compareof Spike . Althougof Spike , we aimeof Spike . On the We present results for five favorable representative aromatic pharmacophore sites identified within the TOP50 S2 Spike segment . The S2 bind for various sites. In the pharmacophore mapping step, the Site 01 (LE = 0.34) was identified as the most favorable site over the entire S2 trimeric structure  which is an extremely buried site in the central cavity of the trimeric structure . As showThe next most favorable site that we report, Site 05 (LE = 0.31) was of interest for several reasons, but our comparison to the recent results of Trigueiro-Louro et al., , highligUsing a structural alignment (structure-sequence) superposition of our S2 spike protein with influenza (5t6n.pdb and 5t6s.pdb), we show where the influenza fusion inhibitor Arbidol most likely binds to the S2 spike, within close proximity to Site 05. Using the UCSF Chimera Matchmaker structural alignment algorithm , 82, a sbind) the most favorable of the knowledge-based sites binding sites (LE = 0.27) was still not as favorable as the previously identified Site 05 (LE = 0.31). Therefore, within close proximity to some of the knowledge-based references, Site 05 is more favorable. The closest of the reference pharmacophores was within (5.7 Å) of Site 05, which also supports this as a likely location for Arbidol binding.The results were also compared with the same protocol using reference “knowledge-based” pharmacophores where a total of 12 reference aromatic pharmacophore positions for Arbidol binding were derived from the structural alignment with (5t6s.pdb) . When thAnother independent report has predicted that Arbidol binds to the S2 segment within proximity to Site 05 . Using mInterestingly, recent crystal structures of two other class I fusion protein inhibitors show that binding sites at several locations on a trimeric prefusion conformation may lead to inhibition. In the structure of the respiratory syncytial virus (RSV) F glycoprotein, several small-molecule inhibitors were found to bind to a three-fold symmetric pocket within the central cavity . The EboMAX = 0.30) compared to the most favorable sites on Mprot (LEMAX = 0.50), similar to our fragment screening data for the Nsp13 helicase. Thus, the most favorable site identified within proximity of where Arbidol likely binds shown in  inhibitor of SARS-CoV-2 virus n assays , 127. Arn assays . UnfortuOur approach of pharmacophore mapping and fragment screening allows a comparison of the most favorable sites among the targets studied in detail. Our calculated ligand efficiencies from each iterative step consistently suggest that Nsp5 Mpro, Nsp12 RdRp, and Nsp16 2’-O MT have more favorable binding sites with greater ligand efficiency compared to Nsp13 helicase and the S2 Spike protein. Pharmacophore mapping results for Nsp5 Mpro correctly identified three of the most favorable peptide side chain substrate recognition sites, which confirmed the accuracy of our methodology. Independent experimental fragment screening structural data for Nsp5 Mpro was able to experimentally corroborate aromatic pharmacophore locations for three additional predicted “minor” fragment ligand binding sites outside of the protease active site.In reviewing the pharmacophore mapping results for the target proteins, it is apparent that many of the most favorable sites happen to be areas that correspond to protein-protein interactions (PPIs) of different constituents of the replicase complex. Nsp12 was found to have the most favorable site (LE = 0.48) which corresponded to the most important Nsp8 binding interaction. The most favorable PPI site identified for Nsp13 (LE = 0.22) has a far lower LE when compared to Nsp12. The most favorable PPIs in the Nsp16:Nsp10 complex were Site 03 (LE = 0.31) and Site 06 (LE = 0.27), in comparison. Therefore, some of the most favorable sites that undergo protein-protein interactions could be targeted to inhibit assembly of the active replicase complex. Our analysis points to the Nsp12 RdRp Site 01 (LE = 0.48), as the single PPI site with the highest ligand efficiency .Our results have shown that the Nsp13 helicase does not have the most thermodynamically favorable sites to target in comparison to several of the other examined