Euphausia superba, and Salpa thompsoni) exert a top-down control on Chl-a and microzooplankton. Stratification of the water column benefitted the availability of adequate food-size (Chl-a <20) for large microzooplankton (tintinnids) development observed during fall. High abundance of omnivores mesozooplankton (Oithona similis and furcilia of E. superba) during sea-ice freezing periods would be due to the presence of available heterotrophic food under or within the sea ice. Finally, the increase in microzooplankton abundance in the middle of spring, when sea-ice melting starts, corresponded to small and medium dinoflagellates and ciliates species, which were possibly part of the biota of sea ice. If glacier retreat continues and the duration and thickness of the sea ice layer fluctuates as predicted by climate models, our results predict a future scenario regarding the zooplankton succession in Antarctic coastal environments.The rapid increase in atmospheric temperature detected in the last decades in the Western Antarctic Peninsula was accompanied by a strong glacier retreat and an increase in production of melting water, as well as changes in the sea-ice dynamic. The objective of this study was to analyze the succession of micro- and mesozooplankton during a warm annual cycle (December 2010-December 2011) in an Antarctic coastal environment (Potter Cove). The biomass of zooplankton body size classes was used to predict predator-prey size relationships  using a Multiple Linear Regression Analysis. The micro- and mesozooplanktonic successions were graphically analyzed to detect the influence of environmental periods  on coupling/uncoupling planktonic biomass curves associated to possible predator-prey size relationship scenarios. At the beginning of the glacial melting, medium and large mesozooplankton (calanoid copepods,  In the Western Antarctic Peninsula (WAP) a rapid increase in atmospheric temperature has been detected in the last decades ,2 accompThe decadal temperature changes in the WAP are not only associated with the drivers of global temperature change but also reflect the extreme natural internal variability of the regional atmospheric circulation . These rGlobal warming could additionally, change the phenology, or the time of occurrence within a succession of planktonic organisms, decoupling top-down control by microzooplankton on phytoplankton ,21. Micra (Chl-a) concentrations have been studied from 1991 to 2009 by Schloss et al. [In Potter Cove (PC), at the South-West of King George Island KGI/Isla 25 de Mayo), the addition of water from melting of the Fourcade Glacier has a significant impact on the temperature, salinity, and hence, stratification, and turbidity of the water column ,12. In t de Mayo,s et al. –28 in PCIn this frame, here we present the first study of the succession of micro- and mesozooplankton in relation to glacier melting and sea-ice dynamics during an annual cycle in PC. The study was conducted in 2011, a year in which average air temperature (-2.36°C) was higher than the average of the previous 60 years (-2.5°C). We hypothesize that 1) variations in wind, glacial melting, and sea ice cover are the main drivers affecting the spatial and temporal dynamics of micro- and mesozooplankton in PC, determining differences in abundance, biomass, and taxonomic composition, and 2) top-down control exerted by zooplankton is linked to the predator-prey size relationships.This study was carried out at Potter Cove  by the Argentine Carlini Station (formerly Jubany) from December 2010 to December 2011. The cove is a fjord-like, shallow coastal environment of 2.5 km wide by 4 km long, with maximum depths > 100 m in the outer zone and < 50 m in the inner zone .Sampling was carried out at two sites and two depths differently impacted by glacial melting . Site 1 -3 . The methodologies used for samplings varied according to the conditions of the cove (i.e. navigable or frozen sea). When navigable (December 2010 –May 2011 and November–December 2011), samples were collected from a Zodiac and when the cove was frozen (June–October 2011), sampling was performed from a hole in the sea-ice at S1. In these cases, sea ice instability conditions prevented the access to S2, except in July, despite the high degree of freezing of the inner zone. At each sampling event, density, salinity, temperature and turbidity profiles, from 30 m to the surface were obtained using a Seabird CTD (19 plus V2). The surface mixed layer depth (Zm) was estimated as the depth at which the gradient in density (σt) over a 1 m depth interval was >0.03 m method: ).a, 5 L water was collected with a Niskin bottle from surface and deep layers in the two sites. Microzooplankton samples for qualitative analyses were additionally obtained using 20 μm mesh net and short and slow horizontal tows. Mesozooplankton samples were collected by 2 knots-horizontal tows at the two depths using a 200 μm mesh net with a flow meter fixed to the mouth net. SMN  office (named Estación Meteorológica Jubany) in the Argentine Carlini Station provided the meteorological data for the studied period. The extent of sea-ice in the cove was estimated by observational records . The duration of sea-ice cover is defined as the difference between dates of sea-ice retreat and advance, corresponding to the last and first day of the year in which sea-ice concentration was higher than 15% for at least five consecutive days in the region [To analyze microzooplankton, SPM and Chl-e region . The appa concentration was determined by filtering 0.5–1 L through GF/F filters. Additionally, 0.5 L samples were pre-filtered through a 20 μm pore diameter mesh to calculate the concentration of Chl-a corresponding to a fraction smaller than 20 μm (Chl-a <20) and filtered again through GF/F filters. The concentration of Chl-a greater than 20 μm (Chl-a >20) was calculated by difference with total Chl-a. Photosynthetic pigments were extracted during 24 h at 4°C under dark conditions with 90% acetone and read on a Shimadzu UV160A spectrophotometer. Chl-a concentration was estimated following Strickland and Parsons [The SPM, organic (OM), and inorganic matter (IM) concentrations, were calculated following the gravimetric technique  with mod Parsons  after co-1) 100 ml of a subsample was left for at least 24 h in a sedimentation chamber prior to the analysis following the Utermöhl method using an inverted microscope [3) by approximation of each organism to a standard geometric configuration of similar characteristics [-1) was calculated using suitable conversion factors for each taxonomic group: aloricate ciliate  were preserved with acid Lugol’s solution (2% f.c.). For the estimation of microzooplankton abundance , tintin.19 x V; ), dinofl [0.939; ), rotife [0.939; ), and na [0.939; ). The es-3). The main taxonomic groups Copepods and Euphausiids were identified at a species level; while the rest of the main taxonomic groups  were grouped as "others taxa" and only Pteropoda and Salpida were identified at species level. To estimate mesozooplankton biomass, the individual dry/wet weight of the most representative taxa  were either taken from the literature (e.g. [-1) in turn, were derived applying conversion factors from the literature [Mesozooplankton samples were preserved in 4% neutralized formaline (f.c.) and then analyzed under stereo microscopes by aliquots (10% of the sample) or total counting to obtain mesozooplankton abundance (ind mre e.g. –48) or c or c-3).re e.g. –51). Car. Car-3).terature ,53.a, and SPM, owing to the rejection of normality and homoscedasticity assumptions. In order to observe any pattern of spatial and temporal distribution of zooplankton biomass and composition between sites, depth, seasons, and environmental periods , we first analyze the data using a Cluster ordination analysis, with a One-way analysis of similarity (ANOSIM) to determine the significance of spatial and temporal dynamic of zooplankton, and a similarity percentage analysis (SIMPER) to observe the percentage contribution of each specie to either the similarities within a given group or dissimilarities between groups. These multivariate analyses were performed using PRIMER V6 software. After that, multivariate redundancy analyses (RDAs) were performed to explore the temporal associations between the biomass of micro-and mesozooplankton taxonomic groups along gradients of Chl-a and environmental data in the four spatial scenarios over the annual cycle studied: S1-Surface, S1-Deep, S2-Surface, and S2-Deep. These statistical analyses were performed after confirming through a preliminary detrended correspondence analysis (DCA) that the length of the gradient in units of standard deviation obtained was lower than 4 [To analyze meteorological and oceanographic data variability among seasons, sampling sites (S1 and S2), and depths (Surface and Deep) non-parametric Kruskal–Wallis tests were performed on seasonal averages of wind, air and water temperature, salinity, turbidity, Chl-r than 4 . RDA and3 cell-1): <103, 103−104, 104−105, and > 105, while mesozooplankton were classified into length-size classes (μm): 103, 103−104, 104−105, and > 105. Phytoplankton biomass (as Chl-a concentration) was classified as Chl-a <20 and Chl-a >20. Micro- and mesozooplankton size-classes were the dependent variables, whereas Chl-a, and micro- and mesozooplankton size-classes  acted as explanatory variables. These statistical analyses were performed using STATISTICA version 7. The micro- and mesozooplanktonic successions in terms of size structure and total biomass were graphically analyzed, to detect the influence of environmental periods  on the plankton assemblages and to identify trophic relationships scenarios (coupling/uncoupling) in the planktonic biomass curves.To detect local trends, the biotic and abiotic dataset obtained in PC during the sampling period was analyzed. The biomass of plankton body size classes (determined by zooplankton size structure) was used to predict predator-prey size relationships  using a Multiple Linear Regression Analysis (MLRA). Microzooplankton was classified into volume-size classes (μm-1) and fall (34.02 ±13.13 Km h-1). October was the windiest month (40.38 ±16.83 Km h-1). West winds were dominant during the study period while the maximum wind speeds were from NW–W. Observations and photographic records obtained at PC indicated that the sea-ice cover lasted 143 days, from day 158 (beginning of June) to day 301 (end of October). The maximum thickness of the sea ice layer was observed in August with 1.5 m in the inner zone and 0.50 m in the outer zone. During the end of August and the beginning of September the entire cove was frozen. In mid-October, the sea-ice cover began to decline, in thickness and extent, only the inner zone remained frozen.The average air temperature in 2011 (−2.36 ±5.30°C) varied from −10.02°C (±5.81) in July to 2.93°C (±1.23) in February. Maximal average wind speed was recorded in spring  than in winter . In contrast, salinity showed the highest average value in winter  compared with the remaining seasons.The average sea water temperature was significantly lower at S1 (0.07 ±1.33°C) than at S2 . Salinity showed a similar, but not significantly, pattern with lower average value at S1 (33.71 ±1.12) than at S2 (34.00 ±0.20). Turbidity at S1 was significantly higher than at S2 . At S1 significant differences between the two layers of the water column were found showing higher values