Knowledge-based scoring function to predict protein-ligand interactions.

By Holger Gohlke, Manfred Hendlich, Gerhard Klebe. 2000

1,037 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology, Computational Chemistry & Drug Discovery

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Citations in the corpus

Molecular Docking and Structure-Based Drug Design Strategies (2015, background): “As knowledge-based functions do not rely on reproducing binding affinities (empirical methods) or ab initio calculations (force-field methods), they offer a suitable balance between accuracy and speed [62].”
Comparing protein–ligand docking programs is difficult (2005, background): “14 Some authors count dockings whose RMSDs lie between 2 and 3 Å as partial successes.”
Advances and Challenges in Protein-Ligand Docking (2010, neutral): “Examples include DrugScore [138,139], SMoG [140,141], BLEEP [142,143], GOLD/ASP [144], MScore [145], and KScore[146].”
Structure-Based Virtual Screening for Drug Discovery: a Problem-Centric Review (2012, neutral): “Common strategies include adding additional factors to account for solvation (10), DOCK (11), GoldScore (14), D-Score (11) Empirical LUDI (62), X-Score (63), PLP (64), ChemScore (65), FlexX/F-Score (12), GlideScore (13), Sur ﬂ ex (15), QXP/Flo+ (66) Knowledge based PMF04 (67), kinase-PMF (68), DrugS”
Protein-ligand docking in the new millennium--a retrospective of 10 years in the field. (2013, methodology): “Historically, most of these comparisons have been made in terms of their ability to reproduce the X-ray pose of selected ligands [8, 18, 21, 32-50], their capability to predict binding free energies from the best-scored pose [16, 21, 24, 27, 28, 35, 51-56], or their ability to identify known binders”
General and targeted statistical potentials for protein–ligand interactions (2005, methodology): “The addition of the SAS term to the pair potential has been reported 14 to give only a slight improvement in recognizing experimental binding modes.”