Whereas the effect of relative deprivation is intuitive, the effect of relative gratification is more difficult to explain. Why would economic prosperity provoke negative attitudes towards immigrants? We first present correlational (Previous research has shown that negative attitudes towards immigrants and support for anti-immigrant parties are observed both among those experiencing relative deprivation lational  and expelational  support  Groups openly advocating anti-immigrant sentiments have made a remarkable comeback in recent years in OECD countries. This trend, which began in the 1980s, can even be witnessed in countries where multiculturalism was once celebrated as a core value defining the national identity. Consider the Netherlands, where the PVV (Party for Freedom) led by Geert Wilders increased its number of seats in parliament from 9 seats in 2006 to 24 in the 2010 elections. Another case in point is Sweden, where, for the first time in the country’s history, the extreme right secured a seat in the national parliament in the 2010 elections.can be associated with harsh attitudes towards immigrants, there is also evidence for the opposite: that economic prosperity can produce harsh attitudes towards minorities—so called relative gratification ).minimized the impact of the GFC both personally and at the country level, either because they or their country had recovered quickly from the GFC or had not been affected as much by it compared to other individuals or countries.Even though Studies 1 to 3 provide good evidence for a v-curve using both correlational and experimental designs, it is not clear yet (a) what forms of relative gratification are most conducive to promote opposition to immigration and (b) why this relationship emerges. These questions were the focus of the fourth and final study where we examined the relationship between perceptions of relative gratification and opposition to immigration in an Australian community sample. To address the first question, we examined a range of different indicators of relative gratification including personal level , and collective level relative gratification . In an attempt to assess whether effects of current relative gratification are similar to effects of past and expected future relative gratification, for both personal and collective level relative gratification, we also examined relative gratification relating to current wealth, current wealth compared to the past, and expected future relative gratification. At the personal level, we also included a measure of class as a relatively fixed indicator or relative gratification. Finally, at both the collective and personal level, we examine the extent to which participants felt relatively gratified when considering the threat posed by the Global Financial Crisis (GFC). More specifically, we focused on whether participants Another important aim of Study 4 was to examine processes underlying relative gratification. We examined the extent to which (1) identification, (2) collective self-definition as competent but cold, and (3) fear for future wealth can account for the relationship between past, present and future collective relative gratification and opposition to immigration.SD = 12.78, 7 missing values). In terms of ethnicity, 76.9% reported to be White Caucasian, 15.8% were Asian, 1.4% were Middle Eastern, .8% were Aboriginal and/or Torres Strait Islander, and 3.9% ticked the ‘other’ category. To the question “what is your highest level of education”, 89 indicated they did not complete year 12, 101 completed year 12, 146 had a post-secondary qualification, 155 had finished an undergraduate degree and 117 participants held postgraduate qualifications (13 preferred not to say). Analyses revealed that controlling for ethnicity or education did not change the interpretation of the results reported below.Participants were 621 Australian residents  with an average age of 40.90  at the University of Queensland. Before completing the questionnaire, participants were informed about the aims of the study. After this, they were informed that continuing with the survey indicated (written) informed consent.The study was part of a larger survey examining participants’ perceptions of their life in Australia and their views of Australian society more generally. Here, we focus on a subset of measures. A professional research company (Taverner Research based in Sydney) collected the data. Participants were sampled from the company’s research panel, which covered all Australian states and territories.Very bad, to 7 = Very good. The scale for the second and third item assessing past collective gratification and future collective gratification ranged from 1 = A lot worse, to 7 = A lot better. Two items were included asking about the extent Australia was unaffected and had recovered well from the Global Financial Crisis: “Our country has already recovered quite well from the negative impact of the global financial crisis”and “The effect of the global financial crisis on our country’s economy has been negligible” .Collective relative gratification was measured with a number of items that tapped different forms of relative gratification relating to collective wealth. Specifically, we measured current, past and future gratification at the collective level using the items: “Please think of the economic situation in Australia at the moment. How would you describe the current economic situation in Australia?”, “Now please think about Australia’s economic situation 3 years ago. To what extent would you describe Australia’s economic situation three years ago to be worse, the same, or better than it is now? “and “Now think about Australia’s economic situation in the next 3 years. To what extent do you expect Australia’s economic situation to be worse, the same, or better in the next 3 years?” Responses to the first item were recorded on a scale ranging from 1 = current personal gratification, 1 = Very bad, to 7 = Very good). We also asked participants about past and future personal gratification with the items “Now please think at your personal economic situation 3 years ago. To what extent would you describe your personal economic situation 3 years ago to be worse, the same, or better than it is now?” and “Now think about your personal economic situation in the next 3 years. To what extent do you expect your personal economic situation to worsen, remain the same, or improve in the next 3 years?” . Finally, two questions asking about relative gratification as being personally unaffected or having recovered well from the Global Financial Crisis: “The effect of the global financial crisis on my personal economic situation has been negligible “and “I have personally already recovered quite well from the negative impact of the global financial crisis” . We also added one item asking about participants’ social class: “How do you perceive your own family’s class/social background?” (1 = Lower class to 7 = Upper class). As a measure of personal wealth, we also asked participants to record their annual household income. However, 40.5% of respondents indicated that they did not know or did not want to provide this information. Given the high number of missing values, we decided not to analyze responses to this measure.Personal relative gratification was measured by asking participants to indicate their level of satisfaction with their current personal financial situation with the item “Please think of your personal economic situation at the moment. How would you describe your current economic personal economic situation?” (Strongly disagree to 7 = Strongly agree). Higher values indicated more identification with the own income group (α = .95).Four items, adapted from Doosje, Ellemers, and Spears  were useStrongly disagree to 7 = Strongly agree the extent to which they perceived Australians to be warm , and competent . The reliability of the warmth (α = .74), and competence scales (α = .64) was satisfactory.Participants were asked to indicate on a 7-point scale from 1 = One item, adapted from Jetten and Wohl  was inclStrongly disagree to 7 = Strongly agree. Participants did not differentiate between realistic and symbolic threat and we combined the items to form one scale, α = .95.Opposition to immigration was measured using 6 items assessing both realistic threat perceptions  and symbolic threat perceptions . Responses were recorded on 7 point scales ranging from 1 = p < .01 was used.A series of curve estimation analyses were conducted exploring the extent to which each of the collective and personal level relative gratification measures predicted opposition to immigration see . Given tβ = -.17, p < .001. There was evidence for curvilinear relationships, such that opposition to immigration was higher among those with lower and among those with higher wealth levels . Interestingly too, the quadratic term of minimizing the impact of the GFC on Australia also predicted opposition to immigration: it was those who felt Australia had not recovered from the GFC (relative deprivation) and those who felt Australia was hardly affected by the GFC (relative gratification), minimizing the effects of the GFC that was associated with higher opposition to immigration, β = .49, p = .007.Inspection of the linear and quadratic effects showed a number of significant relationships. First, focusing on the collective relative gratification predictors of opposition to immigration, only higher current collective relative gratification was linearly associated with lower opposition to immigration, β = -.10, p = .01 and β = -.18, p < .001, respectively. In both cases, the quadratic effect was also significant. Similar to the collective level analyses, and in line with the v-curve hypothesis, higher opposition to immigration was found for those that indicated lower and higher current and future wealth, β = .65, p < .001 and β = .51, p = .002, respectively. Minimizing the personal effects of the GFC or class did not predict opposition to immigration, neither linearly nor curvilinearly  identification, (2) collective self-definition as competent and cold, and (3) fear for the future wealth of Australia to explain the relationship between collective relative gratification and opposition to immigration. These analyses were conducted using only present collective relative gratification measures. Results of these analyses are reported in β = .11, p = .006, collective self-definition as competent, β = .13, p = .001, and fear for future wealth, β = -.23, p = .001. Collective relative gratification was associated with higher identification, a higher collective self-definition as competent and less fear for future wealth. Inspection of the curvilinear relationships revealed only a significant effect for fear for future wealth, β = .76, p < .001. In other words, it was those who were highest and those who were lowest in collective gratification that feared most for the future wealth of Australia.Inspection of the linear relationship between collective relative gratification and each of the mediators revealed a significant linear relationship for identification, β = .16, p < .001, and higher fear for the future wealth of Australia was linearly associated with higher opposition to immigration, β = .26, p < .001.Further analyses revealed