targets. However, while these data suggest that targeting the function of the helicase itself may be difficult, there is promise in targeting the helicase to prevent the formation of the replication complex. Fragment screening at numerous sites on Nsp13 helicase identified several favorable sites on the N-terminal ZBD. Site 01 (LE = 0.31) was found to be the single most favorable site on the entire SARS-CoV helicase structure (6jyt.pdb). Fragment screening data  demonstrThis comparison of sites between SARS-CoV-2 drug target proteins highlights that there are numerous favorable sites to target with small-molecules via virtual screening or biophysical screening approaches. However, due to differences in physiochemical properties and molecular architecture, some small-molecule binding sites are more favorable than others. It is our hope that insights from this work will be helpful to advance the development of preclinical candidates for each of these targets.S1 File(DOCX)Click here for additional data file.S2 File(ZIP)Click here for additional data file.


Corylus avellana) are caused by immunologic cross-reactivity of IgE antibodies to pathogenesis-related class 10 (PR-10) proteins. Intriguingly, the four known isoforms of the hazelnut PR-10 allergen Cor a 1, denoted as Cor a 1.0401–Cor a 1.0404, share sequence identities exceeding 97% but possess different immunologic properties. In this work we describe the NMR solution structures of these proteins and provide an in-depth study of their biophysical properties. Despite sharing highly similar three-dimensional structures, the four isoforms exhibit remarkable differences regarding structural flexibility, hydrogen bonding and thermal stability. Our experimental data reveal an inverse relation between structural flexibility and IgE-binding in ELISA experiments, with the most flexible isoform having the lowest IgE-binding potential, while the isoform with the most rigid backbone scaffold displays the highest immunologic reactivity. These results point towards a significant entropic contribution to the process of antibody binding.A major proportion of allergic reactions to hazelnuts ( Immunologic reactions to these food sources are triggered by several specific proteins, with a significant proportion of individuals being affected by class 10 of pathogenesis-related proteins (PR-10)1. These allergic reactions result in particular from an initial sensitization to the major birch (Betula verrucosa) pollen allergen Bet v 1, a PR-10 protein. Thereafter, immunologic cross-reactivity is developed due to the strong similarity between Bet v 1 and homologous nut allergens5. Indeed, up to 70% of all birch pollen allergic individuals are affected by such birch pollen-related food allergies (BPRFA), with hazelnuts representing one of the most prevalent triggers9. In affected patients, consumption of hazelnuts provokes a variety of clinical symptoms, including itching, scratching, and swelling of the mouth and throat10 as well as in rare cases severe anaphylactic shocks12. Contrary to other food sources, industrial processing at high temperatures does not prevent IgE reactivity in hazelnut products13. Additionally, hazelnut allergens only decompose at much higher temperatures15 than, for example, apple allergens16.Nut allergies in Europe are predominantly related to hazelnuts17. The PR-10 proteins of the common hazel (Corylus avellana) can be grouped into the isoallergens Cor a 1.01 (hazel pollen)18, Cor a 1.02 and Cor a 1.03 (hazel leaf)19, and Cor a 1.04 (hazelnut)20. Interestingly, hazelnut Cor a 1.04 allergens are closely related to the birch pollen allergen Bet v 1, with amino acid sequence identities of about 83%21, while hazelnut and hazel pollen allergens share sequence identities of only about 63%. Likewise, the IgE-epitopes of the hazelnut allergens appear to show higher similarity to those of birch pollen than hazel pollen22, and the C-terminal α-helix of hazelnut Cor a 1.04 allergens contain a main T cell epitope that is not present in birch or hazel pollen allergens23.PR-10 proteins, which are expressed in plants upon environmental or pathogenic stimuli, have a molecular weight of ca. 17.5 kDa and comprise about 160 amino acid residues. These proteins exhibit a canonical fold consisting