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. 2021 Jul 13;17(7):3841-3851.
doi: 10.1021/acs.jctc.1c00114. Epub 2021 Jun 3.

Metadynamics-Based Approaches for Modeling the Hypoxia-Inducible Factor 2α Ligand Binding Process

Lara Callea  1 , Laura Bonati  1 , Stefano Motta  1
Affiliations

Metadynamics-Based Approaches for Modeling the Hypoxia-Inducible Factor 2α Ligand Binding Process

Lara Callea et al. J Chem Theory Comput. .

Abstract

Several methods based on enhanced-sampling molecular dynamics have been proposed for studying ligand binding processes. Here, we developed a protocol that combines the advantages of steered molecular dynamics (SMD) and metadynamics. While SMD is proposed for investigating possible unbinding pathways of the ligand and identifying the preferred one, metadynamics, with the path collective variable (PCV) formalism, is suggested to explore the binding processes along the pathway defined on the basis of SMD, by using only two CVs. We applied our approach to the study of binding of two known ligands to the hypoxia-inducible factor 2α, where the buried binding cavity makes simulation of the process a challenging task. Our approach allowed identification of the preferred entrance pathway for each ligand, highlighted the features of the bound and intermediate states in the free-energy surface, and provided a binding affinity scale in agreement with experimental data. Therefore, it seems to be a suitable tool for elucidating ligand binding processes of similar complex systems.

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Conflict of interest statement

The authors declare no competing financial interest.

Figures

Figure 1
Figure 1
2D structure of THS-020 (A) and KG-721 (B).
Figure 2
Figure 2
THS-020 unbinding pathways. In pathway 1 (left), the ligand passes through Fα and Gβ while in pathway 2 (right) through Fα, Eα, and the AB loop. The starting protein structure is represented as gray cartoons, the ligand conformations in the first and last frames of the trajectory as blue sticks, and the conformations of the ligand in the intermediate frames as transparent sticks.
Figure 3
Figure 3
(A) Plot of the CV1 (s(R)) against simulation time during THS-020 MetaD simulation: the lowest values of s(R) correspond to the bound state while the highest to the unbound ones; (B) one-dimensional projection of the binding free-energy values associated to path 1 during the metadynamics simulation.
Figure 4
Figure 4
Free-energy surface obtained from the PCV approach for the binding/unbinding of the THS-020 ligand. The isolines are drawn using a 1.5 kcal/mol spacing. The 3D structures of the centroids of the main minima are reported with different colors: the protein is represented as cartoons and the ligand as sticks. The black lines indicate the corresponding minima in the FES.
Figure 5
Figure 5
Free-energy surface obtained from the PCV approach for the binding/unbinding of the KG-721 ligand. The isolines are drawn using a 1.5 kcal/mol spacing. The 3D structures of the centroids of the main minima are reported with different colors: the protein is represented as cartoons and the ligand as sticks. The black lines indicate the corresponding minima in the FES.
Figure 6
Figure 6
Comparison between minimum A and the starting structure for the two ligands. On the left: for the THS-020 ligand, the overlay of minimum A, in orange, with the crystallographic structure of the complex, in gray. On the right: for the KG-721 ligand, the overlay of minimum A, in green, with the docking pose, in gray.
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