of turbidity in the surface (7.85 ±8.06 NTU) than in the deep layer  and in opposite trend, higher values of salinity were recorded in the deep (34.05 ±0.09) than in the surface layer . Several variables showed clear seasonal patterns. Significantly higher average values of water temperature, turbidity, OM, and Chl-The CTD profiles  showed tCalanus propinquus and Euphausia frigida (furcilia larvae) were the most discriminating taxa with a contribution higher than 24% and 15%, respectively to the dissimilarity of mesozooplankton temporal dynamics. C. propinquus and furcilia larvae of E. frigida contributed in 48.78% and 17.14%, respectively to the similarity within winter samplings; and in 40.89% and 29.72%, respectively to the similarity within Sea-ice freezing samplings. SIMPER also showed that the significant differences among environmental periods for microzooplankton were due to the presence of Codonellopsis balechi, the most discriminating taxon with a contribution always higher than 22% to the dissimilarity. C. balechi showed a contribution of 76.10% and 44.57% to the average of similarity of Glacial melting-stratification and Sea-ice freezing periods, respectively. In addition, others taxa which characterized environmental periods were: Protoperidinum aff. concavum , Gyrodinium lachryma , and Strombidium spp. (33.92% of Sea-ice melting).The Cluster ordination analysis generated two ordering graphs in which groups of samples related in terms of similarity in biomass and composition of microzooplankton and mesozooplankton . Mesozooa <20 related to some summer sampling dates; and another group formed by different mesozooplankton taxa and Chl-a >20 associated to winter, fall, and spring sampling dates. In the other three spatial scenarios analyzed, RDAs were not statistically significant and only a temporal gradient was detected in S1-Deep where fall, winter and spring sampling dates were associated with high values of salinity and biomass of euphausiids.Considering the RDAs results, the only spatial scenario which showed statistical significance (Monte Carlo test p <0.05) was S1-Surface . In thisE. superba and Salpa thompsoni) followed by calanoid copepods. In these sampling dates, low values of Chl-a and microzooplankton biomass were observed graphically as an uncoupling scenario in relation to mesozooplankton biomass curves (4−105 and > 105 μm) and possible prey  were also identified  composed of athecate dinoflagellates (Gimnodinium sp. and Gyrodinium sp.) and aloricate ciliates  and 103−104 μm (in March) was mostly represented by copepods  and a decrease of Chl-a was observed  accompanied by an increase of large copepods of 103 cell-1  was reco5 and 104−105 μm cell-1 such as nauplius larvae of copepods, C. balechi, and species of the genus Protoperidinium (3−104 μm (mostly C. propinquus and furcila larvae of euphausiids) with <103 μm (O. similis) and >105 μm classes (Clione limacina) as accompanying groups at the beginning and end of this period, respectively  as adults of E. superba and amphipods and then succeeded by 103−104 μm  and 104−105 μm classes  presented negative relationships with large phytoplankton (Chl-a >20) and large microzooplankton , and stratification of the water column. Similar oceanographic conditions were observed in PC during summer in superficial waters close to the glacier ,25,56. Tin situ observations during the winter of 2011, when the thickness of the sea ice was greater than in the years 2009 (~0.4 m) and 2010 .The period in which PC remained covered by sea-ice during 2011 (143 days) was lower than the average recorded by Schloss et al.  but was The spatial-temporal distribution of zooplankton in PC was first modulated by the dynamics of the environmental variables and then, by trophic relationships. This is evident in the results of the analysis of ordering (cluster), since the composition of zooplankton change in relation of the degree of glacial melting and sea-ice freezing. Additionally, the low values of mesozooplankton in some sampling dates of summer 2011 could be explained by the high levels of turbidity, produced by glacial meltwater. In Antarctic coastal zones, turbidity affects mesozooplanktonic organisms, such as euphausiids and copepods, modifying their distribution, decreasing their ingestion rates and feeding capacity ,58,59 anE. superba is mainly herbivorous during summer in the Bransfield Strait. S. thompsoni is recorded as the major herbivorous zooplankton in the Southern Ocean [O. similis, ingests small and motile cells almost exclusively before the bloom; while C. propinquus and M. gerlachei, consume large cells rather than smaller ones, and showed a preference for motile prey compared with similar sized diatoms. This top-down control by copepods on microzooplankton groups has been previously documented in the Southern Ocean [The analysis of the zooplankton succession according to predator-prey size structure allowed identifying trophic relationship scenarios during the different periods, characterized based on the changing environmental conditions. According to Fuentes , the imprn Ocean . In addirn Ocean  showed trn Ocean ,60,64.Water column stratification is essential for phytoplankton development  and domi3−104 μm on Chl-a <20 and Chl-a >20. At the end of this period, during May, the notable decrease in the biomass of both micro and mesozooplankton is possibly related to the decrease in phytoplankton, added to the selective predation of C. propinquus on large microzooplankton organisms as documented by Atkinson [The succession observed in zooplankton between summer and fall is determined by the change in the role as predator or prey of microzooplankton, which defines the transition from a herbivorous to a microbial food web. The increase in small protozooplankton and large phytoplankton could feed both small and large copepods, as observed in early fall (as a bottom-up control). These circumstances would contribute to the increase of microzooplankton biomass in April due to the lower grazing pressure of copepods on larger microzooplankton. In the Antarctic fall, heterotrophic protozoan biomass would then match or exceed phytoplankton biomass . As prevAtkinson .O. similis, C. citer and C. propinquus, begin to increase their abundance, possibly taking advantage of the availability of different microzooplanktonic groups as potential food resources [The only two previous studies documenting the annual variation of mesozooplankton groups in PC ,72 regisesources ,73,74. Oesources . Also, desources . ConsideDuring the spring succession, the instantaneous response of the microzooplankton to the increase in temperature and availability of food is documented in several studies as an increase in its biomass ,77. In oDuring an annual cycle at Potter Cove, mesozooplankton oscillations in abundance and biomass responded to glacier melting  and sea-ice freezing . Under W/NW wind conditions, stratification of the water column benefitted tintinnids development, through an increase in the availability of adequate food-size. The end of the stratification period of the water column is marked by the change in the trophic role of the microzooplankton, from predator to prey defining the transition to a marked microbial food web. Microzooplankton size structure  and feeding strategy of mesozooplankton (herbivores during early summer and omnivores during stratification and sea-ice freezing periods) were the main traits which determined the intensity of bottom-up/top-down controls during the temporal succession. If glacier retreat continues and the duration and thickness of the sea ice layer fluctuates as predicted by climate models, our results could be a prediction of future scenarios regarding the zooplankton succession in Antarctic coastal environments.S1 Data(XLSX)Click here for additional data file.


Infectious bronchitis virus (IBV), a coronavirus, is one of the most important poultry pathogens worldwide due to its multiple serotypes and poor cross-protection. Vaccination plays a vital role in controlling the disease. The efficacy of vaccination in chicken flocks can be evaluated by detecting neutralizing antibodies with the neutralization test. However there are no simple and rapid methods for detecting the neutralizing antibodies.In this study, a peptide enzyme-linked immunosorbent assay (pELISA) as a possible alternative to the neutralization test for evaluating the immune response to IBV vaccine was developed. The pELISA could indirect evaluate neutralizing antibody titers against different types of IBV in all tested sera. The titers measured with the pELISA had a coefficient of 0.83 for neutralizing antibody titers.The pELISA could detect antibodies against different types of IBV in all tested sera. The pELISA has the potential to evaluate samples for IBV-specific neutralizing antibodies and surveillance the infection of IBV. Coronaviridae family, which includes severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV) and the recently emerged novel human coronavirus SARS-CoV-2 [Infectious bronchitis (IB) is a highly contagious disease caused by infectious bronchitis virus (IBV). IBV belongs to the RS-CoV-2 , 2. IBV RS-CoV-2 –5. AlthoRS-CoV-2 . How canRS-CoV-2 , 8. Are RS-CoV-2  and enzyRS-CoV-2 , have beRS-CoV-2 , 12. TheRS-CoV-2 , 14.ELISA for detecting antibodies against IBV have been developed with the whole virion or recombinant S1 proteins, N proteins and nonstructural proteins –17. ThesThe IBV genome encodes four major structural proteins, spike (S), small envelope (E), membrane (M) and nucleocapsid (N); fifteen nonstructural proteins; and some accessory proteins . Among tTo evaluate the pELISA, the specificity and reproducibility of pELISA was detected. The results showed that immune sera against other viruses, such as NDV, ALV, MDV, AIV, IBDV, GPV, REV, ILTV and EDS-76V, were negative in the pELISA Fig. . And theTo further evaluate the pELISA, 300 field serum samples were tested and analyzed with the pELISA and IFA. The results showed that 268 and 32 serum samples were classified as positive and negative, respectively, by the pELISA, while 271 and 29 serum samples were classified as positive and negative, respectively, when the same samples were analyzed by the IFA  and H52 strain (GenBank accession number: EU817497) of IBV were obtained from Sinopharm Yangzhou Vac Biological Engineering Co., Ltd. . The CK/CH/2010/JT1 (GenBank accession number: KU361187), CK/CH/2014/FJ14 (GenBank accession number: MN262521) and CK/CH/2014/QL1403 (GenBank accession number: KU361198) strains of IBV were isolated and identified by our laboratory . Immune The epitope was synthesized by Synpeptide Co., Ltd. , and pELISA was preformed as our previous paper .650 value, standard deviation (SD) and coefficient of variation (CV) were calculated. The calculation formula of Coefficient of variation (CV) is standard deviation (SD)/ mean×100 %.The specificity of the pELISA was tested with serum samples positive against avian influenza virus (AIV), avian leukosis virus (ALV), reticuloendotheliosis virus (REV), gosling plague virus (GPV), Newcastle disease virus(NDV), infectious bursal disease virus(IBDV), infectious laryngotracheitis virus(ILTV), Marek’s disease virus(MDV), or egg drop syndrome-76 virus(EDS-76). The reproducibility within and between runs was assessed as described above with eight serum samples . The mean OD50) of the IBV strains  at 37 °C for 1 h. The mixtures were then added to 96-well plates containing 80 % confluent CEK cell monolayers and incubated for 2 h at 37 °C in 5 % CO2. The supernatant was removed, 200 µl of DMEM/F12 supplemented with 2 % FBS was added, and the plates were incubated for 48 h. The cells were fixed and examined by an indirect immunofluorescence assay. The neutralizing titer of each serum sample against IBV was determined and calculated by the Reed and Muench method.All sera were heat inactivated at 56 °C for 30 min, two-fold serially diluted and incubated with the same volume of 100 50 % tissue culture infectious dose . One-way ANOVA with repeated measures was used to evaluate the reactivity of peptide antigens with immune sera against IBV. Differences were considered statistically significant at


