Machine Learning and Molecular Dynamics Based Insights into Mode of Actions of Insulin Degrading Enzyme Modulators

2017 ◽  
Vol 20 (4) ◽  
Author(s):  
Salma Jamal ◽  
Sukriti Goyal ◽  
Asheesh Shanker ◽  
Abhinav Grover
Keyword(s):  
Machine Learning ◽  
Molecular Dynamics ◽  
Insulin Degrading Enzyme ◽  
Degrading Enzyme

Evolution of Metastable Structures in Bimetallic Catalysts from Microscopy and Machine-Learning Molecular Dynamics

2020 ◽  
Author(s):  
Jin Soo Lim ◽  
Jonathan Vandermause ◽  
Matthijs A. van Spronsen ◽  
Albert Musaelian ◽  
Christopher R. O’Connor ◽  
...  
Keyword(s):  
Machine Learning ◽  
Molecular Dynamics ◽  
Large Scale ◽  
Materials Science ◽  
Complete Characterization ◽  
Layer By Layer ◽  
Surface Restructuring ◽  
Metastable Structures ◽  
Mechanistic Investigation ◽  
Underlying Mechanisms

Restructuring of interface plays a crucial role in materials science and heterogeneous catalysis. Bimetallic systems, in particular, often adopt very different composition and morphology at surfaces compared to the bulk. For the first time, we reveal a detailed atomistic picture of the long-timescale restructuring of Pd deposited on Ag, using microscopy, spectroscopy, and novel simulation methods. Encapsulation of Pd by Ag always precedes layer-by-layer dissolution of Pd, resulting in significant Ag migration out of the surface and extensive vacancy pits. These metastable structures are of vital catalytic importance, as Ag-encapsulated Pd remains much more accessible to reactants than bulk-dissolved Pd. The underlying mechanisms are uncovered by performing fast and large-scale machine-learning molecular dynamics, followed by our newly developed method for complete characterization of atomic surface restructuring events. Our approach is broadly applicable to other multimetallic systems of interest and enables the previously impractical mechanistic investigation of restructuring dynamics.

Characteristics of Insulin-degrading Enzyme in Alzheimer's Disease: A Meta-Analysis

2018 ◽  
Vol 15 (7) ◽  
pp. 610-617 ◽  
Author(s):  
Huifeng Zhang ◽  
Dan Liu ◽  
Huanhuan Huang ◽  
Yujia Zhao ◽  
Hui Zhou
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Enzyme Activity ◽  
Protein Level ◽  
Senile Plaque ◽  
Meta Analysis ◽  
Cochrane Library ◽  
Insulin Degrading Enzyme ◽  
Degrading Enzyme ◽  
Significant Difference

Background: β-amyloid (Aβ) accumulates abnormally to senile plaque which is the initiator of Alzheimer's disease (AD). As one of the Aβ-degrading enzymes, Insulin-degrading enzyme (IDE) remains controversial for its protein level and activity in Alzheimer's brain. Methods: The electronic databases PubMed, EMBASE, The Cochrane Library, OVID and Sinomed were systemically searched up to Sep. 20th, 2017. And the published case-control or cohort studies were retrieved to perform the meta-analysis. Results: Seven studies for IDE protein level (AD cases = 293; controls = 126), three for mRNA level (AD cases = 138; controls = 81), and three for enzyme activity (AD cases = 123; controls = 75) were pooling together. The IDE protein level was significantly lower in AD cases than in controls (SMD = - 0.47, 95% CI [-0.69, -0.24], p < 0.001), but IDE mRNA and enzyme activity had no significant difference (SMD = 0.02, 95% CI [-0.40, 0.43] and SMD = 0.06, 95% CI [-0.41, 0.53] respectively). Subgroup analyses found that IDE protein level was decreased in both cortex and hippocampus of AD cases (SMD = -0.43, 95% CI [-0.71, -0.16], p = 0.002 and SMD = -0.53, 95% CI [-0.91, -0.15], p = 0.006 respectively). However, IDE mRNA was higher in cortex of AD cases (SMD = 0.71, 95% CI [0.14, 1.29], p = 0.01), not in hippocampus (SMD = -0.26, 95% CI [-0.58, 0.06]). Conclusions: Our results indicate that AD patients may have lower IDE protease level. Further relevant studies are still needed to verify whether IDE is one of the factors affecting Aβ abnormal accumulation and throw new insights for AD detection or therapy.

Sign in / Sign up

Export Citation Format

Share Document