Communication between the Ligand-Binding Pocket and the

Subscriber access provided by Iowa State University | Library

Computational Biochemistry

Communication between the ligand-binding pocket (LBP) and the activation function-2 (AF2) domain of androgen receptor revealed by molecular dynamics simulations Ye Jin, Mojie Duan, Xuwen Wang, Xiaotian Kong, Wenfang Zhou, Huiyong Sun, Hui Liu, Dan Li, Huidong Yu, Youyong Li, and Tingjun Hou J. Chem. Inf. Model., Just Accepted Manuscript • DOI: 10.1021/acs.jcim.8b00796 • Publication Date (Web): 18 Jan 2019 Downloaded from http://pubs.acs.org on January 19, 2019

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Journal of Chemical Information and Modeling

Communication between the Ligand-binding Pocket (LBP) and the Activation Function-2 (AF2) Domain of Androgen Receptor Revealed by Molecular Dynamics Simulations

Ye Jina,b, Mojie Duand, Xuwen Wangb, Xiaotian Kongb, Wenfang Zhoub, Huiyong Sunb, Hui Liub, Dan Lib, Huidong Yue, Youyong Lia,*, Tingjun Houa,b,c,*

aInstitute

of Functional Nano and Soft Materials (FUNSOM), Soochow University, Suzhou, Jiangsu

215123, China bCollege cState dKey

of Pharmaceutical Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P. China

Key Lab of CAD&CG, Zhejiang University, Hangzhou, Zhejiang 310058, China

Laboratory of magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic

Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan 430071, China eRongene

Pharma Co., Ltd., Shenzhen, Guangdong 518054, China

*Corresponding authors: Youyong Li Email: [email protected] Phone: +86-512-65882037 Tingjun Hou E-mail: [email protected] Phone: +86-517-8820-8412

1

ACS Paragon Plus Environment

Journal of Chemical Information and Modeling 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 2 of 38

Abstract 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 the 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 was 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 to understand the association of coactivators and rationally develop potent drugs to inhibit the activity of AR.

2


Page 3 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Introduction Androgen receptor (AR) is a hormone-dependent transcriptional factor belonging to the nuclear receptor (NR) superfamily1. The binding of its physiological androgens, such as testosterone or dihydrotestosterone (DHT), stimulates a series of post-receptor biochemical changes, which would result in the activation of a large number of target genes involved in the development and maintenance of the male reproductive system and some other tissues, such as bone and muscle2. As the key regulator in the development and progression of prostate cancer (PCa), AR has been regarded as an essential therapeutic target for the discovery of drugs to treat PCa3-5. In clinical practice, androgen deprivation therapy (ADT), also known as androgen suppression therapy, has been used as the main therapeutic approach for the initial treatment of PCa by reducing the circulating levels of androgens. However, almost all patients eventually progress to castration-resistant PCa (CRPC)6. A number of antiandrogens, especially nonsteroidal antiandrogens, have been developed for clinical use in CRPC patients. Until now all clinically approved AR-targeting antagonists, such as flutamide, nilutamide, bicalutamide and enzalutamide (MDV3100), competitively bind to the ligand-binding pocket (LBP) of AR to block the androgen-dependent activation of AR7-11. Similar to other NR family members, the AR protein is composed of four major structural modules, including the N-terminal domain (NTD) harboring a transcriptional activation function-1 (AF1) domain, the central DNA-binding domain (DBD), a short hinge region (H), and the C-terminal ligand-binding domain (LBD) that contains a ligand-binding pocket (LBP) and a hormone-dependent activation function-2 (AF2) site12-14. The X-ray crystallographic structures revealed that the AR-LBD consists of 11-helices instead of 12-helices in other NR family members due to the absence of the helix 2 (H2), which is folded into a typical three-layer sandwich organization15-18. The LBP responsible for the binding of natural androgens is surrounded by the helices 3, 5, 10, 11, and 12 (H3, H5, H10, H11, and H12). Upon agonist binding, the C-terminal helix of H12 undergoes significant conformational change and then encloses the LBP, which would induce the formation of the AF2 site, an accessible hydrophobic surface encircled by a number of residues in the helices 3, 4 and 12 (H3, H4 and H12) together with a part of the loop between H3 and H4 (L3-4)19. The AF2 serves as a docking site for various AR coactivators, such as members of the p160 family (SRC, steroid receptor coactivators) and ARA family (androgen-receptorassociated proteins)20. Association of the p160 coactivators allows the recruitment and assembly of various other cofactors, which would modulate the state of chromatin and interactions with components of the basal transcription machinery to initiate transcriptional process of AR21. SRC3 was found as a 3



Page 4 of 38

pivotal regulator in the development and progression of certain cancers, which is corroborated by the upregulation of SRC3 activity in breast cancer cells and its overexpression and amplification in PCa cells2225.

Meanwhile, several lines of evidence indicate that there exists a specific functional interplay between

AR and SRC3 in PCa22, 26. It is believed that the conformational arrangement of the AR LBP (especially H12) would effectively regulate the structure of the AF2 surface and further affect the coactivator recruitment ability. However, until recently, the detailed mechanism of the dynamic communication between the AF2 and LBP still remains elusive. A diverse group of coactivators and cofactors recruited by liganded NRs contain a short amphipathic α-helical segment with the LXXLL sequence motif (where L is leucine residue and X is any residue)27, which determines the NR binding affinity and selectivity of coactivators25, 28, 29. Binding of the LXXLL motif to the AF2 groove is primarily stabilized by the hydrophobic interactions of the leucine residues with the non-polar sidechains of some residues in the AF2 and the electrostatic interactions of the LXXLL backbone with the two clusters of positively and negatively charged residues at the two opposite ends of the AF2. Targeting the AF2 site provides an alternative or complementary way to inhibit the AR activity, and therefore understanding the structural basis of the binding of the canonical LXXLL sequence to AR at the atomic level is required. A group of X-ray crystallographic structures of the agonistic ARs have been resolved, including monomeric AR-LBD structures16, 17, 30, 31, DNA-bound AR-DBD dimer32, 33, and coactivator-bound ARLBD homodimer33. However, the crystallographic structure of the wild-type (WT) antagonistic AR has never been reported. Molecular modeling techniques, especially molecular dynamics (MD) simulations, provide a powerful platform to explore the conformational space of proteins and probe the interactions between proteins and ligands34. MD simulations have been employed to investigate the molecular basis of the agonistic and antagonistic mechanisms in the WT or mutated AR-LBDs35-42. Xu et al. studied a structural and functional relay between the bound DHT and coactivator and found that the DHT binding can provide inherent structural stability to the ligand binding domain, and improve the SRC coactivator recruitment.39 By employing microsecond long MD simulations and bias-exchange metadynamics, Liu et al. studied how agonists or antagonists affect the structures of AR and proposed an allosteric pathway linking ligands and H12 of the AR-LBD, and they also analyzed the effects of the ligand binding on the AR-coactivator communications and characterized a ligand-H12-H4/H3-coactivator allosteric pathway.40 However, it appears that these reported studies did not provide the atomic level mechanism about how the impact of the coactivator recruitment on the structure of the agonist or antagonist-bound 4


Page 5 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


AR. Moreover, most of those reported simulations were conducted on a time-scale from several to dozens of nanosecond (ns), and such relatively short simulation time-scale may be not enough to sample the whole conformational space of the antagonistic AR-LBD. In this study, 500 ns MD simulations were conducted to the HFT-LBD systems, in contrast with 200 ns MD simulations for the DHT-LBD simulations. The extra 300 ns relaxation time might enhance the probability to sample the conformational transition from the agonistic form to antagonistic form. To address the nature of the intrinsic coupling effects between the coactivator recruitment and ligand binding, we analyzed not only the structural diversity of the AR-LBDs bound with ligands but also the bidirectional structural communications between the LBP and AF2.

Materials and Methods Initial Structures and System Preparations The initial crystal structure of the DHT-bound AR-LBD in complex with the LXXLL-containing segment in SRC3, referred to as AR·DHT·LXXLL hereafter, was retrieved from the RCSB Brookhaven Protein Data Bank (PDB ID: 3l3x)25. This SRC3 segment is a 12-mer peptide (H618KKLLQLLTCSS629) with the LXXLL motif, where the first conserved leucine residue is termed as +1 or LEU+1 and the residues located N-terminally from LEU+1 are termed as -1, -2, and so on. Due to the absence of the X-ray crystal structure of the WT AR in complex with HFT, the crystal structure of the T877A mutated AR-LBD in complex with HFT and the coregulatory peptide with the FXXLY motif (PDB ID: 4oha)43 was used to model the structure of the WT AR bound with HFT by mutating the 877th residue to THR in the WT AR using the Build Mutants module of the Discovery Studio 3.1 software package. The missing part in the X-ray structure of the HFT-bound AR-LBD was generated by the Modeller program44 based on the structure of the AR·DHT·LXXLL complex. The modeled structure of the WT AR-LBD in complex with HFT and the FXXLY-containing peptide is referred to as AR·HFT·FXXLY. The starting structure of the AR·DHT or AR·HFT binary complex was generated by removing the peptide from the corresponding ternary structure of AR·DHT·LXXLL or AR·HFT·FXXLY, respectively. In order to generate the structure of the HFT-bound AR-LBD in complex with the SRC3 peptide (AR·HFT·LXXLL), the structures of the AR·HFT·FXXLY and AR·DHT·LXXLL complexes were structurally aligned, and the FXXLY-containing peptide in the AR·HFT·FXXLY complex was replaced by the LXXLL-containing peptide extracted from the AR·DHT·LXXLL complex. Thus four models, including AR·DHT, 5



Page 6 of 38

AR·DHT·LXXLL, AR·HFT and AR·HFT·LXXLL, were utilized as the initial structures for the following MD simulations (Table 1).

