A longer isoform of Stim1 is a negative SOCE regulator but increases cAMP-modulated NFAT signaling

Alternative splicing is a potent modifier of protein function. Stro mal interaction molecule 1 (Stim1) is the essential activator of store-operated Ca2+ entry (SOCE) triggering activation of transcrip tion factors. Here, we characterize Stim1A, a splice variant with an additional 31 amino acid domain inserted in frame within its cytosolic domain. Prominent expression of exon A is found in astro cytes, heart, kidney, and testes. Full-length Stim1A functions as a dominant-negative regulator of SOCE and ICRAC, facilitating sequence-specific fast calcium-dependent inactivation and desta bilizing gating of Orai channels. Downregulation or absence of native Stim1A results in increased SOCE. Despite reducing SOCE, Stim1A leads to increased NFAT translocation. Differential proteo mics revealed an interference of Stim1A with the cAMP-SOCE crosstalk by altered modulation of phosphodiesterase 8 (PDE8), resulting in reduced cAMP degradation and increased PIP5K activ ity, facilitating NFAT activation. Our study uncovers a hitherto unknown mechanism regulating NFAT activation and indicates that cell-type-specific splicing of Stim1 is a potent means to regu late the NFAT signalosome and cAMP-SOCE crosstalk

Investigating targets for neuropharmacological intervention by molecular dynamics simulations

Medical research has identified over 500 brain disorders. Among these, there are still only very few neuropathologies whose causes are fully understood and, consequently, very few drugs whose mechanism of action is known. No FDA drug has been identified for major neurodegenerative diseases, such as Alzheimer's and Parkinson's. We still lack effective treatments and strategies for modulating progression or even early neurodegenerative disease onset diagnostic tools. A great support toward the highly needed identification of neuroactive drugs comes from computer simulation methods and, in particular, from molecular dynamics (MD). This provides insight into structure–function relationship of a target and predicts structure, dynamics and energetics of ligand/target complexes under biologically relevant conditions like temperature and physiological saline concentration. Here, we present examples of the predictive power of MD for neuroactive ligands/target complexes. This brief survey from our own research shows the usefulness of partnerships between academia and industry, and from joint efforts between experimental and theoretical groups