that only a few potential mediators predicted opposition to immigration. Higher identification was linearly related to greater opposition to immigration, SE = .012, 95% CI). However, fear for future wealth (linear) turned out to be a significant mediator . Importantly too for our purposes, the quadratic future wealth term was also a significant mediator , indicating that collective gratification predicted opposition to immigration because, relatively speaking, it was those who were highest and lowest in collective gratification that feared most for the future wealth of their country.Because only national identification (linearly) and fear for future wealth (linear and quadratic) met the conditions for mediations, it was only these variables that were included as mediators in bootstrap analyses  using 50or relatively gratified at present or expected to feel so in the future. A similar v-curve was found for the relationship between personal relative gratification and opposition to immigration: it was those who felt relatively poor or wealthy at present or in the future who were more opposed to immigration than those who felt moderately wealthy. Interestingly too, we found that relative gratification by minimizing the negative effects of the GFC on Australia also produced the predicted v-curve relationship. Oppose to immigration to Australia was relatively high among those who denied and those who endorsed the statement that these negative effects were no longer of concern.In sum, even though we found an overall negative relationship between relative collective gratification and opposition to immigration in Australia, in addition to these linear effects we found the predicted v-curve relationship between relative gratification and opposition to immigration. More specifically, we found evidence of a v-curve whereby the relationship between perceived relative gratification and opposition to immigration was most pronounced for those who felt collectively relatively deprived Study 4 also provided evidence for the underlying processes. At the collective level, it was only fear for the future wealth of Australia that mediated the relationship between collective gratification and opposition to immigration. Interestingly, the relationship between collective gratification and fear for the future wealth of Australia was curvilinear: it was those lower and higher in relative gratification who feared future wealth decline of Australia. This finding is consistent with findings by Moscatelli and colleagues  and suggWe set ourselves the task of exploring whether there is evidence for a v-curve shaped relationship between the economic performance of a group or society and opposition to immigration. That is, we predicted that opposition to immigration would be highest among groups that are relatively deprived and poor as well as among those with above average wealth . We found evidence for such a relationship in four studies that examined support for the v-curve in different contexts and using different research designs.In Study 1, we found that voting in favour of a national policy to curb immigration was highest in Swiss cantons where unemployment was lowest and highest (a v-shaped curvilinear relationship). Even though we only found a positive linear relationship and not the predicted curvilinear relationship between canton relative disposable income and voting in favour of this anti-immigration policy, the failure to find evidence for a v-curve was due to the failure to find greater support for this policy among the poorest cantons, not because of the lack of support for higher levels of endorsement of the policy in the wealthier cantons. Even though this finding supports relative gratification theorizing , 11 it iStudies 2 and 3 examined the v-curve using an experimental design. Here too, we found that in both studies opposition to ‘newcomers’ joining a hypothetical society was higher among poor and above average wealth group members than among those in a moderate wealth group condition. Finally, in a cross-sectional study, in line with the v-curve hypothesis, opposition to immigration spiked for those who experienced lower and higher personal or collective levels of current and future wealth. We also found a v-curve between minimizing the effects of the GFC at the collective level and opposition to immigration. In sum, across the four studies, we found consistent support for the v-curve, whereby both wealth deprivation and wealth gratification are associated with greater support for policies aimed at curbing immigration , greaterall wealth groups became more opposed to immigrants when inequality was growing rather than declining. This finding is interesting and suggests that growing inequality is equally threatening for those at the bottom, middle or top of a wealth hierarchy. The finding is consistent with observations by political scientists and sociologists that growing inequality leads to greater status competition whereby everyone experiences greater status instability and status anxiety [In order to better understand the processes underlying the v-curve and the conditions under which outgroup hostility will be most pronounced, it is useful to review other findings that emerged from the studies. First, in our examination of the way societal inequality affects the v-curve , we did  anxiety ,74.Whereas the finding for growing inequality effects is interesting and consistent with Postmes and Smith’s findings , Study 2Study 2, Second, in an attempt to better understand what forms of relative gratification are associated with opposition to immigration, in Study 4 we examined the relationship between collective and personal relative gratification as well as the relationship between current, expected future and past relative gratification with opposition to immigration. Interestingly, past relative gratification  did not predict opposition to immigration. However, and in line with the v-curve hypothesis, opposition to immigration was highest for those who experienced high personal and/or collective levels of current and future relative gratification. We can only speculate why current and expected relative gratification predicted opposition to immigration whereas temporal comparisons with past wealth did not. We suspect that a sense of current and expected future gratification is associated with greater wealth stability  and thatWe also found that relative gratification emerging from a sense that one’s country is relatively more robust against the global financial crisis than other countries also predicted opposition to immigration. This should serve as a reminder that it is not so much absolute wealth, but feeling wealthier than others that matters when predicting outcomes of relative gratification , 9.It is interesting that we found that both personal and collective level gratification predicted opposition to immigration. Even though this appears to go against classic reasoning that collective level outcomes are predicted by collective level processes relating to fraternalistic instead of egoistic deprivation or gratification perceptions , 8, it mFinally, Study 4 provided insight in the processes underlying the relationship between relative gratification and opposition to immigration. Even though self-definitions as competent predicted more opposition to immigration, we did not find that relative gratification was associated with greater competence. We also found no support for the idea that self-definitions as competent triggered self-definitions of being cold. Indeed, self-definitions as warm/cold were not related to either relative gratification or opposition to immigration. It may well be the case that we would find more support for a mediating role of self-definitions as competent and cold in context where wealth is attributed to competence . We suspect that under such conditions wealth may trigger feelings of deservingness and entitlement and these may also be the conditions where groups will self-define as cold, both providing some moral justification for holding negative attitudes of immigrants. This should be examined in future research.We found no support for the prediction that group identification mediates the relationship between relative gratification and opposition to immigration (contrary to ). Even tWe did however find that fear for future wealth mediated the relationship between relative gratification and opposition to immigration and accounted for the observed v-curve. What this suggests is that relative gratification is associated with fear that future wealth may be lost and it is this ‘fear of falling’ notion  that helOur studies are not without limitations and they raise new questions to be examined in future research. First, we suggest that it may be instructive to examine the effects of societal inequality in greater depth in future research. Interestingly, our findings suggest that everyone becomes harsher when income inequality grows compared to when income inequality declines. However, because we needed to ensure that the income of the own wealth group did not change with growing or declining inequality , our inequality manipulation may also have been rather weak. This is because the stability of the own group wealth may have taken away some of the uncertainty that everyone experiences when boundaries between groups become more permeable due to growing inequality, and when all wealth groups start to fear for their future wealth. This too should be explored in future work, whereby societal inequality should be manipulated in different ways.why inequality is associated with such negative outcomes. The paradigm that was presented in Studies 2 and 3 might be useful to examine these underlying processes experimentally.It is also essential in future research to examine the processes underlying growing societal inequality effects. Indeed, while the effects of inequality have been well documented , less prand a general relative deprivation effect  but relative deprivation relationships in Study 4 . Put differently, evidence for the v-curve was found against the backdrop of a general relative gratification effect (Although our work is not the first to demonstrate the v-curve empirically, by examining this relationship in new ways, we have advanced our understanding of the way economic performance of a group affects opposition to immigration. We contribute to this body of work by providing correlational as well as experimental evidence for the v-curve, by examining different forms of relative gratification and by providing greater clarity on the processes underlying the relationship between relative gratification and opposition to immigration. Although wealth undoubtedly reduces certain kinds of stress, we find that relative gratification and wealth also triggers fears that wealth will be lost in the future. Ironically, then, the perception that one is relatively wealthy is therefore not always more comfortable than the perception that one is relatively deprived. In some sense, relative gratification and relative deprivation are not the polar opposites they might seem to be. Feelings of gratification might be pleasing and comfortable at one level, but like all delights such relative advantages might well bring latent insecurities of loss and fears of decline.


