Androgen receptor (AR) plays important roles in the development of prostate cancer (PCa). The antagonistic drugs, which suppress the activity of AR, are widely used in the treatment of PCa. However, the molecular mechanism of antagonism about how ligands affect the structures of AR remains elusive. To better understand the conformational variability of ARs bound with agonists or antagonists, we performed long time unbiased molecular dynamics (MD) simulations and enhanced sampling simulations for the ligand binding domain of AR (AR-LBD) in complex with various ligands. Based on the simulation results, we proposed an allosteric pathway linking ligands and helix 12 (H12) of AR-LBD, which involves the interactions among the ligands and the residues W741, H874, and I899. The interaction pathway provides an atomistic explanation of how ligands affect the structure of AR-LBD. A repositioning of H12 was observed, but it is facilitated by the C-terminal of H12, instead of by the loop between helix 11 (H11) and H12. The bias-exchange metadynamics simulations further demonstrated the above observations. More importantly, the free energy profiles constructed by the enhanced sampling simulations revealed the transition process between the antagonistic form and agonistic form of AR-LBD. Our results would be helpful for the design of more efficient antagonists of AR to combat PCa.

Dimensionality reduction methods have been widely used to study the free energy landscapes and low-free energy pathways of molecular systems. It was shown that the non-linear dimensionality-reduction methods gave better embedding results than the linear methods, such as principal component analysis, in some simple systems. In this study, we have evaluated several non linear methods, locally linear embedding, Isomap, and diffusion maps, as well as principal component analysis from the equilibrium folding/unfolding trajectory of the second β–hairpin of the B1 domain of streptococcal protein G. The CHARMM parm19 polar hydrogen potential function was used. A series of criteria which reflects different aspects of the embedding qualities were employed in the evaluation. Our results show that principal component analysis is not worse than the non-linear ones on this complex system. There is no clear winner in all aspects of the evaluation. Each dimensionality-reduction method has its limitations in a certain aspect. We emphasize that a fair, informative assessment of an embedding result requires a combination of multiple evaluation criteria rather than any single one. Caution should be used when dimensionality-reduction methods are employed, especially when only a few of top embedding dimensions are used to describe the free energy landscape.

Androgen receptor (AR), as a member of the nuclear receptor (NR) superfamily, regulates the gene transcription in response to the sequential binding of diverse agonists and coactivators. Great progress has been made in studies on the pharmacology and structure of AR, but the atomic level mechanism of the bidirectional communications between the ligand-binding pocket (LBP) and the activation function-2 (AF2) region of AR remains poorly understood. Therefore, in this study, molecular dynamics (MD) simulations and free energy calculations were carried out to explore the interactions among water, agonist (DHT) or antagonist (HFT), AR, and coactivator (SRC3). Upon the binding of an agonist (DHT) or antagonist (HFT), the LBP structure would transform to the agonistic or antagonistic state, and the conformational changes of the LBP would regulate the structure of the AF2 surface. As a result, the binding of the androgen DHT could promote the recruitment of the coactivator SRC3 to the AF2, and on the contrary, the binding of the antagonist HFT would induce a perturbation to the shape of the AF2 and then weaken its accommodating capability of the coactivators with the LXXLL motif. The simulation results illustrated that the DHT-AR binding affinity was enhanced by the association of the coactivator SRC3, which would reduce the conformational fluctuation of the AR-LBD and expand the size of the AR LBP. On the other hand, the coactivator-to-HFT allosteric pathway, which involves the SRC3, helix 3 (H3), helix 4 (H4), the loop (L1−3) between helix 1 (H1) and H3, and HFT, was characterized. The HFT's skewness and different interactions between HFT and the LBP were observed in the SRC3-present AR. The mutual communications between the AF2 surface and LBP, together with the processes involving the interplay of the ligand binding and coactivator recruitment events, would help in understanding the association of coactivators and rationally develop potent drugs to inhibit the activity of AR.

The androgen receptor (AR) plays important roles in gene expression regulation, sexual phenotype maintenance, and prostate cancer (PCa) development. The communications between the AR ligand-binding domain (LBD) and its coactivator are critical to the activation of AR. It is still unclear how the ligand binding would affect the AR-coactivator interactions. In this work, the effects of the ligand binding on the AR-coactivator communications were explored by molecular dynamics (MD) simulations. The results showed that the ligand binding regulates the residue interactions in the function site AF-2. The ligand-to-coactivator allosteric pathway, which involves the coactivator, helix 3 (H3), helix 4 (H4), the loop between H3 and H4 (L3), and helix 12 (H12), and ligands, was characterized. In addition, the interactions of residues on the function site BF-3, especially on the boundary of AF-2 and BF-3, are also affected by the ligands. The MM/GBSA free energy calculations demonstrated that the binding affinity between the coactivator and apo-AR is roughly weaker than those between the coactivator and antagonistic ARs but stronger than those between the coactivator and agonistic ARs. The results indicated that the long-range electrostatic interactions and the conformational entropies are the main factors affecting the binding free energies. In addition, the F876L mutation on AR-LBD affects the ligand-to-coactivator allosteric pathway, which could be the reason for point mutation induced tolerance for the antagonistic drugs such as enzalutamide. Our study would help to develop novel drug candidates against PCa.