Mendel Helen C, Hopping Gene, Undheim Eivind A B, Zuegg Johannes, Lewis Richard J, Forbes Briony E, Kaas Quentin, Muttenthaler Markus
Institute for Molecular Bioscience, The University of Queensland, 4072 Brisbane, Australia.
Centre for Ecological and Evolutionary Synthesis, Department of Biosciences, The University of Oslo, 0371 Oslo, Norway.
Gigascience. 2025 Jan 6;14. doi: 10.1093/gigascience/giaf078.
Neuropeptides represent the largest and most diverse class of cell-to-cell signaling molecules, holding important roles in animal physiology and behavior. They are evolutionarily ancient and widely distributed across the animal kingdom. Although over 200 neuropeptides have been identified, only a small fraction has been functionally characterized. A recognized bottleneck is the lack of effective tools to study their biological roles and therapeutic potential. Interestingly, neuropeptide-like peptides are also found in animal venoms, where they contribute to prey capture or defensive strategies. Mapping neuropeptide families across the animal kingdom is challenging due to their high sequence divergence and short mature peptide sequences. To address this, we developed PeptideMiner, a search tool that employs profile-hidden Markov models (profile-HMMs) for family-specific peptide discovery. PeptideMiner was systematically validated and benchmarked against existing methods, demonstrating its superior performance. By applying PeptideMiner to several venom transcriptomes-including 24 previously unpublished datasets-we identified 10 novel natriuretic peptides from distantly related species and 57 novel insulin-like sequences from marine predatory cone snails. Chemical synthesis and structure-activity relationship studies of newly identified conoinsulins at human insulin receptors emphasized the value of our approach in elucidating ligand-receptor interactions and discovering new pharmacological probes and therapeutic leads. PeptideMiner offers a powerful platform for discovering new bioactive peptides and family-specific analogues, accelerating both natural product discovery and evolutionary research.
神经肽是细胞间信号分子中数量最多、种类最多样的一类，在动物生理学和行为中发挥着重要作用。它们在进化上很古老，广泛分布于动物界。尽管已经鉴定出200多种神经肽，但只有一小部分具有功能特征。一个公认的瓶颈是缺乏研究它们生物学作用和治疗潜力的有效工具。有趣的是，动物毒液中也发现了神经肽样肽，它们有助于捕食或防御策略。由于神经肽家族的序列差异大且成熟肽序列短，在整个动物界绘制神经肽家族图谱具有挑战性。为了解决这个问题，我们开发了PeptideMiner，这是一种利用轮廓隐马尔可夫模型（profile-HMMs）进行家族特异性肽发现的搜索工具。PeptideMiner经过系统验证，并与现有方法进行了基准测试，证明了其卓越性能。通过将PeptideMiner应用于多个毒液转录组——包括24个以前未发表的数据集——我们从远缘物种中鉴定出10种新型利钠肽，从海洋捕食性芋螺中鉴定出57种新型胰岛素样序列。新鉴定的芋螺胰岛素在人胰岛素受体上的化学合成和构效关系研究强调了我们的方法在阐明配体-受体相互作用以及发现新药理学探针和治疗先导物方面的价值。PeptideMiner为发现新的生物活性肽和家族特异性类似物提供了一个强大的平台，加速了天然产物发现和进化研究。
