Re-profiling of natural inhibitor via combinatorial drug screening: Brefeldin A variant design as an effective antagonist leading to EPAC2 structure modification and antibody design for identification
Abstract
Drug discovery can be impactful with re-purposing and combinatorial strategies leading to potential pharmaceutical outputs. Epac2 has been a target of interest for various physiological conditions where suppression is inevitable to achieve desired therapeutic effect. Epac isoforms inhibition is crucial in vascular functions to prevent chronic inflammation leading to hypertension and myocardial infarction. An attempt utilizing brefeldin A, a natural inhibitor was subjected to substitution of 3 side chain groups with 43 fragments via combinatorial strategy. This resulted in generating a library of 79507 brefeldin A variants. High throughput virtual screening yielded 68,043 variants followed by precision docking providing 117 lead like brefeldin A variants. The best docked variant (3-((1R,2E,6R,10E,11aS,13S,14A)-6-(methylsulfonamido)-13-(3-methylureido)-4-oxo-4,6,7,8,9,11a,12,13,14,14a-decahydro-1H-cyclopenta[f][1]oxacyclotridecin-1-yl)-2,3-dihydro-1Himidazol-1-ium) has an increased binding efficiency of -10.841 kcal/mol. Simulation studies up to 200ns of complex lead to re-orientation of target tertiary structure resulted in RMSD change of 30.221 [A], suggesting the epac2 structure modification leading to unavailability of RAS-GEF domain and its interaction with Rap1b. A single domain antibody was designed to bind specifically to re-structured epac2 for potential identification over the native target structure. The resulting Brefeldin variant can be potentially labelled as a most effective antagonist against epac2 which induces theoretically irreversible structural re-conformation. This study also provides a robust in-silico workflow for searching of chemical space, generating and screening of combination libraries and the efficient utilization of known inhibitor.
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