Discovering Novel Drug Targets in Clostridioides difficile and Proposing FtsZ Inhibitors via Structure-Based Virtual...

Area of Science:

• Computational drug discovery
• Microbiology
• Structural biology

Background:

• Clostridioides difficile (C. diff) is a significant healthcare-associated pathogen.
• Rising antibiotic resistance necessitates novel therapeutic strategies.
• Older adults are particularly vulnerable to severe C. diff infections.

Purpose of the Study:

• To identify novel drug targets and inhibitors for Clostridioides difficile.
• To computationally screen for compounds effective against C. diff.
• To address the challenge of antibiotic resistance in C. diff infections.

Main Methods:

• In silico identification of C. diff drug targets using bioinformatics tools (EDGAR, PSORTb).
• Structure-based virtual screening of compounds against the FtsZ protein using molecular docking and dynamics simulations.
• Evaluation of binding affinity, drug-likeness (Lipinski's Rule of Five), and ADMET properties.

Main Results:

• Six potential drug targets were identified, including FtsZ.
• Virtual screening identified 27 high-affinity ligands for FtsZ.
• Fasamycin C and formicamycin D demonstrated strong binding affinity and favorable drug-like properties.
• Molecular dynamics simulations confirmed the stability of FtsZ-ligand complexes.

Conclusions:

• FtsZ is a promising drug target for C. diff.
• Fasamycin C and formicamycin D are potential inhibitors for C. diff infections.
• Computational methods accelerate antimicrobial drug discovery for resistant pathogens.
• Further in vitro and in vivo validation is required.