Stingray Venom Proteins: Mechanisms of Action Revealed Using a Novel Network Pharmacology Approach

Animal venoms offer a valuable source of potent new drug leads, but their mechanisms of action are largely unknown. We therefore developed a novel network pharmacology approach based on multi-omics functional data integration to predict how stingray venom disrupts the physiological systems of target...

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Main Authors: Kim N. Kirchhoff, André Billion, Christian R. Voolstra, Stephan Kremb, Thomas Wilke, Andreas Vilcinskas
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Marine Drugs
Subjects:
Online Access:https://www.mdpi.com/1660-3397/20/1/27
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author Kim N. Kirchhoff
André Billion
Christian R. Voolstra
Stephan Kremb
Thomas Wilke
Andreas Vilcinskas
author_facet Kim N. Kirchhoff
André Billion
Christian R. Voolstra
Stephan Kremb
Thomas Wilke
Andreas Vilcinskas
author_sort Kim N. Kirchhoff
collection DOAJ
description Animal venoms offer a valuable source of potent new drug leads, but their mechanisms of action are largely unknown. We therefore developed a novel network pharmacology approach based on multi-omics functional data integration to predict how stingray venom disrupts the physiological systems of target animals. We integrated 10 million transcripts from five stingray venom transcriptomes and 848,640 records from three high-content venom bioactivity datasets into a large functional data network. The network featured 216 signaling pathways, 29 of which were shared and targeted by 70 transcripts and 70 bioactivity hits. The network revealed clusters for single envenomation outcomes, such as pain, cardiotoxicity and hemorrhage. We carried out a detailed analysis of the pain cluster representing a primary envenomation symptom, revealing bibrotoxin and cholecystotoxin-like transcripts encoding pain-inducing candidate proteins in stingray venom. The cluster also suggested that such pain-inducing toxins primarily activate the inositol-3-phosphate receptor cascade, inducing intracellular calcium release. We also found strong evidence for synergistic activity among these candidates, with nerve growth factors cooperating with the most abundant translationally-controlled tumor proteins to activate pain signaling pathways. Our network pharmacology approach, here applied to stingray venom, can be used as a template for drug discovery in neglected venomous species.
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spelling doaj.art-516bde2f5b224f3fb204e67f17a2bde32023-11-23T14:27:38ZengMDPI AGMarine Drugs1660-33972021-12-012012710.3390/md20010027Stingray Venom Proteins: Mechanisms of Action Revealed Using a Novel Network Pharmacology ApproachKim N. Kirchhoff0André Billion1Christian R. Voolstra2Stephan Kremb3Thomas Wilke4Andreas Vilcinskas5Department of Animal Ecology and Systematics, Justus Liebig University Giessen, Heinrich-Buff-Ring 26-32, 35392 Giessen, GermanyDepartment of Bioresources, Fraunhofer Institute for Molecular Biology and Applied Ecology, Ohlebergsweg 12, 35392 Giessen, GermanyDepartment of Biology, University of Konstanz, 78457 Konstanz, GermanyRed Sea Research Center, Division of Biological and Environmental Science and Engineering (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi ArabiaDepartment of Animal Ecology and Systematics, Justus Liebig University Giessen, Heinrich-Buff-Ring 26-32, 35392 Giessen, GermanyDepartment of Bioresources, Fraunhofer Institute for Molecular Biology and Applied Ecology, Ohlebergsweg 12, 35392 Giessen, GermanyAnimal venoms offer a valuable source of potent new drug leads, but their mechanisms of action are largely unknown. We therefore developed a novel network pharmacology approach based on multi-omics functional data integration to predict how stingray venom disrupts the physiological systems of target animals. We integrated 10 million transcripts from five stingray venom transcriptomes and 848,640 records from three high-content venom bioactivity datasets into a large functional data network. The network featured 216 signaling pathways, 29 of which were shared and targeted by 70 transcripts and 70 bioactivity hits. The network revealed clusters for single envenomation outcomes, such as pain, cardiotoxicity and hemorrhage. We carried out a detailed analysis of the pain cluster representing a primary envenomation symptom, revealing bibrotoxin and cholecystotoxin-like transcripts encoding pain-inducing candidate proteins in stingray venom. The cluster also suggested that such pain-inducing toxins primarily activate the inositol-3-phosphate receptor cascade, inducing intracellular calcium release. We also found strong evidence for synergistic activity among these candidates, with nerve growth factors cooperating with the most abundant translationally-controlled tumor proteins to activate pain signaling pathways. Our network pharmacology approach, here applied to stingray venom, can be used as a template for drug discovery in neglected venomous species.https://www.mdpi.com/1660-3397/20/1/27transcriptomicshigh-content screeningmulti-omics data integrationdrug discoveryvenomics
spellingShingle Kim N. Kirchhoff
André Billion
Christian R. Voolstra
Stephan Kremb
Thomas Wilke
Andreas Vilcinskas
Stingray Venom Proteins: Mechanisms of Action Revealed Using a Novel Network Pharmacology Approach
Marine Drugs
transcriptomics
high-content screening
multi-omics data integration
drug discovery
venomics
title Stingray Venom Proteins: Mechanisms of Action Revealed Using a Novel Network Pharmacology Approach
title_full Stingray Venom Proteins: Mechanisms of Action Revealed Using a Novel Network Pharmacology Approach
title_fullStr Stingray Venom Proteins: Mechanisms of Action Revealed Using a Novel Network Pharmacology Approach
title_full_unstemmed Stingray Venom Proteins: Mechanisms of Action Revealed Using a Novel Network Pharmacology Approach
title_short Stingray Venom Proteins: Mechanisms of Action Revealed Using a Novel Network Pharmacology Approach
title_sort stingray venom proteins mechanisms of action revealed using a novel network pharmacology approach
topic transcriptomics
high-content screening
multi-omics data integration
drug discovery
venomics
url https://www.mdpi.com/1660-3397/20/1/27
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