of a seven stranded antiparallel β-sheet (β1—β7) and three α-helices . The two short, consecutive helices α1 and α2 interrupt the β-sheet between strands β1 and β2 while the long C-terminal helix α3 is located above the β-sheet, creating a large and fairly hydrophobic cavity in the protein interior22. The structural basis for the different IgE-binding properties has remained elusive so far. In this work we present the nuclear magnetic resonance (NMR) solution structures of all four Cor a 1.04 isoforms along with in-depth experimental data regarding the structural flexibility, thermal and temporal stability and IgE-binding properties of these proteins. Our data reveal a clear inverse correlation between structural flexibility and IgE-binding, with the most flexible isoform showing the lowest potential to bind specific IgE.Among each other, the four isoforms of the hazelnut (Cor a 1.0401–Cor a 1.0404) share sequence identities of at least 97%. Nevertheless, these four allergens display strikingly different IgE-binding properties in enzyme allergosorbent tests, with a proposed immunologic ranking Cor a 1.0401 > 02 > 03 > 0424. An overlay of the lowest energy NMR structures of the four Cor a 1.04 isoforms shows that slight variations are present regarding the curvature of the β-sheet and the C-terminal helix α3. Very similar structural variations are also present between other PR-10 allergens, e.g. birch pollen and different food sources  containing Pro99 and the adjacent strand β7 (Gly112-Thr123) display only slightly reduced β-strand propensities in Cor a 1.0404 when compared to the other three isoforms26.A sequence comparison of the four Cor a 1.04 isoforms is shown in Fig. 17. In Cor a 1.0401 the surface of the internal cavity  NMR experiments, which provide site-specific information about the presence of different conformers32. In RD-NMR experiments, transitions between different conformers occurring on the micro-to-millisecond time scale cause non-flat dispersion profiles, while conformational homogeneity results in flat dispersions. Experimental RD data for representative amino acid residues  in the four Cor a 1.04 isoforms are shown in Supplementary Fig. 2,eff values) are color-coded on the protein structures in Fig. The NMR solution structural ensembles of the four Cor a 1.04 isoforms  is distributed almost over the entire protein scaffold. Moreover, it is evident that flexible residues are particularly grouped around position 99 in strand β6, which is occupied by proline in Cor a 1.0404 and serine in all other isoforms. This includes residues in the direct proximity of Pro99 in strand β6, such as Ile98 and Tyr100, as well as residues in the adjacent strands β5 and β7. Increased flexibility in β7 of Cor a 1.0404 is evident from both relaxation dispersion (Thr118 and Ser119) and NMR order parameter data , display the highest degree of flexibility in the isoform Cor a 1.0404.In isoforms Cor a 1.0401–03, the backbone amide of Ser99 forms a hydrogen bond to Lys120 in β7. It is likely that the lack of such a hydrogen bond in Cor a 1.0404 causes structural lability of the β-sheet of this particular isoform. Nevertheless, it is clear from the NMR relaxation data that even parts of the protein, which are distal from position 99  exchange measurements that detect the replacement of the backbone amide protons with deuterium upon addition of D2O.The most (Cor a 1.0404) and the least (Cor a 1.0401) structurally flexible isoforms, have been reported as those with the lowest and the highest IgE-binding potential, respectively1H–15N correlation spectra were obtained in ca. 4 min, which enabled us to record reliable H/D exchange data, even for rapidly exchanging backbone amides, revealing significantly accelerated exchange in Cor a 1.0404 compared to Cor a 1.0401. In detail, Ala9, Glu101 and Ala154, which are located in secondary structure elements and hydrogen bonded, have very slow exchange rates in Cor a 1.0401, while Ala107, which is surface exposed in loop L8, displays a moderate exchange rate. In Cor a 1.0404, all four amino acid residues display drastically faster H/D exchange. The positions of these residues are indicated on the Cor a 1.0404 structure in Fig. Figure The fact that hydrogen–deuterium exchange of the