2026-10-14T00:15:29Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33812089 2026-09-15T17:42:01Z category_1 category_4 category_7 category_13 category_14 category_19 category_21 category_502 category_734 category_931 category_64 category_122 portal_5 item_type_3 month_year_09_2026

<p>Candidate Drugs from Primary Cluster of Interest.</p> Thomas E. Diaz (18400530) Joseph A. Kerrigan Jr (24948778) Dawn E. Bowles (12068354) Yared H. Kidane (16814494) Biophysics Biochemistry Medicine Genetics Molecular Biology Pharmacology Biotechnology Astronomical and Space Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified Cancer Mental Health leveraging bioinformatics techniques leveraging bioinformatics approaches generate pharmacological hypotheses future computational characterization established pharmacological countermeasures duration spaceflight missions dock2 molecular docking accelerate pharmaceutical research predicted using drugst explored using cb generating structural assessments functional enrichment analyses experimentally supported interactions potential drug candidates identify candidate drugs space radiation countermeasures drug repositioning offers space radiation drug repositioning constructed using generating framework analyses demonstrate space medicine macromolecule interactions selected drug xlink "> systematic approach strategy introduces significant threat seed nodes protein interactions promising strategy markov clustering ion gcrs health effects gcrs ), gcr exposure experimental investigation <div><p>The health effects of space radiation, primarily Galactic Cosmic Rays (GCRs), on humans remain largely unknown, with potential cardiovascular consequences posing a significant threat to astronauts on long-duration spaceflight missions. Currently, there are no established pharmacological countermeasures for GCR exposure. Drug repositioning offers a promising strategy to accelerate pharmaceutical research in space medicine. This study leverages existing bioinformatics techniques to identify and prioritize potential drug candidates associated with proteomic perturbations following simulated GCR exposure using previously published murine cardiac proteomic data. A protein-protein interaction (PPI) network was constructed using the top differentially expressed proteins (DEPs) from murine heart tissue following exposure to 5-ion GCRs as seed nodes, focusing on experimentally supported interactions. Network topology, Markov clustering, and functional enrichment analyses were used to characterize biologically relevant proteins and pathways. Drug-protein interactions were predicted using Drugst.One and mapped to PPI clusters of interest to identify candidate drugs. Selected drug-macromolecule interactions were further explored using CB-Dock2 molecular docking and short-duration molecular dynamics simulations as hypothesis-generating structural assessments. Analysis of a key PPI network cluster consisting of several ATP synthase proteins identified 23 unique drug candidates. These analyses demonstrate a systematic approach for leveraging bioinformatics techniques to identify candidate molecular targets and generate pharmacological hypotheses in the context of space radiation countermeasures. Ultimately, this strategy introduces a hypothesis-generating framework for the prioritization of potential drug candidates for future computational characterization and experimental investigation against spaceflight stressors.</p></div> 2026-09-15T17:41:46Z Dataset Dataset 10.1371/journal.pone.0357889.t001 https://figshare.com/articles/dataset/_p_Candidate_Drugs_from_Primary_Cluster_of_Interest_p_/33812089 CC BY 4.0