A new concept for multidimensional selection of ligand conformations (MultiSelect) and multidimensional scoring (MultiScore) of protein-ligand binding affinities.
In this work, eight different scoring functions have been combined with the aim of improving the prediction of protein-ligand binding conformations and affinities. The obtained scores were analyzed using multivariate statistical methods to generate expressions, with the ability (1) to select the best candidate between different docked conformations of an inhibitor (MultiSelect) and (2) to quantify the protein-ligand binding affinity (MultiScore). By use of the docking program GOLD, 40 different inhibitors were docked into the active site of three matrix metalloproteinases (MMP's), yielding a total of 120 enzyme-inhibitor complexes. For each complex, a single conformation of the inhibitor was selected using principal component analysis (PCA) for the scores obtained by the eight functions SCORE, LUDI, GRID, PMF_Score, D_Score, G_Score, ChemScore, and F_Score. Binding affinities were estimated based on partial least-squares projections onto latent structures (PLS) on the eight scores of each selected inhibitor conformation. By use of this procedure, R(2) = 0.78 and Q(2) = 0.78 were obtained when comparing experimental and calculated binding affinities. MultiSelect was evaluated by applying the same method for selecting docked conformations for 18 different protein-ligand complexes of known three-dimensional structure. In all cases, the selected ligand conformations were found to be very similar to the experimentally determined ligand conformations. A more general evaluation of MultiScore was performed using a set of 120 different protein-ligand complexes for which both the three-dimensional structures and the binding affinities were known. This approach allowed an evaluation of MultiScore independently of MultiSelect. The generality of the method was verified by obtaining R(2) = 0.68 and Q(2) = 0.67, when comparing calculated and experimental binding affinities for the 120 X-ray structures. In all cases, LUDI, SCORE, GRID, and F_Score were included as important functions, whereas the fifth function was PMF_Score and ChemScore for the MMP and X-ray models, respectively.
Terp
G E
GE
Department of Medicinal Chemistry, Royal Danish School of Pharmacy, Universitetsparken 2, DK-2100 Copenhagen, Denmark.
Johansen
B N
BN
Christensen
I T
IT
Jørgensen
F S
FS
D018360:Crystallography, X-Ray; D008024:Ligands; D061965:Matrix Metalloproteinase Inhibitors; D020782:Matrix Metalloproteinases / Q000737:chemistry; D008958:Models, Molecular; D008968:Molecular Conformation; D015999:Multivariate Analysis; D011480:Protease Inhibitors / Q000737:chemistry; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship
D008024:Ligands; D061965:Matrix Metalloproteinase Inhibitors; D011480:Protease Inhibitors; D011506:Proteins; D020782:Matrix Metalloproteinases