Angiotensin-converting enzyme (ACE) is best known for its formation of the vasopressor angiotensin II that controls blood pressure but is also involved in other physiological functions through the hydrolysis of a variety of peptide substrates. The enzyme contains two catalytic domains (nACE and cACE) that have different affinities for ACE substrates and inhibitors. We investigated whether nACE inhibitor backbones contain a unique property which allows them to take advantage of the hinging of nACE. Kinetic analysis showed that mutation of unique nACE residues, in both the S2 pocket and around the prime subsites (S′) to their C-domain counterparts, each resulted in a decrease in the affinity of nACE specific inhibitors  but it required the combined S2_S′ mutant to abrogate nACE-selectivity. However, this was not observed with the non-domain-selective inhibitors enalaprilat and omapatrilat. High-resolution structures were determined for the minimally glycosylated nACE with the combined S2_S′ mutations in complex with the ACE inhibitors 33RE (1.8 Å), omapatrilat (1.8 Å) and SG6 (1.7 Å). These confirmed that the affinities of the nACE-selective SG6, 33RE and ketoACE-13 are not only affected by direct interactions with the immediate environment of the binding site, but also by more distal residues. This study provides evidence for a more general mechanism of ACE inhibition involving synergistic effects of not only the S2, S1′ and S2′ subsites, but also residues involved in the sub-domain interface that effect the unique ways in which the two domains stabilize active site loops to favour inhibitor binding. Angiotensin-converting enzyme ACE, EC 3.4.15.1) is a zinc metalloprotease which has traditionally been known for its role in blood pressure regulation via the renin–angiotensin–aldosterone system (RAAS). During the last 20 years, there has been an increasing interest in the function of ACE in other biological systems. The somatic form of ACE (sACE) is expressed on the surface of endothelial, epithelial, neuroepithelial and immune cells .4.15.1 i,7. cACE Apart from decreasing blood pressure, the clinical use of non-domain-selective ACE inhibitors has been associated with various antifibrotic effects. Since this is largely attributed to the accumulation of the ubiquitously expressed AcSDKP, selective N-domain inhibition holds the potential for the treatment of fibrosis without affecting blood pressure ,13.ACE has also been implicated in the immune response and recently overexpression of ACE in macrophages and neutrophils was shown to cause an increase in oxidative metabolism and cellular ATP; however, the peptide substrate is currently unknown ,15. Furt2), l-pseudophenylalanine (P1), l-pseudoalanine (P1′) and C-terminal amidated alanine (P2′) moieties that, respectively, bind to the S2, S1, S1′ and S2′ subsites of the ACE active site (2 moiety being replaced by an aminomethyl tetrazole. Mutagenesis studies showed that the three orders of magnitude N-selectivity of these two compounds largely depends on interactions with unique nACE residues of the S2 subsite [2 subsite (Y369 and R381), the S1′ subsite (T358) and distal prime region , referred to as S2 (YR) and S′ , synergistically control the selectivity of 33RE and their mutation to cACE counterparts  completely abolished selectivity. The only unique direct interaction was between the P2 tetrazole of 33RE and Y369. The unique distal prime residues indirectly facilitated 33RE binding by favouring the protein's hinging towards active site cleft closure. In nACE, these residues formed an attractive polar sub-domain interface whereas in cACE, this interface was hydrophobic and caused repulsion between the sub-domains.At present, there are only a handful of ACE inhibitors with substantial N-selectivity, of which the phosphinic peptidomimetic compounds RXP407  and its ive site . Its fra subsite ,20. Howe subsite ,22. It w subsite . Differe2 position of a relatively non-selective ACE inhibitor backbone such as ketoACE to produce ketoACE-13 [2, S′ and combined S2_S′ mutated nACE , as well as solving high-resolution crystal structures of minimally glycosylated nACE with the combined S2_S′ mutations (N389-S2_S′-nACE) in complex with SG6, 33RE and omapatrilat.Previous attempts at designing more drug-like ACE inhibitors with this mechanism of action have had limited success. Although the addition of an aspartate moiety in the PtoACE-13  or enalatoACE-13  increase-glycosylated. Wild-type N-domain (nACE), C-domain (cACE) and the S2-, S′- and S2_S′-nACE mutants were previously created and cloned into pcDNA3.1+ (Invitrogen) for mammalian cell expression [Truncated wild-type or mutant proteins used for kinetic characterization were fully Npression . Chinesepression .−1 cm−1. Subsequent dilutions from the 1 mM stock of were made in assay buffer . The inhibitors 33RE [The fluorogenic substrate Abz-FRK(Dnp)P-OH was a kind gift from Prof A.K. Carmona, Universidade Federal de São Paulo. The peptide was dissolved in 100% DMSO and the concentration determined by measuring the absorbance at 365 nm and extinction coefficient of 17 300 Mors 33RE , SG6 [25ors 33RE  were synors 33RE , fresh 1ors 33RE . A 20 µl2Subsequent dilutions of all inhibitors were prepared from stock solutions in an assay buffer consisting of 50 mM HEPES pH 6.8, 200 mM NaCl and 10 μM ZnCl2 [2, 200 mM NaCl) and variable volumes added to a 96-well plate on ice. A constant volume of the enzyme was added to all wells and the final volume adjusted to 300 μl with buffer to give a constant amount of enzyme with a range of substrate concentrations. The hydrolysis of Abz-FRK(Dnp)P-OH was continuously monitored at excitation and emission wavelengths of 320 nm and 420 nm, respectively, at ambient temperature using a fluorescence spectrophotometer . The amount of active protein was determined immediately after purification by calculating the specific activity. Final enzyme concentrations in these assays were 10 nM for nACE and S′-nACE, and 5 nM for S2-nACE, S2_S′-nACE and cACE. Kinetic constants were calculated by analysis of the initial reaction velocities (at <10% substrate hydrolysis) with the Michaelis–Menten model in GraphPad Prism v.6.0.Binding and hydrolysis of the fluorogenic Abz-FRK(Dnp)P-OH substrate was determined as previously described in an assay buffer consisting of 50 mM HEPES pH 6.8, 200 mM NaCl and 10 µM ZnCl2 . Briefly2-nACE) or 0.33 nM (S2_S′-nACE); for ketoACE-13: 2.6 nM nACE with 4 µM Abz-FRK(Dnp)P-OH, 0.7 nM S′-nACE with 3 µM Abz-FRK(Dnp)P-OH, 0.2 nM S2-nACE with 3 µM Abz-FRK(Dnp)P-OH, 0.2 nM S2_S′-nACE with 2 µM Abz-FRK(Dnp)P-OH or 0.5 nM cACE with 3 µM Abz-FRK(Dnp)P-OH. Control (zero inhibitor) reactions containing the appropriate concentration of methanol or DMSO  were included to correct for any possible vehicle-induced effects on the reaction rate.To evaluate inhibitor binding affinity, a modified Abz-FRK(Dnp)P-OH assay was used. Serial dilutions of an appropriate range were prepared for each inhibitor in the aforementioned assay buffer. An appropriate concentration of enzyme was similarly prepared and incubated with an equal volume of inhibitor for 15 min at 22°C after which 20 µl volumes of the reactions were aliquoted to a 96-well plate. The volume per well was increased to 300 µl by the addition of Abz-FRK(Dnp)P-OH on ice at an appropriate concentration to allow detectable inhibition. The final substrate and enzyme concentrations for these assays were as follows: For SG6 and omapatrilat: 4 µM Abz-FRK(Dnp)P-OH with 2.6 nM enzyme; for enalaprilat: 4 µM Abz-FRK(Dnp)P-OH with enzyme at 1.3 nM (nACE or cACE), 0.66 nM  to obtain Ki values [Initial reaction velocities were analyzed in GraphPad Prism v.6.0 using the Morrison equation i values .2_S′-nACE active site mutant, the asparagine residues at sites 1 (Asn9), 2 (Asn25), 4 (Asn82), 5 (Asn117), 6 (Asn131) and 7 (Asn289) were converted to glutamine residues. Sites 1, 2, 4, 5 and 6 were situated upstream of the active site mutations and could, therefore, be removed by molecular cloning. The N3789-S2_S′-nACE construct was generated by performing sequential Bsu36I and EcoRI (Thermofisher ScientificTM) restriction enzyme digests on the fully glycosylated pcDNA3.1+ S2_S′-nACE and the minimally glycosylated pcDNA 3.1+ N3-nACE [EcoRI and XbaI was performed to screen for the presence of a ∼2000 bp coding region and thus the generation of the pcDNA 3.1+ N3789-S2_S′-nACE construct. Glycosylation site 7 (Asn289) was located amongst the active site mutations and as such was mutated to glutamine via site-directed mutagenesis using the Kapa HiFi PCR kit (Roche Molecular Systems Inc.) and previously designed primers [2_S′-nACE construct, was confirmed by restriction enzyme screening for the simultaneously introduced NdeI site. Additionally, bidirectional nucleotide sequencing was performed to confirm the presence of all active site mutations and N > Q mutation of sites 1, 2, 4, 5, 6 and 7.nACE is routinely crystallized in a minimally glycosylated form where six of the nine N-linked glycosylation sites have been mutated to glutamine residues. The resulting construct, N389-nACE, only retained glycosylation at sites 3 (Asn45), 8 (Asn416) and 9 (Asn480) . To enab), 6 Asn1 and 7 (A primers . Positiv−1 cm−1 for nACE.The construct was transfected into Chinese hamster ovary (CHO-K1) cells using the calcium phosphate Profection® Mammalian Transfection System (Promega Corp.), heterologously expressed and the protein purified from culture medium via lisinopril–sepharose affinity chromatography, as previously described . Protein2_S′-nACE was pre-incubated with the ligands for 1 h at room temperature using a 4 : 1 v/v ratio of 5 mg ml−1 protein  and inhibitor . Hanging drops of 1 µl of the protein-inhibitor complex mixed with an equal volume of reservoir solution were set up. The standard condition for nACE  was used to test for N389-S2_S′-nACE crystallisation, and it produced crystals of the same morphology.N389-SX-ray diffraction data were collected on stations i03 33RE) and i04-1 (omapatrilat and SG6) at the Diamond Light Source , with the crystals kept at a constant temperature (100 K) using a nitrogen stream. Images were collected using PILATUS3 6 M (33RE) and PILATUS-6M-F (omapatrilat and SG6) detectors . Raw data images were indexed and integrated with DIALS , and theRE and i02 subsite and sub-domain interface residues is important for the N-selectivity of 33RE [It is known that synergism between unique S of 33RE . To eval2-nACE (Y369F and R381E), S′-nACE  and S2_S′-nACE  were heterologously expressed in CHO-K1 cells [2-nACE and S2_S′-nACE displayed lower binding affinities  and higher catalytic turnover rates  compared with both wild-type domains and