Structural Diversity of Ligand-Binding Androgen Receptors Revealed by Microsecond Long Molecular Dynamics Simulations and Enhanced Sampling

Discovery of Novel Anti-Resistance AR Antagonists Guided by Funnel Metadynamics Simulation

Androgen receptor (AR) antagonists are widely used for the treatment of prostate cancer (PCa), but their therapeutic efficacy is usually compromised by the rapid emergence of drug resistance. However, the lack of the detailed interaction between AR and its antagonists poses a major obstacle to the design of novel AR antagonists. Here, funnel metadynamics is employed to elucidate the inherent regulation mechanisms of three AR antagonists (hydroxyflutamide, enzalutamide, and darolutamide) on AR. For the first time it is observed that the binding of antagonists significantly disturbed the C-terminus of AR helix-11, thereby disrupting the specific internal hydrophobic contacts of AR-LBD and correspondingly the communication between AR ligand binding pocket (AR-LBP), activation function 2 (AF2), and binding function 3 (BF3). The subsequent bioassays verified the necessity of the hydrophobic contacts for AR function. Furthermore, it is found that darolutamide, a newly approved AR antagonist capable of fighting almost all reported drug resistant AR mutants, can induce antagonistic binding structure. Subsequently, docking-based virtual screening toward the dominant binding conformation of AR for darolutamide is conducted, and three novel AR antagonists with favorable binding affinity and strong capability to combat drug resistance are identified by in vitro bioassays. This work provides a novel rational strategy for the development of anti-resistant AR antagonists.

Androgen receptor cofactors: A potential role in understanding prostate cancer

Prostate cancer (PCa) is witnessing a concerning rise in incidence annually, with the androgen receptor (AR) emerging as a pivotal contributor to its growth and progression. Mounting evidence underscores the AR's ability to recruit cofactors, influencing downstream gene transcription and thereby fueling the proliferation and metastasis of PCa cells. Although, clinical strategies involving AR antagonists provide some relief, managing castration resistant prostate cancer (CRPC) remains a formidable challenge. Thus, the need of the hour lies in unearthing new drugs or therapeutic targets to effectively combat PCa. This review encapsulates the pivotal roles played by coactivators and corepressors of AR, notably androgen receptor-associated protein (ARA) and steroid receptor Coactivators (SRC) in PCa. Our data unveils how these cofactors intricately modulate histone modifications, cell cycling, SUMOylation, and apoptosis through their interactions with AR. Among the array of cofactors scrutinised, such as ARA70β, ARA24, ARA160, ARA55, ARA54, PIAS1, PIAS3, SRC1, SRC2, SRC3, PCAF, p300/CBP, MED1, and CARM1, several exhibit upregulation in PCa. Conversely, other cofactors like ARA70α, PIASy, and NCoR/SMRT demonstrate downregulation. This duality underscores the complexity of AR cofactor dynamics in PCa. Based on our findings, we propose that manipulating cofactor regulation to modulate AR function holds promise as a novel therapeutic avenue against advanced PCa. This paradigm shift offers renewed hope in the quest for effective treatments in the face of CRPC's formidable challenges.

In Vitro, In Vivo, and In Silico Analysis of Pyraclostrobin and Cyprodinil and Their Mixture Reveal New Targets and Signaling Mechanisms

Pyraclostrobin and cyprodinil are broad-spectrum fungicides that are used in crops to control diseases. However, they are excessively used and, as a result, end up in the environment and threaten human health and ecosystems. Hence, knowledge of their mechanisms of action is critical to revealing their environmental fate and negative effects and regulating their use. In the present study, we conducted a comprehensive study to show the adverse effects of pyraclostrobin, cyprodinil, and their mixture using zebrafish larvae and different cell lines. Several end points were investigated, including mortality, development, gene expression, reporter assays, and molecular docking simulations. We found that both compounds and their mixture caused developmental delays and mortality in zebrafish, with a higher effect displayed by pyraclostrobin. Both compounds altered the expression of genes involved in several signaling pathways, including oxidative stress and mitochondrial function, lipid and drug metabolisms, the cell cycle, DNA damage, apoptosis, and inflammation. A noteworthy result of this study is that cyprodinil and the mixture group acted as NFκB activators, while pyraclostrobin demonstrated antagonist activity. The AHR activity was also upregulated by cyprodinil and the mixture group; however, pyraclostrobin did not show any effect. For the first time, we also demonstrated that pyraclostrobin had androgen receptor antagonist activity.

