The advent of cell-cell and cell-extracellular adhesion enabled cells to interact in a coherent manner, forming larger structures and giving rise to the development of tissues, organs and complex multicellular life forms. The development of such organisms required tight regulation of dynamic adhesive structures by signaling pathways that coordinate cell attachment. Integrin-mediated adhesion to the extracellular matrix provides cells with support, survival signals and context-dependent cues that enable cells to run different cellular programs. One mysterious aspect of the process is how hundreds of proteins assemble seemingly spontaneously onto the activated integrin. An emerging concept is that adhesion assembly is regulated by autoinhibition of key proteins, a highly dynamic event that is modulated by a variety of signaling events. By enabling precise control of the activation state of proteins, autoinhibition enables localization of inactive proteins and the formation of pre-complexes. In response to the correct signals, these proteins become active and interact with other proteins, ultimately leading to development of cell-matrix junctions. Autoinhibition of key components of such adhesion complexes—including core components integrin, talin, vinculin, and FAK and important peripheral regulators such as RIAM, Src, and DLC1—leads to a view that the majority of proteins involved in complex assembly might be regulated by intramolecular interactions. Autoinhibition is relieved via multiple different signals including post-translation modification and proteolysis. More recently, mechanical forces have been shown to stabilize and increase the lifetimes of active conformations, identifying autoinhibition as a means of encoding mechanosensitivity. The complexity and scope for nuanced adhesion dynamics facilitated via autoinhibition provides numerous points of regulation. In this review, we discuss what is known about this mode of regulation and how it leads to rapid and tightly controlled assembly and disassembly of cell-matrix adhesion. The emergence of life is an enigmatic question that humankind has pondered for millennia. At some point millions of years ago, the last universal common ancestor (LUCA) appeared and all organisms on earth descended from this initial cell  to form cell-matrix junctions. The ability of cells to form sheets of cells and attach to an underlying matrix was central to the development of multicellular animal life.These attachment points also developed into sensitive sensory modules, able to feel the mechanics of the microenvironment and adopt the role of mechanotransduction centers—enabling cells to monitor and respond to mechanical cues and convert them into biological signals to elicit different cellular responses.Key to the development of complexity is the ability to regulate adhesion and control the proteins that assemble together to form adhesive structures. One way that proteins can be dynamically regulated is via formation of an intramolecular interaction that maintains the protein in an inactive state until adhesion assembly is required. The regulation of autoinhibition, and the factors that enable regulation of the activity of the protein, provides regulatable checkpoints in the system .The concept of autoinhibitory domains can be found throughout biology—these are regions of proteins which can form intramolecular interactions which regulate behavior and activity. We refer the reader to the review on autoinhibitory domains by Pufall and Graves as it provides an excellent, still highly relevant description of the fundamentals of autoinhibition  can relieve this autoinhibitory interaction and drive tail separation, propagating a conformational rearrangement of the ectodomains and unfurling to reveal the ligand-binding motifs  in fibroblasts -like region in F3—this domain is termed integrin binding site 1 (IBS1). As mentioned in the previous section, the interaction between the talin head domain with integrin is sufficient to relieve autoinhibition of the integrin, exposing the previously cryptic binding sites for integrin ligands. However, talin itself is regulated by multiple layers of autoinhibition.The first evidence that talin was autoinhibited came from the initial structural and biochemical characterization of talin in 1987  of R13 limits actin binding  RIAM is activated, which translocates talin to the plasma membrane where (ii) the talin head-tail autoinhibition is relieved. (iii) Once active, talin relieves the autoinhibition of integrin. (iv) By connecting integrins to the actin retrograde flow, talin autoinhibition is further relieved, first with activation of enhanced actin binding to ABS3. (v) As force increases, mechanical activation of vinculin-binding sites in talin occurs, initially by unfolding of the R3 domain, the least stable of the rod domains  to which Vd1 can bind  are well-characterized and, being a kinase, a striking example of coupling regulation of protein activity to downstream signaling cascades. FAK is another linear multidomain protein with numerous binding sites for ligands. As the name suggests, FAK contains an enzymatically active kinase domain able to phosphorylate tyrosine residues in target proteins. FAK comprises an N-terminal FERM domain, a kinase domain, a ligand-binding region and a C-terminal 4-helix bundle termed the focal adhesion targeting (FAT) domain .At rest, FAK adopts an autoinhibited, closed conformation where the FERM domain directly binds and occludes both the catalytic cleft and the activation loop of the kinase domain  and a mutation in the kinase domain (Phe596Asp) .An important regulator of the integrin adhesion complex assembly is Rap1-interacting adapter molecule (RIAM). RIAM is a Rap1 effector that can interact directly with talin and translocate it to the plasma membrane, and thus into close proximity to the integrins  . This INThis Rap1:RIAM:talin nexus is thus tightly controlled in a myriad of ways, and the dynamic balance of activity status of each protein is implicitly entangled. RIAM is likely activated by active Rap1 Bos, , and theRelief of autoinhibition of FAK following activation at adhesion sites leads to FAK autophosphorylation of Tyr397 Frisch,  which prSrc recruitment to, and phosphorylation of, downstream molecules allows many pathways to be regulated through Src, and drives crosstalk between integrin, Src and Rho-family GTPases  (One common mechanism for relieving autoinhibition is s (PTMs) . Here, as (PTMs) , sumoylas (PTMs) , etc. Thproteolytic cleavage  led to insight into the loss of essential developmental phenotypes  and, onto this hub, hundreds of proteins are recruited , will trigger changes to the system as it reorients to this new homeostasis, adopting an altered adhesion signaling complex which augments the programming of the cell.BG and RK wrote the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Three types of datasets are given herein mainly in the form of tables. The first two correspond to databases built based on a compilation of past experimental testing on buckling-restrained braces (BRBs), conducted in different parts of the world. Two distinct objectives motivated such data compilation: (1) to determine a practical range for the parameter named as Yield Length Ratio (YLR), from full-scale and large-scale buckling-restrained braced frame (BRBF) specimens, that allowed for evaluation of the maximum deformation demands of BRBs [1]; and (2) to extract information on the properties of BRB specimens of different types, materials, and origin, for calibration of a numerical model that enabled the simulations of quasi-static cyclic tests of BRBs under five different code-prescribed loading histories  and two proposed global loading protocols (GLP-1 and GLP-2) [1]. The last dataset type corresponds to the results of these numerical simulations, which were conducted using the OpenSees platform. The results show the maximum ductility demand (μmax), cumulative inelastic deformation, in terms of cumulative plastic ductility (CPD) and cumulative plastic strain (CPS), and cumulative hysteretic energy (Ēh) of BRBs as a result of the application of each loading sequence, and they are tabulated by BRB specimen.The data presented in this article constitute a supplementary material and provide support to the study  The dat2The following subsections provide a complete description of the methods used for acquisition of the data shared in this article.2.1YLR typically range from 0.50 to 0.70 in actual buckling-restrained braced frames (BRBFs), depending on the type of end-connections used  and bracing configuration employed . Since the range over which YLR is evaluated directly influences the relative deformation of the BRB, according to Equations (1)–(3) in Aguaguiña et al. [YLR take in very detailed BRBF specimens. As pointed out in Aguaguiña et al. , the valquations –(3) in Aa et al. , were co2.2Fysc, εy); steel core geometry ; and BRB yield force and yield deformation .In Aguaguiña et al. , a total2.3Open System for Earthquake Engineering Simulation (OpenSees) platform [Ly. That is, following the assumption that most of elastic and inelastic deformations take place within the yielding segment of the BRB, small elastic deformations in the transition and connection zones were totally neglected. The BRB model is illustrated in The platform  was emplb, in terms of a common quantity. In this work, all the loading protocols were set in terms of the steel core strain, εb,sc, which only depends on the geometric properties of the BRB specimen . Thus, the US, EU, and CN loading sequences, whose deformation amplitudes were indexed as a function of the BRB design deformation, Δbd, needed to be converted so that the deformation levels were also presented in terms of εb,sc, as the JP and CA loading protocols. Here, two important assumptions were made for estimation of the maximum design demand of BRBs: (1) the design inter-story drift ratio equals the drift limitation in the US, EU, and CN codes; and (2) the design deformation demand, Δbd, is evaluated considering two values of the parameter YLR: 0.50 and 0.60. εb,sc, used for simulations. Additional details on the definition of the loading histories for analyses can be found in Aguaguiña et al. [As described in Aguaguiña et al. , five diof BRBs:  the desiYLR = 0.50) whereas the loading history GLP-2 represents a lower level of demand (YLR = 0.60). Both loading histories were configured so that a series of conditions and criteria were satisfied . GLP-1 μmax, cumulative inelastic deformation, in terms of cumulative plastic ductility, CPD, and cumulative plastic strain, CPS, and cumulative dissipated energy, Ēh. The formulae for computation of μmax, CPD, CPS, and Ēh are given in Equations (4) through (7) in Aguaguiña et al. [Regarding to analyses results, the force and deformation responses resulting from the application of different loading sequences constituted the main output data from numerical simulations. From the force and deformation data corresponding to each BRB specimen and loading protocol, other performance parameters were computed, including the maximum ductility demand, a et al. . The pos2.3.12.3.2