Table 1. Systems for the MD simulations System

Ligand

Coregulator

Simulation time

Initial conformation

Expected conformation

AR·DHT·LxxLL

DHT

SRC3 peptide

200 ns

Agonist

Agonist

AR·DHT

DHT

¯¯

200 ns

Agonist

Agonist

AR·HFT·LxxLL

HFT

SRC3 peptide

500 ns

Agonist

Antagonist

AR·HFT

HFT

¯¯

500 ns

Agonist

Antagonist

Prior to MD simulations, the ligands (DHT and HFT) were optimized by the Hartree-Fock (HF) method at the 6-31 G* level of theory implemented in Gaussian 09, and then their atomic partial charges were determined by fitting the electrostatic potentials through the restrained electrostatic potential (RESP) fitting algorithm. The general Amber force field (GAFF)45 and the Amber force field ff14SB46 were used for the ligands and proteins, respectively. The missing force field parameters for DHT and HFT were created using the antechamber suite in the Amber16 package47. The missing atoms of the proteins and peptides were added using the LEaP module in Amber16. Each complex was immersed into a periodic truncated octahedral box filled with the TIP3P water molecules48 and all the solute atoms were at least 10 Å away from the boundary of the water box. Then, an appropriate number of chloride counterions were added to achieve the electro-neutrality of each system.

Molecular Dynamics Simulations The energy minimization and MD simulations were conducted using the sander and pmemd modules in Amber1647, respectively. The Particle Mesh Ewald (PME) algorithm49 was applied to handle the longrange electrostatic interactions and a cutoff of 10 Å was used for the real-space interactions. To remove the bad contacts in the simulated systems, each complex was optimized by a multistep procedure. Initially, the protein, ligand and peptide were restrained by a harmonic force constant of 50 kcal/(mol·Å2), and the water and counterion molecules were optimized by 1000 cycles of steepest descent and 1000 cycles of conjugate gradient minimizations. Then, the backbone atoms of the protein and peptide were 6


Page 7 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


restrained by a 50 kcal/(mol·Å2) force constant, and the other atoms were optimized by 1000 cycles of steepest descent and 1000 cycles of conjugate gradient minimizations. Third, the backbone atoms of the protein and peptide were restrained with a 10 kcal/(mol·Å2) force constant, and the other atoms were optimized by 1000 cycles of steepest descent and 1000 cycles of conjugate gradient minimizations. Finally, all the atoms were optimized by 5000 cycles of steepest descent and 5000 cycles of conjugate gradient minimizations without any restrain. After minimization, each system was heated to 300 K over a period of 100 ps in the NVT ensemble with the weak harmonic restraint of 2 kcal/(mol·Å2) on the protein and peptide backbone atoms. Subsequently, another 100 ps MD equilibration in the NPT (T = 300 K and P = 1 atm) ensemble with the same restraint was conducted. Afterward, each unrestrained system underwent an additional 1 ns equilibration in the NPT (T = 300 K and P = 1 atm) ensemble with the Langevin thermostat50. After the three rounds of equilibration, 200 ns MD production phase was run in the NPT (T = 300 K and P = 1 atm) ensemble. For the AR·HFT and AR·HFT·LXXLL complexes, in order to capture the transition from the agonistic to antagonistic form, extra 300 ns MD productions were carried out. The SHAKE algorithm51 was used to constrain the covalent bonds involving hydrogen atoms. The time step was set to 2 fs and the snapshots were recorded every 10 ps. The stable trajectories during the last 100 ns of the four simulations were used for the following analyses.

Binding Free Energy Calculations and Energy Decompositions The Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) method52-54 that combines molecular mechanics calculations and continuum solvation models was utilized to calculate the binding free energy (𝛥𝐺𝑏𝑖𝑛𝑑) between each ligand and AR·LXXLL or between the SRC3 peptide and liganded AR-LBD based on the 1,000 snapshots evenly extracted from the last 100 ns stable MD trajectory (Equation 1)54. 𝛥𝐺𝑏𝑖𝑛𝑑 = 𝐺𝑐𝑜𝑚𝑝𝑙𝑒𝑥 ― (𝐺𝑟𝑒𝑐𝑒𝑝𝑡𝑜𝑟 + 𝐺𝑙𝑖𝑔𝑎𝑛𝑑) (1)

= 𝛥𝐸𝑀𝑀 +𝛥𝐺𝑠𝑜𝑙𝑣𝑎𝑡𝑖𝑜𝑛 ―𝑇𝛥𝑆

= 𝛥𝐸𝑀𝑀 + 𝛥𝐺𝐺𝐵 + 𝛥𝐺𝑆𝐴 ― 𝑇𝛥𝑆

where 𝐺𝑐𝑜𝑚𝑝𝑙𝑒𝑥, 𝐺𝑟𝑒𝑐𝑒𝑝𝑡𝑜𝑟 and 𝐺𝑙𝑖𝑔𝑎𝑛𝑑 represent the binding free energies of complex, receptor and ligand, respectively; 𝛥𝐸𝑀𝑀 is the difference of the molecular mechanics gas-phase energies between the receptor-ligand complex and the sum of the energies of the liganded and unliganded receptor, which contains the internal energy, the electrostatic and van der Waals interactions; 𝛥𝐺𝑠𝑜𝑙𝑣𝑎𝑡𝑖𝑜𝑛 represents the 7



Page 8 of 38

solvation free energy composed of the polar (𝛥𝐺𝐺𝐵) and non-polar contributions (𝛥𝐺𝑆𝐴); and ―𝑇𝛥𝑆 stands for the conformational entropy upon ligand binding, which is not considered here since the inclusion of the conformational entropy brings high computational cost but does not always improve the prediction accuracy. Here, the polar contribution of solvation (𝛥𝐺𝐺𝐵) was evaluated using the modified GB model developed by Onufriev et al.55 The dielectric constants for solute and solvent were set to 1 and 80, respectively. The non-polar part of solvation (𝛥𝐺𝑆𝐴) was determined by the solvent-accessible surface area (SASA) approach with the LCPO algorithm56: 𝛥𝐺𝑆𝐴 = 𝛾 × 𝛥𝑆𝐴𝑆𝐴 + 𝛽, where 𝛾 representing the surface tension was set to 0.0072 kcal/(mol·Å2) and the constant 𝛽 was set to 0. Binding free energy was decomposed to the contributions of individual residue–ligand or residueresidue pairs (𝛥𝐺𝑟𝑒𝑠𝑖𝑑𝑢𝑒 ― 𝑙𝑖𝑔𝑎𝑛𝑑) in order to highlight the important residues to ligand/peptide binding. Each residue-ligand interaction consists of four components: the van der Waals contribution (𝛥𝐸𝑣𝑑𝑊), electrostatic contribution (𝛥𝐸𝑒𝑙𝑒), polar solvation contribution (𝛥𝐺𝐺𝐵), and non-polar solvation contribution (𝛥𝐺𝑆𝐴), as displayed in the following equation: 𝛥𝐺𝑟𝑒𝑠𝑖𝑑𝑢𝑒 ― 𝑙𝑖𝑔𝑎𝑛𝑑 = 𝛥𝐸𝑣𝑑𝑊 +𝛥𝐸𝑒𝑙𝑒 +𝛥𝐺𝐺𝐵 +𝛥𝐺𝑆𝐴

(2)

Except for the non-polar solvation energy (𝛥𝐺𝑆𝐴), which was calculated based on the SASA using the ICOSA algorithm57, the other terms were calculated based on the same parameters used in the binding free energy calculations.

MD Trajectory Analysis The cpptraj module in Amber1647 was used for the MD trajectory post-processing and data analysis. Root mean square deviation (RMSD) as a function of simulation time was computed to assess the stability of the MD simulations. Root mean square fluctuation (RMSF) around the mean position of residues as a function of residue number was computed to monitor local conformational flexibility. Hydrogen bonds (H-bonds) were identified based on the geometric criteria that the distance between the hydrogen donor and acceptor heavy atoms should be less than 0.35 nm and the donor-hydrogen-acceptor angle should be larger than 120°. Each MD trajectory was split into 200 equal time windows. The fraction of a H-bond over each time window was also calculated to get a sense for how H-bond lifetimes are changing over the course of long-time simulations.

8


Page 9 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Cluster analysis based on the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm58 was employed to determine the structure populations from the entire simulation trajectory. The most representative structure, defined as the snapshot with the closest distance to the centroid of the largest cluster family, was selected from the MD trajectory for the following structural analysis. For each system, principal component analysis (PCA) was employed to analyze the distribution of the AR-LBD conformations taken from the last 100 ns trajectory. PCA transforms a number of possibly correlated variables into a number of uncorrelated variables called principal components59, 60, and it is a powerful tool to explore the collective motions of macromolecules. To obtain the proper trajectory matrix, the overall translation or rotation motion was removed aforehand by fitting the coordinate data to the average structure. Then, the fitted trajectory data was utilized to generate a positional covariance matrix between the Cα atoms of any two residues, which is defined in Equation 361: 𝜎𝑖𝑗 =< (𝑥𝑖 ―< 𝑥𝑖 > )(𝑥𝑗 ―< 𝑥𝑗 > ) > (𝑖,𝑗 = 1,2,3,…,3𝑁)

(3)

where 𝑥𝑖(𝑥𝑗) is the Cartesian coordinate of the 𝑖𝑡ℎ(𝑗𝑡ℎ) Cα atom, < 𝑥𝑖 > or < 𝑥𝑗 > denotes the time average over all sampled conformations, and 𝑁 represents the number of the Cα atoms considered. The symmetrical covariance matrix 𝜎 is diagonalized to produce the eigenvectors γn, namely the principal component PCn, and the corresponding eigenvalues λn. The eigenvectors γn stand for the directions of atomic motions which are independent to each other in the multidimensional space, and the eigenvalues λn describe the corresponding magnitude. The γn and λn are arranged in a descending order so that λ1 represents the largest eigenvalue. Significantly, the first several eigenvectors of 𝜎 are sufficient to qualitatively describe the large amplitude conformational changes for most cases. The Cα dynamic cross-correlation map (DCCM) analysis was used to reveal the dynamic correlative motions between any pair of residues in the four AR-related simulations. The crosscorrelation coefficient 𝐶𝑖𝑗 between the Cα atoms of the 𝑖𝑡ℎ and 𝑗𝑡ℎ residues is a measure of the correlated nature of their atomic fluctuations relative to their average positions and was computed by the following equation62: 𝐶𝑖𝑗 =

< 𝛥𝑟𝑖 ⋅ 𝛥𝑟𝑗 > < 𝛥𝑟𝑖 ⋅ 𝛥𝑟𝑖 >< 𝛥𝑟𝑗 ⋅ 𝛥𝑟𝑗 >

9


(4)


Page 10 of 38

where 𝛥𝑟𝑖 and 𝛥𝑟𝑗 are the displacement vectors of the 𝑖𝑡ℎ and 𝑗𝑡ℎ residues, respectively. The angle bracket denotes a time average over the trajectory. The value of 𝐶𝑖𝑗 ranges from -1 to 1. The positive value for a correlated residue pair implies the movement in the same direction, whereas the negative value for an anti-correlated pair denotes the movement in opposite directions.

