Design of Substrate Transmembrane Mimetics as Structural Probes for γ-Secretase

This document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of the American Chemical Society (JACS), copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/jacs.9b13405.γ-Secretase is a membrane-embedded aspartyl protease complex central in biology and medicine. How this enzyme recognizes transmembrane substrates and catalyzes hydrolysis in the lipid bilayer is unclear. Inhibitors that mimic the entire substrate transmembrane domain and engage the active site should provide important tools for structural biology, yielding insight into substrate gating and trapping the protease in the active state. Here we report transmembrane peptidomimetic inhibitors of the γ-secretase complex that contain an N-terminal helical peptide region that engages a substrate docking exosite and a C-terminal transition-state analog moiety targeted to the active site. Both regions are required for stoichiometric inhibition of γ-secretase. Moreover, enzyme inhibition kinetics and photoaffinity probe displacement experiments demonstrate that both the docking exosite and the active site are engaged by the bipartite inhibitors. The solution conformations of these potent transmembranemimetic inhibitors are similar to those of bound natural substrates, suggesting these probes are preorganized for high-affinity binding and should allow visualization of the active γ-secretase complex, poised for intramembrane proteolysis, by cryo-electron microscopy.NIH R01 grant GM 122894NIH grant P30GM110761NIH grant P41GM11113

Development of Monsoonal Rainfall Intensity-Duration-Frequency (IDF) Relationship and Empirical Model for Data-Scarce Situations: The Case of the Central-Western Hills (Panchase Region) of Nepal

Intense monsoonal rain is one of the major triggering factors of floods and mass movements in Nepal that needs to be better understood in order to reduce human and economic losses and improve infrastructure planning and design. This phenomena is better understood through intensity-duration-frequency (IDF) relationships, which is a statistical method derived from historical rainfall data. In Nepal, the use of IDF for disaster management and project design is very limited. This study explored the rainfall variability and possibility to establish IDF relationships in data-scarce situations, such as in the Central-Western hills of Nepal, one of the highest rainfall zones of the country (~4500 mm annually), which was chosen for this study. Homogeneous daily rainfall series of 8 stations, available from the government's meteorological department, were analyzed by grouping them into hydrological years. The monsoonal daily rainfall was disaggregated to hourly synthetic series in a stochastic environment. Utilizing the historical statistical characteristics of rainfall, a disaggregation model was parameterized and implemented in HyetosMinute, software that disaggregates daily rainfall to finer time resolution. With the help of recorded daily and disaggregated hourly rainfall, reference IDF scenarios were developed adopting the Gumbel frequency factor. A mathematical model [i = a(T)/b(d)] was parameterized to model the station-specific IDF utilizing the best-fitted probability distribution function (PDF) and evaluated utilizing the reference IDF. The test statistics revealed optimal adjustment of empirical IDF parameters, required for a better statistical fit of the data. The model was calibrated, adjusting the parameters by minimizing standard error of prediction; accordingly a station-specific empirical IDF model was developed. To regionalize the IDF for ungauged locations, regional frequency analysis (RFA) based on L-moments was implemented. The heterogeneous region was divided into two homogeneous sub-regions; accordingly, regional L-moment ratios and growth curves were evaluated. Utilizing the reasonably acceptable distribution function, the regional growth curve was developed. Together with the hourly mean (extreme) precipitation and other dynamic parameters, regional empirical IDF models were developed. The adopted approach to derive station-specific and regional empirical IDF models was statistically significant and useful for obtaining extreme rainfall intensities at the given station and ungauged locations. The analysis revealed that the region contains two distinct meteorological sub-regions highly variable in rain volume and intensity

Drivers of Sustainable Innovation: Exploratory Views And Corporate Strategies

Various forces drive corporate commitment to sustainable innovation including: (a) external stimuli, (b) business opportunities, and (c) a business orientation toward corporate social responsibility. The depth of corporate response to these drivers is shaped by how the managing team of a corporation views the relationship between economic growth and the environment. This paper examines associations between key drivers of sustainable innovation and three alternative views of the economic growth-environment relationship. We also examine three contrasting modes of corporate response (i.e. compliance, commitment and resistance) to those drivers and suggest directions for further research on the corporate practice of sustainable innovation

Opportunities and challenges in Asian bee research and conservation

10.1016/j.biocon.2023.110173BIOLOGICAL CONSERVATIO