The eosinophil counts in nasal polyps could be more accurately assessed by Chromotrope 2R and Congo red compared with MBPmAb immunohistochemistry and conventional hematoxylin and eosin stain. The popularization of Chromotrope 2R and Congo red may help to unify the eosinophil count in the definition of eosinophilic CRSwNP.The study aimed to find a more appropriate method to detect eosinophils in formalin- fixed nasal polyps, since there is no consensus on the standard counting method of eosinophils now. Four 5 μm serial sections were obtained from each 10% neutral formalin-fixed paraffin block and were stained with Chromotrope 2R, Congo red, MBPmAb immunohistochemistry, and conventional hematoxylin and eosin stain respectively. Each section was scanned by the Aperio digital section scanner. The same selected areas were procured for assessment in the serial sections. Chromotrope 2R and MBPmAb immunohistochemistry were specific in detecting eosinophils, which had the lower background staining compared with Congo red and conventional hematoxylin and eosin stain. There were significant differences among the four methods in terms of the eosinophil counting data ( Clinically, CRSwNP is classified into two phenotypes based on the dominant inflammatory cell type: eosinophilic CRSwNP and non-eosinophilic CRSwNP4. It is demonstrated that the degree of eosinophil infiltration in nasal polyps has a significant impact on their clinical characteristics, surgical timing, drug efficacy, and prognosis6.Chronic rhinosinusitis with nasal polyps (CRSwNP), a multifactorial and highly heterogeneous upper airway disease, is a severe phenotype of chronic rhinosinusitis and presents with distinct immunological and histopathological features compared with chronic rhinosinusitis without nasal polyps (CRSsNP)7, Congo red8 and Immunohistochemistry9 could be used in nasal polyps to count eosinophils accurately. Thus, we performed this study aiming to compare the four methods mentioned above to find out the appropriate method to count eosinophils for distinguishment between eosinophilic CRSwNP and non-eosinophilic CRSwNP.There are no standard methods for eosinophils counting in nasal polyps now. Conventional hematoxylin and eosin stain (HE) staining is used to perform manual counting based on the morphological features of eosinophils. However, it may become difficult since the eosin dye can stain the cytoplasm of all cells to different degrees of red, when the cell morphology is not typical or intensive infiltration with other inflammatory cells, especially neutrophil infiltration. We try to make sure if Chromotrope 2R1. Patients with diagnosis of classic allergic fungal sinusitis, unilateral lesions, allergic fungal sinusitis, posterior nasal polyps, and sinus cysts were excluded in the study.This study was approved by the ethics committee of Beijing Shijitan Hospital of Capital Medical University and written informed consent was obtained from each patient. All methods were performed in accordance with the relevant guidelines and regulations. From June 2016 to June 2017, 27 patients with CRSwNP from Beijing Shijitan Hospital of Capital Medical University were selected for the study. The patients were diagnosed of CRSwNP based on European Position Paper on Rhinosinusitis and Nasal Polyps 2012 guidelinesFour 5 μm serial sections were obtained from each 10% neutral formalin-fixed paraffin block. All sections were dewaxed and hydrated through graded alcohols and dipped in water, and then were stained with conventional HE, Chromotrope 2R, Congo red and immunohistochemistry respectively.10.For conventional HE staining, all slides were stained at Department of Pathology of Beijing Shijitan Hospital following a widely used protocol described elsewhere11. Sections were immersed in hematoxylin for 5 minutes at 25 °C before being rinsed in running tap water, then stained with 0.5% Chromotrope 2R solution for 30 minutes at 25 °C. 0.5% Chromotrope 2R solution were prepared by adding 1 g of phenol  to 100 ml of gentle heat water followed by 0.5 g of Chromotrope 2R .The staining protocol of Chromotrope 2R was performed as previously described12. Sections were immersed in Hematoxylin for 5 minutes at 25 °C before being rinsed in running tap water, then stained with 0.5% alcoholic Congo red solution  for 15 minutes  at 25 °C.Then, the sections were placed into 75% alcohol solution to differentiate for a few seconds.The protocol of Congo red was slightly modified according to the previous description to optimize eosinophil detection14. The next day, after washing with aqueous buffer, the goat anti-mouse secondary antibody IgG conjugated with horseradish peroxidase  was added and incubated for 25 minutes at 37 °C. 3,3-Diaminobenzidine was added to stain the slide at 25 °Cand all specimens were counterstained with hematoxylin. Sections incubated with only the secondary antisera were used for negative controls.After dewaxed in xylene for 10 minutes three times and rehydration, antigen was retrieved 0.4% pepsin for 15 minutes at 37 °C. Peroxidase activity was inactivated using 3% hydrogen peroxide solution for 5 minutes at room temperature. Subsequently, the sections were incubated with mouse anti-human eosinophil major basic protein (MBP) monoclonal antibody  at a 1:20 dilution overnight at 4 °CQualitative assessments of staining parameters were performed by experienced pathologists, including specificity of eosinophil staining and background staining.2 and the same selected areas were procured for assessment in the serial sections . ImageScope 12.1(Leica Microsystems) was used to select 9 consecutive square areas for each case. The area of each small square area was fixed to 0.09 mmp = 0.05/6 was considered significant. All tests were done using the two-tailed option. For all analyses, P < 0.05 was considered significant.All of the statistical analyses were performed using the GraphPad prism 5. The counting data were not normally distributed showed by the Shapiro-Wilk’s test. Therefore, the Friedman test was performed to determine whether there were significant differences among the conventional HE, Chromotrope 2R, Congo red and MBPmAb IHC for the eosinophil counting data. The Wilcoxon signed-rank test was used for the pairwise comparisons, if the significant differences were noted. The Bonferroni correction was applied in pairwise comparisons and the adjusted For Chromotrope 2R, Congo red and MBPmAb IHC, none of them stained neutrophils, lymphocytes, plasma cells or mast cells, indicating that these stains specifically stain eosinophils. For conventional HE, the overlapping staining pattern and morphology of eosinophils versus neutrophils sometimes may be the problem. Figure p < 0.05).The conventional HE method yielded a lower eosinophil counting than Chromotrope 2R (p < 0.05), MBPmAb IHC (p < 0.05),and Congo Red (p < 0.05),while the MBPmAb IHC yielded a higher eosinophil counting than Chromotrope 2R (p < 0.05), conventional HE (p < 0.05),and Congo Red (p < 0.05).Interestingly, there was no significant difference between Congo red staining and Chromotrope 2R staining (P = 0.1413).  should be 10/HPFAt present, conventional HE is widely used for counting eosinophils in nasal polyps as this method can reflect the general situation of eosinophil infiltration. However, the eosin can stain the cytoplasm of all cells to different degree of red non-specifically, therefore the cytoplasm of eosinophils are deep red due to the granulars while the neutrophils are stained light red. Consequently, it may become difficult to differentiate eosinophils from neutrophils and it’s easy to cause visual fatigue when reading numerous slides.According to the results of this study, Chromotrope 2R staining is prominent in terms of specificity and background staining and seems to be a suitable staining method. However, When the tissue is over-fixed in 10% neutral formalin, it can affect the staining. In addition, gentle heat water was used to dissolve the phenol, because phenol was slightly soluble in water at room temperature, and it is miscible with water of any proportion above 65 °C.Eosinophils can be dyed orange-red color clearly with Congo red, in distinct contrast with other cellular components. However, elastic fibers also be stained red if they are present in the nasal polyp samples, which increases background staining. In order to control the background staining of Congo red, we found it can be reduced by immersing the sample in 75% ethanol to differentiate, generally 30 seconds, after immersing it in 0.5% ethanol Congo red solution for 15 minutes.24, it may not be a suitable method for eosinophil counting. It is found that MBP-positive area may contaminate the nuclei and make it difficult to distinguish the number of cells. Although the eosinophils are connected together, the other histochemical positive signals do not completely cover the nucleus. In massive degranulation, immunohistochemistry may also stain peripheral cells, thus leading to higher counts (Fig. Although MBP serves as a marker of eosinophils and is used to observe the distribution and degranulation of eosinophilsAccording to the study, both Chromotrope 2R and Congo red are specific and reproducible, and more suitable for accurate eosinophils counting in nasal polyps. The popularization of Congo red staining and Chromotrope 2R staining may help unify the eosinophil count in the definition of eosinophilic CRSwNP.