Results and Discussion Structural Stability and Flexibility The heavy atom RMSDs as a function of simulation time were calculated to monitor the convergence and stability of the studied systems. As shown in Figure 1, the two DHT-bound complexes reached stability relatively earlier than the two HFT-bound complexes (~120 ns for AR·DHT and AR·DHT·LXXLL; ~400 ns for AR·HFT and AR·HFT·LXXLL), indicating that the 877th back-mutation would introduce perturbation to the whole structure. The average RMSD values of the SRC3-absent systems (1.86 Å for AR·DHT and 2.04 Å for AR·HFT) are slightly higher than those of the SRC3-present systems (1.71 Å for AR·DHT·LXXLL and 1.91 Å for AR·HFT·LXXLL). The smaller conformational drift for the ternary complexes suggests that the presence of the SRC3 peptide could stabilize the entire AR-LBD conformation. To verify if the SRC3 peptide would influence the LBP, the motions of the LBP were analyzed. As shown in Figure S1, it can be observed that the RMSDs of the residues of the LBP converged after ~100 ns for the DHT-binding pocket and ~300 ns for the HFT-binding pocket after equilibration. The RMSDs of the residues of the AF2 also tended to converge during the MD production stage (Figure S2). Therefore, the last 100 ns trajectories were used for further analysis.

10


Page 11 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 1. RMSDs of backbone atoms of AR-LBD as a function of simulation time for (A) AR·DHT·LxxLL, (B) AR·HFT·LxxLL, (C) AR·DHT, and (D) AR·HFT. In order to evaluate the flexibility of individual residues, the RMSF of the protein backbone atoms was computed based on the last 100 ns data of each simulation (Figure 2). The four complexes share extremely similar RMSF distributions, and most of the peaks correspond to the loop regions between the adjacent helical structures. The helices H3, H5 and the C-terminal region of H10 (residues 697-721, 741756, and 868-882) that form the core of the LBP exhibit much lower RMSF values, indicating that the conserved active site of the AR-LBD is more stable than the loop regions. The RMSFs of the SRC3absent and SRC3-present ARs differ predominantly in the helix H12 (residues 892-908) and the Cterminal tail of the AR-LBD (residues 909-918), which are located at or adjacent to the AF2 surface. Those regions (residues 892-918) on the SRC3-absent systems with larger fluctuations suggest that the binding of the SRC3 peptide enhances the structural stability of the region around the SRC3-binding pocket.

11



Page 12 of 38

Figure 2. Residue-based RMSFs relative to the initial structure for each system during the last 100 ns MD trajectories for (A) AR·DHT·LxxLL, (B) AR·HFT·LxxLL, (C) AR·DHT, and (D) AR·HFT. The colored regions represent the helices in the AR-LBD.

Hydrogen Bond Analysis The time-dependent H-bonding behavior involving the ligands and the overall occupancies of H-bonds are visualized in Figure 3. The deepness of the blue color is proportional to the length of H-bond lifetime, which represents the percentage of a given H-bond in the time window. As shown in Figure 3, two strong and stable interactions between ASN705 (N-terminal region of H3) and DHT and between THR877 (C-terminal region of H11) and DHT were observed in both the AR·DHT·LXXLL (Figure 3A) and AR·DHT (Figure 3B) systems, which would help pull the Nterminal region of H3 and C-terminal region of H11 towards the center of the LBP. The H-bond between DHT and ARG752 (DHT@O1···ARG752@NH2-HH22) with ~40% occupancy was observed. In addition, two unstable H-bonds between GLN711 and DHT (DHT@O1···GLN711@NE2-HE22 for AR·DHT·LxxLL and DHT@O1···GLN711@NE2-HE21 for AR·DHT) with low occupancies (~3%) were detected. Based on the analysis, we can conclude that DHT recognizes the AR-LBD by forming the H-bonds with the sidechains of ASN705, GLN711, ARG752, and THR877, which is consistent with the previous studies63. However, the H-bonding interaction patterns in the AR·DHT and AR·DHT·LXXLL 12


Page 13 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


complexes do not have large difference, indicating that the binding of the SRC3 peptide to the AF2 has little effect on the H-bonding network related to DHT.

Figure 3. The time-dependent behavior of the H-bonds between the ligands and key residues in the ARLBD and the occupancy for a given H-bond during the whole MD simulations for (A) AR·DHT·LxxLL, (B) AR·DHT, (C) AR·HFT·LxxLL, and (D) AR·HFT. Note that a H-bond is ignored if the occupancy is less than 2%. Each MD trajectory was split into 200 equal time windows. The differentiated shades and deepness of the blue color are used to distinguish the length of H-bond lifetime over time windows, while the light pink color represents the disappearance of a given H-bond during a certain time window.

13



Page 14 of 38

For the AR·HFT system (Figure 3D), we found that a stable H-bond formed between ASN705 and HFT (ASN705@OD1···HFT@O4-H11) in the 500 ns simulations with a high occupancy of 97.37%. The H-bond between THR877 and HFT (HFT@O4···THR877@OG1-HG1) could be observed at the initial stage of the MD simulations but almost disappeared after ~20 ns. However, LEU704 is close to HFT and an alternative H-bond (LEU704@O···HFT@N2-H4) forms with an overall occupancy of 45.41%, and this H-bond partially compensates the loss of the H-bonding interaction between HFT and THR877. Meanwhile, two unstable H-bonds between HFT and ARG752 (HFT@O2···ARG752@NH2HH22, and HFT@O1···ARG752@NH2-HH22) were observed. Unlike the AR·HFT system, the H-bond between HFT and THR877 (THR877@OG1···HFT@O4-H11) in AR·HFT·LXXLL (occupancy = 90.69%) is quite stable. The H-bond between HFT and ASN705 (ASN705@OD1···HFT@O4-H11) gradually disappears (Figure 3C). In brief, the interesting finding here is that the terminal hydroxyl group of HFT would adopt two different orientations, and it can form a stable H-bond with either THR877 or ASN705. The previous studies provide the evidence that the T877A mutation would abolish the Hbonding network around the 877th residue for HFT36, which agrees with the occurrence of the formation of a stable H-bond between THR877 and HFT in the AR·HFT·LXXLL system. In the AR·HFT system, the orientation of HFT is quite similar to that of DHT in the two DHT-related AR structures and a Hbond between ASN705 and HFT is formed, identical to the H-bond observed in the structures of the ARLBD bound with DHT.

Principal Component Analysis The eigenvalue contributions given by PCA for the four systems are summarized in Figure S3, and the results show that the first three components capture most of the cooperative motions. In order to gain insight into the lowest-frequency motions characterized by the principal components, namely eigenmodes, we further quantitatively analyzed the contributions of each residue to the top three eigenmodes, as shown in Figure 4.

14


Page 15 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 4. The mobility of each residue of the AR-LBD relative to the average structure across the first three eigenmodes (PCs) produced by the PCA for (A) AR·DHT·LxxLL, (B) AR·HFT·LxxLL, (C) AR·DHT, and (D) AR·HFT. The eigenmodes of the studied systems share common features, i.e. the structural variation captured by PCA is basically contributed from the loop regions. The subdomains with high contributions to the motions of AR·DHT·LXXLL are the loops L3-4, L6-7, L8-9, L9-10, helix H12 and the terminal tail of the AR-LBD. The PCA results of AR·DHT highlight the concerted maximum displacement of the loops L3-4 and L9-10, which are located in the core region of the LPB or nearby. More importantly, H12 exhibits higher flexibility in AR·DHT·LXXLL compared with AR·DHT, indicating the important role of the SRC3 peptide in the collaborative motions between H12 and helices or loops in the LBP. However, the conformational changes of AR·HFT·LXXLL are mainly contributed by the loops L8-9 and L9-10 (Figure 4B). For the AR·HFT system, H4, L8-9 and L9-10 play significant roles in the wide-range motions. Compared with the AR·HFT·LXXLL system, the residues on H4 of AR·HFT have larger contributions to the protein dynamics. The SRC3 binding would make a difference to the collective motions of the agonistic or antagonistic structure of the AR-LBD. The conformations of the last 100 ns 15



Page 16 of 38

MD trajectories were projected onto the top two eigenmodes space of PCA to visualize the conformational distributions (Figure S4). The LBD proteins in the SRC3-bound systems (AR·DHT·LXXLL and AR·HFT·LXXLL) have broader conformational distributions than those in the SRC3-absent systems (AR·DHT and AR·HFT). Besides, most of the sampled conformations of the HFTbound systems are different from the initial agonistic structures, indicating that the binding of HFT might convert the AR structure from an agonistic to an antagonistic form. To further demonstrate the communications between the LBP and AF2, the DCCM analyses were performed (Figure 5). Those regions marked in maps illustrate that the AR residues move in a different concerted nonrandom fashion with the presence of a specific ligand or coactivator. The DCCM results are consistent with the PCA results, which supports the fact the binding of the SRC3 peptide could make a profound impact on the communication between the LBP and AF2.

