Protein-Ligand Blind Docking Using QuickVina-W With Inter-Process Spatio-Temporal Integration

Area of Science:

• Computational chemistry
• Drug discovery
• Bioinformatics

Background:

• Virtual screening and molecular docking are crucial in silico drug design.
• Traditional docking methods are computationally intensive, limiting their application to small binding sites and requiring manual merging for blind docking.
• Existing methods face challenges with large search spaces and long computation times, especially in blind docking scenarios.

Purpose of the Study:

• To investigate the relationship between search progression and Average Sum of Proximity relative Frequencies (ASoF) in docking threads.
• To develop an improved docking tool for efficient and accurate blind docking.
• To overcome the limitations of existing docking tools regarding search space size and residue number.

Main Methods:

• Studied the correlation between search progression and ASoF of searching threads.
• Developed QuickVina-W, a novel docking tool utilizing an inter-process spatio-temporal integration method.
• Employed QuickVina-W for blind docking without predefined target pockets or search space limitations.

Main Results:

• QuickVina-W demonstrates superior performance compared to Quick Vina 2 and AutoDock Vina.
• The new tool achieves higher speed and accuracy in docking simulations.
• Successfully enables blind docking across large search spaces and with numerous residues.

Conclusions:

• QuickVina-W offers a significant advancement for virtual screening in drug design.
• The tool facilitates rapid and accurate screening of extensive ligand libraries.
• Eliminates the need for prior definition of target pockets, streamlining the drug discovery process.