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Towards Ligand Docking Including Explicit Interface Water Molecules

Overview of attention for article published in PLOS ONE, June 2013
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Title
Towards Ligand Docking Including Explicit Interface Water Molecules
Published in
PLOS ONE, June 2013
DOI 10.1371/journal.pone.0067536
Pubmed ID
Authors

Gordon Lemmon, Jens Meiler

Abstract

Small molecule docking predicts the interaction of a small molecule ligand with a protein at atomic-detail accuracy including position and conformation the ligand but also conformational changes of the protein upon ligand binding. While successful in the majority of cases, docking algorithms including RosettaLigand fail in some cases to predict the correct protein/ligand complex structure. In this study we show that simultaneous docking of explicit interface water molecules greatly improves Rosetta's ability to distinguish correct from incorrect ligand poses. This result holds true for both protein-centric water docking wherein waters are located relative to the protein binding site and ligand-centric water docking wherein waters move with the ligand during docking. Protein-centric docking is used to model 99 HIV-1 protease/protease inhibitor structures. We find protease inhibitor placement improving at a ratio of 9:1 when one critical interface water molecule is included in the docking simulation. Ligand-centric docking is applied to 341 structures from the CSAR benchmark of diverse protein/ligand complexes [1]. Across this diverse dataset we see up to 56% recovery of failed docking studies, when waters are included in the docking simulation.

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Geographical breakdown

Country Count As %
Cuba 1 <1%
United States 1 <1%
Germany 1 <1%
Italy 1 <1%
Unknown 143 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 30 20%
Researcher 27 18%
Student > Bachelor 19 13%
Student > Doctoral Student 12 8%
Student > Master 9 6%
Other 25 17%
Unknown 25 17%
Readers by discipline Count As %
Chemistry 36 24%
Agricultural and Biological Sciences 30 20%
Biochemistry, Genetics and Molecular Biology 15 10%
Pharmacology, Toxicology and Pharmaceutical Science 10 7%
Computer Science 8 5%
Other 18 12%
Unknown 30 20%