Drunkenness is common in nightlife environments and studies suggest it can be considered both desirable and normal by nightlife users. We aimed to compare UK nightlife users’ ideal levels of drunkenness to their expected drunkenness on a night out and their perceptions of descriptive nightlife norms.n = 408, aged 18–35) in three cities. Using a scale from 1 (completely sober) to 10 (very drunk), participants rated: personal drunkenness at survey; expected drunkenness on leaving nightlife; perceived descriptive drunkenness norm in the city’s nightlife; and ideal personal drunkenness. Analyses were limited to those who had or were intending to consume alcohol.A cross-sectional survey with nightlife patrons  expected to get drunker than their reported ideal level on the night of survey, rising to four fifths of those with the highest levels of expected drunkenness. 77.9% rated typical nightlife drunkenness ≥8 but only 40.9% expected to reach this level themselves and only 23.1% reported their ideal drunkenness as ≥8. Higher expected drunkenness was associated with higher ideal drunkenness, higher perceived drunkenness norm and later expected home time.Nightlife users’ perceptions of typical drunkenness in nightlife settings may be elevated and many of the heaviest drinkers are likely to drink beyond their ideal level of drunkenness. Findings can support emerging work to address cultures of intoxication in nightlife environments and suggest that interventions to correct misperceptions of normal levels of nightlife drunkenness may be of benefit.The online version of this article (10.1186/s12889-019-6802-5) contains supplementary material, which is available to authorized users. Harmful drinking and drunkenness are common features of nightlife environments in many countries –6. As weAlcohol is a central part of socialising for many young people  and is rYoung people’s personal drinking behaviours are influenced by their perceptions of drinking norms among peers , 27. Thupersonal drunkenness at survey); 2) How drunk do you think you will be when you leave the city centre tonight? ; 3) Overall, what do you think is the typical level of drunkenness that people reach on a night out in the city centre? (perceived city drunkenness norm); and 4) For you personally, what do you think is the ideal level where you are as happy as you can be after drinking alcohol?  ; alcohol consumption on the night of survey ; whether they had preloaded . Eight participants that had not provided values for all scales of interest were excluded from analyses resulting in a final sample of 408. Data were analysed in SPSS (v21) using descriptive statistics, chi squared and logistic regression (enter method).We surveyed nightlife users aged 18 and over in the streets of three UK cities during peak nightlife hours . Researchers approached potential participants, outlined the study verbally and asked if they had time to participate. A study information sheet was provided to those who were interested, and researchers confirmed informed consent prior to proceeding. Thus, consistent with ethics approval, researchers were trained to visually assess potential participants and those assessed as already so heavily intoxicated that they could not reasonably participate  were not approached or invited to participate. Participants were asked about both their current drunkenness and their expected drunkenness in order to include people who would otherwise be too drunk to be interviewed later in the night. Compliance rates for those asked to participate were 50.6% in City 1, 48.7% in City 2 and 57.2% in City 3. A total of 467 individuals completed the questionnaire, of whom 454 had already consumed, or intended to consume, alcohol that night. For the purpose of this study, we focused on alcohol consumers aged 18–35 years . Most (96.3%) participants had consumed alcohol at the point of survey (median of 10 UK units) and 64.0% reported having preloaded. Median scale values for all cities combined were: personal drunkenness at survey, 4; expected personal drunkenness, 7; perceived city drunkenness norm, 8; and ideal personal drunkenness, 7. Females tended to rate perceived city drunkenness norm as higher and their ideal personal drunkenness as lower than males. Rating perceived city drunkenness norm as high was also less common among participants from City 2, likely reflecting the greater proportion of males surveyed in this location. There were no differences across age categories. However, preloading was associated with higher ratings across all scales  of participants were male Table  and mediFigure In logistic regression analysis , with limited evidence of effectiveness . Such prSocial norms research shows that young people often overestimate alcohol use by their peers, and that perceived alcohol norms are related to personal alcohol use . Here, fFinally, expected levels of drunkenness were associated with later expected home time. This reflects previous research suggesting that late night drinking environments are dominated by heavy drinking individuals –7. ExtenThis study faced a number of limitations common to nightlife surveys. Data were collected opportunistically, sample sizes in each city were relatively small and overall compliance was 51%, thus samples cannot be considered representative of all nightlife users in the three cities. Further, individuals who were visually assessed as being severely intoxicated were excluded to meet ethical requirements . HoweverExcessive drinking and drunkenness in nightlife environments damages public health, drains public resources and poses an ongoing challenge to public services. Addressing cultures of intoxication in nightlife environments requires a better understanding of the social norms that support them. Our study suggests that UK nightlife patrons may have elevated perceptions of typical nightlife drunkenness levels and that substantial proportions may drink beyond their ideal level of drunkenness. Findings could support social marketing approaches to correct social perceptions of drunkenness and can inform further work both in the UK and internationally to better understand the drivers of and potential solutions to harmful drinking behaviours in nightlife environments.Additional file 1:Questionnaire content. Questions used in the study. (PDF 244 kb)


Annotating functional terms with individual domains is essential for understanding the functions of full-length proteins. We describe SDADB, a functional annotation database for structural domains. SDADB provides associations between gene ontology (GO) terms and SCOP domains calculated with an integrated framework. GO annotations are assigned probabilities of being correct, which are estimated with a Bayesian network by taking advantage of structural neighborhood mappings, SCOP-InterPro domain mapping information, position-specific scoring matrices (PSSMs) and sequence homolog features, with the most substantial contribution coming from high-coverage structure-based domain-protein mappings. The domain-protein mappings are computed using large-scale structure alignment. SDADB contains ontological terms with probabilistic scores for more than 214 000 distinct SCOP domains. It also provides additional features include 3D structure alignment visualization, GO hierarchical tree view, search, browse and download options.http://sda.denglab.orgDatabase URL:  E. coli to human containing the catalytic function, and shares conserved catalytic regions with both serine/threonine and tyrosine protein kinases  has been a de facto standard for describing gene and protein function , 19. It Although sequence-based domain annotation and domain-centric protein function prediction have been extensively studied, predicting functions for protein structural domains is, even more, difficult given the lack of comprehensive structural domain information for proteins. Only a few previous efforts have been performed to computationally predict structural domain functions , 23, 24.Recently, we proposed a functional annotation approach for structural domains (SDA) that is largely based on 3D structure-based domain-protein mappings . We usedhttp://sda.denglab.org.Here, we present the SDA database, which provides domain GO annotations predicted from our integrated method, and also includes links to other databases. The server allows users to query functional annotations for input proteins or domains. The results can be visualized in an interactive 3D viewer and a tree viewer. SDADB is available at Structural domains are downloaded from SCOPe version 2.06 , 17. GO d is a SCOP domain, g denotes a GO term, P is the number of PDB proteins containing domain d and having function g, P(d) is the number of PDB proteins containing domain d calculated on the P2D mapping data.We use a structure alignment algorithm 26, 27) to search structural neighbors for SCOP domains against the PDB database, and obtain a significant number of protein-domain (P2D) mappings. The structural similarity between proteins and domains is measured by protein structure distance (PSD) , 27 to s. The GO g) assigned to the SCOP domain is calculated based on the number of InterPro domains that have the function:n is the number of InterPro domains owned by the SCOP domain. If an InterPro domain has the function g, I(g) is 1; otherwise 0.We use the InterProScan tool  to searcl) apart throughout the whole sequence. For a descriptor (one of the 20 basic residue types), the AC variable is calculated as:l denotes the distance between one residue and its neighbor, DL is the length of domain sequence, iX is the PSSM score of the descriptor at position i, l = 10. Based on the PSSM vectors, we build SVM classifiers for each GO term. The probability score of a GO term (g) assigned to a SCOP domain is estimated based on the output of the SVM classifier by a sigmoid function:f(g) is the SVM output score, A and B are estimated using the method of Lin et al.  to estimate the weight of its GO term assigned to the query SCOP domain. The probability for a GO term (g) assigned to the query domain is the sum of weights of sequence homologs that have the GO annotation in UniProt-GOA:n is the number of sequence homologs, b is a constant of log is 1; otherwise 0.We also used PSI-BLAST to search sequence homologs for SCOP domains against the UniProt database. We only select the sequence homologs with alignment coverage >60%. The GO annotations of sequence homologs are obtained from the UniProt-GOA database . We use nt of log. If the f is the component method.We combine the output scores of the four component approaches using a Bayesian network . The BayThe final predicted GOA-SCOP (GO annotation for SCOP domains) data are stored in an MYSQL database. The website is developed using Perl, JavaScript, jQuery (AJAX), CSS and HTML5, and is deployed on an Apache web server. The BioJava  and JSmoThe SDADB database can be queried through the protein/domain accession number (e.g. 1te0/d1te0a2) or protein/domain name (e.g. Stress sensor protease DegS). The server will return a list of GO annotations with corresponding confidence scores . The detUsers can view the annotations by clicking the ‘view GO tree’ button, which shows the hierarchical architecture of GO . Users cF-measure (Fmax) to measure the overall performance. The precision–recall curve shows the trade-off between precision and recall for different thresholds. A high area under the precision–recall curve denotes high overall performance. F-measure considers both the precision and the recall of the GO prediction results of SCOP domains. It is calculated as the harmonic average of the precision and recall. Maximum F-measure (Fmax) is the maximum value of the F-measure over a varying threshold. The coverage is computed by dividing the number of domains with predicted GO annotations by the total number of domains in SCOPe 2.06. For detailed descriptions of the datasets and performance measures, see Reference , a maximum F-score of 0.723 for BP  and a maximum F-score of 0.809 for CC (cellular component). For the coverage, SDADB has GO annotations for most SCOP domains (92.3%). We also compare SDADB with other state-of-the-art approaches on the independent test dataset. As shown in We compare our SDADB database with the four component methods, including structure alignment-based method (Str), Interpro domain-based method (IPR), PSSM profile-based method (PSSM) and sequence homolog-based approach (Seq). The results are summarized in The SDADB database provides large-scale detailed GO annotations at the structural domain level. In contrast to the approaches based on sequence and homology information, an advantage of SDADB is that the method integrates structural neighborhood features together with a variety of heterogeneous information, including SCOP-InterPro domain mapping information, PSSMs and sequence homolog features. The SDADB database now contains 3 482 316 GO annotations for 211 282 SCOP domains with a probability >0.1. Of these, 1 479 652 annotations for 204 948 domains have a probability >0.5. Also, SDADB provides P2D mappings for over 191 060 PDB structures. The vast amount of P2D and domain-function mapping data in the SDADB database can help to investigate the functions of full-length proteins since domains are functional units of proteins. The database will also give valuable insights into protein domain evolution, which are not only likely to be fascinating but will also ultimately improve the power and accuracy of protein function prediction approaches.It is worth pointing out that some common and multifunctional domains may be not well annotated since the presence of a common domain in several proteins does not necessarily imply that these proteins have the same function. Future developments will focus on combining more informative clues and analyzing tools. We also expect the interested user will be able to use the resources provided in the SDADB database as a basis for new efforts on expanding the functional space for both domains and full-length proteins.http://sda.denglab.org/.The SDADB database is freely available at This work was supported by National Natural Science Foundation of China (61672541); Natural Science Foundation of Hunan Province (2017JJ3287); Natural Science Foundation of Zhejiang (LY13F020038); Fundamental Research Funds for the Central Universities of Central South University (2017zzts727) and Shanghai Key Laboratory of Intelligent Information Processing (IIPL-2014-002). Conflict of interest. None declared.