The ectodomain of the human epidermal growth factor receptor (hEGFR) controls input to several cell signalling networks via binding with extracellular growth factors. To gain insight into the dynamics and ligand binding of the ectodomain, the hEGFR monomer was subjected to molecular dynamics simulation. The monomer was found to be substantially more flexible than the ectodomain dimer studied previously. Simulations where the endogeneous ligand EGF binds to either Subdomain I or Subdomain III, or where hEGFR is unbound, show significant differences in dynamics. The molecular mechanics Poisson–Boltzmann surface area method has been used to derive relative free energies of ligand binding, and we find that the ligand is capable of binding either subdomain with a slight preference for III. Alanine-scanning calculations for the effect of selected ligand mutants on binding reproduce the trends of affinity measurements. Taken together, these results emphasize the possible role of the ectodomain monomer in the initial step of ligand binding, and add details to the static picture obtained from crystal structures. Proteins 2013; 81:1931–1943. © 2013 The Authors. Proteins published by Wiley Periodicals, Inc. The human epidermal growth factor receptor (hEGFR), also referred to as ErbB1 or Her1, is a receptor tyrosine kinase (RTK) and part of a family of four closely related receptors (ErbB1–ErbB4). These RTKs provide input to a complicated signalling network controlling such vital cell functions as proliferation, migration, differentiation, and apoptosis. Their activity is controlled by a set of 13 extracellular ligands which bind to the ectodomain.The hEGFR monomer comprises an ectodomain with four subdomains (I–IV), a single transmembrane helix, the juxtamembrane region, a tyrosine kinase domain, and the C-terminal regulatory region. The active receptor is usually considered to be the dimer, with both homo and hetero dimers occurring within the ErbB family. Structural information comes from crystallography of individual domains,13The exact mechanism of ligand binding is unknown but in principal two models are possible.Molecular dynamics (MD) simulations provide a means to supplement experimental structural data with atomic-level information about protein dynamics. Such information is vital to understanding a flexible multiconformation protein such as hEGFR. In recent years, several MD studies of the ectodomain dimerGbind of biologically relevant ligands to proteins.Gbind through direct simulation of the binding event, but such methods are typically computationally expensive as many intermediate states need to be explicitly enumerated and/or multiple runs are required to achieve sufficient numerical convergence. The ectodomain consist of the first 614 residues of hEGFR, whereas the EGF ligand has 53 residues, and so even the monomeric receptor-ligand system is computationally challenging. Some end-point methods on the other hand may conveniently be carried out after the MD trajectory has been computed. Necessarily, these approaches are less reliable in terms of accuracy and absolute binding energies may not be quantitatively possible, but relative energies and ranking may be within reach.Gbind can then be estimated from combining these contributions computed for complex, receptor, and ligand.In addition to exploring the protein dynamics, simulation can also help to understand the energetics of ligand binding. Numerous methods have been devised to estimate free energies of binding ΔA large number of site-directed mutagenesis experiments on ligands have been carried out to gain a deeper understanding of the ligand's interactions with the receptor and the functional role of individual residues. Relevant to the current study are mutations of the EGF ligand at Leu47,In this study, we investigate the dynamics and ligand binding of the monomeric hEGFR ectodomain via MD simulation. Experimental insights into the structural transitions of the monomer have come from crystal structures,The work here lays the foundation for understanding ligand binding in other members of the ErbB family, and in the yet larger dimeric system. It may help to rationalize the effects of dimer asymmetry on ligand binding, seen in Drosophila EGFR17Three independent simulations of the hEGFR ectodomain in the tethered conformation were carried out with: (1) the EGF ligand bound to domain I (bI), 2) the EGF ligand bound to domain III (bIII), and (3) the ligand removed from the receptor (ub). The starting structure for bI was taken from PDBid 1NQL, the EGF M solution of NaCl. Thus, 177 Cl− and 183 Na+ ions were added for the bI, 177 Cl− and 184 Na+ ions were added for the bIII, and 180 Cl− and 182 Na+ ions were added for the ub simulations, respectively. The total number of atoms was about 395,000 for each simulation system leaving a water buffer of at least 30 Å between the protein and the closest box face.Protonation states of titratable residues at pH 7 were determined with PROPKA−1. The pressure was controlled by a Nosé–Hoover Langevin barostatAll heavy atoms of the receptor and the ligand were subjected to positional restraints of 5 kcal/mol/Å. Each system was energy minimized for 1000 steps to relax atom positions and remove bad contacts from the setup procedure. Next, the simulation boxes were heated incrementally from 25 K to the final temperature of 300 K in steps of 1000 over a period of 10,000 steps and kept at the final temperature for an additional 10,000 steps. Over a further 25,000 steps a constant pressure of 1 bar was applied to adjust the box size and the density. The temperature was controlled with a Langevin thermostat and a coupling coefficient of 1 psThe total unrestrained simulation times were 150 ns for each of the three systems. All MD simulations were carried out at a constant temperature of 300 K and a constant pressure of 1 bar. The Langevin barostat decay time was set to 100 fs and the oscillation period to 200 fs. The simulations were run with NAMD22G is calculated from the individual free energies of the three species as G is computed as an average over the trajectory in the following way: EMM is the molecular mechanical energy for the chosen force field including internal and nonbonding degrees of freedom, GPBSA is the solvation free energy with the polar contributions computed through the Poisson–Boltzmann equation and the nonpolar part estimated from the scaled and shifted molecular surface, T is the simulation temperature, and SMM is the conformational entropy of the solute.Erot/tr is the energy due to the six rotational and translational degrees of freedom and in the classical limit is G, this term cancels, and is often neglected.Binding free energies were estimated by means of the MM–PBSA method. G by sampling all three species from a single simulation of the complex. The assumption is that the conformations sampled for protein and peptide in the complex are representative for the unbound state. In the next section, we will discuss how far this is true for the systems studied here.In principle, three independent simulations must be carried out to calculate each term in Eq. 1. In some situations, it may be possible to obtain a reasonable estimate for ΔG for the Ras-Raf complex (a standard test system), and comparing to the Amber results (see Supporting Information). The force field energies EMM were calculated without nonbonded cutoffs. The nonpolar contributions to GPBSA were evaluated with CHARMM's surface module by computing them as Gnonpolar = γA + β γ and β were 0.00542 kcal/ÅA is the molecular surface in Ået al.The MM–PBSA calculations have been carried out with CHARMMα atoms were calculated relative to the structures from the initial minimization step for the four subdomains of the receptor ectodomain. For each simulation, the largest deviations are found for Subdomain II  associated with a flexing along the length of this subdomain. This is in contrast to the soluble ectodomain dimer in which Subdomain II is stabilized by the dimer interface, and Subdomain IV is more flexible.22The root mean square deviations (RMSD) of CRelative motions of the subdomains were analyzed by computing RMSDs with respect to a fixed subdomain I . Although Subdomain II maintains its position relative to Subdomain I, Subdomains III and IV fluctuate strongly, and usually in a correlated manner. The largest fluctuation is seen for the bIII simulation with a relative displacement of 70 Å reached after 106 ns of the simulation. This snapshot is compared in V1 and V2 defining the orientations of Subdomains I and III , effects of intramolecular motion are kept to a minimum.Analysis of RMSDs suggests a highly flexible hEGFR monomer, with Subdomains III and IV moving relative to Subdomain I, at least partly driven by flexing of Subdomain II. To obtain a clearer picture, we have computed angle distributions between two vectors  III see . As refeAs et al.We have also calculated the maximum curvature of a quadratic function fitted through the center of masses of the seven disulfide bond modules of Subdomain II following the procedure of Du −1 for bI and at 0.25 Å−1 for bIII). The unbound monomer shows a wider fluctuation of the curvature, and the distribution covers the range of the two other peaks. From the simulation of the soluble ectodomain dimer,−1 and 0.34 Å−1. For comparison, the three available crystal structures of the tethered ectodomain show maximum curvatures of 0.36 Å−1 (1NQL), 0.36 Å−1 (3QWQ), and 0.19 Å−1 (1YY9).Rg. Time courses of Rg are presented in For each simulation, the gyration tensor has been calculated for the receptor  as a function of simulation time. These tensors are highly anisotropic, reflecting the nonglobular shape of the ectodomain monomer; the average ratios of the eigenvalues are 833/311/76 ÅRg compares well with the experimental value of 35.4 ± 0.11 Å obtained from SAXS.9GlcNAc2) attached to known and presumed glycosylation sites can add about 3 Å to the Rg when positioned approximately perpendicular on the molecular surface.The average Rg values computed for the individual monomers in the dimer simulationDmax.The P(r) obtained from the simulation of the unbound monomer (last 120 ns) with curves calculated directly from the receptor component of the crystal structures 1NQLer last 10 ns withPrincipal component analysis (PCA) has been carried out to gain further insights into the dynamics of the three hEGFR simulations. As large proteins are notoriously slow to converge;Projecting the trajectory against the first two PCA modes  for each simulation further confirms different dynamics in the three systems. For