PreprintArticleVersion 3Preserved in Portico This version is not peer-reviewed
Logic-Based Modeling and Drug Repurposing for the Prediction of Novel Therapeutic Targets and Combination Regimens against E2F1-Driven Melanoma Progression
Version 1
: Received: 12 August 2021 / Approved: 16 August 2021 / Online: 16 August 2021 (11:34:01 CEST)
Version 2
: Received: 17 August 2021 / Approved: 17 August 2021 / Online: 17 August 2021 (11:00:27 CEST)
Version 3
: Received: 12 June 2023 / Approved: 12 June 2023 / Online: 12 June 2023 (10:22:29 CEST)
Singh, N.; Khan, F.M.; Bala, L.; Vera, J.; Wolkenhauer, O.; Pützer, B.; Logotheti, S.; Gupta, S.K. Logic-Based Modeling and Drug Repurposing for the Prediction of Novel Therapeutic Targets and Combination Regimens against E2F1-Driven Melanoma Progression. BMC Chemistry 2023, 17, doi:10.1186/s13065-023-01082-2.
Singh, N.; Khan, F.M.; Bala, L.; Vera, J.; Wolkenhauer, O.; Pützer, B.; Logotheti, S.; Gupta, S.K. Logic-Based Modeling and Drug Repurposing for the Prediction of Novel Therapeutic Targets and Combination Regimens against E2F1-Driven Melanoma Progression. BMC Chemistry 2023, 17, doi:10.1186/s13065-023-01082-2.
Singh, N.; Khan, F.M.; Bala, L.; Vera, J.; Wolkenhauer, O.; Pützer, B.; Logotheti, S.; Gupta, S.K. Logic-Based Modeling and Drug Repurposing for the Prediction of Novel Therapeutic Targets and Combination Regimens against E2F1-Driven Melanoma Progression. BMC Chemistry 2023, 17, doi:10.1186/s13065-023-01082-2.
Singh, N.; Khan, F.M.; Bala, L.; Vera, J.; Wolkenhauer, O.; Pützer, B.; Logotheti, S.; Gupta, S.K. Logic-Based Modeling and Drug Repurposing for the Prediction of Novel Therapeutic Targets and Combination Regimens against E2F1-Driven Melanoma Progression. BMC Chemistry 2023, 17, doi:10.1186/s13065-023-01082-2.
Abstract
Skin melanoma presents increasing prevalence and poor outcomes. Progression to aggressive stages is characterized by overexpression of the transcription factor E2F1 and activation of downstream prometastatic gene regulatory networks (GRNs). Appropriate therapeutic manipulation of the E2F1-governed GRNs holds the potential to prevent metastasis however, these networks entail complex feedback and feedforward regulatory motifs among various regulatory layers, which make it difficult to identify druggable components. To this end, computational approaches such as mathematical modeling and virtual screening are important tools to unveil the dynamics of these signaling networks and identify critical components that could be further explored as therapeutic targets. Herein, we integrated a well-established E2F1-mediated epithelial-mesenchymal transition (EMT) map with transcriptomics data from E2F1-expressing melanoma cells to reconstruct a core regulatory network underlying aggressive melanoma. Using logic-based in silico perturbation experiments of a core regulatory network, we identified that simultaneous perturbation of Protein kinase B (AKT1) and oncoprotein murine double minute 2 (MDM2) drastically reduces EMT in melanoma. Using the structures of the two protein signatures, virtual screening strategies were performed with the FDA-approved drug library. Thus, by combining drug repurposing and computer-aided drug design techniques, followed by molecular dynamics simulation analysis identified two potent drugs (Cialis and Finasteride) that can efficiently inhibit AKT1 and MDM2 protein signatures respectively, and with better therapeutic properties. We proposed that these two drugs could be considered for the development of therapeutic strategies for the management of aggressive melanoma.
Keywords
Melanoma; Core regulatory network; in silico perturbationSystems pharmacology; Boolean model; Small molecule inhibitors; Virtual screening; ADME; E2F1
Subject
Medicine and Pharmacology, Oncology and Oncogenics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Received:
12 June 2023
Commenter:
Shailendra K. Gupta
Commenter's Conflict of Interests:
Author
Comment:
The manuscript is recently extended by including the FDA-approved drug library from the ZINC database. We performed a virtual screening of repurposed drugs and added trajectory analysis for the validation of binding profiles. Based on that, we identified two potent drugs that can efficiently inhibit our protein signatures and could be used as therapeutic options for aggressive melanoma treatment.
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Commenter: Shailendra K. Gupta
Commenter's Conflict of Interests: Author