Staphylococcus simulans and its family enzymes rapidly acquire prominence as the next generation agents in treatment of S. aureus infections. The specificity of lysostaphin is promoted by its C-terminal cell wall targeting domain selectivity toward pentaglycine bridges in S. aureus cell wall. Scission of these cross-links is carried out by its N-terminal catalytic domain, a zinc-dependent endopeptidase. Understanding the determinants affecting the efficiency of catalysis and strength and specificity of interactions lies at the heart of all lysostaphin family enzyme applications. To this end, we have used NMR, SAXS and molecular dynamics simulations to characterize lysostaphin structure and dynamics, to address the inter-domain interaction, the enzyme-substrate interaction as well as the catalytic properties of pentaglycine cleavage in solution. Our NMR structure confirms the recent crystal structure, yet, together with the molecular dynamics simulations, emphasizes the dynamic nature of the loops embracing the catalytic site. We found no evidence for inter-domain interaction, but, interestingly, the SAXS data delineate two preferred conformation subpopulations. Catalytic H329 and H360 were observed to bind a second zinc ion, which reduces lysostaphin pentaglycine cleaving activity. Binding of pentaglycine or its lysine derivatives to the targeting domain was found to be of very low affinity. The pentaglycine interaction site was located to the N-terminal groove of the domain. Notably, the targeting domain binds the peptidoglycan stem peptide Ala-d-γ-Glu-Lys-d-Ala-d-Ala with a much higher, micromolar affinity. Binding site mapping reveals two interaction sites of different affinities on the surface of the domain for this peptide.Lysostaphin from  Staphylococcus aureus causes numerous diseases, ranging from minor skin abscesses to meningitis and even toxic shock syndrome  are a distinct feature of the 2+-coordinating amino acid residues  strain. DNA encoding the CWT domain (residues 402-493) was amplified (primers 5′-CGCGGATCCTGGAAAACCAATAAATATGGCACGC-3′ and 3′-CGCGAATTCTTATTTGA TGGTGCCCCACAGG-5′) using this plasmid as template and was cloned into pGEX-2T vector separately at the BamH1 and EcoR1 cloning sites as well.Gene for mature lysostaphin (residues 251-493) was synthesized de novo at GenScript  and cloned into pGEX-2T vector  at the BamH1 and EcoR1 cloning sites. Resulting plasmid was transformed into 2HPO4, 22 mM KH2PO4, 12 mM NaCl, 1 mM MgSO4, 100 μM CaCl2, 10 μM FeSO4, 0.001 % w/w biotin, and 0.1 mg/ml ampicillin, pH 7.0). Upon cells reaching OD600, protein expression was induced with isopropyl β-D-1-thiogalactopyranoside (IPTG), 0.5 mM final concentration, and further incubated for 3 h. Harvested cells were disrupted by sonication, and soluble fraction was loaded on Glutathione Sepharose 4 Fast Flow resin . Lysostaphin was released from resin-bound glutathione tag by thrombin and protein was further purified by gel filtration on HiLoad 16/60 Superdex 75 column . Removal of innately bound metal ions was carried out with EDTA, which was thereafter dialyzed away in PBS buffer and protein was concentrated with Amicon®; 5000 MWCO centrifugal filters.Protein expression and purification was carried out as described in detail previously NH, (H)CC(CO)NH, H(CCO)NH, HBHA(CO)NH, (HB)CB(CGCD)HD, (HB)CB(CGCDCE)HE, 1H, 15N NOESY-HSQC, 1H, 13C NOESY-HSQC in 7% D2O/93% H2O, and 1H, 13C HSQC-NOESY in 100% D2O. The latter five spectra were employed for the assignment of the aromatic residues as well as the source of distance restraints for structure determination. Additional structural restraints were derived from the chemical shifts in the form of TALOS-N . Binding characteristics of a PG peptide mimic were determined by titration of the CWT domain with A-d-EKGGGGGA-d-EK-d-A and comparing 1H, 15N HSQC spectra acquired at approximate peptide to CWT domain molar ratios of 0, 0.5, 1, 2, 5, 10, and 24. Similarly, the pentapeptide A-d-γ-EK-d-A-d-A (Bachem) and muramyl dipeptide N-acetylmuramyl-l-alanyl-d-isoglutamine hydrate (Carbosynth Ltd) were titrated to a CWT domain sample, and 1H, 15N HSQC spectra were collected at approximate peptide to CWT domain molar ratios of 0, 0.5, 1, 2, 4, 8, 16, 32, 45, and 60. CSPs, calculated as Δδ = (ΔδH2+(0.154 × ΔδN)2)1/2, were plotted as a function of the molar ratio of titrated ligand to CWT domain. Dissociation constants for individual residues were obtained by nonlinear least squares fitting, as implemented in the program xcrvfit . Site-specific dissociation constants were calculated as averages of dissociation constants of individual residues within the site. In all binding site studies protein to zinc concentration ratio was 1:1.The pentaglycine binding site on the CWT domain was determined by comparing the 1H, 15N HSQC spectrum.CAT domain–SH3 domain interaction was probed by replacing zinc with paramagnetic manganese (1:1 protein to cation ratio) and observing peak bleaching in a 15N T1, T2 and heteronuclear NOE spectra were acquired for one- and three-zinc bound lysostaphin in the presence and absence of substrate pentaglycine on a Bruker AVANCE III HD 800 MHz spectrometer, equipped with a TCI 1H/13C/15N cryoprobe. For T1 relaxation delays of 20, 60, 100, 200, 400, 600, 900, 1,400, 2,000, and 2,600 ms were used. For T2 the delays were multiples of loop length 16.96 ms, with the loop counter set to 1, 2, 3, 4, 5, 6, 7, 8, 10, and 12. The recycle delay was set to 3.1 and 2.6 s for the T1 and T2 experiments, respectively. All spectra were acquired as pseudo 3D spectra and Fourier transformed with NMRPipe. Peak intensities were fitted to decaying exponential function as implemented in Sparky. Heteronuclear NOE values were calculated as the intensity ratios of peaks from a pair of spectra measured with and without 1H presaturation during the recycle delay. The relaxation delay was set to 5 s. The CWT domain relaxation spectra were recorded on a Bruker AVANCE III 500 MHz spectrometer. For T1, relaxation delays of 20, 60, 100, 200, 400, 600, 800, 1,200, 1,600, and 2,000 ms. The recycle delay was set to 2.5. For T2, the loop counter was set to 1, 2, 4, 8, 10, 12, 14, and 16 and the recycle delay was 1.5 s. Heteronuclear NOE spectra were acquired as for full-length lysostaphin.1H NMR as described previously  and lysostaphin concentrations were 1 mM and 2.25 μM, respectively. Metal ions  were added as needed. Residual activity of lysostaphin “apo” form was taken into account in activity calculations. Measurements were carried out by using a Bruker Avance III 600 MHz spectrometer, equipped with a QCI 1H/13C/15N/31P cryoprobe and a SampleJet automated sample changer. The preheater of the sample changer was used for sample incubation when product formation was measured as a time series with 3-h intervals for 48 h. Single time-point samples were incubated in an incubator for 21 h and reactions were quenched by heating at 90°C for 15 min before proton spectra acquisitions at 37°C. The data were processed with Bruker TopSpin 3.5 software.Pentaglycine cleavage by lysostaphin was monitored by MD simulations in explicit solvent were performed with AMBER 16 . The measurements were carried out at 288 K in PBS buffer. Three different protein concentrations  were used in the data acquisition. PRIMUS  and maximum dimensions (Dmax) distribution.BM29 beamline, ESRF, Grenoble, France was used for collecting the SAXS data on a PILATUS 1M image plate using sample to detector distance of 2.9 m and a wavelength of 1.0 Å , the catalytic groove embracing loops and the catalytic histidines are conformationally dispersed, which results in a poorer overall structural match in these regions. The conformational spread in the NMR ensemble is the result of solvent exposure and flexibility of residues in these regions  leading to line-broadening, affecting peak intensity, up to 35 Å from the paramagnetic center depending on the paramagnetic probe , which can also be used to untangle the confines of inter-domain mobility. The τcs derived from 15N R2, R1 rates are notably