CACHE Challenge #1: Targeting the WDR Domain of LRRK2, A Parkinson’s Disease Associated Protein

The CACHE challenges are a series of prospective benchmarking exercises to evaluate progress in the field of computational hit-finding. Here we report the results of the inaugural CACHE challenge in which 23 computational teams each selected up to 100 commercially available compounds that they predicted would bind to the WDR domain of the Parkinson's disease target LRRK2, a domain with no known ligand and only an apo structure in the PDB. The lack of known binding data and presumably low druggability of the target is a challenge to computational hit finding methods. Of the 1955 molecules predicted by participants in Round 1 of the challenge, 73 were found to bind to LRRK2 in an SPR assay with a K<sub>D</sub> lower than 150 μM. These 73 molecules were advanced to the Round 2 hit expansion phase, where computational teams each selected up to 50 analogs. Binding was observed in two orthogonal assays for seven chemically diverse series, with affinities ranging from 18 to 140 μM. The seven successful computational workflows varied in their screening strategies and techniques. Three used molecular dynamics to produce a conformational ensemble of the targeted site, three included a fragment docking step, three implemented a generative design strategy and five used one or more deep learning steps. CACHE #1 reflects a highly exploratory phase in computational drug design where participants adopted strikingly diverging screening strategies. Machine learning-accelerated methods achieved similar results to brute force (e.g., exhaustive) docking. First-in-class, experimentally confirmed compounds were rare and weakly potent, indicating that recent advances are not sufficient to effectively address challenging targets.

Authors

Institutions

Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2024-11-05
DOI
https://doi.org/10.1021/acs.jcim.4c01267
Citations
23
Primary Topic
RNA and protein synthesis mechanisms
Type
article
Field-Weighted Citation Impact
5.38

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

CACHE Challenge #1: Targeting the WDR Domain of LRRK2, A Parkinson’s Disease Associated Protein

Leon Obendorf, Yu Chen, Valerij Talagayev, Filipp Gusev et al.
23 citations
Journal of Chemical Information and Modeling
RNA and protein synthesis mechanisms
5.38
article

CACHE Challenge #1: Targeting the WDR Domain of LRRK2, A Parkinson’s Disease Associated Protein

Leon Obendorf, Yu Chen, Valerij Talagayev, Filipp Gusev, Olexandr Isayev, C.H. Arrowsmith, Sumera Perveen, Kristina Puls, Chamali Narangoda, A.M. Edwards, Levon Halabelian, Albina Bolotokova, Merveille Eguida, Julian M. Kleber, Irene Chau, Maria G. Kurnikova, Jixian Zhang, Guzel Minibaeva, Jens Meiler, Emanuele Carosati, Alina Kutlushina, Marko Breznik, Christoph Gorgulla, Christina Schindler, Didier Rognan, Kristina Edfeldt, David Ryan Koes, Ian Dunn, Oanh Vu, Dennis Della Corte, Kam Y. J. Zhang, Elisa Gibson, Evgeny Gutkin, Rachel Harding, Austin J. Jarrett, Judith Günther, Uta Lessel, Rick Stevens, Jan H. Jensen, John J. Irwin, Sorin Draga, Dmitri Kireev, Vera Pütter, Amit Pandit, Scott Houliston, Katrin Denzinger, Fabian Ließmann, Gennady Poda, Theresa Noonan, Wei Lu, Clemens Alexander Wolf, Christopher Barden, Fuqiang Ban, Dylan Roskams-Edris, Casper Steinmann, Aleksandra Ivanová, Vojtěch Spiwok, Artem Cherkasov, Rocco Moretti, Szymon Pach, Francois Berenger, Akhila Mettu, Célien Jacquemard, Shuangjia Zheng, Matthieu Schapira, W. Patrick Walters, Guillaume Bret, Lars Wortmann, Connor J. Morris, Francesco Gentile, Anders Hogner, Gerhard Wolber, Pegah Ghiabi, Pavel Polishchuk, Spencer Gardiner, Hartmut Beck, Hong Zeng, S. Benjamin Koby, Jan Beránek, Suzanne Ackloo, Alexander Hillisch, Lukas Friedrich, François Sindt, Paul Eisenhuth, Xiaowen Wang, Sijie Liu, Ashutosh Kumar, Fengling Li, A. Dong, Anders Gunnarsson, Laurent Hoffer, Damon Tingey, Marta Glavatskikh, Carlos Zepeda, Alexander Fürll, Zhenyu Wang
article en
23 citations

