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Molecular dynamics analysis to evaluate docking pose prediction.

ABSTRACT: The accurate prediction of a ligand-protein complex structure is important for computer-assisted drug development. Although many docking methods have been developed over the last three decades, the success of binding structure prediction remains greatly limited. The purpose of this study was to demonstrate the usefulness of molecular dynamics (MD) simulation in assessing a docking pose predicted using a docking program. If the predicted pose is not unstable in an aqueous environment, MD simulation equilibrates the system and removes the ligand from the predicted position. Here we investigated two proteins that are important potential therapeutic targets: ?2 adrenergic receptor (?2AR) and PR-Set7. While ?2AR is rigid and its ligands are very similar to the template ligand (carazolol), PR-Set7 is very flexible and its ligands vary greatly from the template ligand (histone H4 tail peptide). On an empirical basis, we usually expect that the docking prediction is accurate when the protein is rigid and its ligands are similar to the template ligand. The MD analyses in this study clearly suggested such a tendency. Furthermore, we discuss the possibility that the MD simulation can predict the binding pose of a ligand.

SUBMITTER: Sakano T

PROVIDER: S-EPMC5042163 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Molecular dynamics analysis to evaluate docking pose prediction.

Sakano Takako T Mahamood Md Iqbal MI Yamashita Takefumi T Fujitani Hideaki H

Biophysics and physicobiology 20160714

The accurate prediction of a ligand-protein complex structure is important for computer-assisted drug development. Although many docking methods have been developed over the last three decades, the success of binding structure prediction remains greatly limited. The purpose of this study was to demonstrate the usefulness of molecular dynamics (MD) simulation in assessing a docking pose predicted using a docking program. If the predicted pose is not unstable in an aqueous environment, MD simulati ...[more]

PMID: 27924273

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Project description:Background: Indicaxanthin, a betaxanthin belonging to the betalain class of compounds, has been recently demonstrated to exert significant antiproliferative effects inducing apoptosis of human melanoma cells through the inhibition of NF-κB as the predominant pathway. Specifically, Indicaxanthin inhibited IκBα degradation in A375 cells. In resting cells, NF-κB is arrested in the cytoplasm by binding to its inhibitor protein IκBα. Upon stimulation, IκBα is phosphorylated by the IKK complex, and degraded by the proteasome, liberating free NF-κB into the nucleus to initiate target gene transcription. Inhibition of the IKK complex leads to the arrest of the NF-κB pathway. Methods: To acquire details at the molecular level of Indicaxanthin's inhibitory activity against hIKKβ, molecular modeling and simulation techniques including induced-fit docking (IFD), binding pose metadynamics (BPMD), molecular dynamics simulations, and MM-GBSA (molecular mechanics-generalized Born surface area continuum solvation) have been performed. Results: The computational calculations performed on the active and inactive form, and the allosteric binding site of hIKKβ, revealed that Indicaxanthin inhibits prevalently the active form of the hIKKβ. MM-GBSA computations provide further evidence of Indicaxanthin's stability inside the active binding pocket with a binding free energy of -22.2 ± 4.3 kcal/mol with respect to the inactive binding pocket with a binding free energy of -20.7 ± 4.7 kcal/mol. BPMD and MD simulation revealed that Indicaxanthin is likely not an allosteric inhibitor of hIKKβ. Conclusion: As a whole, these in silico pieces of evidence show that Indicaxanthin can inhibit the active form of the hIKKβ adding novel mechanistic insights on its recently discovered ability to impair NF-κB signaling in melanoma A375 cells. Moreover, our results suggest the phytochemical as a new lead compound for novel, more potent IKKβ inhibitors to be employed in the treatment of cancer and inflammation-related conditions.

Dataset Information

Molecular dynamics analysis to evaluate docking pose prediction.

Publications

Molecular dynamics analysis to evaluate docking pose prediction.

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