Figure 5. The DCCMs to illustrate the correlation of motions between the Cα atoms of residues in (A) AR·DHT·LxxLL, (B) AR·HFT·LxxLL, (C) AR·DHT, and (D) AR·HFT around their mean positions during the last 100 ns MD simulation. The extent of the correlated motions and anticorrelated motions 16


Page 17 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


are color-coded in the panel. Dark blue indicates highly positive correlation whereas dark red refers to strong anticorrelation. The regions of R1 represent the correlation of motions between H10 and H11Loop-H12. The regions of R2 represent the correlation of motions between H3-Loop-H4 and H10. The regions of R3 represent the correlation of motions between H3-Loop-H4 and H8-Loop-H9.

Ligand Binding Affinity Analysis MM/GBSA was then employed to identify the key factors affecting the SRC3 peptide recruitment. The binding free energies (𝛥𝐺𝑏𝑖𝑛𝑑) and the contributions of individual energy terms are summarized in Table 2. The predicted binding free energies for the AR·DHT·LXXLL, AR·DHT, AR·HFT·LXXLL and AR·HFT complexes are -51.13 kcal/mol, -50.12 kcal/mol, -40.59 kcal/mol and -42.57kcal/mol, respectively. The binding of DHT in AR·DHT·LXXLL (-51.13 kcal/mol) is slightly stronger than that in AR·DHT (-50.12 kcal/mol). This observation is in agreement with the previous experimental evidence that the presence of SRC enhances the DHT binding to AR (the binding free energy is -14.69 kcal/mol31 for DHT·AR·SRC and -12.72 kcal/mol64 for DHT·AR). In addition, the predicted binding affinities for DHT and HFT in AR·DHT and AR·HFT (-50.12 kcal/mol for AR·DHT and -42.57kcal/mol for AR·HFT) are also consistent with the experimental data (Ki=0.3 nM for AR·DHT and 25 nM for AR·HFT65).

Table 2. The binding free energies and the corresponding energetic components of the two small organic molecules in complex with the AR-LBDs predicted by MM/GBSA (kcal/mol)a

aStandard

Complexes

AR·DHT·LxxLL

AR·DHT

AR·HFT·LxxLL

AR·HFT

ΔEele

-6.87±0.02

-6.90±0.04

-5.48±0.08

-8.72±0.09

ΔEvdW

-47.79±0.33

-46.71±0.16

-39.18±0.04

-40.73±0.15

ΔGSA

-4.05±0.02

-4.00±0.01

-3.99±0.01

-3.91±0.01

ΔGGB

7.57±0.01

7.49±0.01

8.05±0.05

10.79±0.06

ΔGnon-polar

-51.84±0.35

-50.71±0.16

-43.17±0.04

-44.64±0.16

ΔGpolar

0.70±0.03

0.59±0.05

2.57±0.03

2.07±0.03

ΔGbind

-51.13±0.38

-50.12±0.12

-40.59±0.08

-42.57±0.13

deviations were calculated based on the predictions of two blocks (block 1: 1~500 snapshots; block 2: 501~1000 snapshots).

17



Page 18 of 38

The 𝛥𝐺𝑏𝑖𝑛𝑑 difference between AR·DHT and AR·DHT·LXXLL appear to be inconspicuous. The electrostatic energies (𝛥𝐸𝑒𝑙𝑒) for AR·DHT·LXXLL (-6.87 kcal/mol) and AR·DHT (-6.9 kcal/mol) are almost the same, resulting from their highly similar H-bonding networks as mentioned above. The difference of the van der Waals energies (𝛥𝐸𝑣𝑑𝑊) for AR·DHT·LXXL (-47.79 kcal/mol) and AR·DHT (-46.71 kcal/mol) indicates that some crucial hydrophobic residues around the binding pocket of the SRC3-present system may form tighter contacts with DHT. On the other side, the binding of HFT to AR becomes obviously weaker upon the binding of the SRC3 peptide (-40.59 kcal/mol for AR·HFT·LXXLL and -42.57 kcal/mol for AR·HFT). The recruitment of the SRC3 peptide results in an appreciable loss of the electrostatic energy (𝛥𝐸𝑒𝑙𝑒), nearly 3.24 kcal/mol, but the change of the polar energies ( 𝛥𝐸𝑒𝑙𝑒 +𝛥𝐺𝐺𝐵) is quite small (~0.5 kcal/mol). The decreased binding affinity of HFT in AR·HFT·LXXL primarily arises from the decrease of the non-polar energy (𝛥𝐸𝑣𝑑𝑊 +𝛥𝐺𝑆𝐴 = -43.17 kcal/mol for AR·HFT·LXXL and 44.64 kcal/mol for AR·HFT). To evaluate the key residues in the AR-LBP for ligand binding, the residue-specific binding free energies between the LBP and ligands (DHT and HFT) were calculated. The decomposed results are shown in Figures 6 and 7, and the contributions of the important residues are listed in Tables S1 and S2. According to Figures 6 and 7, the residues in H3 and H5 make significant contributions in all the four systems. The binding of DHT and HFT to the AR-LBD are predominantly contributed from the residues LEU704, ASN705, LEU707, GLN711, MET742, MET745, VAL746, MET749, PHE764, LEU873 and THR877. The hydrophobic interactions play essential roles in AR-ligand recognition. It can be seen that the non-polar interactions (𝛥𝐸𝑣𝑑𝑊 +𝛥𝐺𝑆𝐴) of the hydrophobic residues LEU704, LEU707, MET742, MET745, VAL746, MET749, PHE764 and LEU873 in AR play important roles in binding (Tables S1 and S2, Figures 8C, 8D, 9C and 9D). As shown in Table 3, the stronger binding affinity of the SRC3 peptide in AR·DHT·LXXLL than that in AR·HFT·LXXLL (-52.22 kcal/mol for AR·DHT·LXXLL and -46.49 kcal/mol for AR·HFT·LXXLL) is contributed by both the favorable polar (𝛥𝐸𝑒𝑙𝑒 +𝛥𝐺𝐺𝐵 = -1.54 kcal/mol for AR·DHT·LXXLL and 1.85 kcal/mol for AR·HFT·LXXLL) and nonpolar interactions (𝛥𝐸𝑣𝑑𝑊 +𝛥𝐺𝑆𝐴 = -50.68 kcal/mol for AR·DHT·LXXLL and -48.34 kcal/mol for AR·HFT·LXXLL). As shown in Figure 10, the residues related to the SRC3 recruitment mainly locate on the regions around the Ctermini of H3, L3-4, H4 and H12. Furthermore, several residues with high affinities were observed in both of the AR·DHT·LXXLL and AR·HFT·LXXLL systems, including VAL713, VAL716, LYS720, 18


Page 19 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


VAL730, GLN733, MET734, ILE737, GLU893, MET894 and GLU897. Much more emphasis would also be put on the investigations of the residues with distinct contributions in the two models, such as the residues LYS720, ARG726, MET734 and GLU897. Table 3. The binding free energies and the corresponding energetic components of the SRC3 peptides in complex with the liganded AR-LBDs predicted by MM/GBSA (kcal/mol)a Complexes

AR·DHT·LxxLL

AR·HFT·LxxLL

ΔEele

-77.36±0.68

-44.48±2.42

ΔEvdW

-44.97±0.25

-43.48±0.12

ΔGSA

-5.71±0.02

-4.86±0.01

ΔGGB

75.82±0.75

46.33±2.28

ΔGnon-polar

-50.68±0.23

-48.34±0.13

ΔGpolar

-1.54±0.07

1.85±0.14

ΔGbind

-52.22±0.16

-46.49±0.27

aStandard

deviations were calculated based on the predictions of two blocks (block 1: 1~500 snapshots; block 2: 501~1000 snapshots).

19



Page 20 of 38

Figure 6. Per-residue binding free energy decomposition of the total receptor-ligand binding free energy for (A) AR·DHT·LxxLL and (B) AR·DHT. Critical regions composing the LBP are marked in gray boxes. (C) Difference between the contributions of each AR residue to the binding free energies of 𝑑𝑖𝑚𝑒𝑟 𝑡𝑟𝑖𝑚𝑒𝑟 𝑑𝑖𝑚𝑒𝑟 AR·DHT·LxxLL and AR·DHT. 𝛥𝛥𝐺𝑟𝑒𝑠𝑖𝑑𝑢𝑒 = 𝛥𝐺𝑡𝑟𝑖𝑚𝑒𝑟 𝑏𝑖𝑛𝑑 ―𝛥𝐺𝑏𝑖𝑛𝑑 , where 𝛥𝐺𝑏𝑖𝑛𝑑 and 𝛥𝐺𝑏𝑖𝑛𝑑 represent

the binding free energy of AR·DHT·LxxLL and AR·DHT, respectively.

20


Page 21 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 7. Per-residue binding free energy decomposition of the total receptor-ligand binding free energy for (A) AR·HFT·LxxLL and (B) AR·HFT. Critical regions composing the LBP are marked in gray boxes. (C) Difference between the contributions of each AR residue to the binding free energies of 𝑑𝑖𝑚𝑒𝑟 𝑡𝑟𝑖𝑚𝑒𝑟 𝑑𝑖𝑚𝑒𝑟 AR·HFT·LxxLL and AR·HFT. 𝛥𝛥𝐺𝑟𝑒𝑠𝑖𝑑𝑢𝑒 = 𝛥𝐺𝑡𝑟𝑖𝑚𝑒𝑟 𝑏𝑖𝑛𝑑 ―𝛥𝐺𝑏𝑖𝑛𝑑 , where 𝛥𝐺𝑏𝑖𝑛𝑑 and 𝛥𝐺𝑏𝑖𝑛𝑑 represent

the contributions of the residues in AR·HFT·LxxLL and AR·HFT, respectively.