example, the bI simulation displays possible energy barriers in the 2D trajectory, while phase space is populated more densely in the other simulations. However, the probabilities obtained from the projections of the trajectory onto the first five eigenvectors  indicate strong non-Gaussian distributions in the lowest modes. The largest amplitude motions cannot be expected to be harmonic but the rather broad distribution suggests sampling issues. It would therefore be misleading to attach too much significance to the motions implied by the PCA modes.G of the ligand EGF to its monomeric receptor hEGFR has been estimated with the MM–PBSA method.G between EGF bound to Domain I and EGF bound to Domain III. This may suggest where  the ligand preferentially binds to the monomeric receptor, as well as identify the relative contributions of the two interfaces in the ligated dimer. Absolute ΔGs are difficult to obtainThe binding free energy ΔKd of about 450 nm.The crystal structure 1NQL was found to bind the ligand weakly at domain I at pH 5.G is sensitive to the grid resolution used, with a finer grid leading to a more negative ΔG in most cases. Although there is no obvious convergence with respect to the grid resolution, finer grids lead to smaller fluctuations over the trajectory  and are assumed to be more accurate.In TableG values. Moreover, the two approaches suggest opposite binding preferences, with the ligand preferring Domain I with the single-trajectory approach and Domain III with the three trajectories approach. The high flexibility of the ectodomain and the differences seen between the bound and unbound simulations indicate that representative receptor or ligand conformations cannot realistically be taken from the trajectory of the complex. This can be quantified with the reorganization free energyGreorg, noS which is the free energy difference of a particular component in the complex and in an unbound state. We find  5.9 and 12.3 kcal/mol for the ligand, and −0.4 and −30.2 kcal/mol for the receptor in the bI and bIII simulations, respectively. We thus conclude that the single-trajectory approach is not valid for the system considered here. Finally, ΔGs were calculated only for the three trajectories approach.Comparing the single with the three trajectories approach, we find that they give very different ΔSv has been estimated through normal mode analysis. However, obtaining entropies from the very large hEGFR–ligand complex  is not only very time and memory consuming but it is also difficult to calculate reliable minimized structures. Therefore, we followed a previous suggestionThe vibrational entropy ΔSv is similar in magnitude for both Domain I and Domain III binding. As the ligand is also in close contact to Domains II and III in the Domain I binding case, we included also parts of Domain II and III (residues 261–375) in the entropy calculation and computed a new ΔSv which was almost the same  as in the smaller system . We conclude that the change in vibrational entropy has only a minor effect on the final ΔGtot. In many MM–PBSA studies, it is in fact neglected from the outset  changes in ΔEele and ΔGPB. The I23A mutation is close to the wild type in Domain III binding, but ΔGnoS is slightly less favorable for Domain I binding. As for L47A, this difference comes largely from a change in ΔEvdw. The K28A mutation has only a small effect on both Domain I and Domain III binding. As for R41A, the electrostatic contributions vary strongly from the wild type, but in this case largely cancel out.The L47A and R41A mutations have little effect on Domain I binding, but are unfavorable for Domain III binding as expected. Comparing the component energies with those of the wild-type Table, the difGnoS values calculated for these mutants are smaller than the standard errors of the individual ΔGnoS. On the other hand, we are reassured that the changes in the individual components make chemical sense, and that the control calculation for A25A gives essentially zero .It must be noted that the ΔΔMolecular simulation of the tethered hEGFR monomer provides a detailed picture of the dynamics of both the unbound state (ub) and bound states where the EGF ligand binds to either domain I (bI) or domain III (bIII). In all three cases, the monomer remains in the tethered conformation for the duration of the simulation. Thus, any major structural rearrangement is likely to occur on a longer timescale than the 150 ns probed by our atomistic simulation. This is in agreement with a recent simulation study of the ErbB4 ectodomain monomer, with the ligand NRG1β bound to Domain I, which showed a transition to a partially extended state at around 400 ns after breaking of the Domain II/Domain IV tether.10et al.Nevertheless, our simulations do reveal that the tethered monomer is extremely flexible as demonstrated by, for example, angle  and maxiDimerization has a strong effect on both intradomain and interdomain motions generally leading to a globally less dynamic system. In previous work,et al.From a study of tryptophan fluorescence, Kozer et al.A central question for growth factor binding is whether these ligands bind to the tethered conformation, and if so whether there is a preference for the Domain I or the Domain III binding site. In their simulation of the tethered ErbB4 ectodomain, Du We therefore consider both Domain I and Domain III binding to remain potentially relevant. Ligand binding in both systems (bI and bIII) appears stable over the 150 ns of simulation. Nevertheless, we also see clear differences between these simulations, suggesting that the location of ligand binding has an effect on the dynamics of the monomer. et al.et al. may be applicable in this case as well.Conversely, binding of the ligand to Domain I leads to larger fluctuations in Domain II than when the ligand binds to Domain III . Du et al.et al.Application of the MM–PBSA method gives some insight into the free energy of ligand binding. The highly dynamical hEGFR monomers rule out the use of the single-trajectory approach in which it is assumed that representative conformations for all three of complex, receptor, and ligand can be obtained from a single simulation of the complex. The large conformational changes seen over tens of ns also support the use of relatively long simulation times . An analysis of the correlation between snapshots used in the MM–PBSA calculation shows correlation times up to 10 ns for some components. For comparison, Luo Both Domain I and Domain III of hEGFR contribute to ligand binding in the extended conformation.2et al.Gbind for binding of EGF to dimeric EGFR of −102 kcal/mol. Entropy terms are not included, so this is to be compared to the values of −76 and −87 kcal/mol taken from TableIn a recent comparison of different EGFR ligands, Sanders IC50 values).The changes in binding free energy we have found for selected ligand mutants Table are mostOur results for key mutations thus make some sense in terms of the known structural interactions. They confirm the experimental affinity measurements and suggest that specific ligand interactions with Domain III are vital for ligand binding. Although ligand binding to Domain I is predicted to have a similar strength overall, partly due to backbone hydrogen bonding, specific side chain interactions appear to be less important.In general, the current results may be limited by the simplicity of the structural model. First, we have not modeled the membrane environment, in contrast to our earlier study10In summary, our calculations suggest that the EGF ligand can bind to the tethered monomer, and that binding has an effect on the dynamics of this flexible protein. There are clear differences between Domain I and Domain III binding of the ligand, with some hints that Domain III binding produces more significant changes in the average conformation. Free energy estimates also show a slight preference for ligand binding to Domain III. Although we find that ligand binding to Domain I is also possible, the evidence of a role for specific ligand residues is not so strong. These two binding interfaces are of course also relevant to ligand binding in the extended dimer, where both contribute to the overall binding. If asymmetric dimers


Lactococcus lactis strains is the most prominent member. Nisin has multiple mode of actions of which binding to the cell wall precursor lipid II and subsequent insertion into the bacterial membrane to form pores are the most effective. The nisin producing strains express the lipoprotein NisI to prevent a suicidal effect. NisI binds nisin, inducing a reversible cell clustering to prevent nisin from reaching the membrane. Importantly NisI does not modify nisin and releases it as soon as the concentration in the media drops below a certain level. The human pathogen Streptococcus agalactiae is naturally resistant against nisin by expressing a resistance protein called SaNSR, which is a nisin degrading enzyme. By cleaving off the last six amino acids of nisin, its effectiveness is 100-fold reduced. This cleavage reaction appears to be specific for nisin since SaNSR recognizes the C-terminal located lanthionine rings. Recently, the structures of both NisI and SaNSR were determined by NMR and X-ray crystallography, respectively. Furthermore, for both proteins the binding site for nisin was determined. Within this review, the structures of both proteins and their different defense mechanisms are described.Lantibiotics are potential alternatives to antibiotics because of their broad-range killing spectrum. The producer strain is immune against its own synthesized lantibiotic via the expression of two proteins LanI and LanFEG. Recently, gene operons are found in mainly human pathogenic strains, which confer resistance against lantibiotics. Of all the lantibiotics discovered till date, nisin produced by some  Since the beginning of the last century, the heterogeneous group of bacteriocins have become an interesting research topic for various applications like food preservatives or pharmaceutical purposes as antibiotic alternatives . BacteriWithin the group of bacteriocins a large family exists, which are called lantibiotics . These aLactococcus lactis strains which is linked to the potential biomedical application against bacterial mastitis, treatment of methicillin-resistant Staphylococcus aureus (MRSA) and enterococcal infections. Other examples are the lantibiotics Gallidermin/Epidermin, which are associated with acne, eczema, follicultis, impetigo as possible compound for treatment , transport  across the cellular membrane are with a few exceptions encoded on a single gene cluster (lanK and lanR) is present on this operon, which up-regulates the expression of these genes  as well as for its biosynthesis and modification ( cluster . Furtherse genes .lanI and lanFEG) encode a lantibiotic specific (auto-)immunity system. Interestingly, although lantibiotics are grouped in different classes based on their size and specific activities . When these proteins are expressed, the producing strains survives a high level of immunity against nisin, of up to ~750 nM nisin -immunity system is conserved and present in al most all lantibiotic producing strain. For example, the subtilin producing d SpaFEG ; the epid EpiFEG ; the galses PepI . More exses PepI .lctGEFlcrXRS in Streptococcus mutans conferring resistance against nisin, nukacin ISK-I and lacticin 481 . The genes encoded on this operon are called nsr (encoding for nisin resistance protein) and nsrFP (encoding for an ABC transporter), which are probably auto-regulated by a two-component system formed by nsrR and nsrK immunity protein NisI from . lactis  as well e SaNSR;  have beeL. lactis strains, the LanI immunity protein is called NisI, which is a 27.8 kDa in size comprising of 245 amino acid residues (Table 1). The sequence contains a signal peptide which is cleaved off after secretion followed by a site for lipidation . Various studies have shown the importance of the C-terminus of NisI for its activity, especially the last 22 amino acids  are crucial for its binding to lipid II , which iS. agalactiae is the nisin resistance protein (SaNSR), which contains 320 amino acids and has a molecular weight of 36.2 kDa (Table 1). SaNSR has a N-terminus hydrophobic region predicted to encode a transmembrane helix . SaNSR belongs to the S41 family of peptidases and contains a highly conserved TASSAEM sequence motif, which harbors the catalytically active serine residue at position 236  completely abolished the resistance, clearly indicating the importance of the last ring as well as the C-terminal tail of nisin for recognition by SaNSR. This is in contrast to the specificity of NisI. Nisin shares a high sequence similarity of around 63% with subtilin from B. subtilis, and like nisin the lantibiotic subtilomycin also harbors five lanthionine-based rings . The N-terminal part (1–111 residues) is connected to the C-terminal domain (120–226) via a flexible linker (112–119). Interestingly and rather unusual is that both domains adopt a similar unique fold, which has been previously observed for SpaI from B. subtilis, the immunity protein against subtilin . Therefore, this domain is thought to be localized at the membrane surface. On the contrary, the C-terminal domain of NisI does not bind to lipids. Instead this C-terminal domain binds nisin as observed in NMR titration experiments. This is inline with the previous observations that the C-terminally located last 22 amino acids are important for the functioning of NisI in vivo. Although structurally similar, both domains of NisI differ in their surface properties. While the surface of the N-terminal domain of NisI is highly positively charged and interacts with membranes, the C-terminal domain has negatively charged surface with hydrophobic patches and is able to bind nisin , thereby modulating the membrane affinity of the N-terminal domain of NisI by shielding its membrane binding surface . NisI has not been shown to interact with other lantibiotics and displays rather high substrate specificity. A protein consisting of the N-terminal SpaI domain fused to the C-terminal domain of NisI, however, displays immunity against nisin  was solved using X-ray crystallography and consists of eleven α-helices and eleven β-strands , form helices α1-α3. This domain ends in a triple glycine motif before entering the protease cap domain. This protease cap domain consists of helix α4 and a β-hairpin structure formed by two strands and forms a lid-like structure above the tunnel. The last domain called the protease core is formed by six strands βb-βg and five helices α5-α9 and adopts a ‘protease fold’ domain as observed in other S41 peptidases . The protease core domain also contains the highly conserved TASSAEM region that harbors the previously identified catalytically active serine at position 236 (The crystal structure of nisin resistance protein from ptidases . Togethetion 236 .SaNSR consists of a catalytic dyad formed by residues Ser236 (The active center of s Ser236 , which is Ser236  and alsos Ser236 .SaNSR. Additionally, the residues forming the hydrophobic interactions for proper orientation of rings D and E of nisin are embedded in the protease core domain within or on the outside of the tunnel that is situated in the middle of SaNSR protein.Unfortunately, the crystal structure lacks the substrate nisin. Instead a peptide called N-pep, belonging to symmetry-related molecule was bound within the tunnel. This information was used for molecular dynamic simulation studies to determine the nisin-binding site. It was observed that nisin is stably bound in the tunnel formed in between the domains of SaNSR/nisin complex demonstrates the significance of C-terminally located lanthionine rings D and E of nisin for substrate specificity (SaNSR did not recognize nisin variants lacking the last or the last two rings.The model of cificity . The impL. lactis cells. Immunity is thereby provided without harming or modifying the own lantibiotic produced.The expression of NisI and NSR reduce the activity of nisin. In the nisin producing strains, the immunity protein NisI solely binds nisin thereby reducing the amount of nisin reaching the lipid II target molecule in the membrane. To achieve this NisI not only binds to nisin but also induces a “shielding mechanism” of the In contrast, NSR present in nisin non-producing strains cleaves nisin in two parts, thus, reducing the ability of nisin to form pores in the membrane.NisI and NSR, however, represent the first line of defense and within both immunity and the resistance operons, an additional protein system is also encoded. In case of the immunity system, it is the ABC transporter NisFEG and for the resistance system, it is NsrFP. It has been shown that NisFEG and NisI act cooperatively. However, for the nsr system such a cooperative mechanism has not been detected so far and it has to be further investigated whether these resistance proteins are also able to act together in their battle against the lantibiotic nisin. Although, lantibiotics are considered to be powerfull biological antimicrobial compounds already resistance mechanisms are present in some human pathogenic strains. This hampers the usage of lantibiotics for medical purposes. A detailed knowledge about these resistance mechanisms would pave a way to bypass these inherently present systems.SK, ML, and SS wrote the manuscript. SK, ML prepared the figures. SK, ML, and SS finalized 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.


Drosophila third chromosome, the locus became known of as the bithorax complex (BX-C). One of the key findings of Lewis’ article was that it revealed for the first time, to a wide scientific audience, that there was a remarkable correlation between the order of the segment-specific mutations along the chromosome and the order of the segments they affected along the AP axis. In Ed Lewis’ eyes, the mutants he discovered affected “segment-specific functions” that were sequentially activated along the chromosome as one moves from anterior to posterior along the body axis (the colinearity concept now cited in elementary biology textbooks). The nature of the “segment-specific functions” started to become clear when the BX-C was cloned through the pioneering chromosomal walk initiated in the mid 1980s by the Hogness and Bender laboratories . Through this molecular biology effort, and along with genetic characterizations performed by Gines Morata’s group in Madrid  and Robert Whittle’s in Sussex , it soon became clear that the whole BX-C encoded only three protein-coding genes . Later, immunostaining against the Ubx protein hinted that the segment-specific functions could, in fact, be cis-regulatory elements regulating the expression of the three protein-coding genes. In 1987, Peifer, Karch, and Bender proposed a comprehensive model of the functioning of the BX-C, in which the “segment-specific functions” appear as segment-specific enhancers regulating, Ubx, abd-A, or Abd-B . Key to their model was that the segmental address of these enhancers was not an inherent ability of the enhancers themselves, but was determined by the chromosomal location in which they lay. In their view, the sequential activation of the segment-specific functions resulted from the sequential opening of chromatin domains along the chromosome as one moves from anterior to posterior. This model soon became known of as the open for business model. While the open for business model is quite easy to visualize at a conceptual level, molecular evidence to validate this model has been missing for almost 30 years. The recent publication describing the outstanding, joint effort from the Bender and Kingston laboratories now provides the missing proof to support this model . The purpose of this article is to review the open for business model and take the reader through the genetic arguments that led to its elaboration.After nearly 30 years of effort, Ed Lewis published his 1978 landmark paper in which he described the analysis of a series of mutations that affect the identity of the segments that form along the anterior-posterior (AP) axis of the fly (Lewis 1978). The mutations behaved in a non-canonical fashion in complementation tests, forming what Ed Lewis called a “pseudo-allelic” series. Because of this, he never thought that the mutations represented segment-specific genes. As all of these mutations were grouped to a particular area of the  Drosophila embryos and larvae harbor a head, three thoracic segments (T1–T3) and eight abdominal segments , respectively. Typically, loss-of-function mutations in the BX-C result in the transformation of a given segment into a copy of the segment directly anterior to it. The fact that mutations in individual “segment-specific functions” always cause transformations toward the segment immediately anterior to them and not toward the ground state (T2) indicates that everything required for the identity of the more anterior segments still functions in the more posterior segments. Thus, Ed Lewis proposed that the segment-specific functions act in an additive fashion: once they are turned on in the segment they specify, they remain active in the more posterior segments. Lewis synthesized these