S′-nACE (kcat/Km) was, however, comparable between all proteins studied in agreement with our previous study [The truncated (single domain) wild-type N-domain (nACE), wild-type C-domain (cACE) and N-domain mutant constructs SK1 cells . The sec S′-nACE . The oveus study .Ki of 11.21 nM) and had ∼1000-fold selectivity over cACE [2-nACE and S2_S′-nACE mutations, respectively, leading to decreases in binding affinity of 22-, 254- and 900-fold [2 mutations have a greater effect than the S′ on 33RE affinity of nACE and that upon combining all eight mutations in S2_S′-nACE, a synergistic effect occurs so that the affinity for 33RE is similar to that seen for cACE  as a fraction of velocity in the absence of inhibitor (V0) for the wild-type and mutant enzymes. Omapatrilat, enalaprilat and SG6 showed picomolar to nanomolar potency for all enzymes tested and exhibited a tight-binding mode of inhibition ) .Ki values of 0.093 nM and 76.77 nM for nACE and cACE, respectively, and thus 825-fold N-selectivity similar to that of 33RE. The effect of mutation follows a similar trend to that of 33RE with S2 and sub-domain interface residues synergistically controlling N-selectivity. The S′ mutations resulted in a modest 11-fold decrease in affinity (Ki of 1.09 nM), followed by a more pronounced decrease in 474-fold with S2-nACE (Ki of 44.05 nM) and a drastic decrease in 784-fold when all mutations were combined in S2_S′-nACE (Ki of 72.93 nM), thereby yielding cACE-like affinity. From these data, it can be concluded that for 33RE and SG6 some, or all, of the S′ residues play a significant role in their binding, although this appears to be mainly if the affinity from the direct binding interactions (S2 residues) has also been reduced.The diprolyl analogue of enalaprilat, SG6, displayed Ki values of 1000 nM and 8250 nM for nACE and cACE, respectively  which, considering the low selectivity of ketoACE-13, was a drastic change towards cACE-like inhibition. Interestingly, S2-nACE and S2_S′-nACE had even lower affinities than cACE for ketoACE-13 with Ki values of 17 810 nM and 47 750 nM, respectively. Since the active site of S2-nACE is essentially equivalent to that of cACE, some property distal to the cACE active site appears to minimize the effect of Y369 and R381 loss on its inhibition by ketoACE-13. This property is likely lacking in nACE and it, therefore, depends on the S2 and sub-domain interface residues for inhibition by ketoACE-13.The binding affinities obtained here for ketoACE-13 (ectively ) were hiresidues . This waKi values of 0.75 nM and 0.16 nM for nACE and cACE, respectively), yet mutation ofS′, S2 and S2_S′ counterintuitively resulted in slightly decreased binding affinities  compared with nACE. This suggests that these residues facilitate nACE inhibition even in the absence of a P2 moiety and that cACE relies on some factor distal to the binding site for its effective inhibition. Addition of a P2 aspartate, as in SG6, likely strengthens the intrinsic synergism between nACE subsites to bring about selectivity.This property potentially also affects the binding of enalaprilat. This compound binds with a 5-fold greater affinity to cACE than nACE  to gain structural insight into the pronounced effects that these mutations have on inhibitor binding. The N-linked glycosylation sites 1 (Asn9), 2 (Asn25), 4 (Asn82), 5 (Asn117) and 6 (Asn131) were converted to glutamine residues by subcloning the N-terminus of S2_S′-nACE with that of N389-nACE. Replacement of site 7 (Asn289), however, required the use of site-directed mutagenesis due to its location between the E262S and D354E mutations of the active site. The minimally glycosylated active site mutant N389-S2_S′-nACE was successfully created, stably transfected, expressed and purified as illustrated by the lower molecular mass on SDS–PAGE compared with S2_S′-nACE  N389-S2_S′-nACE crystals grew. The N389-nACE protein also rarely crystallises in the native form, and even when crystals do form, they always have elements from the purification and crystallization conditions bound in the active site.The minimally glycosylated N389-nACE readily crystallises in the presence of ligands using a single condition that was identified from initial screens, and no screening around this condition is needed even for new ligand complexes. Therefore, this condition  was tried for N389-S2_S′-nACE readily crystallised in the presence of the three ligands . All the complexes were in the P1 space group with two molecules of the protein in the asymmetric unit. The structures were determined at high resolutions of 1.8 Å for both 33RE and omapatrilat, and 1.7 Å for SG6  show a very similar overall fold to each other and are also essentially the same as seen for N389-nACE  clear, unambiguous electron density for the bound ligands was observed in the mFo-DFc omit maps  has a hydrophobic interaction with His331.The backbone carbonyl of the P1 backbone carbonyl of a peptide and forms a bidentate interaction with the zinc ion as well as hydrogen bonds with Tyr501, His361 and His365. The P1 backbone nitrogen of 33RE interacts with a water molecule that co-ordinates with Glu389, Arg500 and Tyr501. The phenylalanine-like sidechain hydrophobically interacts with His331, Ser333, Phe490 and Thr496.The zinc-binding group of 33RE is a phosphinic acid that replaces the P2 group of 33RE has a peptide-like backbone with the carbonyl having a hydrogen bond with Ala334. The 33RE P2 sidechain, a tetrazole, shows hydrophobic interactions with His365, and hydrogen bonds to two water molecules that are also bound by the Gly382 backbone nitrogen, Pro385 backbone carbonyl and Glu389 sidechain. There are also three ethylene glycol molecules  that interact with the 33RE P2 group via the backbone nitrogen, another nitrogen from the tetrazole group and a hydrophobic interaction with the tetrazole carbon atom.The P2′ and P1′ groups of SG6 are essentially mimics of proline and alanine, respectively. Therefore, it is not surprising that the P2′ carboxylic acid group has identical interactions with Gln259, Lys489, His491 and Tyr498 described above for 33RE  of two bicine molecules, a calcium ion and water molecules that is adjacent to the SG6 P2 aspartate. The carboxylic acid group of the aspartate forms part of the calcium ion's coordination sphere, as well as interacting with one of the bicine molecules. In addition, the backbone nitrogen of the aspartate has direct, and water-mediated hydrogen binds with the second bicine.SG6 has a P2′ carboxylic acid group that binds in the typical S2′ carboxy-terminus binding site showing direct hydrogen bonds with Gln259, Lys489 and Tyr498, a water-mediated interaction with Lys489, and hydrophobic interaction with His491 . Theref2_S′-nACE contains mutations in the S2 subsite  are located at the edge of the S′ lobe on either side of where the two sub-domains of nACE come together  and are ted here . Examina2 subsite residues (YR), the S1′ T358 (which has no direct interactions) and the distal prime subsite residues (SEDSE) was responsible for the 1000-fold N-selective binding of 33RE [1′ pseudoalanine (T358) and creating a polar sub-domain interface to drive active site closure via hinging at the neighbouring hinge regions 2 and 4. This is consistent with the sub-domain interactions described above for the crystal structures presented here.Previously, it was shown that synergism between the S of 33RE , the mol1′ pseudoalanine) follows the same mechanism of action as 33RE. These two moieties are, therefore, not a requirement for N-selectivity. Although it had the same level of selectivity, SG6 was, however, much more potent than 33RE with picomolar to nanomolar affinities for all enzymes tested. This is likely due to its stronger zinc-binding (carboxylic acid) and/or C-terminal (proline with free carboxylic acid) moieties.Prior to obtaining the kinetic results presented here, it was believed that 33RE was the only ACE inhibitor to date with this mechanism of action due to some unique properties contained in its backbone. Amidation of the C-terminal pseudoalanine was thought to be crucial in conferring selectivity based on an earlier study on the parent of 33RE, RXP407 , whereas2 aspartate and P2′ amidated pseudoalanine or -proline moieties were incorporated onto this backbone had much lower N-selectivities compared with RXP407 [1′ pseudoalanine. This group is commonly found in many ACE inhibitors and is often described as being important for potency, but not necessarily domain-selectivity [1 to P2′ groups, the addition of a P1′ pseudoalanine would likely increase binding, but not selectivity, by introducing a hydrophobic moiety in the proximity of the nACE residue T358 and its cACE counterpart V380. Although these residues are not in direct contact with the P1′ pseudoalanine , they likely create a more favourable environment for positioning of the inhibitor and direct interaction with the zinc and conserved residues. In the case of 33RE or SG6, however, this group likely enhances the active site closure mediated by the SEDSE residues, thus increasing the selectivity relative to ketoACE-13.Previous work on ketoACE analogues where Ph RXP407 . The kinectivity . For mor2_S′ resulted in binding affinities that were, respectively, 6-fold and 19-fold lower than that of cACE. These mutations created a binding site which was essentially equal to that of cACE and indicates that although the direct enalaprilat interactions are conserved between the two domains, the mechanism of inhibition differed. To better understand this phenomenon, the previously published structure of enalaprilat complexed to cACE (PDB ID 1UZE) [2 group for interaction with Y369. The P2 group is likely not required for potent nACE inhibition when the P1′ pseudoalanine and acidic P2′ pseudoproline moieties are present, as in enalaprilat. Since cACE is less favoured for active site closure due to repulsion at the sub-domain interface, but still effectively inhibited by enalaprilat, we hypothesized that some property distal to the active site might assist in its inhibition. The P1 pseudophenylalanine is present in ketoACE-13 as well as enalaprilat and interacts with nACE T496 or cACE V518. Although the more hydrophobic valine might slightly increase the strength of the P1 interaction, it is unlikely to explain the discrepancy between cACE and S2_S′-nACE inhibition by enalaprilat. Interestingly, the T496/V518 residues are located on a long loop region that connects the helix harbouring nACE Y523/cACE Y501 (which binds to the inhibitor backbone) to conserved residues  which bind to the inhibitor's prime moieties   was caremoieties . This loTypically, protein–ligand interactions are usually the focus for the design of inhibitor potency and specificity. In this study, we show that to achieve the desired domain specificity of next-generation ACE inhibitors, it is important to also consider intra-protein interactions and distal residues that the inhibitor may transiently interact with during entry into the binding site. Thus, the entire protein must be considered as a dynamic molecule and not just the active site in isolation.While this does add to the complexity for the design process, due to the high degree of similarity between the binding sites of nACE and cACE, this new information will prove beneficial in obtaining new domain-specific inhibitors. Further study is required to fully understand these distal effects and this will help with inhibitor development.


