Abstract
The huge conformational space stemming from the inherent flexibility of peptides is among the main obstacles to successful and efficient computational modeling of protein-peptide interactions. Current peptide docking methods typically overcome this challenge using prior knowledge from the structure of the complex. Here we introduce AnchorDock, a peptide docking approach, which automatically targets the docking search to the most relevant parts of the conformational space. This is done by precomputing the free peptide's structure and by computationally identifying anchoring spots on the protein surface. Next, a free peptide conformation undergoes anchor-driven simulated annealing molecular dynamics simulations around the predicted anchoring spots. In the challenging task of a completely blind docking test, AnchorDock produced exceptionally good results (backbone root-mean-square deviation ≤ 2.2Å, rank ≤15) for 10 of 13 unbound cases tested. The impressive performance of AnchorDock supports a molecular recognition pathway that is driven via pre-existing local structural elements.
| Original language | American English |
|---|---|
| Pages (from-to) | 929-940 |
| Number of pages | 12 |
| Journal | Structure |
| Volume | 23 |
| Issue number | 5 |
| DOIs | |
| State | Published - 5 May 2015 |
Bibliographical note
Funding Information:We thank Dr. Miriam Eisenstein for sharing the source code of ANCHORSmap, developed by Ben-Shimon and Eisenstein at the Weizmann Institute of Science. We thank Dr. James Keck for kindly providing the X-ray coordinates of target T65 after the CAPRI 29 round was concluded, and Dr. Talia Yarnitzky and Dr. Michal Slutzki for critical reading of the manuscript. Valazzi-Pikovsky postdoctoral fellowship to A.B.S. and funding from the Chief Ministry of Health via the ERA-net network to M.Y.N. are gratefully acknowledged.
Publisher Copyright:
© 2015 Elsevier Ltd.