21



Page 22 of 38

Figure 8. Comparison of the binding of DHT to the AR-LBDs. Overall structural superposition of the AR·DHT·LxxLL (blue) and AR·DHT (purple) models in the (A) front and (B) back views. The ARLBD and SRC3 peptides are depicted as cartoons, and the bound DHT is in ball-and-stick representation. These helices of the AR-LBD are marked and numbered 1 to 12. Closeup of the key residues in the LBP responsible for the DHT binding in the (C) AR·DHT·LxxLL model or (D) AR·DHT model, colored in blue or purple, respectively. The ligand DHT is shown as wires. (E-G) Details of the structural superposition of the LBP in the AR·DHT·LxxLL (blue) and AR·DHT (purple) models. (E) Closeup of 22


Page 23 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


the superposition of DHT shown in ball-and-stick representation. (F-G) Closeup of the relevant residues with remarkable different orientations. For clarity, the ligand DHT is shown as wires, and the residues LEU704, TRP741, MET742, MET895 and ILE899 are depicted as sticks and labelled.

Figure 9. Comparison of the binding of HFT to the AR-LBDs. Overall structural superposition of the AR·HFT·LxxLL (orange) and AR·HFT (pink) models in the (A) front and (B) back views. The AR-LBD protein and SRC3 peptides are depicted as cartoons, and the bound HFT is in ball-and-stick representation. The helices of the AR-LBD are marked and numbered 1 to 12. Closeup of the key residues 23



Page 24 of 38

in the LBP responsible for the HFT binding in the (C) AR·HFT·LxxLL model or (D) AR·HFT model, colored in orange or pink, respectively. The HFT ligands are shown as wires. (E-G) Details of structural superposition of the LBP in the AR·HFT·LxxLL (orange) and AR·HFT (pink) models. (E) Closeup of superposition of HFT shown in ball-and-stick representation. Two HFT ligands occupy similar positions in the LBP, but the HFT plane is twisted in AR·HFT·LxxL (orange). (F-G) Closeup of relevant residues with remarkable different orientations. For clarity, the ligand HFT is shown as wires, and the residues LEU704, ASN705, ARG752, MET780 and LEU873 are depicted as sticks and labelled.

Figure 10. Per-residue binding free energy decomposition of the total receptor-peptide binding free energy for (A) AR·DHT·LxxLL and (B) AR·HFT·LxxLL. Critical regions composing the AF2 are marked in gray boxes. (C) Difference between the contributions of each AR residue to the binding free energies of AR·DHT·LxxLL and the AR·HFT·LxxLL. 𝛥𝛥𝐺𝑟𝑒𝑠𝑖𝑑𝑢𝑒 = 𝛥𝐺𝐴𝑅·𝐷𝐻𝑇·𝐿𝑥𝑥𝐿𝐿 , ― 𝛥𝐺𝐴𝑅·𝐻𝐹𝑇·𝐿𝑥𝑥𝐿𝐿 𝑏𝑖𝑛𝑑 𝑏𝑖𝑛𝑑 24


Page 25 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


where 𝛥𝐺𝐴𝑅·𝐷𝐻𝑇·𝐿𝑥𝑥𝐿𝐿 and 𝛥𝐺𝐴𝑅·𝐻𝐹𝑇·𝐿𝑥𝑥𝐿𝐿 represent the contributions of the residues in AR·DHT·LxxLL 𝑏𝑖𝑛𝑑 𝑏𝑖𝑛𝑑 and AR·HFT·LxxLL, respectively.

Structural Difference of LBP in AR·DHT and AR·DHT·LXXLL The AR·DHT and AR·DHT·LXXLL structures were compared to understand how the SRC3 peptide recruitment influences the interactions between the LBP and AF2. A superposition of the representative structures of the AR-LBD proteins in the two systems (AR·DHT and AR·DHT·LXXLL) is displayed in Figure 8. The secondary structural elements of the two systems are similar. The largest structural difference locates on the AF2 region, including the C-termini of H3, L3-4, and the N-termini of H4, H11 and H12 that are close to the SRC3 fragment. H5 and H6 of the SRC3-bound system tend to move outward, leading to the expansion of the DHT-binding pocket (the volumes of the LBP cavities in AR·DHT and AR·DHT·LXXLL computed using the CASTp server66 are 207.551 Å3 and 252.749 Å3, respectively). Remarkable differences in the orientations as well as the contributions of several residues were also observed, i.e. LEU704, TRP741, MET742, MET895 and ILE899. The rotation of the isobutyl group of LEU704 to the interior of the LBP of AR·DHT·LXXLL would enhance the hydrophobic attraction between DHT and the non-polar aliphatic sidechain of LEU704 (Figure 8F). The sidechain of TRP741 moves into the space occupied by MET742 in the AR·DHT·LXXLL model (Figure 8F). TRP741 and MET742 interact with each other to avoid their steric hindrance with DHT. ILE899, a vital part of H12, and its neighboring residues move towards the center of the LBP of AR·DHT·LXXLL (Figure 8G).

Structural Difference of LBP in AR·HFT and AR·HFT·LXXLL We also attempted to gain insight into the fate of the HFT-binding pocket under the influence of the binding of the SRC3 peptide to the AF2. As represented by the superposition of the representative structures shown in Figure 9A and B, most helices in the trimer have a high degree of overlap with those in the dimer. In the AR·HFT·LXXLL model, we observed the outward dislodgment of the upper part of H3, L3-4 and H12 at the rim of the AF2 pocket, accompanied by the upward movement of H4 at the bottom of the AF2. Those coupled movements consequently provide enough space to accommodate the SRC3 peptide. Meanwhile, H9 and L9-10 at the back of the AF2 region move in a large range of motions

25



Page 26 of 38

in line with their remarkable flexibility (Figure 2A). The lower part of H10 also moves laterally in the AR·HFT·LXXLL model but its upper part close to HFT does not move significantly. Closer inspection reveals that the conformational features of several important residues within the LBP exhibit significant differences between the trimer and dimer, such as LEU704, ARG752, MET780, LEU873 and MET895. In the dimer, the backbone of HFT maintains an approximate planar conformation (Figure 9E), which is similar to the orientations of DHT in the two DHT-bound AR models (Figure 8E), consequently placing HFT roughly close to LEU704 as well as ASN705 and forming H-bond interactions (Figure 9F). The skewed n-propylamide group of HFT in the ternary system precludes the formation of the H-bonding contact with LEU704 or ASN705, but this could make its group much closer to the hydrophobic sidechains of MET780 and LEU873 (Figure 9F), thereby forming stronger hydrophobic interactions with MET780 (𝛥𝐺𝑛𝑜𝑛𝑝𝑜𝑙𝑎𝑟 = -1.58 kcal/mol for AR·HFT·LXXL and -0.6 kcal/mol for AR·HFT) and LEU873 (𝛥𝐺𝑛𝑜𝑛𝑝𝑜𝑙𝑎𝑟 = -3.12 kcal/mol for AR·HFT·LXXL and -1.84 kcal/mol for AR·HFT). In the AR·HFT binary system, ARG752 is embedded in the LBP (Figure 9G), similar to its closedlike orientation in the DHT-bound AR-LBD models. For the ternary model, ARG752 adopts a closedlike conformation at the beginning of the simulation but then undergoes a conformational transition to an open-like conformation and maintains so until the end of the simulation. As seen in the AR·HFT·LXXLL model, ARG752 alters its state in a manner that the rotatable and long straight sidechain of the arginine residue is dislodged outwards from the pocket with a rotation angle of almost 180° relative to the dimer. This might explain the loss of the electrostatic potential contributed from ARG752 in the trimer (𝛥𝐸𝑒𝑙𝑒 = 0.94 kcal/mol for AR·HFT·LXXL and -3.12 kcal/mol for AR·HFT). On the other hand, the pocket is emphatically expanded to accommodate the HFT's skewness in the ternary system, in line with the volume calculations of the HFT-binding pocket (179.742 Å3 in AR·HFT·LXXLL and 148.417 Å3 in AR·HFT). Other conformational changes were detected in the vicinity of ARG752, such as VAL684 and TRP751. In the binary model, the position of ARG752 might be stabilized roughly by the direct steric barrier from VAL684 and TRP751. After the recruitment of the SRC3 peptide, H4 draws close to the peptide, coupled with the outward dislodgment of the upper part of H3 (Figure 9A and B) through electrostatic and hydrophobic interactions (Figure 10B and Table S3). Especially, VAL713 and VAL716 from H3 in AR·HFT·LXXLL exhibit stronger interactions with SRC3 (Figure 10C) than those in AR·DHT·LxxLL. H3 and H4 transmit a pushing force and a pulling force to L1-3 (VAL684) and H5 (TRP751), respectively. Therefore, the cooperative motions of these residues provide 26


Page 27 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


a chance for the guanidinium end of ARG752 to rotate outwards and escape from the pocket. An allosteric pathway of the coactivator→H3/H4→L1-3/H5→HFT exists in the antagonistic form of ARs. Meanwhile, this supports a previous assumption that there exist mutual perturbations between the two subunits, the LBP and AF238.

Structural Characterization of SRC3 Peptide Binding with AF2 Herein, the SRC3 peptide contains 12 residues with a core LXXLL motif flanked by three and four residues at the N and C termini. The sidechains of the three conserved leucines (LEU+1, LEU+4 and LEU+5) are found to align and form a core hydrophobic face of the coactivator α-helix which packs against this deep narrow pocket (Figure 11 A and B). The sidechains of the two non-conserved residues (LEU+2 and GLN+3) of the core LXXLL motif are largely solvent exposed and might not exhibit specific interactions with the receptor (Figure 11C). The residues outside this core LXXLL motif are in an extended random coiled-coil conformation. The AF2 is a hydrophobic coactivator-binding surface formed by the helices H3, H4 and H12 together with a part of the loop L3-4. In some ways, this highly conserved site in AR resembles those in other NRs: it is a L-shaped narrow cleft comprised of three distinct subdomains bearing hydrophobic groups at the +1, +4, and +5 positions of the LXXLLcontaining peptides (Figure 11C). As observed in the representative structures of the two SRC3-present models (Figure 12A and B), the AR-LBD in AR·DHT·LXXLL overlaps well with that in AR·HFT·LXXLL. Apparently, the SRC3 peptide is unable to disturb the core scaffolds of ARs, but indepth comparisons reveal strikingly different arrangements of the AF2 surfaces, thus inducing nonequivalent positions of the SRC3 peptides (Figure 12C). The AF2 narrow cavity of AR·DHT·LXXLL apparently increases the distance between its lateral sides to pack the sidechains of the three leucines in LXXLL tightly, in conformity to the stronger binding affinity of the SRC3 peptide. In the HFT-bound ternary model, H4 moves towards the center of the AF2 pocket, coupled with the upward movement of H12, resulting in a relatively small pocket (buried surface area: 601.408 Å2 for AR·DHT·LXXLL and 525.332 Å2 for AR·HFT·LXXLL). Simultaneously, the SRC3 peptide moves towards H3 to avoid steric hindrance from the H12 residues, thus helping to explain why the SRC3 peptide does not interact well with the HFT-bound AR.

