Turnover of amyloid precursor protein family members determines their nuclear signaling capability

The amyloid precursor protein (APP) as well as its homologues, APP-like protein 1 and 2 (APLP1 and APLP2), are cleaved by α-, β-, and γ-secretases, resulting in the release of their intracellular domains (ICDs). We have shown that the APP intracellular domain (AICD) is transported to the nucleus by Fe65 where they jointly bind the histone acetyltransferase Tip60 and localize to spherical nuclear complexes (AFT complexes), which are thought to be sites of transcription. We have now analyzed the subcellular localization and turnover of the APP family members. Similarly to AICD, the ICD of APLP2 localizes to spherical nuclear complexes together with Fe65 and Tip60. In contrast, the ICD of APLP1, despite binding to Fe65, does not translocate to the nucleus. In addition, APLP1 predominantly localizes to the plasma membrane, whereas APP and APLP2 are detected in vesicular structures. APLP1 also demonstrates a much slower turnover of the full-length protein compared to APP and APLP2. We further show that the ICDs of all APP family members are degraded by the proteasome and that the N-terminal amino acids of ICDs determine ICD degradation rate. Together, our results suggest that different nuclear signaling capabilities of APP family members are due to different rates of full-length protein processing and ICD proteasomal degradation. Our results provide evidence in support of a common nuclear signaling function for APP and APLP2 that is absent in APLP1, but suggest that APLP1 has a regulatory role in the nuclear translocation of APP family ICDs due to the sequestration of Fe65

Group Contribution-Based Method for Determination of Solubility Parameter of Nonelectrolyte Organic Compounds

Comment on "Group Contribution-Based Method for Determination of Solubility Parameter of Nonelectrolyte Organic Compounds" and "Solubility Parameters of Nonelectrolyte Organic Compounds: Determination Using Quantitative Structure-Property Relationship Strategy" Sierra Rayne, Industrial & Engineering Chemistry Research 2013 52 (10), 3947-3948; DOI: 10.1021/ie400117h Reply to "Comment on 'Group Contribution-Based Method for Determination of Solubility Parameter of Nonelectrolyte Organic Compounds' and 'Solubility Parameters of Nonelectrolyte Organic Compounds: Determination Using Quantitative Structure-Property Relationship Strategy"' Farhad Gharagheizi, Ali Eslamimanesh, Amir H. Mohammadi, and Dominique Richon, Industrial & Engineering Chemistry Research 2013 52 (10), 3949-3949; DOI: 10.1021/ie400202tInternational audienceThe determination of the solubility parameter of organic compounds has been of much significance in the chemical industry. In this study, we propose a predictive method based on the combination of the Group Contribution strategy with the Artificial Neural Network to calculate/estimate the solubility parameter values of about 1620 nonelectrolyte organic compounds at 298.15 K and atmospheric pressure. The chemical functional groups are obtained for various compounds categorized in 81 different chemical families. The final results indicate the following statistical parameters of the presented method: average relative deviation (ARD %) of the determined properties from existing experimental values of 1.5% and a squared correlation coefficient of 0.985. It is finally inferred that the developed model is more accurate and predictive than our previously proposed models based on the Quantitative Structure Property Relationship algorithm, which yielded 4.6, 3.4, and 3.1 ARD % from experimental values