different for the CAT and CWT domains, 7.8 and 6.0 ns at 35°C, respectively  method was employed to analyse the SAXS data. In EOM calculations, lysostaphin CAT (residues 251-384) and CWT (410-493) domains of the NMR structure reported here were used as rigid bodies, and residues 385-409 as random coil. EOM runs yielded reproducible ensembles neatly fitting the experimental data with χ4 Figure . The res Figures . The DmaA dynamic inter-domain interaction in lysostaphin has been presented previously .NMR suits particularly well to study weak or transient molecular interactions. We performed CWT domain binding site mapping with hexapeptides G5 Figure . The pre5K were observed for N405, Y411, G430-F432, V452, M453, and Y472. Residues in strands β1 and β2 and the loop in between (K403-K412) form the bottom of the pentaglycine binding groove, and residues G430-F432 from the loop between strands β3 and β4 and Y472 in strand β7 the ceiling of the groove. Binding site mapping demonstrates CSPs for a delimited set of residues, without secondary, rearrangement-induced perturbations. Our data are nicely in accordance with the crystal structure of the lysostaphin CWT–pentaglycine complex (PDB ID 5LEO), which reveals that only very small structural rearrangements, namely few sidechain reorientations, occur upon binding of pentaglycine. The dissociation constant of the interaction is estimated to be ultra-weak, > 10 mM, in line with those observed for other pentapeptide–SH3b-type CWT domain interactions .We reasoned that d-EKGGGGGA-d-EK-d-A, which would resemble the stem-cross-bridge-stem sequence in native PG, resulted, instead, in significant CSPs at considerably lower concentration ratios, ~24 molar excess. In addition to CSPs of residues in the pentaglycine groove, CSPs were observed for two groups of peaks with distinct binding affinities. If viewing the CWT domain the pentaglycine groove laying horizontally toward the viewer, the N-terminus of the bound pentaglycine on the right (PDB ID 5LEO), then K412-S413, S415-A416, V459, T491, and I492 form an elongated patch on the right side of the domain  we suspect that one peptide molecule binds via its tail to the elongated site, and boosts the affinity of the pentaglycine site for the pentaglycine moiety of the peptide.Titration of the CWT domain with a synthetic peptide A-n Figure . K412 isd-γ-EK-d-A-d-A resulted in a complex peak behavior with three distinct patterns of peak position movement , or be the result of stem peptide contacts present within the PG architecture, that is from stem peptides not directly linked to the pentaglycine recognized by the N-terminal groove. According to the parallel-stem architecture proposed by Kim et al.  and the PDB (https://www.rcsb.org/) with accession codes 34121 and 5NMY, respectively.The assigned chemical shifts and coordinates of lysostaphin have been deposited in the BioMagResBank (PP conceived and designed the research. VR and LK produced and purified the proteins. VR and HM performed enzyme activity studies. UP performed SAXS measurements and SAXS data analysis. HT carried out MD simulations. HT, LK, and PP conducted CWT domain NMR studies. HT and PP performed full-length lysostaphin NMR studies. All authors wrote the paper.HM was employed by company VTT Technical Research Centre of Finland Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Bordetella pertussis, the causative agent of whooping cough. The incidence of pertussis is currently increasing, and represents a global public health concern. Bordetella pertussis, a Gram-negative bacteria, has been identified by Jules Bordet and Octave Gengou who initially described “Le microbe de la coqueluche” in an article published in the Annales de l’Institut Pasteur in 1906. During the last decades, multidisciplinary approaches have contributed to improve our knowledge on CyaA, and showed that this toxin plays a crucial role in the early stages of respiratory tract colonization by disrupting the host immune response. CyaA is a 1706-residue-long, multi-domain, and bifunctional toxin containing a hemolysin and a calmodulin-activated adenylate cyclase producing supraphysiological levels of cAMP in host cells. This toxin is a unique well-characterized bacterial toxin able to translocate its catalytic domain directly across the plasma membrane of target cells. The molecular mechanism by which CyaA intoxicates host cells remains, however, largely unknown. Recent advances worldwide open new perspectives for both basic sciences and CyaA-based biotechnological applications, such as antigen delivery vehicles and CyaA-containing pertussis vaccines. These various aspects are discussed in this Special Issue of Toxins on the adenylate cyclase toxin.The adenylate cyclase (CyaA) toxin is produced by Bordetella [The first review from Nicole Guiso provides us with an overview on the properties of CyaA toxins produced by the bacteria from the genus rdetella . Due to Pertussis colonization of the host respiratory tract launches the primary innate immune defense. In their review, Giorgio Fedele and colleagues describe how CyaA is actively involved in the subversion of host immune responses by intoxicating a vast array of target cells . In partThe ability of CyaA to deliver its catalytic domain into antigen presenting cells, such as in dendritic cells, has been exploited to engineer CyaA-based non-replicating recombinant proteins in which antigens are genetically inserted into the detoxified CyaA catalytic domain. Daniel Ladant and myself review these biotechnological applications he initiated in collaboration with Claude Leclerc in the early 1990s . We illuBordetella isolates using state-of-the-art mass spectrometry methods [This Special Issue then focuses on the molecular processes involved in CyaA biogenesis, membrane translocation, and the effects of cAMP intoxication. CyaA is produced as a protoxin, proCyaA, which is acylated in the bacteria before its secretion. Acylation is crucial for CyaA activation, i.e., to gain the ability to translocate its catalytic domain into target host cells. In a research article, Valérie Bouchez and colleagues characterize the nature of the acyl chains of CyaA toxins from various  methods . The autJakub Novak et al. and Helena Ostolaza et al. provide two complementary reviews describing the molecular basis of CyaA biogenesis and translocation. Novak and colleagues further highlight the diverse effects of CyaA on host phagocytes , while tIn a research article, Alexis Voegele and colleagues present new results on a membrane-active peptide derived from the CyaA translocation region, which is required for the delivery of the catalytic domain into host cytosol. They show that the arginine residues from the segment 454–484 from CyaA are involved in the successive steps of membrane interaction, folding, and permeabilization . The autKurehong and collaborators report the effect on the pore-forming activity of point mutations of two residues (Q574 and E581) from the hydrophobic region of CyaA. They show that mutations to positively charged residues, which mimic the local positive valence as observed in hemolytic RTX proteins, increase the pore forming activity of CyaA [These last decades, intensive research activities have been dedicated to investigate the activation of the CyaA enzymatic domain. Recently, we showed that the catalytic domain contains a large region of structural disorder , and is Finally, Beyza Bulutoglu and Scott Banta review the works they have done using the C-terminal RTX domain of CyaA to engineer calcium-dependent nanotools they developed in the fields of bioseparation, hydrogel catalysis, and molecular recognition . These aTaken together, CyaA is intensively investigated to provide new insights into its intoxication process and how it disrupts host immune responses. As illustrated in the reviews and research articles of this Special Issue, methodologies from fundamental sciences applied to CyaA are crucial to provide a better understanding of the toxin and also to develop CyaA-based biotechnologies and vaccines.