two proteins Cor a 1.0401 and Cor a 1.0404, despite sharing similar structural scaffolds, exhibit significantly different exchange rates, indicates that hydrogen bonds in the Cor a 1.0404 isoform are weaker. This structural lability could be elicited by the missing hydrogen bond between Pro99 and Lys120 in the center of the β-sheet. Of note, the only other difference between the two isoforms is position 4 at the N-terminus, which is occupied by a cysteine in Cor a 1.0401 and a serine in Cor a 1.0404.To investigate the impact of the two variable amino acid residues at positions 4 and 99 in Cor a 1.0401 and Cor a 1.0404 in detail, we performed time-dependent NMR degradation assays Fig. . After 51H–15N-HSQC spectra at different temperatures in the range of 10 °C to 70 °C  to the four hazelnut Cor a 1.04 isoforms34. The patients show birch-pollen related hazelnut allergy (specific IgE to Cor a 1 > 0.35 kU/mL and Bet v 1 > 0.35 KU/mL), positive skin-prick test to hazelnut extract and oral allergy symptoms to hazelnuts (see demographic data in Table We verified the immunologic activity of our recombinantly produced Cor a 1.04 proteins using blood sera from twenty-two Austrian patients (Tyrol) included in a pilot study22. Likewise, agreement of basophil release data with allergosorbent data was shown in a study comparing the different hazelnut allergens Cor a 1, Cor a 8, Cor a 9, and Cor a 11 by Blanc et al.35. This supports the notion that the effect seen in our ELISA experiments indeed originates from different IgE-binding of the four isoforms.In immunosorbent assays, different blotting efficiencies of proteins on hydrophobic surfaces of microplates and different propensities to desorb off the surface during the washing procedure can affect the amount of antigen that is available for IgE-binding and detection. These effects limit the use of immunosorbent assays per se for comparing IgE-binding of different isoforms. Nevertheless, the ranking of the immunologic activity of the four hazelnut Cor a 1 isoforms observed in basophil release assays complies with enzyme allergosorbent tests, reported by Lüttkopf et al.A statistical analysis of the ELISA data and ImmunoCAP data are shown in Fig. 22. This is corroborated by our IgE-binding data for the isoforms Cor a 1.0402 and Cor a 1.0403, which differ only at position 4 (Ser4/Cys4) and display comparable IgE-binding, with Cor a 1.0403 having only a slightly higher binding potential than Cor a 1.0402. These data suggest that replacement of a serine by a cysteine residue at position 4 has a minor effect on IgE-binding, even though these residues are surface exposed, as previously noted in enzyme allergosorbent tests22.As mentioned above, between Cor a 1.0401 and Cor a 1.0404, only two amino acid residues are different (Cys4/Ser4 and Ser99/Pro99), with their side-chains located on the protein surface, and our mutational studies suggest that proline at position 99 of Cor a 1.0404 causes the structural lability of this particular isoform. Likewise, Pro99 is presumably the main reason for the dramatically reduced IgE-binding potential of Cor a 1.0404 compared to Cor a 1.0401, as suggested by Lüttkopf et al.36. Cor a 1.04 isoforms contain between two and three cysteine residues  that are surface exposed and accessible for cysteine-mediated dimerization. Therefore, we probed the oligomerization state of Cor a 1.0401 (three cysteines) and Cor a 1.0404 (Cys82 and Cys160) under the buffer conditions that we employed for our ELISA and NMR experiments using pulsed-field gradient experiments. Cor a 1.0401 has a hydrodynamic radius of 18.6 ± 0.1 Å without and 18.7 ± 0.4 Å with a reducing agent (DTT) being present, respectively, which is consistent with a monomeric protein in both cases and comparable to other monomeric PR-10 proteins37. This is supported by the retention times observed in size exclusion chromatography, which are characteristic for a monomeric PR-10 protein. Likewise, the hydrodynamic radius of Cor a 1.0404 is 18.6 ± 0.5 Å, again indicating a monomeric protein. Cor a 1.04 isoforms thus show no tendency for dimerization or oligomerization under the experimental conditions that were used for IgE-binding measurements.In principle, IgE-binding can also be modulated by the formation