Background and Objectives: Transesophageal echocardiography (TEE) guidance is the current gold standard for catheter-based procedures in the treatment of structural heart diseases. Intracardiac echocardiography (ICE), which can be performed under local anesthesia, has been recently introduced and is becoming more widely used. We aimed to compare the efficacy and safety of ICE and TEE in patent foramen ovale (PFO) device closure. Materials and Methods: All 74 patients with a history of cryptogenic stroke undergoing PFO closure for secondary prophylaxis were selected from our registry. Intraprocedural TEE was performed by echocardiographer-cardiologists with the patient under general anesthesia. Conversely, ICE was performed with the patient under local anesthesia. Baseline characteristics, procedural details, and immediate outcomes were compared between the TEE and ICE groups . Results: Although patients in the ICE group were older , sex and comorbidity variables were similar between the two groups. The degree of inducible right-to-left shunt via the PFO, assessed using preprocedural TEE, was also comparable. Notably, fluoroscopy time , radiation dose , and total procedural time in the catheter laboratory  were significantly lower in the ICE group than those in the TEE group. The entire hospital stay was similar between groups . No procedural complications, such as device embolization, pericardial hemorrhage, major bleeding, mortality, or access-related vascular injury were reported in either group. Conclusions: ICE-guided PFO device closure is quicker and less hazardous in terms of radiation exposure than the TEE-guided procedure, with similar procedural outcomes and duration of hospital stay. The foramen ovale is a physiological shunt of fetal circulation and normally fuses spontaneously after birth. However, the process of fusion fails in about a quarter of the general population, resulting in a patent foramen ovale (PFO) . PFO is PFO device closure is usually performed under the guidance of real-time transesophageal echocardiography (TEE) with the assistance of echocardiographer-cardiologists. However, the main drawback of TEE-guided PFO device closure is the requirement of general anesthesia, which necessitates an anesthesiology team. Alternatively, the recently introduced intracardiac echocardiography (ICE), which is usually performed by an interventional cardiologist, is being more widely used to guide the closure of interatrial communications because it is well tolerated by patients ,9,10. AlThis was a retrospective observational study using the PFO registry of the attending hospital. From March 2014 to September 2019, all 165 patients who had experienced a CS or recurrent transient ischemic attack (TIA) had a PFO documented using TEE, and underwent PFO device closure, were entered in the registry. Among them, 74 patients were identified as the study population.® PFO Occluder , GORE® Septal Occluder , and Occlutech Figulla® PFO Occluder  were implanted in all patients. The current study conformed to the Declaration of Helsinki (sixth revision). The Institutional Review Board of Gil Medical Center, Gachon University College of Medicine approved this study , and all patients provided written informed consent before enrollment.CS was defined as a stroke with no identifiable cause after excluding carotid or intracranial artery stenosis, atrial fibrillation, intracardiac thrombus, and atheromatous plaque at the aortic arch . PFO cloPFO shunt size was assessed by using TEE-based agitated saline contrast study with the Valsalva maneuver. A shunt was defined as the appearance of contrast bubbles in the left atrium (LA) within three cardiac cycles of opacification of the right atrium (RA). Shunt degrees were defined as mild, moderate, and severe if 3–9, 10–30, and >30 contrast bubbles, respectively, appeared in the LA ,12,13. SThe closure procedure was performed under general anesthesia. All procedures were performed by one operator (W.C.K.). One experienced echocardiographer-cardiologist (J.M.) performed TEE to help the operator make decisions during the procedure. After achieving femoral venous access, the PFO was crossed with a 5-Fr multipurpose catheter, which was advanced into the left upper pulmonary vein and exchanged over a 0.035-inch J-tipped stiff guidewire for an 8- or 9-Fr guiding sheath. Procedural anticoagulation was initiated with intravenous administration of 5000 units of unfractionated heparin. Thereafter, additional heparin was administered throughout the procedure to maintain an activated clotting time of ≥250 s. The size of the device was based on the TEE measurements of the distance between the PFO and aortic root. Device implantation was performed using previously described methods . TEE wasAll ICE-guided PFO closure procedures were performed under local anesthesia without conscious sedation. All procedures were performed by one operator (W.C.K.). The right and left femoral veins were punctured to introduce an 8- or 9-Fr and 8.5-Fr sheaths for the PFO closure device and ICE catheter, respectively. The ICE catheter was positioned in the RA through the sheath and was maneuvered for optimal visualization of the PFO. The procedure did not differ from the TEE-guided one except that the device was deployed under the guidance of ICE images.The recommended anti-platelet therapy after the procedure included daily intake of both aspirin 100 mg and clopidogrel 75 mg for at least 6 months. Thereafter, further use of any blood thinners was left to the discretion of the attending physician. The Risk of Paradoxical Embolism (RoPE) scoring system—comprised of age, history of hypertension, diabetes mellitus, stroke/TIA, smoking status, and cortical infarct on imaging—was used to stratify patients with PFO and CS according to the probability that the latter was attributable to the former ,17. Contt-test, whereas categorical variables were compared using chi-square and Fisher’s exact tests. Analysis of primary endpoint longitudinal data was performed using Kaplan–Meier estimates with log-rank test. p-values of <0.05 were considered statistically significant. The analysis was performed using SPSS version 20 .Continuous data are presented as mean ± standard deviation. Discrete variables are presented as absolute value and percentage. Continuous variables were compared using a two-sample Baseline clinical and TEE characteristics are shown in p < 0.05 for all). The length of hospital stay did not differ between the TEE and ICE groups. No procedural complications were reported in both groups.The number of cases of PFO device closure for secondary prophylaxis of CS has been consistently increasing since its introduction in the late 1980s . Most ofThe feasibility of ICE to guide device closure for intreratrial septal communication has been established ,19,23,24Although ICE-guided PFO closure is safe and effective, another issue that needs to be considered is the validation of ICE images. Vigna et al.  reportedThis study has all the inherent limitations of non-randomized single-center studies. The patient numbers and demographic features were not equal between the TEE and ICE groups. In addition, the sample size was small; hence, the difference in numbers between the two groups was not adjusted for. The use of closure devices from different manufacturers were not evenly distributed in the TEE- and ICE- group for technical issues and might be a confounder. Our institution is a tertiary referral medical center; hence, the current study patients may not be representative of all CS patients undergoing PFO device closure for secondary prevention. Notably, we enrolled consecutive patients, and the main operator in all procedures was identical ; therefore, the procedural learning curve favors a shorter procedural time in the ICE group because ICE was introduced later (June 2018) than TEE at our center. Atrial arrhythmia, including atrial premature complex, sustained-/non-sustained atrial tachycardia, or atrial fibrillation, occurs occasionally during PFO-device closure. Although no atrial fibrillation was detected in the current cohort, we do not have data of procedure-related transient cardiac rhythm disorder, so they were omitted from analysis.ICE-guided PFO device closure is quicker and less hazardous in terms of radiation exposure than the TEE-guided procedure, with similar procedural outcomes and hospital stay duration. As such, ICE is a promising imaging modality for its safety and efficacy, and it would be more widely used to guide the PFO closure. However, the discrepancy between preprocedural TEE and intraprocedural ICE images requires validation.


This trend was supported from both in vitro and in silico results. Both tetra-cinnamoyl CSEs 5 and 9 showed the highest α-glucosidase inhibitory activities of 77 ± 5%, 74 ± 9%, respectively, against acarbose at 27 ± 4%, and highest α-amylase inhibitory activities of 98 ± 2%, 99 ± 1%, respectively, against acarbose at 93 ± 2%. CSEs 3, 4, 6, 7, 8 showed desired higher inhibition of α-glucosidase than α-amylase suggesting potential for further development as AGIs with reduced side effects. Molecular docking studies on CSEs 5 and 9 attributed the high inhibition of these compounds to multiple π-π interactions and favorable projection of the cinnamoyl moieties  in the enzyme pockets. This work proposes CSEs as new AGIs with potentially reduced side effects.Cinnamoyl sucrose esters (CSEs) were evaluated as AGIs and their enzyme inhibition activity and potency were compared with gold standard acarbose. The inhibition activity of the CSEs against α-glucosidase and α-amylase depended on their structure including the number of the cinnamoyl moieties, their position, and the presence or absence of the acetyl moieties. The inhibitory values of the CSEs  Alpha Glucosidase Inhibitors (AGIs) acarbose, voglibose, and miglitol are effective oral antidiabetic drugs . They fuPhenylpropanoid sucrose esters (PSEs) are naturally occurring compounds isolated from various plant species such as Arecaceae, Liliaceae, Polygonaceae, Rosaceae, Brassicaceae, and Smilaceae . PSEs fe1 (We have earlier reported that feruloyl sucrose esters (FSEs)  function1  significHerein, we evaluate cinnamoyl sucrose esters (CSEs) as AGIs and compare their % α-glucosidase and α-amylase inhibition activities with gold standard acarbose. The factors that influence the selectivity and inhibition of the enzymes are also discussed.2–9 were specifically designed to differ in: (i) the number of cinnamoyl moieties, (ii) the degree of acetylation of the sucrose core, and (iii) the presence or absence of the diisopropylidene bridges on sucrose core  and α-amylase inhibitions . In both cases, the % α-glucosidase inhibition remained roughly >4 times higher than the % α-amylase inhibition as seen in the case of free OH in CSEs 3 and 4. The modest increase in selectivity may be attributed to the steric effects that the acetyl groups cause, which favors better docking of CSEs 6 and 7 at the active sites of the enzymes. Though the increase in inhibition was modest, acylation of the OH groups with other larger acetyl groups could be a means to influence the inhibition activities. CSE 8 without the diisopropylidene or acetyl groups exhibited a similar α-glucosidase inhibition value of 34 ± 4% as compared to its counterpart, CSEs 4 with 32 ± 3%. However, it’s α-amylase inhibition value of 16 ± 2% is double that of CSEs 4 at 8 ± 4%. These results once again clearly show that the diisopropylidene bridges on the sucrose core have no significant influence on α-glucosidase inhibition: a similar trend observed in the case of FSEs. CSE 9 with four cinnamoyl moieties and no diisopropylidene bridges showed α-glucosidase inhibition of 74 ± 9%, which is similar to its counterpart CSE 5 with an inhibition value of 77 ± 5%. Interestingly, both CSEs 9 and 5 showed similar α-amylase inhibition values at 99 ± 1% and 98 ± 2%, respectively. This result disagrees with the observations from the FSEs where the inhibition activity decreases in the presence of the diisopropylidene bridges [5 vs. 9, and 4 vs. 8). This observation contrasts with the results observed in the case of FSEs [5 and 9 with four cinnamoyl moieties, were several folds higher than those of the CSEs 3, 4, 6, and 7 with two of three cinnamoyl moieties, indicating that the number of substituents on the sucrose core plays a key role in enzyme inhibition. CSEs 3, 4, 6, 7, and 8 showed similar α-glucosidase inhibition values as compared to acarbose at 27 ± 4% . The site of docking, as well as the amino acid residues that interact with the CSE 9, are presented in the binding modes and the Ligand Interaction Diagrams (LIDs)  . The cins (LIDs) . The cins (LIDs) . We hypocosidase .5 and 9 were chosen since CSE 5 has a restricted configuration due to the bridging of the glucose and fructose moieties by the diisopropylidene rings while CSE 9 is more flexible. Binding mode pictures and the Ligand Interaction diagrams of CSEs 5 and 9 are presented in 5 and 9 docked in a similar region around amino acid residues 50–63; 145–151; 197–200; 233–240; and 300–306 , Dinitro Salicylic Acid (DNSA), DMSO, NaHPO4, Na2HPO4).All the chemicals and reagents used in this study were purchased from Sigma Aldrich  substrate solution (in phosphate buffer) was added. The microplate was incubated at 37 °C for another 15 min. The absorbance was then measured using a microplate reader at 405 nm. The percentage inhibition was calculated using the formula:α-Glucosidase inhibition was tested according to previously reported methods with some modifications . 