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Updated: Sep 17, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
Published on: February 23, 2024
Exploring Protein-Protein Docking Tools: Comprehensive Insights into Traditional and Deep-Learning Approaches
Mina Barhoon1, Hamid Mahdiuni1
1Bioinformatics Lab., Department of Biology, School of Sciences, Razi University, P.O. Box Kermanshah 67149-67346, Iran.
Abstract:
Protein-protein interactions are crucial for numerous biological activities such as signaling, enzyme catalysis, gene expression regulation, cell adhesion, immune response, and drug action. Structural characterization of these interactions can elucidate the functions of proteins in living systems, as well as for designing novel therapeutics with high specificity and low toxicity. Since experimental characterization is difficult, several computational tools have been developed for protein-protein docking. However, it may be difficult for many researchers and scientists to find the most suitable tool quickly. This assessment provides a comprehensive review of the commonly used tools for protein-protein docking analysis, which consists of deep-learning-based and traditional tools. In addition, the advantages and limitations of each tool are also discussed in this paper and further help researchers select more suitable tools for their study.
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