Docking flexible peptide to flexible protein by molecular dynamics using two implicit-solvent models: an evaluation in protein kinase and phosphatase systems.
Reliable prediction of protein-ligand docking pose requires proper account of induced fit effects. Treating both the ligand and the protein as flexible molecules is still challenging because many degrees of freedom are involved. Peptides are one type of ligand that are particularly difficult to study because of their extreme flexibility. In this study, we tested a molecular dynamics-based simulated-annealing cycling protocol in docking peptides to four protein kinases and two phosphatases using two implicit-solvent models: a distance-dependent dielectric model (epsilon(r) = 4r) and a version of the Generalized Born model termed GBMV. We found that the simpler epsilon(r) = 4r model identified docking pose better than the more expensive GBMV model. In addition, rescoring structures obtained from one implicit-solvent model with the other identified good docking poses for all six systems studied. Including protein energy in scoring also improved results.
Department of Chemistry and Biochemistry and Center for Nanoscience, University of Missouri-Saint Louis, One University Boulevard, St. Louis, Missouri 63121, USA.
Zunnan
Z
Huang
Chung F
CF
Wong
D000595:Amino Acid Sequence; D008956:Models, Chemical; D056004:Molecular Dynamics Simulation; D010455:Peptides / Q000737:chemistry* / Q000378:metabolism; D010744:Phosphoric Monoester Hydrolases / Q000737:chemistry* / Q000378:metabolism; D011485:Protein Binding; D011494:Protein Kinases / Q000737:chemistry* / Q000378:metabolism; D012997:Solvents / Q000737:chemistry*; D013816:Thermodynamics
D010455:Peptides; D012997:Solvents; D011494:Protein Kinases; D010744:Phosphoric Monoester Hydrolases