Activation loop dynamics are controlled by conformation-selective inhibitors of ERK2

Conformational selection by small molecules expands inhibitory possibilities for protein kinases. Nuclear magnetic resonance (NMR) measurements of the mitogen-activated protein (MAP) kinase ERK2 have shown that activation by dual phosphorylation induces global motions involving exchange between two states, L and R. We show that ERK inhibitors Vertex-11e and SCH772984 exploit the small energetic difference between L and R to shift the equilibrium in opposing directions. An X-ray structure of active 2P-ERK2 complexed with AMP-PNP reveals a shift in the Gly-rich loop along with domain closure to position the nucleotide in a more catalytically productive conformation relative to inactive 0P-ERK2:ATP. X-ray structures of 2P-ERK2 complexed with Vertex-11e or GDC-0994 recapitulate this closure, which is blocked in a complex with a SCH772984 analog. Thus, the L→R shift in 2P-ERK2 is associated with movements needed to form a competent active site. Solution measurements by hydrogen-exchange mass spectrometry (HX-MS) reveal distinct binding interactions for Vertex-11e, GDC-0994, and AMP-PNP with active vs. inactive ERK2, where the extent of HX protection correlates with R state formation. Furthermore, Vertex-11e and SCH772984 show opposite effects on HX near the activation loop. Consequently, these inhibitors differentially affect MAP kinase phosphatase activity toward 2P-ERK2. We conclude that global motions in ERK2 reflect conformational changes at the active site that promote productive nucleotide binding and couple with changes at the activation loop to allow control of dephosphorylation by conformationally selective inhibitors

Activation loop dynamics are controlled by conformation-selective inhibitors of ERK2

Conformational selection by small molecules expands inhibitory possibilities for protein kinases. Nuclear magnetic resonance (NMR) measurements of the mitogen-activated protein (MAP) kinase ERK2 have shown that activation by dual phosphorylation induces global motions involving exchange between two states, L and R. We show that ERK inhibitors Vertex-11e and SCH772984 exploit the small energetic difference between L and R to shift the equilibrium in opposing directions. An X-ray structure of active 2P-ERK2 complexed with AMP-PNP reveals a shift in the Gly-rich loop along with domain closure to position the nucleotide in a more catalytically productive conformation relative to inactive 0P-ERK2:ATP. X-ray structures of 2P-ERK2 complexed with Vertex-11e or GDC-0994 recapitulate this closure, which is blocked in a complex with a SCH772984 analog. Thus, the L→R shift in 2P-ERK2 is associated with movements needed to form a competent active site. Solution measurements by hydrogen-exchange mass spectrometry (HX-MS) reveal distinct binding interactions for Vertex-11e, GDC-0994, and AMP-PNP with active vs. inactive ERK2, where the extent of HX protection correlates with R state formation. Furthermore, Vertex-11e and SCH772984 show opposite effects on HX near the activation loop. Consequently, these inhibitors differentially affect MAP kinase phosphatase activity toward 2P-ERK2. We conclude that global motions in ERK2 reflect conformational changes at the active site that promote productive nucleotide binding and couple with changes at the activation loop to allow control of dephosphorylation by conformationally selective inhibitors

Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology

Gould E, Fraser H, Parker T, et al. Same data, different analysts: variation in effect sizes due to analytical decisions in ecology and evolutionary biology. 2023.Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different (mostly social science) fields, and has found substantial variability among results, despite analysts having the same data and research question. We implemented an analogous study in ecology and evolutionary biology, fields in which there have been no empirical exploration of the variation in effect sizes or model predictions generated by the analytical decisions of different researchers. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment), and the project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future