findings into two rules for BX-C regulation: “… a [segment-specific function] derepressed in one segment is derepressed in all segments posterior thereto…” and “the more posterior a segment… the greater the number of BX-C [segment-specific functions] that are in a derepressed state”  associated with embryonic lethality also exist within the BX-C. They cause the transformation of a group of segments into a more anterior segment (Lewis Ubx (Ultrabithorax) mutant embryos have their T3 and A1 segments transformed into T2, as if both the abx/bx and bxd/pbx segment-specific functions were inactivated in Ubx alleles. In agreement with Ed Lewis’ observations, Ubx mutations fail to complement abx, bx, bxd, or pbx alleles. This lack of complementation is contrasted by the observation that heterozygous flies, with bx or abx mutations on one chromosome and bxd or pbx mutations on the other, looked normal. Ed Lewis proposed the term “pseudo-allelism” to describe these conflicting observations.Three classes of mutations , the phenomenon of pseudo-allelism was finally explained. In situ hybridization and antibodies generated against these proteins allowed the determination of their expression patterns , iab-2 though iab-4 regulate abd-A (blueish). Finally, iab-5 through iab-8 regulate Abd-B  are made up of reiterated units along the AP axis. Each unit of expression is roughly equivalent to one segment in length, but slightly shifted relative to the morphological body segments that appear during mid embryogenesis. These units are known as parasegments (Martinez-Arias and Lawrence It should be noted that the embryonic expression patterns of cis-regulatory elements clarified the genetic schema that Ed Lewis had been working on for decades. Due to the size of the regulatory regions in question (from 10 to 60 kb), multiple enhancers were hypothesized to exist within each regulatory domain. This was supported by some of the early work using bxd mutations. There are many bxd mutations caused by chromosome breaks. These mutations make up an allelic series with differing strengths of transformation (lowering the Ubx expression in PS6). It turns out that mutations with breakpoints closer to the Ubx promoter cause stronger transformations, while mutations with breakpoints further away from the promoter cause weaker transformations  were exchanged between different domains, were able to consolidate the model by entirely fulfilling the predictions made by the open for business model.The idea that BX-C enhancers might be regulated coordinately through chromatin domains primarily came from the analysis of dominant gain-of-function (GOF) mutations, where a given segment develops like a copy of the segment that lies immediately posterior to it. Peifer et al  focused Cbx1 is a gain-of function mutation that transforms the posterior half of the wing (T2) into the posterior half of the haltere (T3). Fine structure mapping led Lewis to discover that the original Cbx1 chromosome contained two, separable mutations. One of them was associated with the dominant GOF phenotype and the other one was associated with a recessive phenotype. The recessive mutation was named postbithorax1 (pbx1) in accordance with the transformation of the posterior haltere into the posterior wing  abolishes Ubx expression in the posterior half of the haltere imaginal disc . In PS5, the abx/bx DNA domain opens up, enabling the A and B enhancers to activate Ubx in the A and B cells of PS5. As the domain remains open in more posterior parasegments , the A and B enhancers remain active as well in those more posterior parasegments  opens up, enabling the C and D enhancers to activate Ubx in different cell types  was another GOF mutation that had been localized on the DNA map  but differing at their proximal breakpoints .Drosophila was accomplished using P-element transposons as vectors. Insertion of the transgenic constructs was more or less random. Because of the promiscuous nature of enhancers and other chromatin regulatory elements (such as Polycomb-Response-Elements and heterochromatin), expression from the transgenes was often influenced by the neighboring chromosomal environment, a phenomenon known as position-effect (PE). The phenomenon of PE inspired Cahir O’Kane and Walter Gehring to engineer a lacZ-based reporter transposon aimed at trapping the activity of regulatory elements in the vicinity of the insertion site of a transposon  is shifted one parasegment posterior, in PS6. These three insertions map to the region previously assigned to the bxd/pbx region that controls Ubx expression in PS6. Once again, the tissue distribution and intensities of lacZ expression varies between the three lines but the anterior border of each starts at PS6.With the help of the By examining a large number of enhancer trap lines in the BX-C, Bender and Hudson  made thriab phenotypes to draw the extent of the regulatory domains. If, as mentioned above, boundary elements limit the extent of each domain, then we can infer the position of other boundary elements using this figure. P-elements in close proximity but expressed in different parasegments, give the most precise information for mapping boundaries. This is the case, for example, for the boundary separating the abx/bx domain (orange) from the bxd/pbx domain (red). This region contains the Ubx promoter. Similarly, the putative boundary (Fab-3) separating iab-4 from iab-5 can be localized accurately between the 2 transposons inserted on each side of it and that are expressed in PS9 and PS10, respectively.In Fig. Fub, Fab-2, Fab-3, Fab-4, Mcp, and Fab-8 are all highlighted by the presence of CTCF binding sites , cell-type-specific enhancers, silencers and insulators  abolishes iab-6 function, even though 18 kb of iab-6 sequences remains. This results in an A6 to A5 transformation, as the iab-5 domain is active in parasegments posterior to A5/PS10 . This caused a A5 to A6 transformation, as seen in Fig. open for business model.If initiator elements truly perform this function, then there are certain predictions that can be made. First, the removal of an initiator from a domain should completely abolish the activity of the whole domain. And second, switching an initiator from one domain for the initiator of a more anterior domain should cause activation of the more posterior domain in the parasegment specified by the more anterior initiator. We have directly addressed both of these predictions using a technique that coupled homologous recombination and ΦC31 site-specific integration to target the S10 Fig. . Next, wopen in parasegments where they should be active. Thus far, we have described the evidence supporting a parasegment-specific activation of chromosomal domains and how these domains sense a parasegmental address. What we have not described is what it means to be active or open. To do this, we must first introduce the last group of players in this puzzle: the Polycomb-Group (Pc-G) and trithorax-Group (trx-G) genes.Since its conception, the open-for-business model always proposed that enhancer domains somehow cis-regulatory domain to determine their ultimate expression pattern along the AP axis  and are thought to maintain the active or inactive state of each domain by modifying its chromatin structure  with distinct chromatin modifying activities. While the PRC1 complex seems to ubiquitylate histone H2A  experiments performed with Drosophila tissue culture cells , a mark associated with active genes . After tissue disruption, specific nuclei are sorted by FACS or by affinity purification on streptavidin columns .In 2010, Deal and Henikoff developed a system called INTACT to bypass this problem for ChIP by sorting specific populations of abx/bx domain, it would express the Gal4 activator from PS5 until the posterior end of the embryo. Meanwhile, a Gal4 inserted into the bxd/pbx domain would express from PS6 until the posterior end of the embryo. What Bender’s group did, was to create double insert lines where a Gal4 transgene was inserted into one cis-regulatory domain and a Gal80 expressing transgene  was inserted into the next more posterior domain abx/bx doopening, predicted by the domain model (Fig. abx/bx domain (Fig. abx/bx domain and the bxd/pbx domain (controlling Ubx in PS6; Fig. abx/bx domain until the iab-2 domain (Fig. Using these lines, nuclei were isolated from individual parasegments for ChIP-seq experiments. H3K27me3 ChIP on these samples confirmed the remarkable domain del Fig. . Nuclei ain Fig. . Nuclei ain Fig.  (Bowman ain Fig. .open for business model, the work of Bowman et al. confirmed a number of important details. First was the precision in which a domain was activated. In their experiment, Bowman et al. found that the retracting H3K27me3 signal essential went from one point on the chromosome to another, without any sloping intermediate zones. ChIP experiments directed against the boundary protein CTCF confirmed that these places of abrupt transition coincided with expected boundary elements. Next, in the absence of H3K27me3, H3K27 acetylation marks were found. As H3K27Ac is a mark associated with active chromatin, it seems like domains that are not silenced become active, or open. Lastly, these experiments showed that even in parasegments where a given homeotic gene is not the primary segment-determining gene, domains controlling more anterior homeotic genes are still active. This was seen in the PS7 ChIP experiments where the abx/bx and bxd/pbx domains remained active, even though it is iab-2 controlling abd-A expression that is the primary determinant of PS7 identity.With regards to the To spatially regulate the activation of homeotic genes along the AP axis, the open for business model proposes that enhancer containing domains open sequentially along the chromosome as one follows the anterior-posterior axis of the fly Fig. . At firsAlthough many questions still remain about the mechanisms by which each of the elements perform their function, the open for business model has been, for the most part, validated. As part of the community of researchers who contributed to the creation and validation of this model, this has been quite comforting. In our lab, we have a term for the experience of making a startling prediction that proves to be true. We call such instances, “Walter Gehring moments”, in honor of the numerous instances where Walter Gehring and his colleagues made incredible predictions that, through the elegant fusion of genetics and molecular biology, were proven to be true. For this reason, it seems quite fitting that this review to be placed in a series of articles dedicated to his memory.


