최순강 (Harvard Medical School, Dana-Farber Cancer Institute) | 한빛사논문 > 한빛사

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Harvard Medical School, Dana-Farber Cancer Institute

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Mol. Syst. Biol., 11 March 2024 | https://doi.org/10.1038/s44320-024-00019-8 AI-guided pipeline for protein–protein interaction drug discovery identifies a SARS-CoV-2 inhibitor

Philipp Trepte^1,2,17,*, Christopher Secker ^1,3,17,*, Julien Olivet ^{4,5,6,7,8,18,19}, Jeremy Blavier ^4,18, Simona Kostova ¹, Sibusiso B Maseko⁴, Igor Minia ⁹, Eduardo Silva Ramos ¹, Patricia Cassonnet¹⁰, Sabrina Golusik ¹, Martina Zenkner ¹, Stephanie Beetz ¹, MaraJ Liebich ¹, Nadine Scharek ¹, Anja Schütz ¹¹, Marcel Sperling ¹², Michael Lisurek ¹³, Yang Wang ^5,6,7, Kerstin Spirohn ^5,6,7, Tong Hao^5,6,7, Michael A Calderwood ^5,6,7, David E Hill ^5,6,7, Markus Landthaler^9,14, Soon Gang Choi ^5,6,7,*, Jean-Claude Twizere ^{4,5,15,16,19,*}, Marc Vidal ^5,6,19,* & Erich E Wanker ^1,19,*

¹Proteomics and Molecular Mechanisms of Neurodegenerative Diseases, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany.
²Brain Development and Disease, Institute of Molecular Biotechnology of the Austrian Academy of Sciences, 1030 Vienna, Austria.
³Zuse Institute Berlin, Berlin, Germany.
⁴Laboratory of Viral Interactomes, Interdisciplinary Cluster for Applied Genoproteomics (GIGA)-Molecular Biology of Diseases, University of Liège, 4000 Liège, Belgium.
⁵Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA 02215, USA.
⁶Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA02115, USA.
⁷Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA.
⁸Structural Biology Unit, Laboratory of Virology and Chemotherapy, RegaInstitute for Medical Research, Department of Microbiology, Immunology and Transplantation, Katholieke Universiteit Leuven, 3000 Leuven, Belgium.
⁹RNA Biology and Posttranscriptional Regulation, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, 13125 Berlin, Germany.
¹⁰Département de Virologie, Unité de Génétique Moléculaire des Virus à ARN (GMVR), Institut Pasteur, Centre National de la Recherche Scientifique (CNRS), Université de Paris,Paris, France.
¹¹Protein Production & Characterization, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany.
¹²Multifunctional Colloids and Coating, Fraunhofer Institute for Applied Polymer Research (IAP), 14476 Potsdam-Golm, Germany.
¹³Structural Chemistry and Computational Biophysics, Leibniz-Institut für Molekulare Pharmakologie (FMP), 13125 Berlin, Germany.
¹⁴Institute of Biology, Humboldt-Universität zu Berlin, 13125 Berlin, Germany.
¹⁵TERRA Teaching and Research Center, Gembloux Agro-Bio Tech, University of Liège, 5030 Gembloux, Belgium.
¹⁶Laboratory of Algal Synthetic and Systems Biology, Division of Science and Math, New York University Abu Dhabi, Abu Dhabi, UAE.
¹⁷These authors contributed equally as first authors: Philipp Trepte, Christopher Secker.
¹⁸These authors contributed equally as second authors: Julien Olivet, Jeremy Blavier.
¹⁹These authors contributed as senior authors: Julien Olivet, Jean-Claude Twizere, Marc Vidal, Erich E Wanker.

^*Corresponding authors: correspondence to Philipp Trepte, Christopher Secker, Soon Gang Choi, Jean-Claude Twizere or Erich E Wanker

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.

논문정보

형식Research article
게재일2024년 03월 (BRIC 등록일 2024-03-12)
연구진국외 연구진
분야 생명과학 > 유전학

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