Molecular Recipe for γ‑Secretase Modulation from Computational Analysis of 60 Active Compounds

γ-secretase is a membrane protease
complex 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 validation
on 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 simply
by 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 provide
a structural–chemical model of the modulation of Aβ production.