AI-guided pipeline for protein–protein interaction drug discovery identifies a SARS-CoV-2 inhibitor
Open accessPublished version of a preprint
Abstract
Protein–protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays or AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold-Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.
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References 100 · Cited by 35
- Authors
- Trepte, P., Secker, C., Olivet, J., Blavier, J., Kostova, S., Maseko, S. B., Minia, I., Silva Ramos, E., Cassonnet, P., Golusik, S., Zenkner, M., Beetz, S., Liebich, M. J., Scharek, N., Schütz, A., Sperling, M., Lisurek, M., Wang, Y., Spirohn, K., Hao, T., Calderwood, M. A., Hill, D. E., Landthaler, M., Choi, S. G., Twizere, J.-C., Vidal, M., & Wanker, E. E.
- Affiliations
- Institute of Molecular Biotechnology (AT)
- Zuse Institute Berlin (DE)
- Harvard University (US)
- Max Delbrück Center (DE)
- University of Liège (BE)
- Centre National de la Recherche Scientifique (FR)
- Fraunhofer Institute for Applied Polymer Research (DE)
- Leibniz-Forschungsinstitut für Molekulare Pharmakologie (DE)
- New York University Abu Dhabi (AE)
- Corresponding author
- Trepte, Philipp
- Secker, Christopher
- Choi, Soon Gang
- Twizere, Jean-Claude
- Vidal, Marc
- Wanker, Erich E
- ORCID
- Trepte, Philipp
- Secker, Christopher
- Olivet, Julien
- Blavier, Jeremy
- Maseko, Sibusiso B
- Minia, Igor
- Silva Ramos, Eduardo
- Cassonnet, Patricia
- Schütz, Anja
- Sperling, Marcel
- Lisurek, Michael
- Wang, Yang
- Spirohn, Kerstin
- Hao, Tong
- Calderwood, Michael A
- Hill, David E
- Landthaler, Markus
- Choi, Soon Gang
- Twizere, Jean-Claude
- Vidal, Marc
- Wanker, Erich E
- Venue
- Molecular Systems Biology
- Published
- 2024-03-11
- Volume
- 20
- Issue
- 4
- Pages
- 428-457
- ISSN
- 1744-4292 (ISSN-L)
- PMC
- PMC10987651
- OpenAlex
- W4392642017
- Cited by
- 35
- References
- 100
- Citations by year
- 2026: 14 · 2025: 12 · 2024: 8 · 2023: 1
- FWCI
- 7.21
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Molecular Systems Biology (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Lirias (submittedVersion, cc-by-nc-nd)
- PubMed Central (submittedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- edoc Publication server (Humboldt University of Berlin) (submittedVersion, cc-by)
- MDC Repository (Max-Delbrueck-Center for Molecular Medicine) (submittedVersion)
- Lirias (submittedVersion, cc-by)
- Open Repository and Bibliography (University of Liège) (submittedVersion, other-oa)
- Fraunhofer-Publica (Fraunhofer-Gesellschaft) (submittedVersion, other-oa)
- edoc Publication server (Humboldt University of Berlin) (cc-by)
- Funders
- Bundesministerium für Bildung und Forschung (01GS0844)
- Helmholtz Association
- Helmholtz-Israel Initiative on Personalized Medicine
- CHDI Foundation
- Deutschen Konsortium für Translationale Krebsforschung
- Deutsche Forschungsgemeinschaft (LA 2941/17-1)
- Claudia Adams Barr Award
- Fonds De La Recherche Scientifique - FNRS (FC27371, FC38907, FC34947)
- Wallonia-Brussels International (WBI)-World Excellence Fellowship (40003579)
- National Institute of Health (P50HG004233, R01GM130885, U41HG001715, R01CA266194)
- LabEx IBEID (10-LABX-0062)
- Deutsche Krebshilfe
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- protein-protein interaction, SARS-CoV-2, drug discovery, AlphaFold-Multimer, virtual screening, antiviral agents, viral replication inhibition, protein complexes
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