Issue 47, 2020

Identification of a nanomolar affinity α-synuclein fibril imaging probe by ultra-high throughput in silico screening

Abstract

Small molecules that bind with high affinity and specificity to fibrils of the α-synuclein (αS) protein have the potential to serve as positron emission tomography (PET) imaging probes to aid in the diagnosis of Parkinson's disease and related synucleinopathies. To identify such molecules, we employed an ultra-high throughput in silico screening strategy using idealized pseudo-ligands termed exemplars to identify compounds for experimental binding studies. For the top hit from this screen, we used photo-crosslinking to confirm its binding site and studied the structure–activity relationship of its analogs to develop multiple molecules with nanomolar affinity for αS fibrils and moderate specificity for αS over Aβ fibrils. Lastly, we demonstrated the potential of the lead analog as an imaging probe by measuring binding to αS-enriched homogenates from mouse brain tissue using a radiolabeled analog of the identified molecule. This study demonstrates the validity of our powerful new approach to the discovery of PET probes for challenging molecular targets.

Graphical abstract: Identification of a nanomolar affinity α-synuclein fibril imaging probe by ultra-high throughput in silico screening

Supplementary files

Article information

Article type
Edge Article
Submitted
15 Dzi 2020
Accepted
31 Mha 2020
First published
10 Ndz 2020
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY license

Chem. Sci., 2020,11, 12746-12754

Identification of a nanomolar affinity α-synuclein fibril imaging probe by ultra-high throughput in silico screening

J. J. Ferrie, Z. Lengyel-Zhand, B. Janssen, M. G. Lougee, S. Giannakoulias, C. Hsieh, V. V. Pagar, C. Weng, H. Xu, T. J. A. Graham, V. M.-Y. Lee, R. H. Mach and E. J. Petersson, Chem. Sci., 2020, 11, 12746 DOI: 10.1039/D0SC02159H

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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