27



Page 28 of 38

Figure 11. Details of the AF2 coactivator-interacting surface of the AR-LBD in AR·DHT·LxxLL. (A) Overall surface representation of the AR-LBD (yellow) that forms tight binding with the SRC3 peptide (light gray cartoons) with the LxxLL motif (the side chains represented as sticks). The bound DHT is shown in sphere representation. (B) Opened surface representation of the binding interface between the SRC3 peptide and AR-LBD. The side chains of the key residues involved in the direct protein-peptide contacts are shown as sticks, and the interfaces or residues belonging to the SRC3 peptide and AR-LBD are colored in green and brown, respectively. (C) Closeup of the AF2 binding groove with the bound SRC3 peptide shown as light gray cartoons (the side chains of the LxxLL motif represented as sticks). AF2 surface contains three distinct subdomains: +1 (dark blue), +4 (pink), and +5 (red).

Similar patterns were observed for the interactions between the LXXLL motifs and the AF2 sites in all the complexes despite some exceptions as discussed in detail below. The three leucine residues (LEU+1, LEU+4 and LEU+5) in the LXXLL motif tightly packed into the groove form quite favorable hydrophobic interactions with a number of hydrophobic residues in the AF2, including VAL716, VAL730, MET734, ILE737, MET894, ILE898, and the non-polar parts of ASP731 and GLU893 and GLU897 (Figure 12D and G, and Table S3). Typically, two highly conserved “charge clamp” residues at either end of the AF2 (GLU897 in H12 and LYS720 in H3) that are especially critical for the AF2 functions appear to act as a charge clamp to hold the coactivator α-helix in position (Figure 12C). LYS720 and GLU897 make favorable electrostatic interactions with the main chain atoms at the ends of the α-helix: LYS720 with the carbonyl group of LEU+5, and GLU897 with the amide nitrogens of LEU+1 (Figure 12C).

28


Page 29 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 12. Comparisons of the binding of the SRC3 peptide to the AR-LBDs. Overall structural superposition of the AR·DHT·LxxLL (blue) and AR·HFT·LxxLL (orange) models in the (A) front and (B) back views. The AR-LBD protein and SRC3 peptides are depicted as cartoons and licorices, and the bound DHT or HFT is in ball-and-stick representation. (C) Details of the structural superposition of the AF2 coactivator-binding pocket of the AR-LBD in the AR·DHT·LxxLL (blue) and AR·HFT·LxxLL (orange) models. Typically, LYS720 and GLU897, the so-called electrostatic "charge clamp" residues, are depicted as sticks and labelled. Closeup of the AF2 surface colored by amino acid hydrophobicity for the (D) AR·DHT·LxxLL and (G) AR·HFT·LxxLL models. The most polar residues are colored in green 29



Page 30 of 38

and the most hydrophobic residues in yellow. (E, H) Closeup of the AF2 surface highlighting the relevant residues with remarkably different orientations. (F, I) Closeup of the H-bonding contacts (indicated with green lines) between the SRC3 peptide and AR-LBD. Residues are shown as color-coded sticks (hydrogen, white; oxygen, red; nitrogen, bright blue; carbon, yellow or blue or orange) and labelled. Comparison of the representative structures also reveals several different features of the interaction modes. MET734 of AR functions as a mediator to change the geometry of the +1 and +5 subdomains (LEU+1 and LEU+5). In contrast to an almost perpendicular conformation to the surface of the protein in AR·DHT, MET734 moves away from the +5 subdomain and extends into the +1 subdomain in AR·DHT·LXXLL, followed by a shift of LEU+2 to reach over MET734 and clamp the methionine residue between LEU+2 and LEU+1 (Figure 12E). This rearrangement could simultaneously widen and shallow the +5 subdomain and make it easy for LEU+5 to interact with LYS720. In the AR·HFT·LXXLL model, MET734 of AR occupies a similar position, but LYS720 is too distant to form effective helicalcapping interactions with the +5 carbonyl group (Figure 12H) because of a different orientation and placement of the LXXLL motif into the groove. Small shifts in the position of the N-terminal region of H12 can be observed in AR·HFT·LXXLL, which repositions MET894 to form more optimal contacts with the +4 residue bound at the +4 subdomain. The carbonyl of the C-terminal residue (LEU+5) of the LXXLL helix forms a stable H-bond with LYS720 in AR·DHT·LXXLL (Figure 12F), while this Hbond is not observed in AR·HFT·LXXLL (Figure 12I). The SRC3 peptide forms new interactions with the AR-LBD to compensate for the lack of the H-bonding interactions between the clamp residue GLU897 and its LXXLL motif. GLU897 forms H-bonding contacts with the second upstream residue (LYS-2) in the two ternary models. The upstream lysine residues (LYS-1 and LYS-2) and downstream serine residues (SER+8 and SER+9) outside the core LXXLL motif also participate in the H-bonding interactions with specific residues of the DHT-bound AR, while these interactions are barely observed in the HFT-bound complex. Unexpectedly, the basic residue, ARG726 appears to play the extra Cterminal capping role in the DHT-bound complex to stabilize the whole peptide other than the LXXLL α-helix motif, but not in the HFT-bound complex. In conclusion, the SRC3 peptide recruitment in the HFT-bound AR differs from that in the DHT-bound AR particularly resulting from the loss of several significant H-bonds between the core LXXLL motifs and AF2.

30


Page 31 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Conclusions It is still unclear about the fate of the ligands in the LBP under the influence of the binding of the SRC3 peptide to the AF2. In this work, the all-atom MD simulation, as well as MM/GBSA free energy calculations were employed to study the bidirectional communication between the hormone-binding pocket (HBP) and the activation function-2 (AF2) domain. 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. The androgen DHT binding process promotes the SRC3 peptide recruitment to the AF2, as AR·DHT·LXXLL exhibits the stronger MM/GBSA binding free energy of SRC3 than AR·HFT·LXXLL. The AF2 structure in AR·DHT·LXXLL could help pack the LXXLL motif to ARs tightly, in contrast with AF2 in AR·HFT·LXXLL. In the presence of an agonist DHT, the conserved LYS720 in H3 contacts with the C-terminal residue (LEU+5) of the LXXLL motif. The conserved GLU897 in H12 participates in the H-bonding contacts with the lysine residue (LYS-2) outside this core LXXLL instead of capping the N-terminal amide of the LXXLL motif. On the other hand, the binding of HFT changes the structure of the AF2 and therefore decreases the capability to accommodate the SRC3 peptides. The SRC3 peptide in AR·HFT·LXXLL was found to occupy an ill-suited position in the AF2 groove through an energetically non-favorable conformation, which would disturb the H-bonding interactions between LEU+5 and LYS720. We also found that the DHT binding affinity of AR would be enhanced by the association of the coactivator SRC3, which would reduce the conformational flexibility of the AR-LBD and stabilize the structure of the LBP. The SRC3 recruitment would regulate the interactions between the AF2 and LBP, leading to a larger binding pocket for the DHT binding. However, it appears that the SRC3 association would not facilitate the binding of the antagonist (𝛥𝐺𝑏𝑖𝑛𝑑 = -40.59 kcal/mol for AR·HFT·LXXLL and 42.57 kcal/mol for AR·HFT). After recruitment of the SRC3 peptide, the AF-2 region is rearranged, including the outward dislodgment of H3 and upward movements of H4. A concomitant push-pull effort from the AF2 surface (H3 and H4) is transmitted to the HFT binding pocket (H5), and then the pocket is expanded to accommodate HFT's skewness. The structure of the ligand in the AR·HFT·LXXLL complex is distinct from that in the AR·HFT complex. HFT in the AR·HFT complex prefer to the orientation adopted by agonist, thus establishing different H-bonding networks. Our work highlights the important role of the coactivators to the ligand binding and improves the understanding of ligand binding 31



Page 32 of 38

mechanism, which provides valuable information for the rational design of potent drugs to inhibit the activity of ARs.

Acknowledgements This work was financially supported by the National Key R&D Program of China (2016YFA0501701, 2016YFB0201700), the National Science Foundation of China (21575128, 81773632), and Shenzhen City Science & Technology Innovation Program (CYZZ20160525094052606).

Supporting Information Table S1. The contributions of the important residues for the binding of DHT with the AR protein (kcal/mol); Table S2. The contributions of the important residues for the binding of HFT with the AR protein (kcal/mol); Table S3. The contributions of the important residues for the binding of the SRC3 peptide with the AR protein (kcal/mol); Figure S1. RMSDs of the heavy atoms of the residues in the LBP as a function of simulation time (residues 697-721,741-756 and 868-908) for (A) AR·DHT·LxxLL, (B) AR·HFT·LxxLL, (C) AR·DHT, and (D) AR·HFT; Figure S2. RMSDs of the heavy atoms of the residues in the AF2 as a function of simulation time (residues 697-739, 892-908) for (A) AR·DHT·LxxLL, (B) AR·HFT·LxxLL, (C) AR·DHT, and (D) AR·HFT; Figure S3. The proportion of the eigenvalue contribution of the eigenmodes (PCs) to the variance of the covariance matrix and the cumulative contribution for each eigenmode (descending order) for (A) AR·DHT·LxxLL, (B) AR·HFT·LxxLL, (C) AR·DHT, and (D) AR·HFT; Figure S4. The projection of the snapshots along the calculated first and second eigenmodes (PCs) for (A) AR·DHT·LxxLL, (B) AR·HFT·LxxLL, (C) AR·DHT, and (D) AR·HFT. The blue bullet point represents each member of the last 100 ns trajectory. The red square represents the initial liganded AR structure in the agonistic form.

