TY - JOUR
T1 - Molecular Recipe for γ-Secretase Modulation from Computational Analysis of 60 Active Compounds
AU - Tang, Ning
AU - Somavarapu, Arun Kumar
AU - Kepp, Kasper Planeta
N1 - This is an open access article published under an ACS AuthorChoice License, which permits copying and redistribution of the article or any adaptations for non-commercial purposes.
PY - 2018
Y1 - 2018
N2 - γ-secretase is a membrane proteasecomplex that catalyzes the cleavage of the amyloid precursor protein to produce the infamous Aβ peptides involved in Alzheimer’s disease (AD). Major efforts aim to modulate this cleavage to reduce the formation of longer,more toxic Aβ peptides, yet the molecular basis of this modulation remains unknown. We studied the quantitative structure–activity relations using a carefully curated data set of 60 experimental EC50 values (the GSL60 data set). To ensure adequate optimization,we used 10 different methods to build the models, Y-randomization,10-fold repeated cross-validation, and explicit external validationon a secondary data set. Neural network optimization best reproduced experimental log EC50. We find that only four descriptors,the number of hydrogen-bond acceptor sites, the topology of the drug, the dehydration energy, and the binding energy to γ-secretase, define most of the potency of γ-secretase modulators. We explain this as a compromise between the binding free energy to the protein and required hydrogen bond networks in the actual modulatory sites.Our model suggests that many molecules can modulate cleavage simplyby contributing their binding energy to stabilize the compact ternary complex with C99. This result is in line with a mechanism, referred to here as FIST (Fit, Stay, Trim), where stronger binding to the semiopen state leads to longer retention time and maximal C99 trimming to produce shorter innocent Aβ peptides, whereas AD-causing PSEN1 mutations favor the open state by reducing hydrophobic packing, retention time,and trimming and modulators strengthen interactions in the ternary complex to increase the C99 retention time and trimming, ultimately producing more short, nonpathogenic Aβ peptides. Our results may aid the development of new γ-secretase modulators with optimal hydrogen bonds, shape, and hydrophobicity but more importantly providea structural–chemical model of the modulation of Aβ production.
AB - γ-secretase is a membrane proteasecomplex that catalyzes the cleavage of the amyloid precursor protein to produce the infamous Aβ peptides involved in Alzheimer’s disease (AD). Major efforts aim to modulate this cleavage to reduce the formation of longer,more toxic Aβ peptides, yet the molecular basis of this modulation remains unknown. We studied the quantitative structure–activity relations using a carefully curated data set of 60 experimental EC50 values (the GSL60 data set). To ensure adequate optimization,we used 10 different methods to build the models, Y-randomization,10-fold repeated cross-validation, and explicit external validationon a secondary data set. Neural network optimization best reproduced experimental log EC50. We find that only four descriptors,the number of hydrogen-bond acceptor sites, the topology of the drug, the dehydration energy, and the binding energy to γ-secretase, define most of the potency of γ-secretase modulators. We explain this as a compromise between the binding free energy to the protein and required hydrogen bond networks in the actual modulatory sites.Our model suggests that many molecules can modulate cleavage simplyby contributing their binding energy to stabilize the compact ternary complex with C99. This result is in line with a mechanism, referred to here as FIST (Fit, Stay, Trim), where stronger binding to the semiopen state leads to longer retention time and maximal C99 trimming to produce shorter innocent Aβ peptides, whereas AD-causing PSEN1 mutations favor the open state by reducing hydrophobic packing, retention time,and trimming and modulators strengthen interactions in the ternary complex to increase the C99 retention time and trimming, ultimately producing more short, nonpathogenic Aβ peptides. Our results may aid the development of new γ-secretase modulators with optimal hydrogen bonds, shape, and hydrophobicity but more importantly providea structural–chemical model of the modulation of Aβ production.
U2 - 10.1021/acsomega.8b02196
DO - 10.1021/acsomega.8b02196
M3 - Journal article
VL - 3
SP - 18078
EP - 18088
JO - ACS Omega
JF - ACS Omega
SN - 2470-1343
IS - 12
ER -