of dimers or higher oligomersOur experimental NMR and immunologic data suggest an inverse relationship between IgE-binding observed in ELISA experiments and the structural flexibility of the four known isoforms of the Cor a 1 hazelnut allergens, even though their three-dimensional structures are highly similar. Cor a 1.0401 is the isoform with the highest potential to bind IgE, while it is the protein in this group with the most rigid backbone scaffold. Cor a 1.0404, on the other hand, is the isoform that has the lowest IgE-binding potential, yet this protein is strikingly flexible and conformationally heterogeneous in solution and displays a weak hydrogen bonding network. Cor a 1.0402 and Cor a 1.0403 are intermediate between these isoforms regarding their IgE-binding potential and their structural flexibility.38, including those from the PR-10 family of proteins40. Only for the major birch pollen allergen, Bet v 1, isoform-specific flexibility data have been reported, revealing Bet v 1.0101 to be fairly rigid and having substantially higher IgE-binding potential than the structurally flexible isoform Bet v 1.010241. As with Cor a 1, structural flexibility in Bet v 1 is distributed across the entire PR-10 scaffold, including secondary structure elements and loops. These observations parallel our experimental data for the hazelnut allergen described here.Enhanced levels of structural flexibility have been observed for various allergens42. The reduction of antibody structural flexibility was proposed as means to lower the entropic cost of complex formation in order to design antibodies with increased affinities43. Along these lines, it has been shown by experiment that complex formation leads to antibody rigidification43, and reduced antibody flexibility has been proposed as general feature of antigen–antibody binding44.Structural flexibility has been recognized as a critical component of antigen–antibody bindingExperimental data regarding the rigidification of allergens in antibody complexes are not available to date. Considering the pronounced flexibility of PR-10 allergens in solution, it is possible that complex formation is indeed accompanied by rigidification of the protein scaffold, resulting in a loss in conformational entropy and causing a lower binding affinity for more flexible isoforms. According to the concept of conformational selection, it is also conceivable that in the more rigid isoforms the binding-competent conformation is highly populated in solution. The more flexible isoforms on the other hand may fluctuate between several conformational states, resulting in a lower population of the binding-competent conformation. This lack of structural pre-organization could contribute to lower IgE-binding. The inverse relation between structural flexibility and IgE-binding observed in our Cor a 1 study suggests that entropic contributions indeed play an appreciable role in complex formation between these allergens and antibodies.Additional methods are described in the supplementary methods section (Supplementary Information).26. Plasmid constructs encoding the mutant forms C4S Cor a 1.0401, P99A Cor a 1.0404, and P99T Cor a 1.0404 were created by site-directed mutagenesis using Phusion DNA polymerase  for C4S Cor a 1.0401 and Platinum SuperFi DNA polymerase  for P99A Cor a 1.0404, and P99T Cor a 1.0404 according to the protocol of the manufacturers. The mutant forms P99A Cor a 1.0404 and P99T Cor a 1.0404 were generated using C4S Cor a 1.0401 as template. The used oligonucleotides were 5′-ccatgggcgtgttctcctacgaagatgagg-3′ and 5′-cctcatcttcgtaggagaacacgcccatgg-3′ for C4S Cor a 1.0401, 5′-ccctggaaaaaatcgcctacgagattaaaatggc-3′ and 5′-gccattttaatctcgtaggcgattttttccaggg-3′ for P99A Cor a 1.0404, and 5′-ccctggaaaaaatcacctacgagattaaaatggc-3′ and 5′-gccattttaatctcgtaggtgattttttccaggg-3′ for P99T Cor a 1.0404 (underlined nucleotides were mutated). Mutagenesis was verified by DNA-sequencing , Cor a 1.0402 (accession no. AAG40329), Cor a 1.0403 (accession no. AAG40330), and Cor a 1.0404 (accession no. AAG40331) and the subsequent expression has been described previously26. The same protocol was used for the three mutant forms. All NMR samples contained 20 mM sodium phosphate buffer (pH 6.9), 2 mM DTT, 9% D2O and 0.5 