TY - JOUR
T1 - MedusaDock 2.0
T2 - Efficient and Accurate Protein-Ligand Docking with Constraints
AU - Wang, Jian
AU - Dokholyan, Nikolay
N1 - Funding Information:
Jian Wang: 0000-0001-7768-2802 Nikolay V. Dokholyan: 0000-0002-8225-4025 Funding This work is supported by NIH grants R01GM114015, R01GM064803, and R01GM123247. Notes The authors declare no competing financial interest.
Publisher Copyright:
© 2019 American Chemical Society.
PY - 2019/6/24
Y1 - 2019/6/24
N2 - Molecular docking is the key ingredient of virtual drug screening, a promising and cost-effective approach for finding new drugs. A critical limitation of this approach is the inadequate sampling efficiency of both ligand and/or receptor conformations for finding the lowest energy bound state. To circumvent this limitation, we develop a protein-ligand docking methodology capable of incorporating structural constraints, experimentally derived or theoretically predicted, to improve accuracy and efficiency. We develop a web server with a user-friendly online graphical interface as a platform for accurate and efficient protein-ligand molecule docking.
AB - Molecular docking is the key ingredient of virtual drug screening, a promising and cost-effective approach for finding new drugs. A critical limitation of this approach is the inadequate sampling efficiency of both ligand and/or receptor conformations for finding the lowest energy bound state. To circumvent this limitation, we develop a protein-ligand docking methodology capable of incorporating structural constraints, experimentally derived or theoretically predicted, to improve accuracy and efficiency. We develop a web server with a user-friendly online graphical interface as a platform for accurate and efficient protein-ligand molecule docking.
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U2 - 10.1021/acs.jcim.8b00905
DO - 10.1021/acs.jcim.8b00905
M3 - Article
C2 - 30946779
AN - SCOPUS:85064969123
SN - 1549-9596
VL - 59
SP - 2509
EP - 2515
JO - Journal of Chemical Information and Modeling
JF - Journal of Chemical Information and Modeling
IS - 6
ER -