Saccharomyces cerevisiae Mex67:Mtr2 also contributes to RNA binding. Moreover, the 3.3 Å resolution crystal structure of the Mex67ΔUBA:Mtr2 complex, supplemented with small angle X-ray scattering data, indicated that the LRR domain has a defined spatial relationship to the Mex67NTF2L:Mtr2 region. Conversely, the RRM domain and especially the UBA domain are more mobile. The conformation assumed by the LRR and NTF2-like domains results in clusters of positively-charged residues on each becoming arranged to form a continuous interface for binding RNA on the opposite side of the complex to the region that interacts with FG-nucleoporins to facilitate passage through nuclear pores.The Mex67:Mtr2 complex is the principal yeast nuclear export factor for bulk mRNA and also contributes to ribosomal subunit export. Mex67 is a modular protein constructed from four domains  that have been thought to be joined by flexible linkers like beads on a string, with the RRM and LRR domains binding RNAs and the NTF2-like and UBA domains binding FG-nucleoporins to facilitate movement through nuclear pores. Here, we show that the NTF2-like domain from  Saccharomyces cerevisiae. Mex67 is a member of the NXF family of proteins and has conserved homologs through eukaryotes from yeast to humans. Although sequence conservation is poor between S. cerevisiae Mex67 and Homo sapiens NXF1, they do show functional complementarity, in that over-expression of NXF1:NXT1 can rescue an otherwise lethal Mex67:Mtr2 deletion strain in S. cerevisiae (The Mex67:Mtr2 complex (TAP:p15 or NXF1:NXT1 in metazoans) is the principal mRNA export factor in revisiae .H. sapiens NXF1 in complex with a fragment of the constitutive transport element (CTE-B), a viral RNA motif, confirmed that these two-N terminal domains are involved in binding cargo  –5. A cryng cargo . Crystalng cargo . The Mexrevisiae ,10.S. cerevisiae Mex67:Mtr2 complex using X-ray crystallography and small angle X-ray scattering (SAXS) that confirms the presence of the RRM and LRR domains as well as identifying a previously uncharacterized spatial relationship between the LRR and NTF2L domains that derives from interactions between Mtr2 and the linker between the LRR and NTF2L domains. We also show that RNA binding by the complex requires a contribution from the NTF2L domain in addition to the RRM and LRR domains. The alignment of the LRR and NTF2-like domains functions to generate an extensive positively-charged surface on the molecule that facilitates RNA binding and which positions the mRNA cargo on the opposite side of the nuclear export complex to that on which is located the sites that interact with FG-nucleoporins to mediate passage through nuclear pores.Although high-resolution crystal structures of the individual NTF2L:Mtr2 region and UBA domains of Mex67:Mtr2 are available, the extent of sequence similarity to other NXF1 family members shown by the RRM domain is low and this has raised the possibility that Mex67 may differ from its metazoan counterparts in this region . Moreove6 tagged constructs of Mex67:Mtr2. Domain boundaries were chosen based on crystal structures, resulting in the following constructs: Mex67 , Mex67ΔUBA (residues 1–487), Mex67LRR-NTF2L (residues 101–487), Mex67NTF2L (residues 264–487) and Mex67RRM-LRR (residues 2–262). All proteins were expressed in Escherichiacoli BL21-CodonPlus(DE3)-RIL cells by IPTG induction at 18°C for 16 h. All purification steps and manipulations were conducted at 4°C unless stated otherwise.All constructs were cloned into the pETDuet-1 vector where Mex67 was cloned into the first multiple cloning site (MCS) and Mtr2 was cloned into the second MCS to generate various TEV cleavable His6 tag. The sample was then diluted with 50 mM HEPES-NaOH pH 8.0 to reduce the NaCl concentration to ∼150 mM and purified with heparin affinity chromatography, using a 100 mM to 1 M NaCl gradient. The protein was then purified to homogeneity using a HiLoad 26/60 Superdex 200 column  in 20 mM HEPES-NaOH pH 8.0, 200 mM NaCl. Small aliquots of purified proteins were flash-frozen in liquid nitrogen in their final buffers and stored at -80°C until required.Harvested cell pellets were resuspended in 5 ml of 50 mM Tris-HCl pH 8.0, 500 mM NaCl, 20 mM imidazole pH 8.0 per gram of wet cell pellet, after which the cells were lysed by high-pressure cavitation using 2 passes through an EmulsiFlex-C3 (AVESTIN). The lysate was clarified by centrifugation, and the supernatant incubated with Ni-NTA agarose beads for 1 h. Non-specifically bound proteins were removed by washing with 50 mM Tris-HCl pH 8.0, 500 mM NaCl, 20 mM imidazole pH 8.0. Bound protein was eluted with 50 mM Tris-HCl pH 8.0, 500 mM NaCl, 250 mM imidazole pH 8.0 and incubated with TEV protease overnight to remove the HisΔUBA:Mtr2 were grown at 4°C by sitting-drop vapor diffusion in which 200 nl of purified protein was mixed with 200 nl of reservoir buffer . Crystals were obtained after 2–3 days and were harvested and cryo-cooled in mother liquor supplemented with 20% glycerol. X-ray diffraction data to a resolution of 3.3 Å were collected using beamline I04–1 at the Diamond Light Source , indexed and integrated using XDS (Chaetomium thermophilum Mex67 LRR domain (PDB ID: 4WP6) and S. cerevisiae Mex67NTF2L:Mtr2 complex (PDB ID: 1OF5) as search models generated an initial model that, after iterative cycles of rebuilding using COOT (Rwork of 21.6% (Rfree = 28.3%), excellent geometry, and a MolProbity score (th percentile). Detailed data collection and refinement statistics are given in Table Crystals of Mex67sing XDS , and refsing XDS ,14. Molesing XDS  and the ing COOT  and refiing COOT  generatety score ,19 of 1.s*Rg<1.3) were confirmed in all cases . Pair distance distribution functions of the particles P(r) and the maximum sizes Dmax were computed using GNOM (I(0) of the samples obtained using Guinier analysis by AUTORG (SAXS was performed using an on-line HPLC system (Viscotek) equipped with a Superdex 200 Increase 3.2/300 column  mounted on beamline BM29 at the European Synchrotron Radiation Facility . Data collection was conducted at 20°C, using a wavelength of 0.995 Å and a sample-to-detector distance of 1 m. Data were processed automatically by the on-line pipeline AUTOSUB  was mixed with serially diluted protein in 20 mM Tris pH 8.0, 50 mM NaCl. Polarization readings were measured in a PHERAstar Plus microplate reader using the FP 540–20 590–20/590–20 module. Data analysis was conducted in the Prism software package and curves were fitted to the standard quadratic equation:min is the baseline anisotropy, ΔmAUmax is the maximum anisotropy change observed, L is the ligand concentration and X is the protein concentration.The interaction of RNA with a range of Mex67 constructs was assessed using fluorescence anisotropy assays in which 10 nM of DY-547 labeled homopolymeric RNA (AΔUBA:Mtr2). These crystals had 1P2 symmetry and diffracted to 3.3 Å resolution using synchrotron radiation. Molecular replacement using the structure of the Mex67NTF2L:Mtr2 complex  indicated that there were four copies of the protein complex in the asymmetric unit, arranged as two pairs related by pseudo-translational symmetry  into this density, followed by rebuilding and refinement. After further cycles of refinement and rebuilding, a final model with an Rwork of 21.4% (Rfree = 28.4%) and excellent geometry was obtained  togethey Figure . AlthougOF5;  tog2Fo-Fc maps, continuous density corresponding to the linker between the RRM and LRR domains was not observed, which prevented a completely unambiguous identification of each chain. Although it had previously been unclear whether S. cerevisiae Mex67 contained an RRM domain because the N-terminal region is ∼100 residues shorter when compared to metazoan homologues, the crystal structure clearly shows that a RRM domain is present, even though the sequence similarity is low o-(G/A)i-Fo-Vi-Xo-(F/Y)i and RNP2 (L/I)i-(Y/F)o-(V/I)i-(G/N)o-(G/N)o-(L/M)i where the subscripted ‘o’ or ‘i’ signify whether the side chain is surface exposed or facing the core of the RRM fold. In the case of S. cerevisiae Mex67, the structurally equivalent residues deviated from the consensus so that the RNP1 region had the sequence G-Po-Lo-Vi-Io-G-Yo-Vi and RNP2 had Ii-So-Vi-Ro-No-Wi. The LRR domain showed the characteristic pattern of alternating α-helices and β-strands arranged to form a gently curving structure similar to that observed in the H. sapiens NXF1 . Althoue server ). The RRens NXF1 . There wΔUBA:Mtr2 complex in the asymmetric unit showed a conserved spatial arrangement of the LRR domain relative to the NTF2L domain. A dense network of interactions was observed between the region linking the LRR and NTF2L domains (the LRR-NTF2L linker) and specific regions of Mtr2. These additional interactions between Mex67 and Mtr2  appeared to contribute to the spatial arrangement of the LRR and NTF2L domains. In contrast to the defined spatial orientation of the LRR domain and the NTF2L:Mtr2 region, the position taken up by the RRM domain relative to the LRR domain appeared to be dictated primarily by lattice contacts and so, although a spatial arrangement between the RRM domain and the LRR domain was observed in the NXF1RRM-LRR:CTE-B RNA structure . This dex alone .H. sapiens NXF1NTF2L:NXT1 