mM 15N labeled or 15N/13C labeled protein.The protein purification protocol for the four wild-type hazelnut isoforms has been described previouslyhttps://bmrb.wisc.edu) under the accession numbers 27965, 27961, 27967, and 28016 for Cor a 1.0401, Cor a 1.0402, Cor a 1.0403, and Cor a 1.0404, respectively26. For structure determination, three-dimensional 1H–15N-NOESY-HSQC, 1H–13C-NOESY-HSQC, and aromatic 1H-13C-NOESY-HSQC experiments with a mixing time of 150 ms each were carried out at 25 °C on a 500 MHz Agilent DirectDrive 2 spectrometer equipped with a room temperature probe. Processing of the NMR data was performed with NMRPipe45, and spectra were visualized with nmrDraw45 and analyzed using CcpNmr46.The resonance assignments for the four isoforms with all corresponding NMR experiments have been reported previously and are available at the Biological Magnetic Resonance Data Bank 51. Hydrogen bond restraints were derived from the CS-Rosetta structure model for the secondary structure elements, if no water cross-peak was detected in the proton TOCSY spectra. Dihedral angle restrains (Φ and Ψ) were derived from the program TALOS+52.For the manual assignment of the NOE cross-peaks an initial CS-Rosetta53 waters with at least 10 Å from each atom to the box boundaries. The LEaP module of AMBER 1854 using the Amber force field 14SB55 parameterized the system. After solvent relaxation56, simulated annealing calculations with a Langevin thermostat57 (collision frequency: 2 ps−1) and a Berenden barostat58 (relaxation time: 2 ps) were performed. Hydrogen bonds were constrained with the SHAKE algorithm59 and a van der Waals cutoff of 10 Å was used along with the particle-mesh Ewald method60 for long range electrostatics. A simulated annealing scheme of 50 ns with a time step of 1 fs for each structure was performed using the NOE distance restraints. The protein structure validation software (PSVS) suite61 was used to validate the refined structures. Internal cavity volumes and surface hydrophobicity were determined using SiteMap63 as implemented in the Schrödinger Maestro Software Suite64. RMSD values between the different PR-10 proteins were obtained using the program SuperPose65.For the final structure determination, 500 structures were calculated in 3000 steps at an initial temperature of 7000 K, followed by 10,000 cooling steps, using an extended starting structure. The 20 structures with the lowest energy were further refined in explicit solvent. For this purpose, each structure was surrounded by a cubic box of TIP3P1H–15N-HSQC spectra on a 700 MHz Bruker Avance Neo spectrometer equipped with a Prodigy CryoProbe at different temperatures . Chemical shifts were referenced at all temperatures using an external standard sample containing 1% (w/v) 4,4-dimethyl-4-silapentane-1-sulfonic acid (DSS) in 450 µL 20 mM sodium phosphate buffer (pH 6.9), 2 mM DTT, supplemented with 10% D2O.The temperature sensitivity of Cor a 1.0401 and Cor a 1.0404 was probed by recording 66. The employed gradient field strengths were 2.0, 4.5, 7.0, 9.5, 12.0, 14.5, 17.0, 19.5, 22.0, and 24.5 G/cm with a constant diffusion time of 160 ms. Hydrodynamic radii were determined for all dispersed peaks in the 1H–15N-HSQC spectrum by using an in-house MATLAB fitting program and the Stokes–Einstein equation, as described in detail for Bet v 137. Average values and standard deviations of the hydrodynamic radii were calculated from the 20 residues with the lowest RMSD values.For the determination of the oligomerization state of Cor a 1.0401 and Cor a 1.0404 stimulated echo pulsed field gradient experiments were used1H–15N-HMQC spectra67 acquired at 700 MHz using a Prodigy CryoProbe at 10 °C and a rapid injection device, as described by Schanda et al.68. NMR samples were prepared in 20 mM sodium phosphate buffer (pH 6.9) with 2 mM DTT, and hydrogen–deuterium exchange was initiated by addition of an equal volume of the same buffer in D2O to a final protein concentration of 0.3 mM. A series of SOFAST 1H–15N-HMQC spectra were recorded immediately after sample mixing, each lasting for 4.12 min (Cor a 1.0401) or 3.8 min (Cor a 1.0404). Using an in-house MATLAB fitting script, the hydrogen–deuterium exchange rates were obtained from exponential decay fits.Hydrogen–deuterium