Blueprint for antimicrobial hit discovery targeting metabolic networks

Area of Science:

• Genomics
• Network Biology
• Computational Chemistry
• Drug Discovery

Background:

• Drug discovery faces challenges in identifying novel targets and effective small molecules.
• System-level approaches are needed to integrate biological networks with molecular modeling.
• Antibiotic resistance necessitates innovative strategies for anti-infective therapy.

Purpose of the Study:

• To demonstrate a drug discovery pipeline integrating system-level target identification with atomistic molecular modeling.
• To identify common antibiotic targets in Escherichia coli and Staphylococcus aureus.
• To validate computationally predicted inhibitors experimentally.

Main Methods:

• Deduction of shared essential metabolic reactions in bacterial metabolic networks.
• Virtual screening of small molecules against identified enzyme targets.
• In vitro enzyme inhibition assays and bacterial cell viability assays.

Main Results:

• Identified shared essential metabolic reactions as common antibiotic targets in E. coli and S. aureus.
• Predicted and experimentally validated a subset of small molecules as potent enzyme inhibitors.
• Demonstrated inhibition of enzyme activity and reduction in bacterial cell viability by validated compounds.

Conclusions:

• The developed pipeline effectively integrates systems biology and computational chemistry for drug discovery.
• This approach is applicable to any sequenced organism with a metabolic reconstruction.
• Suggests a generalizable strategy for developing strain-specific anti-infective therapies.