Applying molecular docking to pesticides

Pesticide creation is related to the development of sustainable agricultural and ecological safety, and molecular docking technology can effectively help in pesticide innovation. This paper introduces the basic theory behind molecular docking, pesticide databases, and docking software. It also summarizes the application of molecular docking in the pesticide field, including the virtual screening of lead compounds, detection of pesticides and their metabolites in the environment, reverse screening of pesticide targets, and the study of resistance mechanisms. Finally, problems with the use of molecular docking technology in pesticide creation are discussed, and prospects for the future use of molecular docking technology in new pesticide development are discussed. © 2023 Society of Chemical Industry.

Ligand-induced shifts in conformational ensembles that describe transcriptional activation

Nuclear receptors function as ligand-regulated transcription factors whose ability to regulate diverse physiological processes is closely linked with conformational changes induced upon ligand binding. Understanding how conformational populations of nuclear receptors are shifted by various ligands could illuminate strategies for the design of synthetic modulators to regulate specific transcriptional programs. Here, we investigate ligand-induced conformational changes using a reconstructed, ancestral nuclear receptor. By making substitutions at a key position, we engineer receptor variants with altered ligand specificities. We combine cellular and biophysical experiments to characterize transcriptional activity, as well as elucidate mechanisms underlying altered transcription in receptor variants. We then use atomistic molecular dynamics (MD) simulations with enhanced sampling to generate ensembles of wildtype and engineered receptors in combination with multiple ligands, followed by conformational analysis and correlation of MD-based predictions with functional ligand profiles. We determine that conformational ensembles accurately describe ligand responses based on observed population shifts. These studies provide a platform which will allow structural characterization of physiologically-relevant conformational ensembles, as well as provide the ability to design and predict transcriptional responses in novel ligands.

Structure-Based Study to Overcome Cross-Reactivity of Novel Androgen Receptor Inhibitors

The mutation-driven transformation of clinical anti-androgen drugs into agonists of the human androgen receptor (AR) represents a major challenge for the treatment of prostate cancer patients. To address this challenge, we have developed a novel class of inhibitors targeting the DNA-binding domain (DBD) of the receptor, which is distanced from the androgen binding site (ABS) targeted by all conventional anti-AR drugs and prone to resistant mutations. While many members of the developed 4-(4-phenylthiazol-2-yl)morpholine series of AR-DBD inhibitors demonstrated the effective suppression of wild-type AR, a few represented by 4-(4-(3-fluoro-2-methoxyphenyl)thiazol-2-yl)morpholine (VPC14368) exhibited a partial agonistic effect toward the mutated T878A form of the receptor, implying their cross-interaction with the AR ABS. To study the molecular basis of the observed cross-reactivity, we co-crystallized the T878A mutated form of the AR ligand binding domain (LBD) with a bound VPC14368 molecule. Computational modelling revealed that helix 12 of AR undergoes a characteristic shift upon VPC14368 binding causing the agonistic behaviour. Based on the obtained structural data we then designed derivatives of VPC14368 to successfully eliminate the cross-reactivity towards the AR ABS, while maintaining significant anti-AR DBD potency.

Determination of Molecule Category of Ligands Targeting the Ligand-Binding Pocket of Nuclear Receptors with Structural Elucidation and Machine Learning