References 1.

Gao, W. Q.; Bohl, C. E.; Dalton, J. T., Chemistry and Structural Biology of Androgen Receptor. Chem. Rev. 2005, 105, 3352-3370. 32


Page 33 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

2. 3. 4. 5. 6. 7. 8. 9. 10. 11.

12. 13. 14. 15. 16.

17.


Vanderschueren, D.; Laurent, M. R.; Claessens, F.; Gielen, E.; Lagerquist, M. K.; Vandenput, L.; Borjesson, A. E.; Ohlsson, C., Sex Steroid Actions in Male Bone. Endocr. Rev. 2014, 35, 906-960. Attard, G.; Parker, C.; Eeles, R. A.; Schroder, F.; Tomlins, S. A.; Tannock, I.; Drake, C. G.; de Bono, J. S., Prostate Cancer. Lancet 2016, 387, 70-82. Augello, M. A.; Den, R. B.; Knudsen, K. E., Ar Function in Promoting Metastatic Prostate Cancer. Cancer Metastasis Rev. 2014, 33, 399-411. Brinkmann, A. O.; Blok, L. J.; de Ruiter, P. E.; Doesburg, P.; Steketee, K.; Berrevoets, C. A.; Trapman, J., Mechanisms of Androgen Receptor Activation and Function. J. Steroid Biochem. Mol. Biol. 1999, 69, 307-313. Miyamoto, H.; Messing, E. M.; Chang, C. S., Androgen Deprivation Therapy for Prostate Cancer: Current Status and Future Prospects. Prostate 2004, 61, 332-353. Bassetto, M.; Ferla, S.; Pertusati, F.; Kandil, S.; Westwell, A. D.; Brancale, A.; McGuigan, C., Design and Synthesis of Novel Bicalutamide and Enzalutamide Derivatives as Antiproliferative Agents for the Treatment of Prostate Cancer. Eur. J. Med. Chem. 2016, 118, 230-243. Goldspiel, B. R.; Kohler, D. R., Flutamide: An Antiandrogen for Advanced Prostate Cancer. Dicp Ann. Pharmacother. 1990, 24, 616-623. Hara, T.; Miyazaki, J.; Araki, H.; Yamaoka, M.; Kanzaki, N.; Kusaka, M.; Miyamoto, M., Novel Mutations of Androgen Receptor: A Possible Mechanism of Bicalutamide Withdrawal Syndrome. Cancer Res. 2003, 63, 149-153. Dole, E. J.; Holdsworth, M. T., Nilutamide: An Antiandrogen for the Treatment of Prostate Cancer. Ann. Pharmacother. 1997, 31, 65-75. Scher, H. I.; Fizazi, K.; Saad, F.; Taplin, M. E.; Sternberg, C. N.; Miller, K.; de Wit, R.; Mulders, P.; Chi, K. N.; Shore, N. D.; Armstrong, A. J.; Flaig, T. W.; Flechon, A.; Mainwaring, P.; Fleming, M.; Hainsworth, J. D.; Hirmand, M.; Selby, B.; Seely, L.; de Bono, J. S.; Investigators, A., Increased Survival with Enzalutamide in Prostate Cancer after Chemotherapy. N. Engl. J. Med. 2012, 367, 1187-1197. Huang, P. X.; Chandra, V.; Rastinejad, F., Structural Overview of the Nuclear Receptor Superfamily: Insights into Physiology and Therapeutics. Annu. Rev. Physiol. 2010, 72, 247-272. Haelens, A.; Tanner, T.; Denayer, S.; Callewaert, L.; Claessens, F., The Hinge Region Regulates DNA Binding, Nuclear Translocation, and Transactivation of the Androgen Receptor. Cancer Res. 2007, 67, 4514-4523. Mangelsdorf, D. J.; Thummel, C.; Beato, M.; Herrlich, P.; Schutz, G.; Umesono, K.; Blumberg, B.; Kastner, P.; Mark, M.; Chambon, P.; Evans, R. M., The Nuclear Receptor Superfamily: The Second Decade. Cell 1995, 83, 835-839. Li, Y.; Lambert, M. H.; Xu, H. E., Activation of Nuclear Receptors: A Perspective from Structural Genomics. Structure 2003, 11, 741-746. Matias, P. M.; Donner, P.; Coelho, R.; Thomaz, M.; Peixoto, C.; Macedo, S.; Otto, N.; Joschko, S.; Scholz, P.; Wegg, A.; Basler, S.; Schafer, M.; Egner, U.; Carrondo, M. A., Structural Evidence for Ligand Specificity in the Binding Domain of the Human Androgen Receptor Implications for Pathogenic Gene Mutations. J. Biol. Chem. 2000, 275, 26164-26171. Sack, J. S.; Kish, K. F.; Wang, C. H.; Attar, R. M.; Kiefer, S. E.; An, Y. M.; Wu, G. Y.; Scheffler, J. E.; Salvati, M. E.; Krystek, S. R.; Weinmann, R.; Einspahr, H. M., Crystallographic Structures of the Ligand-Binding Domains of the Androgen Receptor and Its T877a Mutant Complexed with the Natural Agonist Dihydrotestosterone. Proc. Natl. Acad. Sci. U. S. A. 2001, 98, 4904-4909. 33



18. 19. 20. 21. 22. 23. 24.

25. 26.

27. 28. 29. 30. 31.

32. 33.

Page 34 of 38

Dehm, S. M.; Tindall, D. J., Androgen Receptor Structural and Functional Elements: Role and Regulation in Prostate Cancer. Mol. Endocrinol. 2007, 21, 2855-2863. He, B.; Kemppainen, J. A.; Voegel, J. J.; Gronemeyer, H.; Wilson, E. M., Activation Function 2 in the Human Androgen Receptor Ligand Binding Domain Mediates Interdomain Communication with the Nh2-Terminal Domain. J. Biol. Chem. 1999, 274, 37219-37225. Heinlein, C. A.; Chang, C. S., Androgen Receptor (Ar) Coregulators: An Overview. Endocr. Rev. 2002, 23, 175-200. Hur, E.; Pfaff, S. J.; Payne, E. S.; Gron, H.; Buehrer, B. M.; Fletterick, R. J., Recognition and Accommodation at the Androgen Receptor Coactivator Binding Interface. PLoS Biol. 2004, 2, 1303-1312. Zhou, H. J.; Yan, J.; Luo, W. P.; Ayala, G.; Lin, S. H.; Erdem, H.; Ittmann, M.; Tsai, S. Y.; Tsai, N. J., Src-3 Is Required for Prostate Cancer Cell Proliferation and Survival. Cancer Res. 2005, 65, 7976-7983. Anzick, S. L.; Kononen, J.; Walker, R. L.; Azorsa, D. O.; Tanner, M. M.; Guan, X. Y.; Sauter, G.; Kallioniemi, O. P.; Trent, J. M.; Meltzer, P. S., Aib1, a Steroid Receptor Coactivator Amplified in Breast and Ovarian Cancer. Science 1997, 277, 965-968. Kirkegaard, T.; McGlynn, L. M.; Campbell, F. M.; Muller, S.; Tovey, S. M.; Dunne, B.; Nielsen, K. V.; Cooke, T. G.; Bartlett, J. M. S., Amplified in Breast Cancer 1 in Human Epidermal Growth Factor Receptor-Positive Tumors of Tamoxifen-Treated Breast Cancer Patients. Clin. Cancer Res. 2007, 13, 1405-1411. Zuo, G.; Huang, Q.; Wei, G.; Zhou, R.; Fang, H., Plugging into Proteins: Poisoning Protein Function by a Hydrophobic Nanoparticle. Acs Nano 2010, 4, 7508-14. He, B.; Gampe, R. T.; Kole, A. J.; Hnat, A. T.; Stanley, T. B.; An, G.; Stewart, E. L.; Kalman, R. I.; Minges, J. T.; Wilson, E. M., Structural Basis for Androgen Receptor Interdomain and Coactivator Interactions Suggests a Transition in Nuclear Receptor Activation Function Dominance. Mol. Cell 2004, 16, 425-438. Heery, D. M.; Kalkhoven, E.; Hoare, S.; Parker, M. G., A Signature Motif in Transcriptional Co-Activators Mediates Binding to Nuclear Receptor. Nature 1997, 387, 733-736. Lonard, D. M.; O'Malley, B. W., The Expanding Cosmos of Nuclear Receptor Coactivators. Cell 2006, 125, 411-414. Glass, C. K.; Rosenfeld, M. G., The Coregulator Exchange in Transcriptional Functions of Nuclear Receptors. Genes Dev. 2000, 14, 121-141. Bohl, C. E.; Gao, W. Q.; Miller, D. D.; Bell, C. E.; Dalton, J. T., Structural Basis for Antagonism and Resistance of Bicalutamide in Prostate Cancer. Proc. Natl. Acad. Sci. U. S. A. 2005, 102, 6201-6206. Estebanez-Perpina, E.; Moore, J. M. R.; Mar, E.; Delgado-Rodrigues, E.; Nguyen, P.; Baxter, J. D.; Buehrer, B. M.; Webb, P.; Fletterick, R. J.; Guy, R. K., The Molecular Mechanisms of Coactivator Utilization in Ligand-Dependent Transactivation by the Androgen Receptor. J. Biol. Chem. 2005, 280, 8060-8068. Shaffer, P. L.; Jivan, A.; Dollins, D. E.; Claessens, F.; Gewirth, D. T., Structural Basis of Androgen Receptor Binding to Selective Androgen Response Elements. Proc. Natl. Acad. Sci. U. S. A. 2004, 101, 4758-4763. Nadal, M.; Prekovic, S.; Gallastegui, N.; Helsen, C.; Abella, M.; Zielinska, K.; Gay, M.; Vilaseca, M.; Taules, M.; Houtsmuller, A. B.; van Royen, M. E.; Claessens, F.; Fuentes-Prior, P.; Estebanez-Perpina, E., Structure of the Homodimeric Androgen Receptor Ligand-Binding Domain. Nat. Commun. 2017, 8, 14. 34


Page 35 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

34. 35. 36. 37. 38. 39. 40. 41. 42. 43.

