New Research by Z. Faidon Brotzakis from Skretas Lab on Identification of potent high-affinity secondary nucleation inhibitors of Aβ42 aggregation from an ultra-large chemical library using deep docking.
The aggregation of the Aβ42 peptide into amyloid fibrils is characteristic of Alzheimer's disease (AD). Identifying inhibitors of this aggregation is challenging due to limitations in experimental screening size.
Τhe interdisciplinary team comprising University of Cambridge and BSRC Fleming overcame this challenge by developing an open-source Deep Docking pipeline to computationally screen an ultra-large chemical library of over 539 million compounds. Applying this pipeline, they prioritized 35 candidates for in vitro testing, achieving a 54% hit rate (19 inhibitors).
The two most potent compounds demonstrated better inhibitory action than a previously reported potent inhibitor (adapalene). Consistent with targeting the fibril surface, these compounds proved to be high-affinity Aβ42 fibril binders, showing a low nanomolar equilibrium dissociation constant in surface plasmon resonance experiments.
This is contribution reports the first-in-class nanomolar fibril binders that inhibit Αβ42 secondary nucleation as seen in the in vitro kinetic analysis, and inhibit aggregation in iPSC-derived neuronal cultures.
This work validates that structure-based docking methods using deep learning offer a cost-effective and rapid strategy for discovering potent drug candidates against protein misfolding diseases.