Prospective performance evaluation of selected common virtual screening tools. Case study: Cyclooxygenase (COX) 1 and...

Area of Science:

• Computational chemistry and drug discovery.
• Pharmacology and cheminformatics.

Background:

• Computational methods accelerate drug development by identifying lead compounds and predicting properties.
• Selecting the optimal virtual screening (VS) technique for specific research goals remains challenging.

Purpose of the Study:

• To prospectively evaluate and compare the performance of common virtual screening methods.
• To assess the impact of different VS approaches on hit identification and prioritization in drug discovery.

Main Methods:

• Compared pharmacophore modeling, shape-based modeling, and docking for virtual screening.
• Validated VS hits using external bioactivity profiling tools and in vitro assays.
• Assessed performance based on hit rates, true/false positives, and hitlist composition.

Main Results:

• All evaluated virtual screening methods demonstrated effectiveness.
• Significant differences were observed in hit rates, accuracy (true/false positives), and the composition of identified hitlists.
• The choice of VS method directly influenced the outcomes of the drug discovery process.

Conclusions:

• A rational, objective-driven selection of computational methods is crucial for maximizing success in drug discovery projects.
• Understanding the distinct performances of various VS tools enables more efficient prioritization of potential drug candidates.