The mechanism of transcriptional activation/repression of the nuclear receptors (NRs) involves two main conformations of the NR protein, namely, the active (agonistic) and inactive (antagonistic) conformations. Binding of agonists or antagonists to the ligand-binding pocket (LBP) of NRs can regulate the downstream signaling pathways with different physiological effects. However, it is still hard to determine the molecular type of a LBP-bound ligand because both the agonists and antagonists bind to the same position of the protein. Therefore, it is necessary to develop precise and efficient methods to facilitate the discrimination of agonists and antagonists targeting the LBP of NRs. Here, combining structural and energetic analyses with machine-learning (ML) algorithms, we constructed a series of structure-based ML models to determine the molecular category of the LBP-bound ligands. We show that the proposed models work robustly and with high accuracy (ACC > 0.9) for determining the category of molecules derived from docking-based and crystallized poses. Furthermore, the models are also capable of determining the molecular category of ligands with dual opposite functions on different NRs (i.e., working as an agonist in one NR target, whereas functioning as an antagonist in another) with reasonable accuracy. The proposed method is expected to facilitate the determination of the molecular properties of ligands targeting the LBP of NRs with structural interpretation.

Structural view on the role of the TRD loop in regulating DNMT3A activity: a molecular dynamics study

DNA methyltransferase 3A (DNMT3A) has been regarded as a potential epigenetic target for the development of cancer therapeutics. A number of DNMT3A inhibitors have been reported, but most of them do not have good potency, high selectivity and/or low cytotoxicity. It has been suggested that a non-conserved region around the target recognition domain (TRD) loop is implicated in the DNMT3A activity under the allosteric regulation of the ATRX-DNMT3-DNMT3L (ADD) domain, but the molecular mechanism of the regulation of the TRD loop on the DNMT3A activity needs to be elucidated. In this study, based on the reported crystal structures, the dynamics of the TRD loop in different multimerization with/without the bound guest molecule, namely the ADD domain or the DNA molecule, was investigated using conventional molecular dynamics (MD) and umbrella sampling simulations. The simulation results illustrate that the TRD loop exhibits relatively higher flexibility than the other components in the whole catalytic domain (CD), which could be well stabilized into different local minima through the binding with either the ADD domain or the DNA molecule by forming tight hydrogen-bond and salt-bridge networks involving distinct residues. Moreover, the movement of the TRD loop away from the catalytic loop upon activation could be triggered simply by the detachment of the ADD domain, but not necessarily induced by the ADD domain relocation on the CD. All these dynamic structural details could be a supplement to the previously reported crystal structure, which underlines the importance of the structural flexibility for the critical residues in the TRD loop, arousing more interest in the rational design of novel DNMT3A inhibitors targeting this region.

An insight about the mechanism of action (MoA) of R-bicalutamide on the androgen receptor homodimer using molecular dynamic

R-bicalutamide is a first-line therapy used to treat prostate cancer (PCa) inhibiting the androgen receptor (AR) which plays an important role in the development and the progression of PCa. However, after a protracted drug administration, many patients develop a form of androgen insensitivity since R-bicalutamide starts to exhibit some agonistic properties lead by the W741L AR mutation in the ligand-binding pocket even if the mechanism of the antagonist-agonist switch is still not clear. To study the drug-resistant mechanism, we explored the structural effects of the antagonist R-bicalutamide on the homodimer stability considering both the AR wild-type and W741L employing molecular dynamic (MD) simulations. The results obtained indicate that the binding of R-bicalutamide in the two AR monomers induces a great instability in the homodimer, which may determine the monomer's dissociation preventing AR migration into the nucleus and avoiding the transcriptional activity. If the W741L mutation occurs, the homodimer tends to have a behaviour close to the agonistic system where the two monomers are tightly bound, which may explain the effect of the W741L in drug insensitivity from a structural point of view.

Discovery of a Novel Androgen Receptor Antagonist Manifesting Evidence to Disrupt the Dimerization of the Ligand-Binding Domain via Attenuating the Hydrogen-Bonding Network Between the Two Monomers

Androgen receptor (AR) has proved to be a vital drug target for treating prostate cancer. Here, we reported the discovery of a novel AR antagonist 92 targeting the AR ligand-binding pocket, but distinct from the marketed drug enzalutamide (Enz), 92 demonstrated inhibition on the AR ligand-binding domain (LBD) dimerization, which is a novel mechanism reported for the first time. First, a novel hit (26, IC₅₀ = 5.57 μM) was identified through virtual screening based on a theoretical AR LBD dimer bound with the Enz model. Then, guided by molecular modeling, 92 was discovered with 32.7-fold improved AR antagonistic activity (IC₅₀ = 0.17 μM). Besides showing high bioactivity and safety, 92 can inhibit AR nuclear translocation. Furthermore, 92 inhibited the formation of the AR LBD dimer, possibly through attenuating the hydrogen-bonding network between the two monomers. This interesting finding would pave the way for the discovery of a new class of AR antagonists.

