Distinct Dibasic Cleavage Specificities of Neuropeptide-Producing Cathepsin L and Cathepsin V Cysteine Proteases Compared to PC1/3 and PC2 Serine Proteases

Understanding peptide hormones: from precursor proteins to bioactive molecules

Peptide hormones are fundamental regulators of biological processes involved in homeostasis regulation and are often dysregulated in endocrine diseases. Despite their biological significance and established therapeutic potential, there is still a gap in our knowledge of their processing and post-translational modifications, as well as in the technologies for their discovery and detection. In this review, we cover insights into the peptidome landscape, including the proteolytic processing and post-translational modifications of peptide hormones. Understanding the full landscape of peptide hormones and their modifications could provide insights into leveraging proteolytic mechanisms to identify novel peptides with therapeutic potential. Therefore, we also discuss the need for future research aiming at better predicting, detecting, and characterizing new peptides with biological activities.

Computational approaches for identifying neuropeptides: A comprehensive review

Neuropeptides (NPs) are key signaling molecules that interact with G protein-coupled receptors, influencing neuronal activities and developmental pathways, as well as the endocrine and immune systems. They are significant in disease contexts, offering potential therapeutic targets for conditions such as anxiety, neurological disorders, cardiovascular health, and diabetes. Understanding and detecting NPs is crucial because of their complex functions in health and disease. Historically, identifying NPs via wet lab techniques has been time-consuming and costly. However, integrating computational methods has shown the potential to improve efficiency, accuracy, and cost-effectiveness. Computational techniques, such as artificial intelligence and machine learning, have been extensively researched in recent years for the identification of NP. This review explores the application of machine learning (ML) techniques in predicting various aspects of NPs, including their sequences, cleavage sites, and precursors. Additionally, it provides insights into databases containing NP metadata and specialized tools used in this domain.

Investigating the role of phenylalanine residues for amyloid formation of the neuropeptide neurokinin B

Neurokinin B (NKB) is a tachykinin peptide that has diverse roles in biology, including in human reproductive development. Cellular processing of this peptide is thought to involve formation of a dense core vesicle during transit through the regulated secretory pathway. The ability of NKB to rapidly form an amyloid can contribute to formation of the secretory granule but features that support amyloid formation of NKB are not well understood. NKB contains a diphenylalanine sequence well recognised as an important motif for self-assembly of other peptides including amyloid β. Using mutations of the diphenylalanine motif we show that this motif in NKB is necessary for amyloid formation, and it is the unique combination of aromaticity and hydrophobicity of phenylalanine that is crucial for aggregation. Using disulfide cross-linking we propose that phenylalanine at sequence position 6 is important for stabilising inter-sheet interactions in the NKB amyloid fibril. Although having a highly conserved sequence, the NKB peptide from zebrafish only contains a single phenylalanine and does not fibrillise as extensively as mammalian NKB. Analysis of self-assembly of NKB-like peptides from different species may help in elucidating their biological roles. Taken together, this work shows that mammalian NKB has evolved, within only 10 residues, a sequence optimised for rapid self-assembly, whilst also containing residues for metal-binding, receptor binding and receptor discrimination.

Multiplex substrate profiling by mass spectrometry for proteases

Proteolysis is a central regulator of many biological pathways and the study of proteases has had a significant impact on our understanding of both native biology and disease. Proteases are key regulators of infectious disease and misregulated proteolysis in humans contributes to a variety of maladies, including cardiovascular disease, neurodegeneration, inflammatory diseases, and cancer. Central to understanding a protease's biological role, is characterizing its substrate specificity. This chapter will facilitate the characterization of individual proteases and complex, heterogeneous proteolytic mixtures and provide examples of the breadth of applications that leverage the characterization of misregulated proteolysis. Here we present the protocol of Multiplex Substrate Profiling by Mass Spectrometry (MSP-MS), a functional assay that quantitatively characterizes proteolysis using a synthetic library of physiochemically diverse, model peptide substrates, and mass spectrometry. We present a detailed protocol as well as examples of the use of MSP-MS for the study of disease states, for the development of diagnostic and prognostic tests, for the generation of tool compounds, and for the development of protease-targeted drugs.