complex  produced the worst fit with χFoXS = 3.74 (data not shown).The SAXS profile collected for Mex67e Figure . Configu15, U15, C15 and G15 RNA polynucleotides, A15 and G15 RNA were bound more tightly than U15 and C15 RNA  together with Mtr2 were required . Intriguingly, the Mex67RRM-LRR construct, in which the NTF2L:Mtr2 region had been removed, had a much weaker affinity of 12 μM, even though it retained the domains previously thought to be primarily involved in binding RNA. Conversely, deletion of the RRM domain (resulting in the Mex67LRR-NTF2L:Mtr2 construct) produced only a marginal decrease in affinity for A15 RNA (340 nM) compared to the Mex67ΔUBA:Mtr2 construct (310 nM). The observation that the Mex67RRM-LRR construct showed comparatively weak affinity for A15 RNA whereas the Mex67LRR-NTF2L:Mtr2 showed only a marginal decrease indicated that the NTF2L domain in complex with Mtr2 itself might bind RNA and indeed was shown to bind A15 RNA with 860 nM affinity.The way in which the spatial arrangement of the LRR and NTF2L domains and Mtr2 generated a large positively-charged surface on Mex67 indicated that the NTF2L domain might contribute to RNA binding, even though previously this function had thought to reside in the RRM and LRR domains. Consistent with previous RNA binding studies  that introduced charged residues into a principally hydrophobic interface, and which reduced the affinity of Mex67ΔUBA:Mtr2 for A15 RNA from 310 nM (wild-type) to 820 nM (L263D + M265D). This reduced affinity for A15 RNA was comparable to that seen with the NTF2L:Mtr2 region alone (that is with the RRM and LRR domains deleted) where an affinity of 860 nM was observed. Ala and Tyr substitutions exhibited a reduced impact on the affinity (640 nM and 420 nM respectively) probably because they were less efficient at disrupting the interaction interface that was dominated by hydrophobic contacts in this region.The hypothesis that the spatial positioning of the LRR domain relative to NTF2L:Mtr2 contributed to a continuous RNA binding interface was tested by employing mutagenesis to impair the interaction between the domains Figure . Two resBoth crystallography and SAXS have identified a previously uncharacterized spatial organization within the Mex67:Mtr2 complex in which the LRR domain has a defined orientation relative to the NTF2L:Mtr2 region that is generated primarily by an interaction between Mtr2 and the LRR-NTF2L linker. A conserved interaction between the pre-α1 loop of the NTF2L domain and Mtr2 appears to be important for this domain organization, with additional interactions formed between the LRR domain and Mtr2. This spatial arrangement generates a large, positively-charged, surface on one side of the molecule in which the NTF2L domain augments the contributions made to RNA binding by the RRM and LRR domains.NTF2L:Mtr2 interact directly with RNA in the absence of the RRM and LRR domains, together with the results of the range of truncation mutants in which individual domains were removed  into the mainly hydrophobic interface between the linker and Mtr2 reduced the affinity of the Mex67ΔUBA:Mtr2 complex for RNA to levels comparable to a construct only including Mex67NTF2L:Mtr2 alone, consistent with the spatial arrangement of the LRR and NTF2L domains contributing to the RNA binding interface. These mutations were in regions of the Mex67:Mtr2 complex previously thought to be unrelated to RNA binding. Both Leu263 and Met265 reside on the negatively charged side of the structure, where the FG-nucleoporin binding site is also located , the position of the RRM domain appeared to be more variable  and did not correspond to that observed in the crystal structure of CTE-RNA complexed with the RRM-LRR region of ens NXF1 , furtherS. cerevisiae Mex67ΔUBA:Mtr2 complex has shown an unanticipated spatial arrangement of the LRR and NTF2L domains that generates a large positively-charged surface on one side of the complex that is ideally positioned to form a continuous RNA binding surface. Moreover, in addition to facilitating nuclear export through interactions with FG-nucleoporins, the NTF2L domain of Mex67 also makes an important contribution to the affinity of the complex for RNA in addition to the previously characterized binding activity of the RRM and LRR domains.In summary, the crystal structure of the ΔUBA:Mtr2 complex have been deposited in the Protein Data Bank with accession number 4WWU.Coordinates and structure factors for the 3.3 Å resolution Mex67Supplementary Data are available at NAR Online.


Summary: MoDPepInt (Modular Domain Peptide Interaction) is a new easy-to-use web server for the prediction of binding partners for modular protein domains. Currently, we offer models for SH2, SH3 and PDZ domains via the tools SH2PepInt, SH3PepInt and PDZPepInt, respectively. More specifically, our server offers predictions for 51 SH2 human domains and 69 SH3 human domains via single domain models, and predictions for 226 PDZ domains across several species, via 43 multidomain models. All models are based on support vector machines with different kernel functions ranging from polynomial, to Gaussian, to advanced graph kernels. In this way, we model non-linear interactions between amino acid residues. Results were validated on manually curated datasets achieving competitive performance against various state-of-the-art approaches.Availability and implementation: The MoDPepInt server is available under the URL http://modpepint.informatik.uni-freiburg.de/Contact: backofen@informatik.uni-freiburg.deSupplementary information: Supplementary data are available at Bioinformatics online. Protein–protein interactions are often mediated by modular protein domains in eukaryotes and play an essential role in diverse biological processes such as signal transduction, cellular growth and cell polarity . ModularTo this end, we used state-of-the-art machine learning approaches to build support vector machine models that can accurately predict binding specificity. We have collected into a unified web-based system called MoDPepInt (Modular Domain Peptide Interaction), three different tools: SH2PepInt, SH3PepInt and PDZPepInt for three different modular domains, namely, SH2, SH3 and PDZ . CurrentSupplementary Table S1).In summary, MoDPepInt unique features include (i) a domain-peptide prediction system for SH2, SH3 and PDZ in a single platform and (ii) the largest number of modeled domains (see All tools have a unified input format. Query sequences (up to a maximum number of 500) can be supplied either in a FASTA format or using UniProt database accession numbers. PDZPepInt offers predictions also for domains that are newly developed and/or not comprised in the original 226 PDZ domains: the unknown query domain should be supplied in FASTA format. Multiple query domain sequences can also be provided.phosphotyrosine filter that only considers those peptides whose tyrosine phosphorylation has already been experimentally verified and reported in PhosphoSitePlus database  residues of binding proteins. For this reason, in SH2PepInt, we offer a proline-rich filter that uses 31 regular expressions to select proline-rich peptides  balances the submitted jobs in parallel. MoDPepInt is implemented in C++, perl and shell scripting, with runtimes typically ranging in the order of few minutes.The output for all three tools is formatted as a downloadable table. We report for each domain–ligand protein interaction pair (i) the sequence ID, (ii) the ligand binding position, (iii) the ligand binding sequence and (iv) the ligand binding domains. See MoDPepInt collects three protein–protein interaction predictive models that can be efficiently tuned using data derived from various high-throughput experimental techniques and thus do not require structural information as in SH2PepInt uses polynomial kernels, and it is trained on additional high-confidence negatives obtained via semisupervised techniques.SH3PepInt uses graph kernels on a complex representation of both the peptide sequence and the aligned domains. The adoption of a graph-type representation allows the inclusion of the physico-chemical properties of amino acids, which increases the generalization capacity of the models. Furthermore, the method does not need any prior alignment of the peptides. This is a big advantage because poly-proline-rich peptides are hard to align.PDZPepInt uses Gaussian kernels, and it is trained on interaction data from additional highly related domains. Using pooling from closely related domains allows to leverage the limited information available for some domains and to extrapolate to unseen, but alignable, novel domains.Once trained, all models can be used to efficiently scan entire proteomes to identify novel interactions with typical runtimes of few minutes.Supplementary Information.In addition, we offer a meta-web server to be used in non-expert mode that submits the input simultaneously to all tools and displays a summary of the main results. For performance comparisons, details on the novelty of the methods and description of the meta-web server, see Funding: This work was funded by the Bundesministerium für Bildung und Forschung  and the Excellent Initiative of the German Federal and State Governments (EXC 294 to R.B.).Conflict of interest: none declared.