Molecular dynamics simulations reveal the plausible agonism/antagonism mechanism by steroids on androgen receptor mutations

Androgen receptors (AR) are the primary drug target in prostate cancer (PCa). There are several drugs developed against its activity for prostate cancer treatment, but cancer cells revive AR signaling against those drugs by using alternative steroids such as glucocorticoids. In addition, antagonists become agonists due to emergence of mutations in AR gene. The mechanism by which antagonists are converted into agonists and how AR signaling is recovered by other steroids has yet to be fully elucidated. In this study, we interrogated the role of bicalutamide conformation in its antagonist function and how glucocorticoids such as prednisolone and dexamethasone revive AR signaling at the molecular level by means of molecular dynamics. We found that the ''closed'' conformation of bicalutamide is essential for its antagonist function and W741 residue is forcing it into this conformation. Moreover, we show that prednisolone and dexamethasone behave like natural agonist DHT which confirm the experimental results that show their role in the reviving AR signaling in the case of AR^L701H mutation.

Probing Allosteric Regulation Mechanism of W7.35 on Agonist-Induced Activity for μOR by Mutation Simulation

The residue located at 15 positions before the most conserved residue in TM7 (7.35 of Ballesteros-Weinstein number) plays important roles in ligand binding and the receptor activity for class A GPCRs. Nevertheless, its regulation mechanism has not been clearly clarified in experiments, and some controversies also exist for its impact on μ-opioid receptors (μOR) bound by agonists. Thus, we chose the μ-opioid receptor (μOR) of class A GPCRs as a representative and utilized a microsecond accelerated molecular dynamics simulation (aMD) coupled with a protein structure network (PSN) to explore the effect of W318^7.35 on its functional activity induced by the agonist endomorphin2 mainly by a comparison of the wild system and its W7.35A mutant. When endomorphin2 binds to the wild-type μOR, TM6 in μOR moves outward to form an open intracellular conformation that is beneficial to accommodating the β-arrestin transducer, rather than the G-protein transducer due to the clash with the α5 helix of G-protein, thus acting as a β-arrestin biased agonist. However, the W318A mutation induces the intracellular part of μOR to form a closed state, which disfavors coupling with either G-protein or β-arrestin. The allosteric pathway analysis further reveals that the binding of endomorphin2 to the wild-type μOR transmits more activation signals to the β-arrestin binding site while the W318A mutation induces more structural signals to transmit to common binding residues of the G protein and β-arrestin. More interestingly, the residue at the 7.35 position regulates the shortest allosteric pathway in indirect ways by influencing the interactions between other ligand-binding residues and endomorphin2. W293^6.48 and F289^6.44 are important for regulating the different activities of μOR induced either by the agonist or by the mutation. Y336^7.53, F343^8.50, and D340^8.47 play crucial roles in activating the β-arrestin biased signal induced by the agonist endomorphin2, while L158^3.43 and V286^6.41 devote important contributions to the change in the activity of endomorphin2 from the β-arrestin biased agonist to the antagonist upon the W318A mutation.

