Dynamic Profiling and Binding Affinity Prediction of NBTI Antibacterials against DNA Gyrase Enzyme by...

Area of Science:

• Medicinal Chemistry
• Computational Biology
• Antimicrobial Drug Discovery

Background:

• Bacterial type II topoisomerases are crucial targets for antibacterial chemotherapy.
• Novel bacterial topoisomerase inhibitors (NBTIs) represent a promising new class of antibacterials.

Purpose of the Study:

• To develop predictive models for NBTI binding affinity to bacterial DNA gyrase.
• To facilitate the de novo design and optimization of novel antibacterial agents.

Main Methods:

• Construction of multidimensional DNA gyrase surrogate models for Staphylococcus aureus and Escherichia coli using in vitro NBTI data.
• Molecular dynamics (MD) simulations to investigate NBTI dynamic profiles and binding interactions.
• Linear Interaction Energy (LIE) method for computing binding free energies with in-house derived parameters.

Main Results:

• Developed models accurately predicted IC₅₀ values for 26 NBTIs.
• MD simulations confirmed key hydrogen-bonding and hydrophobic contacts between NBTIs and DNA gyrase.
• LIE method provided accurate binding free energy predictions applicable to Gram-positive and Gram-negative pathogens.

Conclusions:

• An integrated modeling approach combining QSAR and MD simulations accurately predicts NBTI binding affinity.
• This approach is valuable for the rational design and optimization of novel NBTIs.
• The findings contribute to combating resistant bacterial pathogens through improved antibacterial drug development.