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July 2, 20260 citationsOpen Access

Multi-target computational drug repurposing identifies FDA-approved candidates with micronutrient-dependent efficacy modulation for pancreatic ductal adenocarcinoma: the ARES v5 pipeline

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LMLUIS MIGUEL MORENO MENDEZ

Key Points

  • To identify FDA-approved drugs that can be repurposed effectively for pancreatic ductal adenocarcinoma (PDAC) using a multi-target computational approach.
  • Developed ARES v5 computational pipeline to screen 333 FDA-approved and investigational compounds against six oncogenic targets.
  • Utilized molecular docking and ADMET filtering to analyze compound efficacy and safety profiles.
  • Incorporated micronutrient-dependent efficacy adjustments based on patient nutritional status.
  • Confirmed accuracy with known inhibitors; Olaparib and Apixaban ranked as top candidates with binding to 5 of 6 targets.
  • Both compounds demonstrated significant sensitivity to micronutrient availability, with Mg2+ identified as a limiting factor.
  • Olaparib remains effective for BRCA-mutated patients, while Apixaban shows promise across a broader patient population.

Abstract

Background: Pancreatic ductal adenocarcinoma (PDAC) remains the most lethal solid tumor, with a 5-year survival rate of 13% and limited therapeutic options. Current standard-of-care regimens, gemcitabine-based and FOLFIRINOX, provide modest survival benefit, and targeted therapies remain restricted to the approximately 7% of patients harboring BRCA1/2 mutations. Drug repurposing offers a strategy to rapidly identify candidates with established safety profiles for PDAC. Methods: We developed ARES v5, a multi-target computational pipeline that screens 333 compounds (FDA-approved drugs, investigational agents, and structural analogs) against six oncogenic targets critical in PDAC signaling: EGFR, KRAS, STAT3, SOS1, HSP90, and JAK2. The pipeline integrates molecular docking (AutoDock Vina 1. 2. 7), ADMET filtering based on structural alerts (hERG, hepatotoxicity, Ames, BBB), synergy analysis with established PDAC therapies, consensus scoring, and a novel micronutrient-dependent efficacy correction module that adjusts predicted binding based on cofactor dependencies specific to PDAC patient nutritional status. Results: Internal cross-validation with five known inhibitors (Gefitinib, Rucaparib, Axitinib, Sunitinib, Momelotinib) confirmed pipeline accuracy. Sensitivity analysis across three weight configurations demonstrated that Olaparib (rank 1) and Apixaban (rank 2) maintained top-3 FDA-approved positions in all configurations, establishing conclusion robustness. Among 212 ADMET-clean compounds, Olaparib (scorefinal = 0. 8875) and Apixaban (scorefinal = 0. 8787) emerged as the top FDA-approved candidates, each binding 5 of 6 targets with favorable docking energies (best dG: -9. 26 and -8. 64 kcal/mol, respectively). Both compounds showed high micronutrient-dependent sensitivity (45% score reduction with cofactor depletion), with Mg2+ identified as the critical limiting cofactor. Conclusions: ARES v5 identifies Olaparib and Apixaban as robust multi-target candidates for PDAC. While Olaparib's efficacy is limited to BRCA-mutated patients (7% of PDAC), Apixaban targets conserved oncogenic pathways active in more than 90% of PDAC cases. The finding that Apixaban, a generic anticoagulant available globally for less than 1 EUR per day, shows strong multi-target binding against PDAC-critical kinases warrants urgent experimental validation, particularly given the convergence with Edoxaban's experimentally demonstrated STAT3 suppression via the Factor Xa-PAR2 axis.

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LUIS MIGUEL MORENO MENDEZ (2026) studied this question.

synapsesocial.com/papers/6a4600a29ed1343031310a89https://doi.org/10.5281/zenodo.21074401
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Abstract 980: Multimodal chemogenomic modeling-based drug repurposing for targeted therapy of PDAC2026
  2. 2Prediction of therapeutic targets and drug candidates for pancreatic ductal adenocarcinoma by network-based computational framework2026
  3. 3Targeting Advanced Pancreatic Ductal Adenocarcinoma: A Practical Overview2025 · 2 citations
  4. 4A systems-level omics and hallmark–based analysis of pancreatic cancer for the identification of potential multi-target drugs.2026
  5. 5Abstract 6485: Profile guided low dose drug combination strategies and kinase activities with prognostic and therapeutic avenues in pancreatic ductal adenocarcinoma2024