Structural aspects and physiological consequences of APP/APLP trans-dimerization

The amyloid precursor protein (APP) is one of the key proteins in Alzheimer’s disease (AD), as it is the precursor of amyloid β (Aβ) peptides accumulating in amyloid plaques. The processing of APP and the pathogenic features of especially Aβ oligomers have been analyzed in detail. Remarkably, there is accumulating evidence from cell biological and structural studies suggesting that APP and its mammalian homologs, the amyloid precursor-like proteins (APLP1 and APLP2), participate under physiological conditions via trans-cellular dimerization in synaptogenesis. This offers the possibility that loss of synapses in AD might be partially explained by dysfunction of APP/APLPs cell adhesion properties. In this review, structural characteristics of APP trans-cellular interaction will be placed critically in context with its putative physiological functions focusing on cell adhesion and synaptogenesis

Application of Consensus Scoring and Principal Component Analysis for Virtual Screening against β-Secretase (BACE-1)

BACKGROUND: In order to identify novel chemical classes of β-secretase (BACE-1) inhibitors, an alternative scoring protocol, Principal Component Analysis (PCA), was proposed to summarize most of the information from the original scoring functions and re-rank the results from the virtual screening against BACE-1. METHOD: Given a training set (50 BACE-1 inhibitors and 9950 inactive diverse compounds), three rank-based virtual screening methods, individual scoring, conventional consensus scoring and PCA, were judged by the hit number in the top 1% of the ranked list. The docking poses were generated by Surflex, five scoring functions (Surflex_Score, D_Score, G_Score, ChemScore, and PMF_Score) were used for pose extraction. For each pose group, twelve scoring functions (Surflex_Score, D_Score, G_Score, ChemScore, PMF_Score, LigScore1, LigScore2, PLP1, PLP2, jain, Ludi_1, and Ludi_2) were used for the pose rank. For a test set, 113,228 chemical compounds (Sigma-Aldrich® corporate chemical directory) were docked by Surflex, then ranked by the same three ranking methods motioned above to select the potential active compounds for experimental test. RESULTS: For the training set, the PCA approach yielded consistently superior rankings compared to conventional consensus scoring and single scoring. For the test set, the top 20 compounds according to conventional consensus scoring were experimentally tested, no inhibitor was found. Then, we relied on PCA scoring protocol to test another different top 20 compounds and two low micromolar inhibitors (S450588 and 276065) were emerged through the BACE-1 fluorescence resonance energy transfer (FRET) assay. CONCLUSION: The PCA method extends the conventional consensus scoring in a quantitative statistical manner and would appear to have considerable potential for chemical screening applications

The self-organizing fractal theory as a universal discovery method: the phenomenon of life

A universal discovery method potentially applicable to all disciplines studying organizational phenomena has been developed. This method takes advantage of a new form of global symmetry, namely, scale-invariance of self-organizational dynamics of energy/matter at all levels of organizational hierarchy, from elementary particles through cells and organisms to the Universe as a whole. The method is based on an alternative conceptualization of physical reality postulating that the energy/matter comprising the Universe is far from equilibrium, that it exists as a flow, and that it develops via self-organization in accordance with the empirical laws of nonequilibrium thermodynamics. It is postulated that the energy/matter flowing through and comprising the Universe evolves as a multiscale, self-similar structure-process, i.e., as a self-organizing fractal. This means that certain organizational structures and processes are scale-invariant and are reproduced at all levels of the organizational hierarchy. Being a form of symmetry, scale-invariance naturally lends itself to a new discovery method that allows for the deduction of missing information by comparing scale-invariant organizational patterns across different levels of the organizational hierarchy

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