Phosphoinositide 3-kinase alpha (PI3Kα) is involved in fundamental cellular processes including cell proliferation and differentiation and is frequently mutated in human malignancies. One of the most common mutations is E545K, which results in an amino acid substitution of opposite charge. It has been recently proposed that in this oncogenic charge-reversal mutation, the interactions between the protein catalytic and regulatory subunits are abrogated, resulting in loss of regulation and constitutive PI3Kα activity, which can lead to oncogenesis. To assess the mechanism of the PI3Kα E545K activating mutation, extensive Molecular Dynamics simulations were performed to examine conformational changes differing between the wild type (WT) and mutant proteins as they occur in microsecond simulations. In the E545K mutant PI3Kα, we observe a spontaneous detachment of the nSH2 PI3Kα domain  from the helical domain  causing significant loss of communication between the regulatory and catalytic subunits. We examine the allosteric network of the two proteins and show that a cluster of residues around the mutation is important for delivering communication signals between the catalytic and regulatory subunits. Our results demonstrate the dynamical and structural effects induced by the p110α E545K mutation in atomic level detail and indicate a possible mechanism for the loss of regulation that E545K confers on PI3Kα. PI3Kα is comprised of a catalytic subunit, p110α, encoded by the PIK3CA gene, and a regulatory subunit, p85α, encoded by the PIK3R1 gene -positive breast cancers, but depending on the type of the PI3Kα mutation different therapeutic regimes must be followed13.Phosphoinositide 3-kinase alpha (PI3Kα) is a lipid kinase that plays a crucial role in cell processes involving growth and survivalPIK3CA (p110α subunit) and consequently for the discovery of mutant-specific inhibitors. The crystal structure elucidation of PI3Kα WT17 and H1047R mutant18 has enabled the mechanistic understanding of PI3Kα overactivation by the H1047R mutant. By using a combination of Molecular Dynamics (MD) simulations and experiments, it was shown that the H1047R mutation, which is located in the kinase domain of PI3Kα, abolishes the auto-inhibitory role of the C-terminal tail of the protein, enhances protein-membrane binding, and alters the conformation of H917, a critical residue for ATP hydrolysis20. Although a crystal structure bearing the PI3Kα E545K mutation, which is located in the helical domain of PI3Kα, is not yet available, several studies suggest that this mutation leads to elevated kinase activity by an entirely different mechanism than H1047R. Moreover, it has been shown in biochemical experiments that when both mutations are introduced they act independently and synergistically, indicating that the molecular mechanisms for the mutation-induced gain of function in helical and kinase domain mutations are complementary and reciprocal21. Helical domain mutants (such as E545K) lead to activation by abolishing the inhibitory contact of p85α that regulates PI3Kα activation (such mutants are p85α independent), however, they still need to interact with RAS to reach the membrane. On the other hand, while kinase domain mutants (such as H1047R) are active in RAS absence, they require the interaction with the regulatory subunit p85α21.Structural and functional studies of the PI3Kα wild type (WT) and hotspot mutants are of paramount importance for understanding the effect of oncogenic mutations on the constitutive lipid kinase activity of 23. In a low activity state, the nSH2 and iSH2 domains of the regulatory subunit p85α stabilize p110α and inhibit its enzymatic activity. In one of these inhibitory contacts, the nSH2 domain of p85α interacts strongly with the helical domain of p110α and stabilizes the inactive state of PI3Kα. This contact is physiologically released by phosphotyrosine (pY)-containing peptides, which bind at the nSH2-helical interface and activate the enzyme (pY-activated state of the WT)25. The E545K charge reversal mutation in the helical domain of p110α is located exactly at the position where pY-peptides bind nSH2. Later studies also suggest that the E545K mutant increases lipid kinase activity by disrupting the nSH2-helical interface, mimicking the pY-activated state of the protein28. This mechanism has been further supported by biochemical studies investigating the kinetics of PI3Kα activation for the WT and oncogenic mutant  proteins29. Both mutants show a 2-fold increase in lipid kinase activity compared to the activated WT29. However, contrary to H1047R, the E545K mutant cannot be further activated in the presence of growth factor stimulation (pY-peptides), suggesting that this mutant activates p110α through the same mechanism as the binding of pY-peptides27. Nevertheless, so far, there is no crystal structure of the mutant E545K available to provide structural evidence for this mechanism.Early studies have indicated that E545K acts by altering the p110α-p85α interface30. Burke et al. showed that the E545K helical mutation enhances three out of the four distinct events that occur during the physiological transition of the WT PI3Kα from an inactive to an active state. These three events require breaking of the nSH2-helical interface, disruption of the iSH2-C2 interface, and movement of the ABD domain relative to the rest of the catalytic subunit30. Although the experiments capture the dynamic nature of the enzyme activation, the order with which these events are taking place remains unclear.A recent hydrogen/deuterium exchange mass spectrometry (HDX-MS) study gave the first insight into the structural mechanism of activation of PI3Kα caused by the E545K mutation31. Conventional MD34 or biased, enhanced sampling methodologies37 have been extensively used to study the mechanism of constitutive activation of various protein kinases as well as the mechanism of action of anti-cancer drugs38. A recent MD study of oncogenic mutations of PI3Kα suggests that all tumor-associated mutants weaken p110α-p85α interactions by increasing positional fluctuations of nSH2 (p85α) domain39. However, the limited sampling of these simulations could not allow the observation of significant conformational changes. Another recent study of E545K and E542K mutants of PI3Kα, involving docking of catalytic (p110α) and regulatory (p85α) subunits and subsequent MD simulations, indicates fewer interactions of p110α-p85α in the mutants compared to the native structure40. In this study, a connection between nSH2 (p85α) flexibility and helical mutations  was observed, however, it remains unclear how this effect could eventually lead to nSH2 detachment and allosteric regulation of the enzyme activity, perhaps due to the approximation of docking the two subunits and not using the crystal structure in the simulations.MD simulations have been successfully used for the identification of intermediate structures during the activation pathway of various kinasesPIK3CA E545K activating mutation by monitoring structural and dynamical elements of the WT and mutant proteins.In the present study, we performed microsecond-long simulations of the full-length WT and E545K p110α/niSH2 heterodimer to investigate the structural and dynamical changes induced by the mutation through unbiased MD simulations. For the first time, we have been able to follow in atomic-level detail the unforced detachment of nSH2 (p85α) from the helical (p110α) domain in the PI3Kα mutant form, monitoring the series of events leading to this disruption. The molecular mechanism that emerges from our study could explain how the nSH2 domain detaches gradually from the helical one, resulting in loss of this inhibitory contact that can eventually lead to overactivation of the enzyme. We also investigated the allosteric network connecting key residues in the WT and mutant proteins and show that a cluster of residues around 545 is critical for delivering communication signals between the catalytic and regulatory subunits. Our simulations are in agreement with HDX experimental data and allow us to provide atomic-detail insights into the mechanism of the 30 and structural studies18. The movement of nSH2 relative to the helical domain is clearly seen in Fig. Calculation of the Root Mean Square Deviation (RMSD) with respect to the initial structure shows that a significant conformational change takes place in one of the PI3Kα E545K mutant simulations -E542) in the WT, is almost completely absent in the mutant E545K simulation Fig.  and S3. The detachment of nSH2 from the helical domain in the mutant protein also alters the interactions of nSH2 with the neighboring C2 and kinase domains of the catalytic p110α subunit. As seen in Fig. 41. Indeed, our simulations show that this interaction persists until the end of our simulation, and we may hypothesize that the detachment described in the current work constitutes the first step for the complete dissociation of nSH2 from its neighboring counterparts, which will lead to constitutive relief of inhibition.nSH2 contacts the kinase domain with its 339–347 helix, which interacts with helix α10 of the C-lobe of the kinase domain. We observe that during the detachment, the 339–347 helix serves as a hinge around which nSH2 rotates and detaches from the helical domain Fig.  that is 45 even in the absence of large conformational changes. In our case, where a significant conformational change takes place, we expect to see differences in the communication between domains of PI3Kα in the WT and E545K mutant proteins, indicating a possible mechanism for allosteric regulation of the enzyme activity controlled by E545K. Comparison of the RMSF of the E545K mutant simulation, where nSH2 detaches (open-state), with the WT (closed-state) shows that there are specific regions in functional domains that are more flexible in the mutant open-state. As seen in Supplementary Fig. 30 . The results are presented in Fig. 2 and correspond to pairs of atoms of nSH2-helical, nSH2-C2, and nSH2-kinase domains, indicate rigid body-like motions that could propagate strong allosteric communication between these domains. Therefore, as seen in the Mutant run 1 simulation , the detachment of nSH2 results in significant distance fluctuations, weakening the communication between nSH2-helical and nSH2-C2 domains. Interestingly, although nSH2 seems to physically approach the kinase domain  maps for the Cα atoms of the nSH2-helical, nSH2-C2 and nSH2-kinase domainsain Fig.  the commain Fig. .Figure 549. To understand the role of residue E545K in allosteric regulation within PI3Kα, we have constructed network models obtained from our MD simulations. For our analyses, we used the Dynamical Network Analysis method as implemented in the program VMD51 (see Methods section and the SI for a detailed explanation). Based on this model, allosteric signals are dependent on positional correlations of protein residues, and correlated motion is used to generate a weight of the signal transmitted through two residues. Apart from identifying allosteric pathways, the method also applies hierarchical clustering using the Girvan-Newman algorithm to cluster residues whose motion is highly correlated in so-called “communities” that are highly intra-connected but loosely inter-connected (see SI for more information)52. The