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PharmDock: a pharmacophore-based docking program
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DOI：10.1186/1758-2946-6-14.png)
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摘要
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Background: Protein-based pharmacophore models are enriched with the information of potential interactions between ligands and the protein target. We have shown in a previous study that protein-based pharmacophore models can be applied for ligand pose prediction and pose ranking. In this publication, we present a new pharmacophore-based docking program PharmDock that combines pose sampling and ranking based on optimized protein-based pharmacophore models with local optimization using an empirical scoring function. Results: Tests of PharmDock on ligand pose prediction, binding affinity estimation, compound ranking and virtual screening yielded comparable or better performance to existing and widely used docking programs. The docking program comes with an easy-to-use GUI within PyMOL. Two features have been incorporated in the program suite that allow for user-defined guidance of the docking process based on previous experimental data. Docking with those features demonstrated superior performance compared to unbiased docking. Conclusion: A protein pharmacophore-based docking program, PharmDock, has been made available with a PyMOL plugin. PharmDock and the PyMOL plugin are freely available from http://people.pharmacy.purdue.edu/similar to mlill/software/pharmdock.
Keyword:
Protein pharmacophores
Docking
Scoring
Biased docking
Constraint docking
Confined docking
GUI
PyMOL
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5.7
论文数:
1.5K
被引数:
1.1W
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The PDBbind database: Collection of binding affinities for protein-ligand complexes with known three-dimensional structuresPDBbind数据库: 具有已知三维结构的蛋白质-配体复合物的结合亲和力的收集
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