title: Case-specific performance of MM-PBSA, MM-GBSA, and SIE in virtual screening.
abstract: In drug discovery the reliable prediction of binding free energies is of crucial importance. Methods that combine molecular mechanics force fields with continuum solvent models have become popular because of their high accuracy and relatively good computational efficiency. In this research we studied the performance of molecular mechanics generalized Born surface area (MM-GBSA), molecular mechanics Poisson-Boltzmann surface area (MM-PBSA), and solvated interaction energy (SIE) both in their virtual screening efficiency and their ability to predict experimentally determined binding affinities for five different protein targets. The protein-ligand complexes were derived with two different approaches important in virtual screening: molecular docking and ligand-based similarity search methods. The results show significant differences between the different binding energy calculation methods. However, the length of the molecular dynamics simulation was not of crucial importance for accuracy of results.
authors.affiliation: University of Jyvaskyla, Computational Bioscience Laboratory, Department of Biological and Environmental Science & Nanoscience Center, P.O. Box 35, FI-40014 University of Jyvaskyla, Finland.
authors.forename: Salla I
authors.initials: SI
authors.lastname: Virtanen
authors.affiliation: University of Jyvaskyla, Computational Bioscience Laboratory, Department of Biological and Environmental Science & Nanoscience Center, P.O. Box 35, FI-40014 University of Jyvaskyla, Finland.
authors.forename: Sanna P
authors.initials: SP
authors.lastname: Niinivehmas
authors.affiliation: University of Jyvaskyla, Computational Bioscience Laboratory, Department of Biological and Environmental Science & Nanoscience Center, P.O. Box 35, FI-40014 University of Jyvaskyla, Finland. Electronic address: olli.t.pentikainen@jyu.fi.
authors.forename: Olli T
authors.initials: OT
authors.lastname: Pentikäinen
mesh_terms: D000449:Aldehyde Reductase / Q000737:chemistry; D019540:Area Under Curve; D001426:Bacterial Proteins / Q000737:chemistry; D001665:Binding Sites; D055808:Drug Discovery / Q000379:methods; D018841:HSP90 Heat-Shock Proteins / Q000737:chemistry; D006801:Humans; D006860:Hydrogen Bonding; D057927:Hydrophobic and Hydrophilic Interactions; D008956:Models, Chemical; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D010726:Phosphodiesterase Inhibitors / Q000737:chemistry; D010727:Phosphoric Diester Hydrolases / Q000737:chemistry; D011485:Protein Binding; D012372:ROC Curve; D011980:Receptors, Progesterone / Q000737:chemistry; D065093:beta-Lactamase Inhibitors / Q000737:chemistry; D001618:beta-Lactamases / Q000737:chemistry
chemical_list: D001426:Bacterial Proteins; D018841:HSP90 Heat-Shock Proteins; D010726:Phosphodiesterase Inhibitors; D011980:Receptors, Progesterone; D065093:beta-Lactamase Inhibitors; C484670:AKR1B1 protein, human; D000449:Aldehyde Reductase; D010727:Phosphoric Diester Hydrolases; C048795:AmpC beta-lactamases; D001618:beta-Lactamases
keywords: Aldose reductase 2; Ampc beta-lactamase; Docking; Heat shock protein 90; Molecular dynamics simulation; Molecular mechanics Poisson–Boltzmann surface area (MM-PBSA); Molecular mechanics generalized Born surface area (MM-GBSA); Phosphodiesterase; Progesterone receptor; Shape comparison; Solvated interaction energy (SIE); Virtual screening