How well do the substrates KISS the enzyme? Molecular docking program selection for feruloyl esterases

Area of Science:

• Computational chemistry
• Biochemistry
• Drug discovery

Background:

• Molecular docking is a key computational technique in drug discovery, predicting how small molecules bind to target structures.
• Existing studies often use default software protocols, potentially overlooking optimal parameter tuning for specific targets.
• Feruloyl esterases are industrially relevant enzymes where understanding substrate specificity is important.

Purpose of the Study:

• To identify the best molecular docking and scoring function combinations for predicting substrate specificity in feruloyl esterases.
• To address the limitations of 'black box' evaluations by exploring parameter optimization.
• To introduce a novel evaluation metric, the Key Interaction Score System (KISS), for docking programs.

Main Methods:

• Evaluation of 88 distinct docking algorithm-scoring function combinations.
• Application of these combinations to predict substrate specificity for feruloyl esterases.
• Development and application of the Key Interaction Score System (KISS) for assessing pose prediction accuracy.

Main Results:

• Identification of optimal docking and scoring function pairings for feruloyl esterase substrate specificity.
• Demonstration that parameter selection significantly impacts docking performance.
• Validation of the KISS system as a biochemically relevant measure for docking program evaluation.

Conclusions:

• The selection of docking and scoring functions, along with parameter optimization, is critical for reliable substrate specificity predictions.
• The Key Interaction Score System (KISS) offers a more meaningful approach to evaluating molecular docking programs.
• This work provides a framework for selecting appropriate docking tools for specific enzymatic targets in drug discovery.