Automated molecular simulation based binding affinity calculator for ligand-bound HIV-1 proteases

Area of Science:

• Biomedical simulations
• Computational drug discovery
• Molecular modeling

Background:

• High-throughput molecular simulations are crucial for determining biochemical properties.
• Assessing antiretroviral inhibitor efficacy against HIV strains requires calculating drug-protein binding affinities.
• Current methods may not operate on a clinically relevant timescale.

Purpose of the Study:

• To introduce the Binding Affinity Calculator (BAC), a tool for automated calculation of HIV-1 protease-ligand binding affinities.
• To enable high-throughput molecular dynamics simulations for drug resistance assessment.
• To provide quantitative, clinically relevant information on drug resistance within 96 hours.

Main Methods:

• Utilizes fully atomistic molecular simulations.
• Employs the molecular mechanics Poisson-Boltzmann solvent accessible surface area (MMPBSA) free energy methodology.
• Automates all stages: model preparation, equilibration, simulation, postprocessing, and data-marshaling on computational grids.

Main Results:

• Successfully calculated binding free energies for HIV-1 protease-ligand complexes, including FDA-approved inhibitors and natural substrates.
• Enabled ranking of inhibitor efficacy across protease mutant strains relative to wildtype.
• Demonstrated quantitative information on drug resistance at the molecular level within 96 hours.

Conclusions:

• BAC facilitates high-throughput molecular dynamics, offering a significant advancement over manual methods.
• The tool provides clinically relevant insights into drug resistance, aiding patient-specific treatment decisions.
• BAC supports decision-making for optimal drug treatment and therapy response assessment based on genotype.