SEARCH

SEARCH BY CITATION

Abstract

  1. Top of page
  2. Abstract
  3. Induced Fit Docking
  4. References

Structured-based drug design has traditionally relied on a single receptor structure as a target for docking and screening studies. However, it has become increasingly clear that in many cases where protein flexibility is an issue, it is critical to accurately model ligand-induced receptor movement in order to obtain high enrichment factors. We present a novel protein-ligand docking method that accounts for both ligand and receptor flexibility and accurately predicts the conformation of protein-ligand binding complexes. This method can generate viable receptor ensembles that can be used in virtual database screens.


Induced Fit Docking

  1. Top of page
  2. Abstract
  3. Induced Fit Docking
  4. References

Schrödinger has developed technology that accounts for receptor flexibility in ligand-receptor docking by iteratively combining rigid receptor docking [using Glide (1,2)] with protein structure prediction and refinement [using Prime (3–5)] (6). While traditional rigid-receptor docking methods work well when the receptor structure does not change substantially upon ligand binding, success is limited when the protein conformation must change in order to accommodate the correct binding conformation of the ligand. Schrödinger's induced fit docking (IFD) protocol accounts for both small backbone relaxations in the receptor structure as well as significant side-chain conformational changes. This IFD protocol has been validated on a large set of pharmaceutically relevant examples with surprisingly good results (6). In a study of 21 cases requiring a wide range of receptor movements to properly accommodate particular ligands, traditional rigid-receptor docking yields an average ligand root-mean-square deviation (RMSD) of 5.5 Å, while the average ligand RMSD for IFD is 1.4 Å, and in 18 cases the RMSD is less than 1.8 Å (6). As seen in Figure 1, over 95% of the cases from IFD have an RMSD less than 2 Å, when compared with less than 20% for rigid-receptor docking.

image

Figure 1. A comparison of rigid receptor and induced fit docking. The number of cases that fall within the specified ligand RMSD ranges are shown.

Download figure to PowerPoint

The IFD protocol described above has recently been extended to allow for full flexibility in loop regions. In a study of the activation loop in p38 MAP kinase, the automated IFD protocol was successfully used to generate the DFG-out conformation starting from a DFG-in structure (1a9u) and the ligand from 1kv1 (BMU). The high degree of similarity between the IFD structure and 1kv1 (ligand RMSD = 1.15 Å) is striking given the significant difference between the DFG-out structure and the starting DFG-in structure (Figure 2).

image

Figure 2. Structure of the binding pocket of 1a9u (DFG-in), 1kv1 (DFG-out) and the induced fit structure generated from the 1a9u structure and 1kv1 ligand. The insert in the 1kv1 panel highlights the Glu71 hydrogen bond interaction with the urea group of BIRB 796, which is nearly identical to the hydrogen bond interaction between the very similar 1kv1 ligand and the IFD structure.

Download figure to PowerPoint

In a retrospective virtual screening study of 25K decoy ligands and 46 known actives, using an ensemble consisting of the IFD structure (DFG-out) and the 1a9u crystal structure (DFG-in), 14 actives were identified in the top 1% of the database, including BMU and BIRB 796. This is compared to only three actives when 1a9u was used alone. In summary, we have produced, using a fully automated protocol, the DFG-out conformation of p38 MAPK starting from the DFG-in conformation and an inhibitor that binds to DFG-out. Combining the induced-fit structure in an ensemble with the original DFG-in structure dramatically increased enrichment of actives in a database screen. These results demonstrate that it is possible with IFD to produce viable receptor structures that as part of an ensemble with other conformations of the receptor can produce significantly higher enrichment factors in database screening.

References

  1. Top of page
  2. Abstract
  3. Induced Fit Docking
  4. References
  • 1
    Friesner R.A., Banks J.L., Murphy R.B., Halgren T.A., Klicic J.J., Mainz D.T., Repasky M.P., Knoll E.H., Shelley M., Perry J.K., Shaw D.E., Francis P., Shenkin P.S. (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem;47: 17391749.
  • 2
    Halgren T.A., Murphy R.B., Friesner R.A., Beard H.S., Frye L.L., Pollard W.T., Banks J.L. (2004) Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. J Med Chem;47: 17501759.
  • 3
    Jacobson M.P., Kaminski G.A., Friesner R.A., Rapp C.S. (2002) Force field validation using protein side chain prediction. J Phys Chem B;106: 1167311680.
  • 4
    Jacobson M.P., Friesner R.A., Xiang Z.X., Honig B. (2002) On the role of the crystal environment in determining protein side-chain conformations. J Mol Biol;320: 597608.
  • 5
    Jacobson M.P., Pincus D.L., Rapp C.S., Day T.J., Honig B., Shaw D.E., Friesner R.A. (2004) A hierarchical approach to all-atom protein loop prediction. Proteins;55: 351367.
  • 6
    Sherman W., Day T., Jacobson M.P., Friesner R.A., Farid R. (in press) Novel procedure for modeling ligand/receptor induced fit effects. J Med Chem;49. In press.