communication between different communities passes through specific residue interactions that form critical edges.In allosteric communication, a signal is propagated over a long distance through the protein structure from one site to another. It has been argued that allosteric communication in proteins relies upon networks of collective, rigid body motions and residue-residue contact motionsA detailed analysis of the inter-domain communication network has been performed for the WT (closed-state) and mutant (open-state) using the dynamical network analysis method (see Methods section). As can be seen in Fig. One of the key interactions between nSH2 and helical domains that is almost immediately lost in the majority of the E545K mutant simulations, is the R358-E542 salt bridge Fig. . Our netThe communication between nSH2-C2 domains is also significantly distorted in the mutant open-state. Although upon the nSH2-helical detachment the nSH2-C2 interface is largely affected, based on the maps of distance fluctuations Fig. , one cri2)53. Indeed, a recent crystallographic structure (PDB ID 4OVV) of PI3Kα in complex with a PIP2 mimetic, reveals that PIP2 binds very close to the activation loop and forms a salt-bridge or water-mediated hydrogen bond with K941 of the activation loop  and E342 (nSH2) , which is closer to the lipid substrate, should be able to deprotonate the 3′-hydroxyl of PIP2. A schematic representation of the area around the activation loop and the lipid substrate binding pocket is given in Fig. 15. They suggest that the interactions that nSH2 forms with the activation loop regulate its position and keep the latter in its inactive conformation, away from the lipid substrate binding site. The detachment of nSH2 (p85α) from the helical (p110α) domain should disrupt the interactions between nSH2 and the activation loop, and allow the latter to adopt an active-like conformation, in which it will be positioned in the vicinity of the lipid substrate binding site. We find in our simulations that nSH2 forms persistent hydrogen bonds with the activation loop in the WT PI3Kα protein -K948(activation loop) bond in the mutant breaks during nSH2 detachment from the helical domain resulting in a total loss of contact and communication between nSH2 and activation loop. Although the nSH2-activation loop interaction is diminished in the mutant open-state (Mutant run 1), we do not observe any significant conformational change in the activation loop that could be attributed to the detachment of nSH2  remains unchanged even in the absence of nSH2-activation loop interactions. We offer below an explanation why this may be the case.Although the kinase domain of the catalytic region of PI3Ks is highly conserved, members of Class I PI3K exhibit high lipid substrate specificity, determined by residues on the activation loop (res. 933–958) see Fig. . Amino aoop Fig. 15. Moreoein Fig. . In accoSH2 Fig. . This isSH2 Fig. . Therefo15, this interface is mediated by hydrophobic contacts between L598  and F945  and a hydrogen bond between Q591  and K948 . Ιn the mutant E545K these interactions are enhanced. iSH2 attracts the activation loop through mainly hydrophobic interactions . One hydrogen bond is formed between iSH2 W597 and the activation loop K944, and one salt bridge is formed between the C-terminal carboxylic acid of iSH2 L598 and the side chain of the activation loop K944. We should note finally, that the activation loop does not become more solvent exposed after nSH2 detachment 16 was employed in order to capture the nSH2 domain. The free p110α-p85α niSH2 complex that we are using in this study (PDB ID 4OVU)15 has shown a considerable degree of ordering in the nSH2 domain. However, even in this structure, the intrinsic disorder of nSH2 is still evident in the relatively high B factors15 of nSH2 and the region of iSH2 in the proximity of nSH2. Expensive Metadynamics calculations are required to increase the sampling and provide valuable information about intermediate structures and energetic barriers. However, these calculations are still beyond the current accessible computational time for such large systems (500 K atoms) to reach convergence and provide accurate insights.Large conformational changes in protein kinases take place over a timescale of microseconds to milliseconds30. Indeed, our simulations indicate a significant reduction in polar interactions at the nSH2-helical interface in the case of the mutant protein. Interestingly, a complete nSH2 detachment from the helical domain is observed in one out of the eight simulation runs of the mutant. The alteration of the polar contact network around the mutant residue 545K and the breaking of crucial hydrogen bonds between nSH2 and helical domains, lead to the detachment of the two domains that can be observed through a stepwise mechanism -helical(p110) inhibitory contactsism Fig. . A criti30  and E342 (p85α). At the same time, K948 is also locked by an interaction with Q591 of the iSH2 domain. The mutation E545K at the helical-nSH2 interface causes a conformational change that breaks the K948 (p110α) – E342 (p85α) interaction with the activation loop, resulting in loss of communication between nSH2 and the activation loop of the catalytic subunit. The loss of contact between the activation loop and nSH2 is accompanied by an enhanced interaction between the activation loop and the iSH2 domain, which maintains an inhibitory role for the activation loop. Loss of contact with iSH2 would also be required for activation; this may be induced by the approach of the high negative charge of PIP2 in the proximity of the positive activation loop  were smoothly decaying between cut-off distances 0.8–1.0 nm. Prior to MD simulations, both structures were relaxed by 10,000 steps of energy minimization using the steepest descent algorithm, followed by positional restraint equilibration first in the NVT and then in the NPT ensemble for 200 ps each. Finally, unbiased MD simulations were carried out with the atomic coordinates of the systems saved every 2 ps. Two simulations were performed using the WT structure for 1.7 μs in total. In the absence of relevant literature that indicates the protonation state of crucial PI3Kα residues such as 545K, for our initial simulations, we have used the PROPKA algorithm59 to predict residue protonation states. PROPKA predicted that K379, in the microenvironment of the charged 545K and other positively-charged residues in the vicinity, should be unprotonated, while in the microenvironment of the E545 it should be protonated. We, thus, performed four independent simulations with the mutant residue K379 unprotonated  and four with the mutant residue K379 protonated .The entire crystal structure of the human WT PI3Kα (PDB ID: 4OVU)55 and VMD51 tools. To assess the intrinsic flexibility and the apparent plasticity of the protein, maps of distance fluctuations were constructed following the procedure reported by Chiappori et al.46. In this work, we also use the dynamical network analysis method, which constructs networks of biomolecules constituting nodes (atoms) and edges (connecting atoms), weighted by correlation data. This method has been previously applied to study residue networks of several proteins and protein complexes64 and explore putative allosteric communication pathways8. Using this method, time-dependent positional correlations between residues are calculated. Based on these residue-correlated motions a network representation of the protein is constructed, where the residues (or sets of atoms) are the nodes of the network, which are connected to each other by links (edges) that depend on the node interaction strength.The trajectory was analyzed using GROMACS v5.0.4“critical edges” and the nodes connected by these edges are established as “critical nodes” for allosteric signal transduction. The last 200 ns of all reported simulations were used for the dynamical network analysis.The method outputs the shortest paths between residues (nodes) as the most dominant mode of their communication. Edges that most frequently belong in short paths are named All methods are presented in detail in the Supplementary Information.Supporting Information


The 3′X domain of hepatitis C virus has been reported to control viral replication and translation by modulating the exposure of a nucleotide segment involved in a distal base-pairing interaction with an upstream 5BSL3.2 domain. To study the mechanism of this molecular switch, we have analyzed the structure of 3′X mutants that favor one of the two previously proposed conformations comprising either two or three stem–loops. Only the two-stem conformation was found to be stable and to allow the establishment of the distal contact with 5BSL3.2, and also the formation of 3′X domain homodimers by means of a universally conserved palindromic sequence. Nucleotide changes disturbing the two-stem conformation resulted in poorer replication and translation levels, explaining the high degree of conservation detected for this sequence. The switch function attributed to the 3′X domain does not occur as a result of a transition between two- and three-stem conformations, but likely through the sequestration of the 5BSL3.2-binding sequence by formation of 3′X homodimers. The genomic RNA of HCV comprises a single ORF flanked at either end by untranslated regions (UTRs) containing structured domains that play key roles in the viral cycle. The 5′-UTR is mostly occupied by an internal ribosome entry site (IRES) involved in the initiation of viral protein synthesis , whereassequence .k and k′, respectively. The k motif of domain 3′X is contained within a 16-nt palindromic tract termed dimer linkage sequence (DLS) .The distal contact established between 3′X and 5BSL3.2 A has beek sequence is included in the DLS, the establishment of the distal contact with 5BSL3.2 and the formation of intermolecular homodimers must be mutually exclusive. This suggests a switch-type function for the DLS/k motif of the HCV genome.The DLS promotes dimerization of viral genomes in vitro  through k motif is almost completely buried in the upper double helix of subdomain SL2′ and apparently unable to form a kissing loop complex with the k′ complementary motif within the 5BSL3.2 apical loop  experiments have been used to study the solution structure of domain 3′X, both in isolation  and compcal loop B. An alteriments . This leeriments . However3.2 loop .To determine the role of 3′X domain structure on the virus cycle and further clarify the mechanism of the proposed conformational switch, we have carried out a structural and functional analysis of this domain including several mutations that either stabilized the two-stem conformation observed for the wild-type domain, or favored the alternative three-stem structure B. The efk tract and were predicted by RNA-folding algorithms to modify the conformation of the domain. Three of them, U3C, U55C, and the double mutant U3C/U55C, stabilized the two-stem structure observed by NMR and SAXS experiments . The results indicated that the monomeric species of the U3C, U55C, and U3C/U55C domain mutants stabilizing the two-stem conformation had an electrophoretic mobility comparable to that of the wild-type sequence. Mutant U3G migrated similarly to the sequences favoring the two-stem