Computational Analysis of Residue-Specific Binding Free Energies of Androgen Receptor to Ligands.

Guangfeng Shao,Xiaolin Pan,Yifei Qi,Xiao He,Jingxiao Bao,John Z. H. Zhang

doi:10.3389/fmolb.2021.646524

Guangfeng Shao, Xiaolin Pan + Show 4 more

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https://doi.org/10.3389/fmolb.2021.646524

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Abstract

Androgen receptor (AR) is an important therapeutic target for the treatment of diseases such as prostate cancer, hypogonadism, muscle wasting, etc. In this study, the complex structures of the AR ligand-binding domain (LBD) with fifteen ligands were analyzed by molecular dynamics simulations combined with the alanine-scanning-interaction-entropy method (ASIE). The quantitative free energy contributions of the pocket residues were obtained and hotspot residues are quantitatively identified. Our calculation shows that that these hotspot residues are predominantly hydrophobic and their interactions with binding ligands are mainly van der Waals interactions. The total binding free energies obtained by summing over binding contributions by individual residues are in good correlation with the experimental binding data. The current quantitative analysis of binding mechanism of AR to ligands provides important insight on the design of future inhibitors.

Highlights

Androgen receptor (AR) is an important target for many diseases including prostate cancer, hypogonadism, muscle wasting, osteoporosis, and benign prostate hyperplasia (Chen et al, 2004; Gao and Dalton, 2007; Dillon et al, 2010; Tan et al, 2015; Li et al, 2019)
The system was slowly heated to 300 K with Langevin dynamics temperature regulation, followed by an equilibration of 500 ps 10-ns MD simulations were carried out in an NPT ensemble and 25,000 snapshots were saved for further analysis
Fifteen ligands binding to AR-ligand-binding domain (LBD) systems with experimental ki/ kd data were used for the binding energy calculations [PDB ID: 1i37 (Sack et al, 2001), 1xnn (Salvati et al, 2005), 2ao6 (He et al, 2004), 2ax6 (Bohl et al, 2005), 2axa (Bohl et al, 2005), 2hvc (Wang et al, 2006), 2ihq (Sun et al, 2006), 2nw4 (Ostrowski et al, 2007), 3b5r (Bohl et al, 2008), 3b65 (Bohl et al, 2008), 3b66 (Bohl et al, 2008), 3b67 (Bohl et al, 2008), 3b68 (Bohl et al, 2008), 3g0w (Nirschl et al, 2009), 5cj6 (Saeed et al, 2016)]

Summary

INTRODUCTION

Androgen receptor (AR) is an important target for many diseases including prostate cancer, hypogonadism, muscle wasting, osteoporosis, and benign prostate hyperplasia (Chen et al, 2004; Gao and Dalton, 2007; Dillon et al, 2010; Tan et al, 2015; Li et al, 2019). We developed a method called interaction entropy (IE) for practical and efficient calculation of entropy in protein-ligand and protein-protein binding (Duan et al, 2016). This method has been used in combination with alanine scanning (Massova and Kollman, 1999) (AS) and MM/GBSA to obtain the residue-specific contribution of each pocket residue (ASE method) (Yan et al, 2017; Liu et al, 2018; Qiu et al, 2018; Zhou et al, 2018; He et al, 2019; Yang et al, 2019; Wang et al, 2020). The 15 ligands are divided into four categories according to their structural similarity [cluster 1: 2hvc (Wang et al, 2006); cluster 2: 3b65 (Bohl et al, 2008), 3b67 (Bohl et al, 2008), 3b5r (Bohl et al, 2008), 3b66 (Bohl et al, 2008), 3b68 (Bohl et al, 2008), 2axa (Bohl et al, 2005), 2ax (Bohl et al, 2005); cluster 3: 3g0w (Nirschl et al, 2009), 1xnn (Salvati et al, 2005), 5cj (Saeed et al, 2016), 2nw (Ostrowski et al, 2007), 2ihq (Sun et al, 2006); cluster 4: 1i37 (Sack et al, 2001), 2ao (He et al, 2004)], common structures in each cluster are highlighted in red

METHODS

RESULTS AND DISCUSSION

CONCLUSION

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