Work

A computer‐aided drug repurposing: the antibacterial agents targeting GroEL

Year: 2025
Type: article
Abstract: BACKGROUND AND PURPOSE: Drug repurposing (DR) presents a compelling alternative to traditional drug discovery, offering lower risk and cost by applying approved drugs to new indications. Computational methods play a vital role in early-stage drug repurposing and the development of robust computational workflows can accelerate antibiotic discovery. EXPERIMENTAL APPROACH: We established a novel computational workflow comprising three key steps: target screening (based on CEG 2.0 database), drug screening (utilizing DrugBank database, antiBac-Pred database, molecular docking and molecular dynamics [MD] simulation) and in vitro antibacterial experiments. KEY RESULTS: Our workflow identified numerous commercially available drugs predicted to target the bacterial chaperone GroEL. Antibacterial assays revealed that both daprodustat and ezetimibe exhibited efficacy against Staphylococcus aureus and Escherichia coli ΔtolC. Notably, the efflux pump inhibitor PAβN enhanced the antibacterial efficacy of daprodustat against both S. aureus and E. coli, while potentiating the antibacterial potency of ezetimibe specifically against S. aureus. MD simulations confirmed stable binding of both drugs to S. aureus or E. coli GroEL, aligning with the antibacterial results. CONCLUSION AND IMPLICATIONS: This study validated our computational workflow for repurposing non-antibacterial drugs as antibacterial agents, demonstrating that cost-effective, computer-aided drug repurposing is a feasible strategy for identifying new therapeutic approaches to diseases, such as cancer, diabetes and COVID-19. Furthermore, the synergistic effect of daprodustat combined with an efflux pump inhibitor (e.g. PAβN) represents a promising therapeutic approach against both Gram-positive and Gram-negative bacterial pathogens.
Authors: Dongdong Zhang, Feng‐Biao Guo, Haotian Li
Language: English
Open Access status: bronze
OpenAlex ID: W4416251496
FWCI: 0.993
Cites: 40
Cited by: 2
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