8 µL ofα-amylase inhibition was tested using previously reported methods  50 µL of50 values for selected CSEs were calculated by plotting a dose-response curve for a range of concentrations of the CSEs (0–25 µg/mL) for the selected CSEs (data not shown) and regression analysis was done using Graphpad Prism software using the in-built function.All measurements were performed in triplicates and the values. The IC(Saccharomyces cerevisiae) which shared 72% sequence identity and 85% similarity with yeast α-glucosidase was used as a template to construct the homology model [A suitable template for building a homology model for α-glucosidase was found using the ‘BLAST’ algorithm. Yeast isomaltase (PDB ID: 3A4A) gy model . AutoDocThe molecular interaction of the CSEs with porcine pancreatic α-amylase was studied using Schrödinger’s Maestro software. The enzyme porcine pancreatic α-amylase (PDB ID: 1OSE) was imported and the structure processed using the Protein Preparation Wizard module. The receptor grid was generated based on the coordinates of the bound acarbose in the crystal structure, known as the primary binding site . The Gli5 and 9, with four cinnamoyl moieties, showed much higher inhibition of α-glucosidase than acarbose and near complete inhibition of α-amylase. Both showed much higher IC50 values than acarbose. From the in silico docking studies, the high inhibition of CSEs 5 and 9 is thought to be due to multiple π-π interactions and favorable projection of the cinnamoyl moieties  in the enzyme pockets. This work demonstrates the potential of CSEs as AGIs. Further studies on developing phenylpropanoid sucrose esters as AGIs with minimum side effects are underway in our lab.Cinnamoyl sucrose esters inhibited α-glucosidase and α-amylase to different extents and the inhibition activity depended on the structure of these compounds. Selective inhibition of α-glucosidase over α-amylase to eliminate the side effects is achievable by tuning the number of cinnamoyl moieties, their positions, diisopropylidene bridges, and the acetyl groups. Among the eight compounds tested, CSEs


Sarecycline is the first narrow-spectrum tetracycline-class antibiotic that was recently approved by the FDA for the clinical treatment of acne vulgaris. In this work, we determined two (2.8-Å and 3.0-Å) X-ray crystal structures of sarecycline bound to the initiation complex of the bacterial 70S ribosome and found that this antibiotic inhibits bacterial ribosome in part using a mechanism of direct mRNA contact, which has not been reported for any other tetracyclines so far. Moreover, our structural analysis rationalizes why sarecycline is able to overcome one of the most common mechanisms of resistance to tetracyclines among pathogenic bacteria. Thus, this work provides mechanistic insights into the function of the tetracycline class of antibiotics on the ribosome with direct clinical relevance. Thermus thermophilus 70S ribosome. Our 2.8-Å resolution structure revealed that sarecycline binds at the canonical tetracycline binding site located in the decoding center of the small ribosomal subunit. Importantly, unlike other tetracyclines, the unique C7 extension of sarecycline extends into the messenger RNA (mRNA) channel to form a direct interaction with the A-site codon to possibly interfere with mRNA movement through the channel and/or disrupt A-site codon–anticodon interaction. Based on our biochemical studies, sarecycline appears to be a more potent initiation inhibitor compared to other tetracyclines, possibly due to drug interactions with the mRNA, thereby blocking accommodation of the first aminoacyl transfer RNA (tRNA) into the A site. Overall, our structural and biochemical findings rationalize the role of the unique C7 moiety of sarecycline in antibiotic action.Sarecycline is a new narrow-spectrum tetracycline-class antibiotic approved for the treatment of acne vulgaris. Tetracyclines share a common four-ring naphthacene core and inhibit protein synthesis by interacting with the 70S bacterial ribosome. Sarecycline is distinguished chemically from other tetracyclines because it has a 7-[[methoxy(methyl)amino]methyl] group attached at the C7 position of ring D. To investigate the functional role of this C7 moiety, we determined the X-ray crystal structure of sarecycline bound to the  Bacterial protein synthesis is targeted and inhibited by many small-molecule compounds . One suc2Cutibacterium acnes (formerly known as Propionibacterium acnes) and antiinflammatory effects (such as the reduction of lipases)  , 8. Bothtet genes, both encoding the tetracycline efflux pumps or ribosome-protection proteins. Members of another group of tetracycline derivatives, such as tigecycline  of the A-site codon (position +6 relative to AUG codon and the translation start site), further stabilizing the drug in its binding pocket. This work provides experimental evidence suggesting that tetracyclines might interact with the messenger RNA (mRNA) on the ribosome and, despite sharing the same binding pocket, might exhibit quite different modes of action.In this work, we report the X-ray crystal structure of SAR in complex with the 70S ribosome from the Gram-negative bacterium Escherichia coli strains, each of which is resistant to TET due to a single-nucleotide mutation in its 16S rRNA  , possess only one rrn operon encoding for the 16S and 23S rRNAs   . All of 3S rRNAs . All mut3S rRNAs . LocatedT. thermophilus 70S ribosome containing mRNA, and P-site–bound deacylated initiator tRNAiMet at 2.80-Å resolution . In this experiment, we used mRNA containing phenylalanine UUC codon positioned in the A site of the ribosome. An unbiased difference Fourier map, calculated using the amplitudes from the crystals and phases derived from a model of the ribosome without the bound compound, revealed positive electron density resembling characteristic features of SAR   , 13. ThiFig. S3) D–F. Simi (2+ ion D and F (6 of h31 D and F.Tetracyclines is not the only class of ribosome-targeting inhibitors that bind and act upon the decoding center (DC) of the bacterial ribosome. Distinct binding sites of the drugs usually indicate that the resistance mechanisms operating against one drug would be inefficient against the other. To check whether binding sites of SAR and other nontetracycline drugs overlap, we superimposed our structure of SAR in complex with the 70S ribosome with the known structures of other DC-binding inhibitors, such as negamycin, streptomycin, aminoglycoside antibiotic paromomycin, and peptide antibiotic odilorhabdin . Our anaIn order to overcome various antibiotic resistance mechanisms, multiple synthetic tetracycline derivatives have been produced. Most of these compounds share the same polar edge, which is essential for drug binding to the bacterial ribosome, but incorporate various modifications at the opposite side of the molecule. For example, tigecycline TIG, B containSI Appendix, Fig. S4A), indicating that mRNA nucleotides must be stabilized by macromolecular interactions. Close examination of the SAR binding site revealed that the third nucleotide (cytidine) of the A-site UUC codon (position +6) is in close proximity to the C7 extension of SAR . However, it is also evident from our structure that the methoxy group of the C7 extension of SAR forms a van der Waals contact with the cytidine in position +6 , which is a weaker type of interaction compared to an H bond but still can provide additional stabilization of the mRNA, explaining why we observe strong electron density corresponding to the nucleotides of the A-site codon . Curiously, when we modeled adenine in the position +6 of the A-site codon, the exocyclic N6 atom of such adenine residue appeared to be within H bond distance (3.0 Å) from the oxygen of the C7 moiety of SAR . This observation indicates that the C7 extension of SAR could potentially interact with the mRNA A-site codon, suggesting that SAR binding or its action could be affected by the mRNA context.Structures of ribosome-bound tetracyclines typically do not contain tRNAs bound in the A site because these compounds compete with the incoming aa-tRNAs for binding to the A site on the 30S subunit. In turn, structures lacking an A-site tRNA, which stabilizes the A-site codon of the mRNA, also lack electron density for the mRNA in the A site. For example, in the previously reported structures of ribosome-bound TET or TIG, there is a complete absence of electron density for the mRNA in the A site , 13. Intn of SAR D and E. iMet, SAR, and an mRNA-containing adenine residue in the third position of the A-site codon . We observed electron density for the entire A-site codon, which was even stronger and more clear than for mRNA with the UUC codon . Most importantly, the adenine residue in position +6 of the A-site codon forms H bond with the C7 extension of SAR . I. IE. colmolecule C (21). Imolecule . Althougmolecule D. Moreovmolecule .SI Appendix, Fig. S2 A and B) and, therefore, act as elongation inhibitors . Unlike TET, SAR causes the majority of ribosomes to stall at the initiator codon  medium. Exponentially growing E. coli cells were diluted to a final culture density of OD600 = 0.001 and grown overnight at 37 °C in 96-well plates (100 µL per well) with increasing concentrations of antibiotics being tested, TET and SAR. The presence of live cells was determined by staining with AlamarBlue dye.All SI Appendix, Table S2) was initially generated by polymerase chain reaction (PCR) using E. coli BW25113 genomic DNA and AccuPrime Taq DNA Polymerase (Thermo Fisher Scientific). The sequences of the primers used for PCR are shown in SI Appendix, Table S3.The synthetic DNA template encoding the amino acid sequence MLILTRRVGETLMIGDEVTVTV . Primer extension products were resolved on 6% sequencing gels as described previously  were prepared as described previously (Tth 70S ribosome complexes were formed in the buffer containing 5 mM Hepes-KOH (pH 7.6), 50 mM KCl, 10 mM NH4Cl, and 10 mM Mg(CH3COO)2, and then crystallized in the buffer containing 100 mM Tris⋅HCl (pH 7.6), 2.9% (wt/vol) PEG-20K, 9–10% (vol/vol) 2-methyl-2,4-pentanediol (MPD), 175 mM arginine, 0.5 mM β-mercaptoethanol .The atomic model of SAR was generated from its known chemical structure C using P in COOT , followe in COOT . The staSupplementary File


