Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments

Computational Approaches to Predict Protein-Protein Interactions in Crowded Cellular Environments

March 27, 2024 | Greta Grassmann, Mattia Miotto, Fausta Desantis, Lorenzo Di Rienzo, Gian Gaetano Tartaglia, Annalisa Pastore, Giancarlo Ruocco, Michele Monti, Edoardo Milanetti
This review, published in the Chemical Reviews virtual special issue "Molecular Crowding," focuses on computational approaches to predict protein-protein interactions (PPIs) in crowded cellular environments. The authors highlight the importance of considering the impact of molecular crowding on protein behavior, including structural stability, diffusion, and binding affinity. They discuss various theoretical and computational methods, such as statistical mechanics for lattice simulations, hydrodynamic interactions, and molecular dynamics (MD) simulations, to model biological systems and complement experimental studies. The review explores how these methods can advance the understanding and prediction of PPIs in the crowded environment of the cell cytoplasm, potentially revolutionizing the characterization of the human interactome. The authors emphasize the need for a synergistic approach combining biophysics and computational biology to address the complex dynamics of protein interactions in crowded environments.This review, published in the Chemical Reviews virtual special issue "Molecular Crowding," focuses on computational approaches to predict protein-protein interactions (PPIs) in crowded cellular environments. The authors highlight the importance of considering the impact of molecular crowding on protein behavior, including structural stability, diffusion, and binding affinity. They discuss various theoretical and computational methods, such as statistical mechanics for lattice simulations, hydrodynamic interactions, and molecular dynamics (MD) simulations, to model biological systems and complement experimental studies. The review explores how these methods can advance the understanding and prediction of PPIs in the crowded environment of the cell cytoplasm, potentially revolutionizing the characterization of the human interactome. The authors emphasize the need for a synergistic approach combining biophysics and computational biology to address the complex dynamics of protein interactions in crowded environments.
Reach us at info@study.space