Literature DB >> 11985464

Docking into knowledge-based potential fields: a comparative evaluation of DrugScore.

Christoph A Sotriffer, Holger Gohlke, Gerhard Klebe.   

Abstract

A new application of DrugScore is reported in which the knowledge-based pair potentials serve as objective function in docking optimizations. The Lamarckian genetic algorithm of AutoDock is used to search for favorable ligand binding modes guided by DrugScore grids as representations of the protein binding site. The approach is found to be successful in many cases where DrugScore-based re-ranking of already docked ligand conformations does not yield satisfactory results. Compared to the AutoDock scoring function, DrugScore yields slightly superior results in flexible docking.

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Year:  2002        PMID: 11985464     DOI: 10.1021/jm025507u

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  4 in total

1.  Assessment of programs for ligand binding affinity prediction.

Authors:  Ryangguk Kim; Jeffrey Skolnick
Journal:  J Comput Chem       Date:  2008-06       Impact factor: 3.376

2.  Distilling the essential features of a protein surface for improving protein-ligand docking, scoring, and virtual screening.

Authors:  Maria I Zavodszky; Paul C Sanschagrin; Rajesh S Korde; Leslie A Kuhn
Journal:  J Comput Aided Mol Des       Date:  2002-12       Impact factor: 3.686

Review 3.  Virtual ligand screening: strategies, perspectives and limitations.

Authors:  Gerhard Klebe
Journal:  Drug Discov Today       Date:  2006-07       Impact factor: 7.851

4.  Accurate Representation of Protein-Ligand Structural Diversity in the Protein Data Bank (PDB).

Authors:  Nicolas K Shinada; Peter Schmidtke; Alexandre G de Brevern
Journal:  Int J Mol Sci       Date:  2020-03-24       Impact factor: 5.923

  4 in total

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