Unknown

Dataset Information

0

Ligand binding mode prediction by docking: mdm2/mdmx inhibitors as a case study.


ABSTRACT: The p53-binding domains of Mdm2 and Mdmx, two negative regulators of the tumor suppressor p53, are validated targets for cancer therapeutics, but correct binding poses of some proven inhibitors, particularly the nutlins, have been difficult to obtain with standard docking procedures. Virtual screening pipelines typically draw from a database of compounds represented with 1D or 2D structural information from which one or more 3D conformations must be generated. These conformations are then passed to a docking algorithm that searches for optimal binding poses on the target protein. This work tests alternative pipelines using several commonly used conformation generation programs (LigPrep, ConfGen, MacroModel, and Corina/Rotate) and docking programs (GOLD, Glide, MOE-dock, and AutoDock Vina) for their ability to reproduce known poses for a series of Mdmx and/or Mdm2 inhibitors, including several nutlins. Most combinations of these programs using default settings fail to find correct poses for the nutlins but succeed for all other compounds. Docking success for the nutlin class requires either computationally intensive conformational exploration or an "anchoring" procedure that incorporates knowledge of the orientation of the central imidazoline ring.

SUBMITTER: Bharatham N 

PROVIDER: S-EPMC4753531 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature

altmetric image

Publications

Ligand binding mode prediction by docking: mdm2/mdmx inhibitors as a case study.

Bharatham Nagakumar N   Bharatham Kavitha K   Shelat Anang A AA   Bashford Donald D  

Journal of chemical information and modeling 20140121 2


The p53-binding domains of Mdm2 and Mdmx, two negative regulators of the tumor suppressor p53, are validated targets for cancer therapeutics, but correct binding poses of some proven inhibitors, particularly the nutlins, have been difficult to obtain with standard docking procedures. Virtual screening pipelines typically draw from a database of compounds represented with 1D or 2D structural information from which one or more 3D conformations must be generated. These conformations are then passed  ...[more]

Similar Datasets

| S-EPMC3480999 | biostudies-literature
| S-EPMC3113661 | biostudies-literature
| S-EPMC8369186 | biostudies-literature
| S-EPMC4086128 | biostudies-literature
| S-EPMC5333476 | biostudies-literature
| S-EPMC3353153 | biostudies-literature
| S-EPMC6030866 | biostudies-literature
| S-EPMC3778940 | biostudies-literature
| S-EPMC10668353 | biostudies-literature
| S-EPMC3012977 | biostudies-literature