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用于发现新型治疗性肽的动物元基因组分子展示

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

作者信息

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

机构信息

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.

出版信息

bioRxiv. 2024 May 28:2024.05.27.595990. doi: 10.1101/2024.05.27.595990.

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 extracting or expressing large numbers of individual venoms and venom-like molecules 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.

摘要

动物毒液以其独特的结构特征和强大的生物活性而著称,是一个庞大且相对未被开发的治疗性分子宝库。然而,与提取或表达大量单个毒液及类毒液分子相关的局限性,使得无法通过高通量筛选对其进行治疗性评估。在此,我们开发了一种创新的计算方法,用于设计一个高度多样化的动物毒液和“超毒液”文库。我们采用可编程的M13超噬菌体展示来保留关键的二硫键结合结构,以便通过高通量DNA测序进行定量的高度并行单轮生物淘选。我们的方法导致发现了靶向人类瘙痒受体Mas相关G蛋白偶联受体X4(MRGPRX4)的含Kunitz结构域的蛋白质,该受体在瘙痒感知中起关键作用。基于深度学习的结构同源性挖掘鉴定出两种内源性人类同源物,即组织因子途径抑制剂(TFPI)和丝氨酸肽酶抑制剂Kunitz型2(SPINT2),它们表现出对MRGPRX4的激动剂依赖性增强作用。因此,对动物毒液和超毒液进行高度多重筛选是发现新候选药物的一种有前景的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c25/11160688/aed0a6db256f/nihpp-2024.05.27.595990v2-f0001.jpg

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