The set of known stable phases of water may not be complete, and some of the phase boundaries between them are fuzzy. Starting from liquid water and a comprehensive set of 50 ice structures, we compute the phase diagram at three hybrid density-functional-theory levels of approximation, accounting for thermal and nuclear fluctuations as well as proton disorder. Such calculations are only made tractable because we combine machine-learning methods and advanced free-energy techniques. The computed phase diagram is in qualitative agreement with experiment, particularly at pressures ≲ 8000 bar, and the discrepancy in chemical potential is comparable with the subtle uncertainties introduced by proton disorder and the spread between the three hybrid functionals. None of the hypothetical ice phases considered is thermodynamically stable in our calculations, suggesting the completeness of the experimental water phase diagram in the region considered. Our work demonstrates the feasibility of predicting the phase diagram of a polymorphic system from first principles and provides a thermodynamic way of testing the limits of quantum-mechanical calculations. Complex interatomic interactions and diverse structures make computing the phase diagram of water very challenging. Here, a combination of machine learning and advanced free-energy methods at three levels of hybrid DFT enables the prediction of the phase diagram in close agreement with experiment. In addition to hexagonal ice (ice Ih) that forms snowflakes, there are currently 17 experimentally confirmed ice polymorphs and several further phases have been predicted theoretically2. The phase diagram of water has been extensively studied both experimentally and theoretically over the last century; nevertheless, it is not certain if all the thermodynamically stable phases have been found, and the coexistence curves between some of the phases are not well characterised2. At high pressures, experiments become progressively more difficult, and therefore computer simulations play an increasingly crucial role.Water is the only common substance that appears in all three states of aggregation—gas, liquid and solid—under everyday conditions13, which inevitably entail severe approximations3. For example, the rigid water models such as TIPnP16 and SPC/E17 cannot describe the fluctuations of the bond lengths and angles and therefore do not explicitly include nuclear quantum effects (NQEs)19, although some have been extended to incorporate fluctuations22. The MB-pol force field23, which includes many-body terms fitted to the coupled-cluster level of theory, has not been fitted to the high-pressure part of the water phase diagram. Describing the phase diagram is a particularly stringent test for water models, and indeed, only the TIP4P-type models16 and the iAMOEBA water model24 reproduce the qualitative picture, while the SPC/E, TIP3P and TIP5P models predict ice Ih to be stable only at negative pressures26.Computing the thermodynamic stabilities of the different phases of water is challenging because quantum thermal fluctuations and, in proton-disordered ice phases, the configurational entropy need to be taken into account in free-energy calculations. Considerable insight has been gained into the phase behaviour of water using empirical potentials27. As an example, MLPs have been employed to reveal the influence of Van der Waals corrections on the thermodynamic properties of liquid water28. Later, a similar framework, also employing accurate reference data at the level of hybrid density-functional theory (DFT), reproduced several thermodynamic properties of solid and liquid water at ambient pressure29. Very recently, multithermal–multibaric simulations were used to compute the phase diagram and nucleation behaviour of gallium30, while simulations using MLPs provided evidence for the supercritical behaviour of high-pressure hydrogen31.A promising route for predicting phase diagrams is from electronic structure methods (i.e. ab initio), but combining these methods with free-energy calculations is extremely expensive. However, machine-learning potentials (MLPs) have emerged as a way of sidestepping the quantum-mechanical calculations by using only a small number of reference evaluations to generate a data-driven model of atomic interactionsh and XI, III and IX, V and XIII, VI and XV, VII and VIII, and XII and XIV34. Ices III and V are known to exhibit only partial proton disorder35. Both full and partial proton disorder make free-energy calculations more challenging. This is because the enthalpies of different proton-disordered manifestations can be significantly different, but the disorder is not possible to equilibrate at the time scale of molecular dynamics (MD) simulations.Before performing free-energy calculations to compute the phase diagram, one must decide which ice phases to consider, bearing in mind that the experimentally confirmed phases may not be exhaustive. Moreover, many ice phases come in pairs of a proton-disordered and proton-ordered form, e.g. I29 as a surrogate model when performing free-energy calculations, and then promote the results to the DFT level as well as account for NQEs. This workflow is illustrated in Fig. Here, we compute the phase diagram of water at three hybrid DFT levels of theory , accounting for thermal and nuclear fluctuations as well as proton disorder. We start from 50 putative ice crystal structures, including all the experimentally known ices. To circumvent the prohibitive cost of ab initio MD simulations, we use a recent MLP36 functional with a semi-classical D3 dispersion correction37. This MLP reproduces many properties of water, including the densities and the relative stabilities of Ih, Ic and liquid water at the ambient pressure29. Because the MLP is only trained on liquid water and not on either the structures or the energetics of the ice phases, it allows us to explore the ice phase diagram in an agnostic fashion. It nevertheless reproduces lattice energies, molar volumes and phonon densities of states of diverse ice phases, since local atomic environments found in liquid water also cover those observed in the ice phases38.For each ice structure, we first obtain the chemical potential over a temperature range of 25 K to 300 K and a pressure range of 0 bar to 10,000 bar by performing classical free-energy calculations using the thermodynamic integration (TI) method as described in the ‘Methods’ section. The MLP employed in these calculations is based on the hybrid revPBE02O throughout this work) at 225 K computed using the MLP are shown in Fig. h, Ic, II, III, V, VI, VII, IX, XI, XIc, XIII and XV—and the liquid. These phases are all known from experiment, which suggests that the experimental phase diagram of water is indeed complete2. Moreover, as the chemical potential difference between Ih and Ic is small and has already been studied in ref. 29, we report the results only for ‘ice I’.The chemical potentials  proton disorder35. We have assumed that the experimental proton disorder is correct for the potential used, which may not be completely accurate42, but is the best assumption we can make, since equilibration of proton disorder is not feasible to achieve on computationally tractable time scales.The treatment of proton-disordered phases is complicated because choosing a non-representative configuration can introduce a significant bias in enthalpy and in turn lead to an incorrect phase diagram43. Specifically, proton order leads to long-range electrostatics that can destabilise the solid, but the MLP only accounts for short-range interactions. Albeit small in absolute terms, the correction to DFT causes a changeover of stability, and in particular reduces the stability of the proton-ordered phases (such as ice II and XV), as can be seen from Fig. We perform a free-energy perturbation to promote the MLP results to the hybrid DFT level  simulations. In general, NQEs serve to stabilise higher-density phases. For all phases, the degree of stabilisation increases with increasing pressure, and decreases with increasing temperature. Whilst the overall form of the chemical potential plot Fig. c changes44, we have estimated the errors arising from each step of the calculation  K. The error bar on the melting point of the current work is larger at ~6 K, primarily because only 5 different realisations of the proton-disordered ice Ih were considered rather than the 16 of ref.  29.] However, at very high pressure, the coexistence curve between ices V and VI has too steep a gradient compared to experiment. This may arise from the inaccuracy of the reference DFT functionals45 or from the finite basis set and energy cutoffs employed in the DFT calculations. To illustrate the effect of employing different DFT approximations, we show analogous phase diagrams for two alternative DFT functionals, B3LYP-D3 and PBE0-D3, in Fig. When the MLP is corrected to the DFT level of theory and NQEs are accounted for, the resulting phase diagram Fig. c is cons42, and the calculated stability thus depends on the specific proton site occupancies considered in addition to the uncertainty in the calculation itself. The main lessons to be drawn from this are that (i) many of the phases are very close in free energy, particularly in the region around 250 K and ~3000 bar, which means that even if they are not thermodynamically stable, they are likely to be metastable and hence may be easier to obtain experimentally at these conditions, and (ii) the phase diagram is an extremely sensitive test of the underlying potential: even a very small change in relative stability can drastically affect the phase behaviour.In none of three phase diagrams shown in Fig. 22.Finally, we show the phase diagram with and without accounting for NQEs in Fig. 2O and D2O exhibit exactly the same thermodynamic behaviour. However, accounting for the difference between them is necessary for example, for polar ice dating and historical atmospheric temperature estimation46, which suggests that a classical description of nuclear motion is not satisfactory. We thus account for NQEs by integrating Eq.  in Fig. 2O is approximately 4 K lower than that for D2O, as investigated previously47. It is interesting that D2O follows almost the same ice I–liquid coexistence line as classical water, since positive and negative contributions to the integral of Eq.  result in similar, but certainly not identical, phase behaviour. It would be interesting to apply the same workflow to other electronic structure methods, including random-phase approximation50. Another intriguing phase transition to study is that between ice VII and liquid water at higher pressures than we have looked at here, which empirical pair potentials do an especially poor job of describing51. Moreover, the same framework can be used to investigate (meta)stability of novel bulk materials. It further lays the groundwork for utilising experimental phase diagrams to correct and improve interatomic potentials based on electronic structure methods.The present study bridges the gap between electronic structure theory and accurate computation of phase behaviour for water. With a robust framework in place, we aim in future work to investigate the behaviour of ice that is less well understood experimentally. For example, tantalisingly, in Fig. 53. We eliminate defected phases, dynamically unstable phases, and the very high pressure phase X, but add the originally missing ice IV. In Supplementary Data We start from the 57 phases that were screened from an extensive set of 15,859 hypothetical ice structures using a generalised convex hull construction, an algorithm for identifying promising experimental candidates54 with the revPBE0-D3, the PBE0-D3 and the B3LYP-D3 functionals. The computational details of the calculations are identical to refs.  55 but for the choice of functionals, and we provide input files in Supplementary Data We compute the energies of the water structures using the CP2K code4. In our approach, we use a series of steps in simulations of physical or artificial systems to compute the various components of the free-energy difference between a reference system and the fully anharmonic, quantum system, as depicted schematically in Fig. We use the method of thermodynamic integration (TI) to compute the Gibbs energy of the selected ice phases at a wide range of thermodynamic conditions, which in turn determine the ice phase diagram. A similar method has previously been used to compute the ice phase diagram using empirical potentials56 to determine the equilibrium lattice