Molecular Display of the Animal Meta-Venome for Discovery of Novel Therapeutic Peptides

Meng-Hsuan Hsiao; Yang Miao; Zixing Liu; Konstantin Schütze; Nathachit Limjunyawong; Daphne Chun-Che Chien; Wayne Denis Monteiro; Lee-Shin Chu; William Morgenlander; Sahana Jayaraman; Sung-Eun Jang; Jeffrey J Gray; Heng Zhu; Xinzhong Dong; Martin Steinegger; H Benjamin Larman

doi:10.1016/j.mcpro.2024.100901

Molecular Display of the Animal Meta-Venome for Discovery of Novel Therapeutic Peptides

Mol Cell Proteomics. 2024 Dec 31:100901. doi: 10.1016/j.mcpro.2024.100901. Online ahead of print.

Authors

Meng-Hsuan Hsiao¹, Yang Miao², Zixing Liu³, Konstantin Schütze⁴, Nathachit Limjunyawong⁵, Daphne Chun-Che Chien⁶, Wayne Denis Monteiro¹, Lee-Shin Chu⁷, William Morgenlander⁸, Sahana Jayaraman⁸, Sung-Eun Jang⁴, Jeffrey J Gray⁷, Heng Zhu⁹, Xinzhong Dong¹⁰, Martin Steinegger¹¹, H Benjamin Larman¹²

Affiliations

¹ Institute for Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Chemical and Biomolecular Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
² Institute for Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Biomedical Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
³ Institute for Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Biology, Zanvyl Krieger School of Arts and Sciences, Johns Hopkins University, Baltimore, MD 21218, USA.
⁴ School of Biological Sciences, Seoul National University, Seoul, South Korea.
⁵ The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Center of Research Excellence in Allergy and Immunology, Research Department, Faculty of Medicine Siriraj Hospital, Mahidol University, Thailand.
⁶ The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
⁷ Department of Chemical and Biomolecular Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
⁸ Institute for Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
⁹ Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Viral Oncology Program, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21231, USA.
¹⁰ The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Howard Hughes Medical Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
¹¹ School of Biological Sciences, Seoul National University, Seoul, South Korea; Artificial Intelligence Institute, Seoul National University, Seoul, South Korea; Institute of Molecular Biology and Genetics, Seoul National University, Seoul, South Korea. Electronic address: [email protected].
¹² Institute for Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA. Electronic address: [email protected].

PMID: 39746545
DOI: 10.1016/j.mcpro.2024.100901

Abstract

Animal venoms, distinguished by their unique structural features and potent bioactivities, represent a vast and relatively untapped reservoir of therapeutic molecules. However, limitations associated with comprehensively constructing and expressing highly complex venom and venom-like molecule libraries have precluded their therapeutic evaluation via high throughput screening. Here, we developed an innovative computational approach to design a highly diverse library of animal venoms and "metavenoms". We employed programmable M13 hyperphage display to preserve critical disulfide-bonded structures for highly parallelized single-round biopanning with quantitation via high-throughput DNA sequencing. Our approach led to the discovery of Kunitz type domain containing proteins that target the human itch receptor Mas-related G protein-coupled receptor X4 (MRGPRX4), which plays a crucial role in itch perception. Deep learning-based structural homology mining identified two endogenous human homologs, tissue factor pathway inhibitor (TFPI) and serine peptidase inhibitor, Kunitz type 2 (SPINT2), which exhibit agonist-dependent potentiation of MRGPRX4. Highly multiplexed screening of animal venoms and metavenoms is therefore a promising approach to uncover new drug candidates.