Docking small peptides remains a great challenge: an assessment using AutoDock Vina

Area of Science:

• Computational biology
• Structural biology
• Biochemistry

Background:

• Flexible peptide-protein binding mechanisms and prediction are of significant interest.
• Short peptides (up to five residues) present unique challenges for docking due to high torsional flexibility.
• Existing docking methods and custom protocols have varying success rates for peptide targets.

Purpose of the Study:

• To compile and present a meta-dataset of 47 peptide-protein complexes from 11 studies.
• To benchmark the performance of AutoDock Vina for flexible peptide docking.
• To provide guidelines for reproducible peptide docking studies and encourage standardized benchmarking.

Main Methods:

• Compiled a meta-dataset of 47 peptide-protein complexes (peptides ≤ 5 residues) from 11 studies.
• Performed benchmarking using AutoDock Vina, a freely available docking tool.
• Assessed docking performance based on the quality of the top-scoring peptide pose.

Main Results:

• Provided a comprehensive overview of reported results from 11 studies, despite varying methodologies.
• AutoDock Vina was benchmarked on the compiled dataset.
• Identified the need for guidelines on sampling for result reproducibility in peptide docking.

Conclusions:

• Flexible peptide-protein docking requires specialized benchmarking and clear guidelines.
• The compiled dataset and benchmarking provide a foundation for future standardized efforts.
• Addressing reproducibility issues is crucial for advancing peptide docking accuracy.