parameters at the conditions of interest. We then prepare a perfect crystal with the corresponding lattice parameters and minimise its energy, compute the Helmholtz energy of the reference harmonic crystal by determining the eigenvalues of the hessian matrix, account for the motion of the centre of mass, and finally perform a thermodynamic integration step to the potential of interest in which classical nuclei are described by the MLP [Fig. 57. In this step, we use reasonably large system sizes  to ensure that finite-size effects are minimised. Determining the chemical potential in this way would have been computationally intractable had we employed ab initio calculations, and is only made possible by the use of the MLP. Once the chemical potential is known for the MLP at one set of conditions, we can find it at other pressures and temperatures by numerically integrating the Gibbs–Duhem relation along isotherms and the Gibbs-energy analogue of the Gibbs–Helmholtz relation along isobars, respectively.In the first step of the free-energy calculation for the solid phases, we equilibrate a sample of an ice phase at the temperature and pressure of interest in an isothermal-isobaric simulation with a fluctuating box with a Parrinello–Rahman-like barostat58 of the liquid in contact with ice Ih at a series of temperatures at 0 bar to determine the coexistence temperature. The melting point Tm = 279.5 K at 1 bar for the MLP, although evaluated in a different way, is in perfect agreement with a previous simulation that used umbrella sampling29. We equate the chemical potentials of the two phases under these conditions and obtain the chemical potential of the liquid at other conditions by thermodynamic integration along isotherms and isobars, as for the ice phases.To find the free energy of the liquid phase at the MLP level, we perform a series of direct-coexistence simulationsT and pressure P using the ML hamiltonian UDFT is the DFT energy and UML is the MLP energy, and N is the number of water molecules in the system. This correction is necessary to recover the true chemical potential at the DFT level, in particular to compensate for the lack of long-range electrostatics, which are particularly important in modulating ice phase stabilities59. Using the MLP-derived chemical potentials without corrections neglects such long-range contributions and significantly hampers the quantitative accuracy of the computed phase diagram. In practice, we first collect trajectories of ice configurations by performing MD simulations in the isothermal-isobaric ensemble for each promising ice phase using the MLP. The number of water molecules in the simulation cell ranges from 56 to 96 molecules, depending on the unit-cell size of each phase. For each of the proton-disordered  or partially disordered phases , we run independent simulations for 5–8 different depolarised proton-disordered configurations. We then select decorrelated configurations from the MD trajectories and recompute their energies at the DFT level. The MLP → DFT correction terms are then computed using Eq.  ≈ 5 meV and ΔΔμ(VI → XV) ≈ 11 meV.In this step, the correction to the chemical potential ranges from −7.9 meV  to 10.8 meV (for ice XV at 275 K and 5000 bar). Ice XV is the proton-ordered analogue of ice VI; similarly, ice XIII, the proton-ordered analogue of ice V, is more stable at the MLP level than it ought to be [e.g. at 225 K and 7000 bar, the corrections to chemical potentials are Δm63. In practice, a change of variable 60, yieldingy = 1/4, 1/2, T ≥ 125 K. Relative to ice II, the correction to the chemical potential arising from NQEs ranges from −8 meV to 5 meV.During the final TI [Fig. To determine the approximate uncertainty associated with the individual chemical potential contributions, we first compute the reference chemical potential of several phases computed from an equilibrated perfect crystal at 125 K and 0 bar. We repeat this calculation between 5 and 10 times and determine the standard deviation of the resulting chemical potentials. For  proton-disordered phases, we split the contributions to the standard deviation arising from thermodynamic integration, which we obtain by computing the reference chemical potential calculation using the same initial configuration in 5 independent simulations, and from proton disorder, which we obtain by averaging over the chemical potentials arising from several distinct manifestations of the proton disorder in the initial configurations. Similarly, we compute the standard deviation of the correction to the chemical potential when the system is integrated from the MLP to the DFT level evaluated at 225 K and 3000 bar. For the correction to NQEs, we determine the statistical error in the measurement of the kinetic energy at each scaled mass. We calculate the integral of Eq. (Peer Review FileDescription of Additional Supplementary FilesSupplementary Data 1


Ganoderic acid A (GAA) is usually used to prevent cancers or other diseases, which make it likely to be used with other drugs metabolized by cytochromes P450. This study investigates the effect of GAA on eight major cytochrome P450 isoforms in human liver microsomes.in vitro using human liver microsomes (HLMs) with specific substrates for the CYPs, and the enzyme kinetic parameters were calculated. The effects of GAA (100 μM) on eight human liver CYP isoforms  were investigated 50IC values of 15.05, 21.83, and 28.35 μM, respectively. Additionally, GAA was not only a non-competitive inhibitor of CYP3A4, but also a competitive inhibitor of CYP2D6 and 2E1, with Ki values of 7.16, 10.07, and 13.45 μM. Meanwhile, the inhibition of CYP3A4 was time-dependent, with the I/KinactK value of 7.91/0.048 μM/min. The results showed that GAA inhibited the activity of CYP3A4, 2D6, and 2E1, but did not affect other isoforms. The inhibition of CYP3A4, 2D6, and 2E1 was concentration-dependent with in vitro study indicated that GAA has the potential to result in drug-drug interactions with other drugs metabolized by CYP3A4, 2D6, and 2E1. Further clinical studies are needed for the identification of this interaction. The  Cytochrome P450 enzymes (CYPs) are one of the most important phase-I enzymes that participate in the metabolism of most clinical drugs in liver and intestine. The status of CYPs might influence the pharmacokinetics of co-administrated drugs and result in adverse effects, which would contribute to costly and late failures of drug development  Karst (Ganodermataceae), also called Ling Zhi in China, has been widely used in traditional Chinese medicine for more than 2000 years to promote health and longevity, as it has been reported to have anticancer and many other beneficial properties , testosterone (CYP3A4), coumarin (CYP2A6), chlorzoxazone (CYP2E1), dextromethorphan (CYP2D6), diclofenac (CYP2C9), S-mephenytoin (CYP2C19) and paclitaxel (CYP2C8), we clarified the effect of GAA on the activity of CYPs, and the inhibition model was determined by the enzyme kinetic studies.In addition to the medicinal application of d-Glucose-6-phosphate, glucose-6-phosphate dehydrogenase, corticosterone (≥98%), NADP+, phenacetin (≥98%), acetaminophen (≥98%), 4-hydroxymephenytoin (≥98%), 7-hydroxycoumarin (≥98%), 4′-hydroxydiclofenac (≥98%), sulfaphenazole (≥98%), quinidine (≥98%), tranylcypromine (≥98%), chlorzoxazone (≥98%), 6-hydroxychlorzoxazone (≥98%), paclitaxel (≥98%), 6β-hydroxytestosterone (≥98%), clomethiazole (≥98%), and furafylline (≥98%) were obtained from Sigma Chemical Co. Montelukast (≥98%) was obtained from Beijing Aleznova Pharmaceutical . Coumarin (≥98%), diclofenac (≥98%), dextromethorphan (≥98%), and ketoconazole (≥98%) were purchased from ICN Biomedicals. Pooled HLMs were purchased from BD Biosciences Discovery Labware. All other reagents and solvents were of analytical reagent grade.Ganoderic acid A (≥98%) and testosterone (≥98%) were obtained from the National Institute for the Control of Pharmaceutical and Biological Products . The chemical structure of GAA is shown in O-deethylation for CYP1A2, testosterone 6β-hydroxylation for CYP3A4, coumarin 7-hydroxylation for CYP2A6, chlorzoxazone 6-hydroxylation for CYP2E1, dextromethorphan O-demethylation for CYP2D6, diclofenac 4′-hydroxylation for CYP2C9, S-mephenytoin 4-hydroxylation for CYP2C19, and paclitaxel 6α-hydroxylation for CYP2C8. All incubations were performed in triplicate, and the mean values were utilized. The typical incubation systems contained 100 mM potassium phosphate buffer (pH 7.4), NADPH generating system , the appropriate concentration of HLMs, a corresponding probe substrate and hispidulin (or positive inhibitor for different probe reactions) in a final volume of 200 μL.As shown in The concentration of GAA was 100 μM, and the positive inhibitor concentrations were as follows: 10 μM furafylline for CYP1A2, 1 μM ketoconazole for CYP3A4, 10 μM tranylcypromine for CYP2A6, 50 μM clomethiazole for CYP2E1, 10 μM quinidine for CYP2D6, 10 μM sulfaphenazole for CYP2C9, 50 μM tranylcypromine for CYP2C19, 5 μM montelukast for CYP2C8. Probe substrates, positive inhibitors  and GAA were dissolved in methanol, with a final concentration of 1% (v/v), and 1% neat methanol was added to the incubations without inhibitor. The final microsomal protein concentration and incubation times for the different probe reactions are shown in 50IC). iK values were obtained by incubating various concentrations of different probe substrates  in the presence of 0–50 μM GAA.GAA (100 μM) was used to initially screen for its direct inhibitory effects towards different human CYP isoforms. For the CYP isoforms whose activities were strongly inhibited, secondary studies were performed to obtain the half inhibition concentration  was pre-incubated with HLMs (1 mg/mL) in the presence of an NADPH-generating system for 30 min at 37 °C. After incubation, an aliquot (20 μL) was transferred to another incubation tube  containing an NADPH-generating system and probe substrates whose final concentrations were approximate to KI and inactK values for the inactivation of CYP3A4, the incubations were conducted using higher probe substrate concentrations  and various concentrations of GAA (0–50 μM) after different preincubation times (0–30 min), with a two-step incubation scheme, as described above.To determine the maxV and mK. Inhibition data from the experiments that were conducted using multiple compound concentrations were represented by Dixon plots, and inhibition constant (iK) values were calculated using non-linear regression according to the following equation:iK is the inhibition constant, S is the concentration of the substrate, and mK is the substrate concentration at half the maximum velocity (maxV) of the reaction. The mechanism of the inhibition was assessed using the Lineweaver-Burk plots and the enzyme inhibition models. All data are represented as Mean ± SD. The data comparison was performed using Student’s t-test and performed using IBM SPSS statistics 20 (SPSS Inc.).The enzyme kinetic parameters for the probe reaction were estimated from the best fit line, using least-squares linear regression of the inverse substrate concentration versus the inverse velocity (Lineweaver-Burk plots), and the mean values were used to calculate 50IC values were 15.05, 21.83, and 28.35 μM, respectively.iK was obtained to be 7.16 μM  over the in vivo concentration of the inhibitor (Ito et al. in vivo investigations are needed for the identification of the interaction between GAA and CYPs. In addition, according to previous studies, the maximum concentration in plasma of GAA was 2.24–10.99 ng/mL after oral administration of 3000 mg Lingzhi, which is much less than the IC50 values of CYP3A4, 2D6, and 2E1. (Teekachunhatean et al. Actually, the In conclusion, this paper investigated the effect of GAA on the activity of CYPs in HLM systemically. The results showed the inhibitory effect of GAA on the activity of CYP3A4, 2D6, and 2E1, while other isoforms were not affected. These results provided direct evidence for the activity of CYPs in the presence of GAA. And it is also recommended that GAA should be used carefully with other drugs metabolized by CYP3A4, 2D6, and 2E1.