44. 45. 46. 47.

48.


Karplus, M.; McCammon, J. A., Molecular Dynamics Simulations of Biomolecules. Nat. Struct. Biol. 2002, 9, 646-652. Bisson, W. H.; Abagyan, R.; Cavasotto, C. N., Molecular Basis of Agonicity and Antagonicity in the Androgen Receptor Studied by Molecular Dynamics Simulations. J. Mol. Graph. Model. 2008, 27, 452-458. Zhou, J. M.; Liu, B.; Geng, G. Y.; Wu, J. H., Study of the Impact of the T877a Mutation on Ligand-Induced Helix-12 Positioning of the Androgen Receptor Resulted in Design and Synthesis of Novel Antiandrogens. Proteins 2010, 78, 623-637. Osguthorpe, D. J.; Hagler, A. T., Mechanism of Androgen Receptor Antagonism by Bicalutamide in the Treatment of Prostate Cancer. Biochemistry 2011, 50, 4105-4113. Duan, M. J.; Liu, N.; Zhou, W. F.; Li, D.; Yang, M. H.; Hou, T. J., Structural Diversity of Ligand-Binding Androgen Receptors Revealed by Microsecond Long Molecular Dynamics Simulations and Enhanced Sampling. J. Chem. Theory Comput. 2016, 12, 4611-4619. Xu, X.; Yang, W.; Wang, X.; Li, Y.; Wang, Y. H.; Ai, C. Z., Dynamic Communication between Androgen and Coactivator: Mutually Induced Conformational Perturbations in Androgen Receptor Ligand-Binding Domain. Proteins 2011, 79, 1154-1171. Liu, N.; Zhou, W. F.; Guo, Y.; Wang, J. M.; Fu, W. T.; Sun, H. Y.; Liu, D.; Duan, M. J.; Hou, T. J., Molecular Dynamics Simulations Revealed the Regulation of Ligands to the Interactions between Androgen Receptor and Its Coactivator. J. Chem. Inf. Model. 2018, 58, 1652-1661. Liu, H.; Wang, L.; Tian, J.; Li, J.; Liu, H., Molecular Dynamics Studies on the Enzalutamide Resistance Mechanisms Induced by Androgen Receptor Mutations. J. Cell. Biochem. 2017, 118, 2792-2801. Sakkiah, S.; Kusko, R.; Pan, B.; Guo, W.; Ge, W.; Tong, W.; Hong, H., Structural Changes Due to Antagonist Binding in Ligand Binding Pocket of Androgen Receptor Elucidated through Molecular Dynamics Simulations. Front. Pharmacol. 2018, 9. Hsu, C. L.; Liu, J. S.; Wu, P. L.; Guan, H. H.; Chen, Y. L.; Lin, A. C.; Ting, H. J.; Pang, S. T.; Yeh, S. D.; Ma, W. L.; Chen, C. J.; Wu, W. G.; Chang, C. S., Identification of a New Androgen Receptor (Ar) Co-Regulator Bud31 and Related Peptides to Suppress Wild-Type and Mutated Ar-Mediated Prostate Cancer Growth Via Peptide Screening and X-Ray Structure Analysis. Mol. Oncol. 2014, 8, 1575-1587. Fiser, A.; Do, R. K. G.; Sali, A., Modeling of Loops in Protein Structures. Protein Sci. 2000, 9, 1753-1773. Wang, J. M.; Wolf, R. M.; Caldwell, J. W.; Kollman, P. A.; Case, D. A., Development and Testing of a General Amber Force Field. J. Comput. Chem. 2004, 25, 1157-1174. Maier, J. A.; Martinez, C.; Kasavajhala, K.; Wickstrom, L.; Hauser, K. E.; Simmerling, C., Ff14sb: Improving the Accuracy of Protein Side Chain and Backbone Parameters from Ff99sb. J. Chem. Theory Comput. 2015, 11, 3696-3713. Pearlman, D. A.; Case, D. A.; Caldwell, J. W.; Ross, W. S.; Cheatham, T. E.; Debolt, S.; Ferguson, D.; Seibel, G.; Kollman, P., Amber, a Package of Computer Programs for Applying Molecular Mechanics, Normal Mode Analysis, Molecular Dynamics and Free Energy Calculations to Simulate the Structural and Energetic Properties of Molecules. Comput. Phys. Commun. 1995, 91, 1-41. Paschek, D.; Day, R.; Garcia, A. E., Influence of Water-Protein Hydrogen Bonding on the Stability of Trp-Cage Miniprotein. A Comparison between the Tip3p and Tip4p-Ew Water Models. Phys. Chem. Chem. Phys. 2011, 13, 19840-19847. 35



49. 50. 51. 52. 53. 54.

55. 56. 57. 58. 59. 60. 61. 62. 63. 64.

65.

Page 36 of 38

Harvey, M. J.; De Fabritiis, G., An Implementation of the Smooth Particle Mesh Ewald Method on Gpu Hardware. J. Chem. Theory Comput. 2009, 5, 2371-2377. Loncharich, R. J.; Brooks, B. R.; Pastor, R. W., Langevin Dynamics of Peptides: The Frictional Dependence of Isomerization Rates of N‐Acetylalanyl‐N′‐Methylamide. Biopolymers 1992, 32, 523-535. Elber, R.; Ruymgaart, A. P.; Hess, B., Shake Parallelization. Eur. Phys. J.-Spec. Top. 2011, 200, 211-223. Rastelli, G.; Del Rio, A.; Degliesposti, G.; Sgobba, M., Fast and Accurate Predictions of Binding Free Energies Using Mm-Pbsa and Mm-Gbsa. J. Comput. Chem. 2010, 31, 797-810. Hou, T. J.; Wang, J. M.; Li, Y. Y.; Wang, W., Assessing the Performance of the Mm/Pbsa and Mm/Gbsa Methods. 1. The Accuracy of Binding Free Energy Calculations Based on Molecular Dynamics Simulations. J. Chem. Inf. Model. 2011, 51, 69-82. Sun, H. Y.; Li, Y. Y.; Tian, S.; Xu, L.; Hou, T. J., Assessing the Performance of Mm/Pbsa and Mm/Gbsa Methods. 4. Accuracies of Mm/Pbsa and Mm/Gbsa Methodologies Evaluated by Various Simulation Protocols Using Pdbbind Data Set. Phys. Chem. Chem. Phys. 2014, 16, 16719-16729. Onufriev, A.; Bashford, D.; Case, D. A., Exploring Protein Native States and Large-Scale Conformational Changes with a Modified Generalized Born Model. Proteins 2004, 55, 383394. Weiser, J.; Shenkin, P. S.; Still, W. C., Approximate Atomic Surfaces from Linear Combinations of Pairwise Overlaps (Lcpo). J. Comput. Chem. 1999, 20, 217-230. Gohlke, H.; Kiel, C.; Case, D. A., Insights into Protein-Protein Binding by Binding Free Energy Calculation and Free Energy Decomposition for the Ras-Raf and Ras-Raigds Complexes. J. Mol. Biol. 2003, 330, 891-913. Ester, M.; Kriegel, H.-P.; Sander, J.; Xu, X., A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96) 1996, 96, 226-231. Pearson, K., On Lines and Planes of Closest Fit to Systems of Points in Space. Philos. Mag. 1901, 2, 559-572. Hotelling, H., Analysis of a Complex of Statistical Variables into Principal Components. J. Educ. Psychol. 1933, 24, 417-441. vanAalten, D. M. F.; Findlay, J. B. C.; Amadei, A.; Berendsen, H. J. C., Essential Dynamics of the Cellular Retinol-Binding Protein - Evidence for Ligand-Induced Conformational Changes. Protein Eng. 1995, 8, 1129-1135. Ichiye, T.; Karplus, M., Collective Motions in Proteins: A Covariance Analysis of Atomic Fluctuations in Molecular Dynamics and Normal Mode Simulations. Proteins-Structure Function and Genetics 1991, 11, 205-217. Tan, M. H. E.; Li, J.; Xu, H. E.; Melcher, K.; Yong, E. L., Androgen Receptor: Structure, Role in Prostate Cancer and Drug Discovery. Acta Pharmacol. Sin. 2015, 36, 3-23. Kemppainen, J. A.; Langley, E.; Wong, C. I.; Bobseine, K.; Kelce, W. R.; Wilson, E. M., Distinguishing Androgen Receptor Agonists and Antagonists: Distinct Mechanisms of Activation by Medroxyprogesterone Acetate and Dihydrotestosterone. Mol. Endocrinol. 1999, 13, 440-454. Bohl, C. E.; Miller, D. D.; Chen, J. Y.; Bell, C. E.; Dalton, J. T., Structural Basis for Accommodation of Nonsteroidal Ligands in the Androgen Receptor. J. Biol. Chem. 2005, 280, 37747-37754. 36


Page 37 of 38 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

66.


Dundas, J.; Ouyang, Z.; Tseng, J.; Binkowski, A.; Turpaz, Y.; Liang, J., Castp: Computed Atlas of Surface Topography of Proteins with Structural and Topographical Mapping of Functionally Annotated Residues. Nucleic Acids Res. 2006, 34, W116-W118.

37



For Table of Contents Only

38


Page 38 of 38

Communication between the Ligand-Binding Pocket and the

Recommend Documents