Soft docking and multiple receptor conformations in virtual screening

Abstract

Protein conformational change is an important consideration in ligand-docking screens, but it is difficult to predict. A simple way to account for protein flexibility is to soften the criterion for steric fit between ligand and receptor. A more comprehensive but more expensive method would be to sample multiple receptor conformations explicitly. Here, these two approaches are compared. A "soft" scoring function was created by attenuating the repulsive term in the Lennard-Jones potential, allowing for a closer approach between ligand and protein. The standard, "hard" Lennard-Jones potential was used for docking to multiple receptor conformations. The Available Chemicals Directory (ACD) was screened against two cavity sites in the T4 lysozyme. These sites undergo small but significant conformational changes on ligand binding, making them good systems for soft docking. The ACD was also screened against the drug target aldose reductase, which can undergo large conformational changes on ligand binding. We evaluated the ability of the scoring functions to identify known ligands from among the over 200 000 decoy molecules in the database. The soft potential was always better at identifying known ligands than the hard scoring function when only a single receptor conformation was used. Conversely, the soft function was worse at identifying known leads than the hard function when multiple receptor conformations were used. This was true even for the cavity sites and was especially true for aldose reductase. To test the multiple-conformation method predictively, we screened the ACD for molecules that preferentially docked to the expanded conformation of aldose reductase, known to bind larger ligands. Six novel molecules that ranked among the top 0.66% of hits from the multiple-conformation calculation, but ranked relatively poorly in the soft docking calculation, were tested experimentally for enzyme inhibition. Four of these six inhibited the enzyme, the best with an IC(50) of 8 microM. Although ligands can get better scores in soft docking, the same is also true for decoys. The improved ranking of such decoys can come at the expense of true ligands.

Figure 1

Binding sites and conformational changes that the protein structures undergo. (A) Cutaway of the molecular surfaces of the polar cavity L99A/M102Q in its apo conformation (yellow), and the conformation that it adopts in complex with 2-fluoro-6-methylaniline (green). The crystallographic configuration of 2-fluoro-6-methylaniline is shown (carbon in gray, nitrogen in blue, fluorine in magenta). (B) Molecular surfaces of aldose reductase in its smaller, Sorbinil-bound conformations (yellow) and its larger, Tolrestat-bound conformation (green). The crystallographic configuration of Tolrestat is shown. Images were made using NEON in Midas-Plus, as were Figures 4, 6, and 7.

Figure 2

Soft 9-6 (red) versus hard 12-6 (blue) van der Waals potential energies between two sp-hybridized carbon atoms. Parameters were adjusted so that the magnitude and location of the minima for the two functions were the same. (A) In the region near the energy minima. (B) In a broader range of distance.

Figure 3

Enrichment of known ligands for (A) the L99A cavity and (B) the L99A/M102Q cavity from docking screens of the ACD database. Three different scoring functions were used to rank the docked molecules: a 12-6 hard Lennard–Jones potential against the apo-cavity conformation (red), a soft 9-6 Lennard–Jones potential against the same structure (blue), and a multiconformation calculation using a hard potential (green).

Figure 4

Comparing docked and crystallographic geometries of three L99A cavity ligands: (A) p-xylene, (B) benzofuran, and (C) isobutylbenzene. Carbon atoms are colored in green in the crystallographic structures, in yellow in the configurations predicted by multiconformational docking, and in orange in the configurations predicted by 9-6 soft docking. Oxygen atoms are colored in red.

Figure 5

Enrichments of known ligands for aldose reductase from docking screens of the ACD database. As in the cavity sites, three different scoring functions were used to rank the database: a hard-docking calculation against the smaller, Sorbinil-bound conformation of the enzyme (red), a soft-docking calculation against the same structure (blue), and docking using a multiconformational approach (green).

Figure 6

Comparing the binding poses predicted by hard docking against multiple receptor conformations (carbons in orange) or by soft docking against the Sorbinil-bound conformation (carbons in green) to the corresponding crystallographic structures (carbons in gray) for two aldose reductase inhibitors: (A) Zenarestat and (B) Tolrestat. For Zenarestat, the rmsd values of the two predictions are 0.4 and 5.3 Å, respectively; for Tolrestat, the rmsd values are 0.3 and 7.2 Å, respectively. Pictures are in stereo. Dashed lines illustrate hydrogen bonds. Color scheme is as in Figure 1.

Figure 7

Docking-predicted pose for compound 1 (carbon in cyan), a new 8 μM inhibitor, in comparison to the observed geometry of Tolrestat (carbon in gray) in the aldose reductase site. The molecular surfaces of the Sorbinil-bound (yellow) and Tolrestat-bound conformations (green) of the enzyme are shown.