exchange of the amide protons of Cor a 1.0401 and Cor a 1.0404 was assessed by SOFAST 15N relaxation dispersion experiments were recorded on a 500 MHz spectrometer, a 600 MHz Bruker Avance II + spectrometer equipped with a Prodigy CryoProbe, and a 700 MHz spectrometer, using sensitivity enhanced Carr-Purcell-Meiboom-Gill (CPMG) sequences69 with 1H continuous-wave decoupling during the CPMG period70. Spectra were recorded at different CPMG field strengths νCPMG = (2τCPMG)−1, with τCPMG being the time between two consecutive 180° pulses in the CPMG pulse train. The νCPMG field strengths were 33.3, 66.7, 100.0, 133.3, 166.7, 200.0, 266.7, 333.3, 466.7, 600.0, 733.3, and 933.3 Hz, with repeat experiments at 66.7 Hz and 600.0 Hz, and the length of the CPMG pulse train was set to Trelax = 30 ms in all experiments. Effective relaxation rates R2,eff = − 1/Trelax × ln(I/I0) were determined from partial peak volumes (intensities in 5 × 5 grids) of the resonances in the individual spectra (I), along with a reference intensity (I0) with Trelax set to 0. The so-obtained relaxation dispersion profiles were analyzed by fitting the exact CPMG expression for two-site exchange using an in-house-written MATLAB script71. Per-residue relaxation dispersion amplitudes  were calculated from the 600 MHz data as ∆R2,eff = R2,eff (νCPMG = 0) − R2,eff (νCPMG = ∞), where R2,eff (νCPMG = ∞) and R2,eff (νCPMG = 0) are the extrapolated R2,eff values at infinite and zero CPMG field strengths, respectively.Backbone amide 73. Serum levels of total IgE and IgE specific for Bet v 1 and Cor a 1 were determined by ImmunoCAP  according to the manufacturer's specifications. The demographical and immunologic data (Table A skin-prick test (SPT) with hazelnut extract , histamine as a positive control and diluent as a negative control was performed on the flexor surface of the forearm according to Heinzerling et al.3 pH 9.7 to a final concentration of 1 µg/mL. In each well of a 96 Well Corning Costar Assay Plate  either 100 µL mAb 107 (for standardization) or 100 µL protein (for specific IgE detection) were placed and incubated at 4 °C overnight. The plate was washed with 150 µL PBS/0.1% Tween 20 the next day and subsequently saturated with 150 µL PBS/3% BSA per well. Incubation was conducted for 90 min under moderate shaking and afterwards the plate was washed as before. The patients’ blood sera were diluted 1:2 (v/v) with PBS and the human IgE standard from the kit was diluted to 100, 50, 20, 10, 5, 2, and 0 ng/mL with PBS. Either 50 µL of diluted serum or diluted standard were added to the wells containing protein or mAb 107, respectively and the plate was incubated at 4 °C overnight. Another washing step was conducted as before and the Anti-Human IgE (ε-chain specific) detecting antibody  was diluted 1:1000 (v/v) with PBS/1% BSA and 50 µL of it were added to each well. Incubation was conducted for 60 min and afterwards the plate was washed as before and 100 µL SureBlue TMB Microwell Peroxidase Substrate  were added to each well and incubated for 20 min in the dark. The reaction was stopped by the addition of 100 µL TMB Stop Solution . Between each incubation step the plate was sealed with adhesive plate sealers to avoid evaporation and contamination. The absorption at 650 nm was measured at a microplate reader. Each protein and standard was measured as triplicate and a linear logarithmic function was derived from the standards. Values for Cor a 1.04 specific IgE [kU/L] was determined using this linear function.The IgE-binding potential and the biological activity of Cor a 1.0401, Cor a 1.0402, Cor a 1.0403, and Cor a 1.0404 was assessed by using an indirect enzyme-linked immunosorbent assay (ELISA). Unlabeled freshly recombinantly produced proteins and the mAb 107 of the Human IgE ELISA development kit HRP , which was used for standardization, were diluted in 0.1 M NaHCO74.The Shapiro–Wilk test was used to evaluate normal distribution. Correlations between specific Cor a 1.04 IgE values with the IgE values determined by ImmunoCAP were assessed by the Spearman rank test. Differences between the groups were tested with the Friedman two-way ANOVA and Post hoc tests. All statistical analyses were done with the program SPSS 25Supplementary Information