Abstract

The CACHE challenges are a series of prospective benchmarking exercises to evaluate progress in the field of computational hit-finding. Here we report the results of the inaugural CACHE challenge in which 23 computational teams each selected up to 100 commercially available compounds that they predicted would bind to the WDR domain of the Parkinson's disease target LRRK2, a domain with no known ligand and only an apo structure in the PDB. The lack of known binding data and presumably low druggability of the target is a challenge to computational hit finding methods. Of the 1955 molecules predicted by participants in Round 1 of the challenge, 73 were found to bind to LRRK2 in an SPR assay with a K<sub>D</sub> lower than 150 μM. These 73 molecules were advanced to the Round 2 hit expansion phase, where computational teams each selected up to 50 analogs. Binding was observed in two orthogonal assays for seven chemically diverse series, with affinities ranging from 18 to 140 μM. The seven successful computational workflows varied in their screening strategies and techniques. Three used molecular dynamics to produce a conformational ensemble of the targeted site, three included a fragment docking step, three implemented a generative design strategy and five used one or more deep learning steps. CACHE #1 reflects a highly exploratory phase in computational drug design where participants adopted strikingly diverging screening strategies. Machine learning-accelerated methods achieved similar results to brute force (e.g., exhaustive) docking. First-in-class, experimentally confirmed compounds were rare and weakly potent, indicating that recent advances are not sufficient to effectively address challenging targets.

Journal of Chemical Information and ModelingVol. 64(22)
Brigham Young University (US), Ontario Institute for Cancer Research (CA), University of North Carolina at Chapel Hill (US), University of Copenhagen (DK), Argonne National Laboratory (US), Centre National de la Recherche Scientifique (FR), St. Jude Children's Research Hospital (US), University Health Network (CA), Boehringer Ingelheim (Germany) (DE), Karolinska University Hospital (SE), Harvard University (US), University of British Columbia (CA), University of Trieste (IT), University of Ottawa (CA), Merck KGaA, Darmstadt (Germany) (DE), University of Pittsburgh (US), University of California, San Francisco (US), Shanghai Jiao Tong University (CN), University of Toronto (CA), Vanderbilt University (US), Princess Margaret Cancer Centre (CA), Structural Genomics Consortium (CA), Karolinska Institutet (SE), University of Chicago (US), Treventis (Canada) (CA), Relay Therapeutics (United States) (US), RIKEN Center for Biosystems Dynamics Research (JP), Laboratoire d'Innovation Thérapeutique (FR), Virtual Corporation (United States) (US), AstraZeneca (Sweden) (SE), Nuvisan (Germany) (DE), Institute of Molecular and Translational Medicine (CZ), UCB Pharma (Germany) (DE), Bayer (Germany) (DE), Université de Strasbourg (FR), Palacký University Olomouc (CZ), The University of Tokyo (JP), Carnegie Mellon University (US), Freie Universität Berlin (DE), University of Missouri (US), Aalborg University (DK), University of Chemistry and Technology, Prague (CZ), Leipzig University (DE)
National Science Foundation, U.S. Department of Energy, Michael J. Fox Foundation for Parkinson's Research, Boehringer Ingelheim, Bristol-Myers Squibb Foundation, Bristol-Myers Squibb, Pfizer, Bayer, Alexander von Humboldt-Stiftung, University of Missouri, Takeda Pharmaceutical Company, McGill University, Genome Canada, Merck KGaA, Diamond Light Source, Ontario Genomics, European Federation of Pharmaceutical Industries and Associations, Strategic Innovation Fund, Ontario Genomics Institute, European Commission, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, Kungliga Tekniska Högskolan, Innovative Medicines Initiative, German Network for Bioinformatics Infrastructure, National Institutes of Health, Genentech, Office of Science, Horizon 2020 Framework Programme, National Institute of General Medical Sciences, Janssen Pharmaceuticals, Office of Research Infrastructure Programs, National Institutes of Health, Argonne National Laboratory
Openalex Percentile: Top 3%
RNA and protein synthesis mechanisms
5.38
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.