Conformational dynamics of androgen receptors bound to agonists and antagonists

The androgen receptor (AR) is critical in the progression of prostate cancer (PCa). Small molecule antagonists that bind to the ligand binding domain (LBD) of the AR have been successful in treating PCa. However, the structural basis by which the AR antagonists manifest their therapeutic efficacy remains unclear, due to the lack of detailed structural information of the AR bound to the antagonists. We have performed accelerated molecular dynamics (aMD) simulations of LBDs bound to a set of ligands including a natural substrate (dihydrotestosterone), an agonist (RU59063) and three antagonists (bicalutamide, enzalutamide and apalutamide) as well as in the absence of ligand (apo). We show that the binding of AR antagonists at the substrate binding pocket alter the dynamic fluctuations of H12, thereby disrupting the structural integrity of the agonistic conformation of AR. Two antagonists, enzalutamide and apalutamide, induce considerable structural changes to the agonist conformation of LBD, when bound close to H12 of AR LBD. When the antagonists bind to the pocket with different orientations having close contact with H11, no significant conformational changes were observed, suggesting the AR remains in the functionally activated (agonistic) state. The simulations on a drug resistance mutant F876L bound to enzalutamide demonstrated that the mutation stabilizes the agonistic conformation of AR LBD, which compromises the efficacy of the antagonists. Principal component analysis (PCA) of the structural fluctuations shows that the binding of enzalutamide and apalutamide induce conformational fluctuations in the AR, which are markedly different from those caused by the agonist as well as another antagonist, bicalutamide. These fluctuations could only be observed with the use of aMD.

Effect of Water Molecules on the Activating S810L Mutation of the Mineralocorticoid Receptor

The mineralocorticoid receptor (MR) is a nuclear receptor whose endogenous ligands are mineralocorticoids, a type of steroid hormone. The activating S810L mutation is known to cause severe early-onset and pregnancy-related hypertension. Progesterone binds to the wild-type (WT) MR as a passive antagonist with fast dissociation; however, it binds to the S810L mutant as a full agonist with slow dissociation. The switch in the biological activity of progesterone is considered to be one of the causes of the disease. First, we used steered molecular dynamics simulations to analyze the dissociation process of progesterone for the WT and the S810L mutant. Progesterone in the WT dissociated from the ligand-binding pocket with a weak force in comparison with progesterone in the S810L mutant due to the large inflow of water molecules into the pocket. Therefore, we used conventional molecular dynamics simulations for the ligand-free structures of the WT and the S810L mutant to investigate the effect of the mutation on the inflow of water. In the WT, water molecules enter the ligand-binding pocket in two ways: in the vicinity of (i) Arg817 and (ii) Ser810. In contrast, few water molecules enter the pocket in the S810L mutant because of the large size and hydrophobic nature of the Leu810 side chain. Fast dissociation is a common feature among passive antagonists of MR; therefore, we inferred that the water inflow could be responsible for the dissociation kinetics of progesterone in the WT and the S810L mutant.

Mechanistic Insights into the Allosteric Inhibition of Androgen Receptors by Binding Function 3 Antagonists from an Integrated Molecular Modeling Study

An androgen receptor (AR) is an intensively studied treatment target for castration-resistant prostate cancer that is irresponsive to conventional antiandrogen therapeutics. Binding function 3 (BF3) inhibitors with alternative modes of action have emerged as a promising approach to overcoming antiandrogen resistance. However, how these BF3 inhibitors modulate AR function remains elusive, hindering the development of BF3-targeting agents. Here, we performed an integrated computational study to interrogate the binding mechanism of several known BF3 inhibitors with ARs. Our results show that the inhibitory effect of the BF3 antagonists arises from their allosteric modulation of the activation function (AF2) site, which alters the dynamic coupling between the BF3 and AF2 sites as well as the AF2-coactivator (SRC2-3) interaction. Moreover, the per-residue binding energy analyses reveal the "anchor" role of the linker connecting the phenyl ring and benzimidazole/indole in these BF3 inhibitors. Furthermore, the allosteric driver-interacting residues are found to include both "positive", e.g., Phe673 and Asn833, and "negative" ones, e.g., Phe826, and the differential interactions with these residues provide an explanation why stronger binding does not necessarily result in higher inhibitory activities. Finally, our allosteric communication pathway analyses delineate how the allosteric signals triggered by BF3 binding are propagated to the AF2 pocket through multiple short- and/or long-ranged transmission pathways. Collectively, our combined computational study provides a comprehensive structural mechanism underlying how the selected set of BF3 inhibitors modulate AR function, which will help guide future development of BF3 antagonists.

