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          Institute: MPI für Informatik     Collection: Computational Biology and Applied Algorithmics     Display Documents

ID: 520893.0, MPI für Informatik / Computational Biology and Applied Algorithmics
Docking and scoring with alternative side-chain conformations
Authors:Hartmann, Christoph; Antes, Iris; Lengauer, Thomas
Date of Publication (YYYY-MM-DD):2009
Title of Journal:Proteins: Structure, Function, and Bioinformatics
Issue / Number:3
Start Page:712
End Page:726
Review Status:Peer-review
Audience:Experts Only
Intended Educational Use:No
Abstract / Description:We describe a scoring and modeling procedure for docking ligands into protein
models that have either modeled or flexible side-chain conformations. Our
methodical contribution comprises a procedure for generating new potentials of
mean force for the ROTA scoring function which we have introduced previously
for optimizing side-chain conformations with the tool IRECS. The ROTA
potentials are specially trained to tolerate small-scale positional errors of
atoms that are characteristic of (i) side-chain conformations that are modeled
using a sparse rotamer library and (ii) ligand conformations that are generated
using a docking program. We generated both rigid and flexible protein models
with our side-chain prediction tool IRECS and docked ligands to proteins using
the scoring function ROTA and the docking programs FlexX (for rigid side
chains) and FlexE (for flexible side chains). We validated our approach on the
forty screening targets of the DUD database. The validation shows that the ROTA
potentials are especially well suited for estimating the binding affinity of
ligands to proteins. The results also show that our procedure can compensate
for the performance decrease in screening that occurs when using protein models
with side chains modeled with a rotamer library instead of using X-ray
structures. The average runtime per ligand of our method is 168 seconds on an
Opteron V20z, which is fast enough to allow virtual screening of compound
libraries for drug candidates.
Last Change of the Resource (YYYY-MM-DD):2010-01-21
External Publication Status:published
Document Type:Article
Communicated by:Thomas Lengauer
Affiliations:MPI für Informatik/Computational Biology and Applied Algorithmics
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