Connectivity maps for biosimilar drug discovery in venoms: The case of Gila Monster Venom and the anti-diabetes drug Byetta

Abstract Like most natural product libraries animal venoms have long been recognized as potentially rich source of biologically active molecules with the potential to be mined for the discovery of drugs, drug leads and/or biosimilars. In this work we demonstrate as a proof of concept a novel approach to explore venoms for potential biosimilarity to other drugs based on their ability to alter the transcriptomes of test cell lines followed by informatic searches and Connectivity Mapping to match the action of the venom on the cell gene expression to that of other drugs in the Connectivity Map (C-Map) database. As our test animal venom we chose Heloderma suspectum venom (Gila monster) since exendin-4, a glucagon-like peptide 1 receptor agonist, isolated from the venom is currently on the market to treat type 2 diabetes. The action of Byetta ® (exentide, synthetic exendin-4), was also used in transcriptome studies. Analysis of transcriptomes from cells treated with the venom or the drug showed similarities as well as differences. The former case was primarily attributed to the fact that Gila monster venom likely contains a variety of biologically active molecules that could alter the MCF7 cell transcriptome compared to that of the single perturbant Byetta ® . Using Ingenuity Pathway Analysis software, insulin-like growth factor 1 signaling was identified in the category of “Top Canonical Pathways” for both the venom and Byetta ® . In the category of “Top Molecules” up-regulated, both venom and Byetta ® shared IL-8, cyclic AMP-dependent transcription factor 3 (ATF-3), neuron-derived orphan receptor 1 (NR4A3), dexamethasone-induced Ras-related protein 1 (RASD1) and early growth response protein 1, (EGR-1) all with potential relevance in diabetes. Using Connectivity Mapping, Gila monster venom showed positive correlation with 1732 instances and negative correlation with 793 instances in the Connectivity database whereas Byetta ® showed positive correlation with 1692 instances and negative correlation with 868 instances. Interestingly, the Gila monster venom and Byetta ® both showed positive correlation with the anti-diabetic drugs troglitazone, of the thiazolidinedione class, and metformin, of the biguanide class, although Byetta ® as a glucagon-like peptide-1 (GLP-1) agonist functions in a different manner than either of these two classes of anti-diabetic drugs. In summary, despite the fact that Gila monster venom contains a mixture of biologically active molecules, similarities in terms of perturbation of gene expression profiles on MCF7 cells were observed between the venom and the drug Byetta ® . Furthermore, using Connectivity Mapping the Gila monster venom was demonstrated to have nodes of positive correlation to several anti-diabetic drugs two of which were the same as observed with Byetta ® . Therefore, this study suggests that by using this approach novel drug activities heretofore unconsidered may be discovered in venoms using informatic tools and Connectivity Mapping.