Unraveling the Allosteric Cross-Talk between the Coactivator Peptide and the Ligand-Binding Site in the Glucocorticoid Receptor

The glucocorticoid receptor (GR) is a nuclear receptor that controls critical biological processes by regulating the transcription of specific genes. There is a known allosteric cross-talk between the ligand and coregulator binding sites within the GR ligand-binding domain that is crucial for the control of the functional response. However, the molecular mechanisms underlying such an allosteric control remain elusive. Here, molecular dynamics (MD) simulations, bioinformatic analysis, and biophysical measurements are integrated to capture the structural and dynamic features of the allosteric cross-talk within the GR. We identified a network of evolutionarily conserved residues that enables the allosteric signal transduction, in agreement with experimental data. MD simulations clarify how such a network is dynamically interconnected and offer a mechanistic explanation of how different peptides affect the intensity of the allosteric signal. This study provides useful insights to elucidate the GR allosteric regulation, ultimately providing a foundation for designing novel drugs.

In silico and in vitro assessment of androgen receptor antagonists

There is a growing concern for male reproductive health as studies suggest that there is a sharp increase in prostate cancer and other fertility related problems. Apart from lifestyle, pollutants are also known to negatively affect the reproductive system. In addition to many other compounds that have been shown to alter androgen signaling, several environmental pollutants are known to disrupt androgen signaling via binding to androgen receptor (AR) or indirectly affecting the androgen synthesis. We analyzed here the molecular mechanism of the interaction between the human AR Ligand Binding Domain (hAR-LBD) and two environmental pollutants, linuron (a herbicide) and procymidone (a pesticide), and compared with the steroid agonist dihydrotestosterone (DHT) and well-known hAR antagonists bicalutamide and enzalutamide. Using molecular docking and dynamics simulations, we showed that the co-activator interaction site of the hAR-LBD is disrupted in different ways by different ligands. Binding free energies of the ligands were also ordered in increasing order as follows: linuron, procymidone, DHT, bicalutamide, and enzalutamide. These data were confirmed by in vitro assays. Reporter assay with MDA-kb2 cells showed that linuron, procymidone, bicalutamide and enzalutamide can inhibit androgen mediated activation of luciferase activity. Gene expression analysis further showed that these compounds can inhibit the expression of prostate specific antigen (PSA) and microseminoprotein beta (MSMB) in prostate cell line LNCaP. Comparative analysis showed that procymidone is more potent than linuron in inhibiting AR activity. Furthermore, procymidone at 10 μM dose showed equivalent and higher activity to AR inhibitor enzalutamide and bicalutamide respectively.

Computational Assessment of Combination Therapy of Androgen Receptor-Targeting Compounds

The ligand-binding domain of the androgen receptor (AR) is a target for drugs against prostate cancer and offers three distinct binding sites for small molecules. Drugs acting on the orthosteric hormone binding site suffer from resistance mechanisms that can, in the worst case, reverse their therapeutic effect. While many allosteric ligands targeting either the activation function-2 (AF-2) or the binding function-3 (BF-3) have been reported, their potential for simultaneous administration with currently prescribed antiandrogens was disregarded. Here, we report results of 60 μs molecular dynamics simulations to investigate combinations of orthosteric and allosteric AR antagonists. Our results suggest BF-3 inhibitors to be more suitable in combination with classical antiandrogens as opposed to AF-2 inhibitors based on binding free energies and binding modes. As a mechanistic explanation for these observations, we deduced a structural adaptation of helix-12 involved in the formation of the AF-2 site by classical AR antagonists. Additionally, the changes were accompanied by an expansion of the orthosteric binding site. Considering our predictions, the selective combination of AR-targeting compounds may improve the treatment of prostate cancer.

Disruption of androgen receptor signaling by chlorpyrifos (CPF) and its environmental degradation products: a structural insight

