A Structure-Based Platform for Predicting Chemical-Induced Parkinson’s Disease

Chemical Research in Toxicology, vol. 39, pp. 890–899

Abstract

Current methods for determining the neurotoxic potential of (agro)chemicals are not comprehensive enough, as is suggested by the increased incidence of Parkinson’s disease (PD) amongst people exposed to certain pesticides. Mechanism-based in silico screening can address this shortcoming by predicting molecular initiating event activation. However, a limited amount protein-binding data has been collected on pesticides, meaning that for screening an approach is required that is well suited for extrapolation to a wide variety of chemicals. Here, the group I metabotropic glutamate receptors (mGluRs) were taken as a case study because of their role in chemical-induced PD. Compounds with known activity for these receptors were docked into the allosteric binding site, interaction fingerprints (IFPs) were computed and used to train classification models. Afterward, model enrichment was evaluated, feature importance was derived, and the applicability domain was analyzed. Both IFP-based mGluR models demonstrated good enrichment with the 95% confidence interval of the area under the Receiver Operating Characteristic Curve (ROC AUC) ranging between 0.71 to 0.85 and 0.84 to 0.91. The interactions that were most important for model predictions were hydrogen bond formation with Asn760 for mGluR1 and aromatic interactions with Trp785 for mGluR5. The applicability domain varied depending on the training set but was consistently larger for IFPs than for Morgan fingerprints a fragment-based descriptor. A virtual screen using the final models identified 132 potential mGluR binders of which one, bifenthrin, had been previously found to bind in in vitro experiments. To promote the implementation of the screening technique presented here, a platform was created where users can make predictions using our models. All in all, these results highlight the potential of combining IFPs with machine learning and contribute to the shift towards mechanism-based in silico toxicology.

Authors 6

1. Linde Schoenmaker Aachen Division of Medicinal Chemistry Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, Leiden 2333 CC, Netherlands

   Leiden University

2. Emmelie van der Veer Aachen Division of Medicinal Chemistry Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, Leiden 2333 CC, Netherlands

   Leiden University

3. Daan A. Jiskoot Aachen Division of Medicinal Chemistry Leiden Academic Centre for Drug Research

   Leiden University · National Institute for Public Health and the Environment

   Affiliation as printed

   Centre for Safety of Substances and Products, National Institute for Public Health and the Environment (RIVM), Antonie van Leeuwenhoeklaan 9, Bilthoven 3721 MA, Netherlands

   Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, Leiden 2333 CC, Netherlands

   Leiden University

   National Institute for Public Health and the Environment

4. Olivier J. M. Béquignon Aachen Division of Medicinal Chemistry Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, Leiden 2333 CC, Netherlands

   Leiden University

5. Gerard J. P. van Westen Aachen Division of Medicinal Chemistry Leiden Academic Centre for Drug Research

   Leiden University

   Affiliation as printed

   Division of Medicinal Chemistry, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, Leiden 2333 CC, Netherlands

   Leiden University

6. Willem Jespers

   University of Groningen

   Affiliation as printed

   Department of Medicinal Chemistry, Photopharmacology and Imaging, Groningen Research Institute of Pharmacy (GRIP), Faculty of Science and Engineering, University of Groningen, Antonius Deusinglaan 1, Groningen 9713 AV, Netherlands

   University of Groningen