Cathepsin V: Molecular characteristics and significance in health and disease

Human cysteine cathepsins form a family of eleven proteases (B, C, F, H, K, L, O, S, V, W, X/Z) that play important roles in a considerable number of biological and pathophysiological processes. Among them, cathepsin V, also known as cathepsin L2, is a lysosomal enzyme, which is mainly expressed in cornea, thymus, heart, brain, and skin. Cathepsin V is a multifunctional endopeptidase that is involved in both the release of antigenic peptides and the maturation of MHC class II molecules and participates in the turnover of elastin fibrils as well in the cleavage of intra- and extra-cellular substrates. Moreover, there is increasing evidence that cathepsin V may contribute to the progression of diverse diseases, due to the dysregulation of its expression and/or its activity. For instance, increased expression of cathepsin V is closely correlated with malignancies (breast cancer, squamous cell carcinoma, or colorectal cancer) as well vascular disorders (atherosclerosis, aortic aneurysm, hypertension) being the most prominent examples. This review aims to shed light on current knowledge on molecular aspects of cathepsin V (genomic organization, protein structure, substrate specificity), its regulation by protein and non-protein inhibitors as well to summarize its expression (tissue and cellular distribution). Then the core biological and pathophysiological roles of cathepsin V will be depicted, raising the question of its interest as a valuable target that can open up pioneering therapeutic avenues.

Proneuropeptide Y and neuropeptide Y metabolites in healthy volunteers and patients with a pheochromocytoma or paraganglioma

Neuropeptide Y (NPY1-36) is a vasoconstrictor peptide co-secreted with catecholamines by sympathetic nerves, the adrenal medulla, and neoplasms such as pheochromocytomas and paragangliomas (PPGLs). It is produced by the intracellular cleavage of proNPY and metabolized into multiple fragments with distinct biological activities. NPY immunoassays for PPGL have a diagnostic sensitivity ranging from 33 to 100%, depending on the antibody used. We have validated a multiplex micro-UHPLC-MS/MS assay for the specific and sensitive quantification of proNPY, NPY1-39, NPY1-37, NPY1-36, NPY2-36, NPY3-36, NPY1-35, NPY3-35, and the C-flanking peptide of NPY (CPON) (collectively termed NPYs), and determined the NPYs reference intervals and concentrations in 32 PPGL patients before, during, and after surgery. Depending on the peptide measured, NPYs were above the upper reference limit (URL) in 20% to 67% of patients, whereas plasma free metanephrine and normetanephrine, the gold standard for PPGL, were above the URL in 40% and 87% of patients, respectively. Age, sex, tachycardia, and tumor localization were not correlated with NPYs. Plasma free metanephrines performed better than NPYs in the detection of PPGL, but NPYs may be a substitute for an early diagnosis of PPGL for patients that suffer from severe kidney impairment or receiving treatments that interfere with catecholamine reuptake.

Dysregulation of Neuropeptide and Tau Peptide Signatures in Human Alzheimer's Disease Brain

Synaptic dysfunction and loss occur in Alzheimer's disease (AD) brains, which results in cognitive deficits and brain neurodegeneration. Neuropeptides comprise the major group of synaptic neurotransmitters in the nervous system. This study evaluated neuropeptide signatures that are hypothesized to differ in human AD brain compared to age-matched controls, achieved by global neuropeptidomics analysis of human brain cortex synaptosomes. Neuropeptidomics demonstrated distinct profiles of neuropeptides in AD compared to controls consisting of neuropeptides derived from chromogranin A (CHGA) and granins, VGF (nerve growth factor inducible), cholecystokinin, and others. The differential neuropeptide signatures indicated differences in proteolytic processing of their proneuropeptides. Analysis of cleavage sites showed that dibasic residues at the N-termini and C-termini of neuropeptides were the main sites for proneuropeptide processing, and data also showed that the AD group displayed differences in preferred residues adjacent to the cleavage sites. Notably, tau peptide signatures differed in the AD compared to age-matched control human brain cortex synaptosomes. Unique tau peptides were derived from the tau protein through proteolysis using similar and differential cleavage sites in the AD brain cortex compared to the control. Protease profiles differed in the AD compared to control, indicated by proteomics data. Overall, these results demonstrate that dysregulation of neuropeptides and tau peptides occurs in AD brain cortex synaptosomes compared to age-matched controls, involving differential cleavage site properties for proteolytic processing of precursor proteins. These dynamic changes in neuropeptides and tau peptide signatures may be associated with the severe cognitive deficits of AD.