conformation, although forming a smeared band. In contrast, the monomeric species of the double (G50C/C52G) and triple (U3G/G50C/C52G) mutants destabilizing the two-stem conformation migrated more slowly . This indicated that the monomeric conformation of the U3C, U55C, U3C/U55C, and U3G mutants was similar to that of the wild-type sequence, whereas the destabilizing double and triple mutants likely adopted a different solution structure.The solution structure of the mutant 3′X domain monomers was first assayed by native gel electrophoresis  were also found to be analogous to those of the wild-type domain and subdomain constructs. This indicated that the stabilizing U3C/U55C mutant formed a two-stem monomer conformation similar to that adopted by the wild-type sequence, as depicted in These observations were corroborated by an NMR analysis of the mutant conformations under conditions of low ionic strength and low RNA concentration, previously shown to favor the presence of monomers . In this mutant, a new U55:A96 Watson–Crick pair was detected, connected with NOEs to U56:A95. Likewise, a new U:G HN3 imino peak appeared, tentatively assigned as U98 . Since U55:A96 and U56:A95 are the only possible consecutive A:U pairs in the entire domain, these observations clearly indicate an extension of the SL1′ stem, induced by the disruptive U3G mutation at the base of the SL2′ helix . Despite these changes, the chemical shifts and NOE patterns of most subdomain SL2′ residues were similar to those detected in the wild-type sequence . Therefore, the NMR results indicated that mutant U3G adopted a two-stem conformation comprising an extended SL1′ subdomain, as illustrated in Supplemental Figure S4B.We also carried out a detailed NMR analysis of U3G/G50C/C52G  indicated that this mutant formed, like U3G, an extended SL1′ subdomain, which is present in the three-stem conformation predicted for this triple mutant sequence . These results indicated that U3G/G50C/C52G adopted a conformation, or mixture of conformations, different to that formed by the wild-type sequence or the U3C/U55C and U3G mutants. The appearance of multiple resonances prevented us from extracting further conclusions regarding the solution structure of this mutant.The imino resonances and NOE crosspeaks detected in the spectra of Usequence B. Howeve3C, U55C, and G50C/C52G, confirmed that the first two adopted a two-stem conformation similar to that of the wild-type and mutant U3C/U55C domains, whereas G50C/C52G, like the triple U3G/G50C/C52G mutant, adopted a different conformation (data not shown).On the other hand, analyses of the homonuclear spectra of the remaining mutants, USupplemental Fig. S8). Experiments involving an isolated subdomain molecule (data not shown) indicated that this transition corresponded to the melting of subdomain SL1′, which was formed by all sequences according to the NMR data (see above). In contrast, the temperature of the first transition was markedly influenced by the different sequences. The U3C, U55C and U3C/U55C mutations stabilizing subdomain SL2′ . On the contrary, the temperature of the transition decreased by 6°C (to 39°C) in mutant U3G, which destabilized subdomain SL2′ but still formed the two-stem conformation as indicated by the NMR data . Mutants U3G/G50C/C52G and G50C/C52G, which according to the NMR results did not adopt the two-stem conformation, failed to exhibit a clear lower-temperature transition . This indicated that in these cases the conformation adopted by the first 50 nt of the domain was unstable, in agreement with the observation of multiple resonances in the NMR spectra of these two sequences .We also assessed the stability of the wild-type and mutant domains with UV thermal denaturation experiments, carried out in conditions of low RNA concentration and low ionic strength favoring the presence of monomeric species . Most seain SL2′ B increasSupplemental Fig. S2), as detected previously for the wild-type 3′X sequence . This indicated that the structure adopted by these homodimers was markedly different relative to wild-type, and was likely multibranched . This was not surprising, as 3′X domain dimerization involves the formation of an intermolecular kissing loop contact between two palindromic DLS tetranucleotides exposed in the apical SL2′ loop of the two-stem conformation .All mutants containing the wild-type DLS motif formed homodimers in conditions of higher ionic strength . This indicated that these mutants likely formed extended symmetric dimers similar to those described for the wild-type sequence . Likewise, since kissing dimers are not predominant in the presence of NaCl, the differences in dimerization efficiency between two-stem and three-stem mutants were reduced relative to those observed at 2 mM MgCl2 . In addition, the U3C/U55C double mutant tended to form homodimers less efficiently than the U3C, U55C or U3G mutants . This indicated that both sequences retained the SL1′ and SL2′ conformation upon binding to cre26, as previously shown for mutant C29G/A31U . These changes can be attributed to the formation of an inter-domain 3′X:cre26 duplex where these U34GUG37 nt of the k sequence motif pair in antiparallel orientation with the complementary k′ motif nt of the unlabeled cre26 sequence . All mutants except U3C exhibited reduced translation levels relative to the wild-type sequence in this assay. However, U3C, U55C, U3C/U55C, and U3G, which adopted the two-stem wild-type conformation and bound domain 5BSL3.2, showed significantly higher translation levels than the G50C/C52G or U3G/G50C/C52G mutants, which formed a dissimilar conformation and exhibited reduced capacity to associate to 5BSL3.2 .The fact that only the mutants adopting the two-stem conformation were able to bind 5BSL3.2 is apparently surprising, since the alternative conformation predicted to be favored by the SL2′-destabilizing mutants exposes the  5BSL3.2 B. Howeve2+ ions . The exact mechanism by which 3′X dimerization influences the viral cycle is not yet clear, but the 16-nt DLS tract driving dimerization is absolutely conserved in all viral isolates  in the apical portion of subdomain SL2′ . This alisolates , pointinactivity A, and thactivity . These ractivity . Likewisactivity . This suactivity .cis-acting element for core binding and packaging , and were obtained from vector pFK-I389-Fluc-NS3-3′ET .http://rna.tbi.univie.ac.at/)  (http://varna.lri.fr/) (Secondary structure models were generated with the RNAfold (.ac.at/)  and/or many.edu)  web servlri.fr/) .3C, U55C, U3C/U55C, U3G, G50C/C52G, and U3G/G50C/C52G mutant 3′X domain molecules  were produced by in vitro transcription with T7-RNA polymerase from ScaI-linearized pUC19 derived plasmids. These vectors were obtained by PCR site-directed mutagenesis from a pUC19 vector containing the wild-type domain (29G/A31U mutant (previously identified as 3′Xm) 3′X domain molecules and the 26-nt-long cre26 molecule comprising the upper portion of the 5BSL3.2 domain  were obtained as described previously , 0.1 mM EDTA with no added salts, or additionally containing either 100 mM NaCl or 2 mM MgCl2. Before each NMR and gel electrophoresis experiment, the RNA samples were heated at 95°C for 5 min and immediately placed on ice for 30 min, except when analyzing extended homodimer formation at 100 mM NaCl, where they were cooled down slowly. For experiments analyzing 3′X-5BSL3.2 complex formation, the samples were snap-cooled in the absence of MgCl2 and then incubated with 2 mM MgCl2 for 150 minutes at 25°C, in the absence or presence of the interaction partner.The 98-nt-long Ue domain  and verieviously , 2018. F3C, U55C, U3C/U55C, U3G, G50C/C52G, and U3G/G50C/C52G mutant 3′X domain molecules were studied using unlabeled samples and two-dimensional watergate-NOESY (with 150 msec mixing time) and watergate-TOCSY experiments (60 msec mixing time) recorded in 90% H2O/10% D2O, typically at two temperatures (16°C and 27°C). The recycle delays were 1.6 and 2 sec for all homonuclear TOCSY and NOESY experiments, respectively.The RNA concentration of the samples used for NMR analyses ranged between 50 and 110 µM. NMR spectra were acquired on a cryoprobe-equipped, 600 MHz Bruker Avance III spectrometer, and analyzed using TopSpin 3.5 (Bruker Biospin) and Sparky 3.110 . All U3C/U55C, U3G, and U3G/G50C/C52G mutant 3′X domain molecules were also analyzed using 13C/15N-labeled samples. For these molecules, two-dimensional 1H–15N HSQC and HNN-COSY  as running buffers. These experiments involved 10–40 µM RNA samples, prepared as specified above. All gels were stained with methylene blue and destained in water. These experiments were used to measure the homodimerization and 5BSL3.2 (cre26) binding capacities of 3′X domain molecules. For each mutant, homodimerization was quantified by obtaining the fraction of 3′X molecules forming homodimers relative to total 3′X RNA present in the gel lane. Cre26 complex (heterodimer) formation was similarly obtained from the fraction of 3′X molecules forming heterodimers relative to total 3′X RNA. In both cases, the results were normalized relative to the wild-type values. Gel bands were quantified with ImageJ (Native gels were run at 4°C for 12 h under constant voltage (80 V). We used 20% 19:1 acrylamide:bisacrylamide gels and either 89 mM tris-borate (TB), or 89 mM tris-borate and 2 mM MgClh ImageJ .−1 and subsequently decreased at the same rate to evaluate the reversibility of the process. No significant variations were detected for the Tm values when applying a temperature gradient of 0.5°C min−1. The experiments were carried out using 0.3–0.8 ODU ml−1 RNA (0.3–0.8 µM) samples dissolved in a low-ionic strength aqueous solution . The melting experiments were repeated three times for each molecule, and before each experiment, RNA samples were heated at 95°C for ∼5 min and immediately placed on ice for 5 min.The thermal stability of the wild-type and mutant RNA molecules was monitored by measuring the UV absorbance at 260 nm as a function of temperature in a Varian Cary 100 UV/VIS spectrophotometer. The temperature was raised from 15°C to 95°C at a gradient of 1°C min3C, U55C, U3C/U55C, U3G, G50C/C52G and U3G/G50C/C52G and C29G/A31U 3′X domain mutations were introduced in the pGL-ICU plasmid . PCR reactions were performed with Q5 high fidelity polymerase (New England Biolabs) and 125 ng of each primer. ICU RNAs were obtained as described previously . Subgenomic HCV replicons were obtained by in vitro transcription as previously described , a luciferase reporter gene, the IRES of the encephalomyocarditis virus directing translation of HCV nonstructural proteins NS3 to NS5B, and the 3′-UTR . To faciescribed . Cap-depescribed .2 atmosphere.Human hepatoma Huh-7 and Huh-7.5 cell line monolayers were maintained in Dulbecco's modified Eagle medium (DMEM) supplemented with 10% heat-inactivated foetal bovine serum (Invitrogen) and 1 mM sodium pyruvate (Sigma), at 37°C in a 5% CORenilla luciferase activities using the Dual-Luciferase Reporter Assay System (Promega).HCV IRES-dependent translation efficiencies were determined as previously described . BrieflyRenilla luciferase activities were measured as described above.The effect of 3′X domain conformation in HCV replication was assayed as previously described . BrieflySupplemental material is available for this article.