Modeling of protein-protein interactions

Modeling of protein-protein interactions

The identification of protein-protein interactions (PPIs) is vital for understanding protein function, elucidating interaction mechanisms, and for practical applications in drug discovery. To improve the state-of-the-art in PPI modeling, we developed eFindSitePPI to predict binding residues in a target protein structure with machine learning, and eRankPPI to identify near-native conformations generated by protein docking with a new scoring function utilizing interface probability estimates and a contact-based symmetry score. Furthermore, we devised a high-throughput protocol for the bottom-up assembly of protein interaction networks based on all-to-all protein docking. These tools can be used to reliably identify and model biologically relevant protein assemblies at the proteome scale.

For more information see:
1 Maheshwari S, Brylinski M. (2015) Predicted binding site information improves model ranking in protein docking using experimental and computer-generated target structures. BMC Struct Biol 15 (1): 23.     
2 Maheshwari S, Brylinski M. (2015) Prediction of protein-protein interaction sites from weakly homologous template structures using meta-threading and machine learning. J Mol Recognit 28 (1): 35-48.     
3 Maheshwari S, Brylinski M. (2015) Predicting protein interface residues using easily accessible on-line resources. Brief Bioinform 16 (6): 1025-34.     
4 Maheshwari S, Brylinski M. (2016) Template-based identification of protein-protein interfaces using eFindSite(PPI). Methods 93: 64-71.     
5 Maheshwari S, Brylinski M. (2017) Across-proteome modeling of dimer structures for the bottom-up assembly of protein-protein interaction networks. BMC Bioinformatics 18 (1): 257.