Androgen-disruptors are chemicals that interfere with the biosynthesis, metabolism or function of endogenous androgens affecting normal male reproductive development and health. Several epidemiological studies have indicated a link between exposure to androgen disrupting chemicals with reduced sperm counts and increased infertility. The actions of androgens within target cells are transduced by the androgen receptors (ARs). Chlorpyrifos (CPF), a chlorinated organophosphorus pesticide, is known to cause impairment in both male and female reproductive systems. Recent publications have shown molecular interactions of CPF and its environmental degradation products with human progesterone receptor and human estrogen receptor. Exposure to CPF causes a marked reduction in sperm counts with lowering in serum testosterone level, which suggests possible molecular interaction of CPF with AR. The investigation to reveal the possibility and the extent of binding of CPF and some of its degradation products (chlorpyrifos-oxon [CPYO], desethyl chlorpyrifos [DEC], trichloromethoxypyridine [TMP] and trichloropyridinol [TCP]) with AR using molecular docking simulation are reported. The findings of the present docking, binding energy and molecular dynamics studies reveal that CPF and its degradation products may bind to ARs and act as a potent androgen disruptor.Communicated by Ramaswamy H. Sarma.

Conformational Changes of Thyroid Receptors in Response to Antagonists

Thyroid hormone receptors (TRs) play a critical role in human development, growth, and metabolism. Antagonists of TRs offer an attractive strategy to treat hyperthyroidism without the disadvantage of a delayed onset of drug action. While it is challenging to examine the atomistic behavior of TRs in a laboratory setting, computational methods such as molecular dynamics (MD) simulations have proven their value to elucidate ligand-induced conformational changes in nuclear receptors. Here, we performed MD simulations of TRα and TRβ complexed to their native ligand triiodothyronine (T3) as well as several antagonists. Based on the examination of 27 μs MD trajectories, we showed how binding of these compounds influences various structural features of the receptors including the helicity of helices 3 and 10 as well as the location of helix-12. Helices 3 and 12 are known to mediate coactivator association required for downstream signaling, suggesting these changes to be the molecular basis for TR antagonism. A mechanistic analysis of the trajectories revealed an allosteric pathway between H3 and H12 to be responsible for the conformational adaptations. Even though a mechanistic understanding of conformational adaptations triggered by TR antagonists is important for the development of novel therapeutics, they have not been previously examined in detail as it was done here.

In silico approach of naringin as potent phosphatase and tensin homolog (PTEN) protein agonist against prostate cancer

Prostate cancer (PC) is one of the major impediments affecting men, which leads approximately 31,620 deaths in both developing and developed countries. Although some chemotherapy drugs have been reported for prostate cancer, they are not effective due to the lack of safety, efficacy and low selectivity. Hence, the novel alternative anticancer agents with remarkable effect are highly appreciable. Natural plants contain several bio-active compounds which have been traditionally used for the various medical treatments. Particularly, naringin is a natural bio-active compound commonly found in the citrus fruits, which have shown numerous biological activities. Phosphatase and tensin homolog (PTEN) is a tumor suppressor gene, which activates both lipid phosphates and protein phosphates. The PTEN gene is negative regulator of PI3K/AKT/mTOR pathways, since, this signaling pathway play an essential role in the cell survival, proliferation and migration. In the present in silico investigation, structure based virtual screening, molecular docking, molecular dynamics simulation and Adsorption, Distribution, Metabolism, Excretion (ADME) prediction were employed to determine the binding affinity, stability and drug likeness properties of top ranked screened compounds and naringin, respectively. The results revealed that the complex has good molecular interactions, binding stability (peak between 0.3 and 0.4 nm) and no violations in the Lipinski Rule of 5 in naringin, but the screened compounds violated the drug likeness properties. From the in silico analyses, it is identified that naringin compound might assist in the development of novel therapeutic candidate against prostate cancer.Communicated by Ramaswamy H. Sarma.

Mechanistic in silico modeling of bisphenols to predict estrogen and glucocorticoid disrupting potentials

Endocrine disrupting chemicals (EDCs) can act as agonists, antagonists or mixed agonists/antagonists toward estrogen receptor α (ERα) and glucocorticoid receptor (GR) in a tissue- and cell-specific manner. However, the activation/inhibition mechanism by which structurally different chemicals induce various types of disruption remain ambiguous. This unrevealed theory limited the in silico modeling of EDCs and the prioritization of potential EDCs for experimental testing. As a kind of chemical widely used in manufacture, bisphenols (BPs) have attracted great attentions on their potential endocrine disrupting effects. BPs used in this study exhibited pure agonistic, pure antagonistic or mixed agonistic/antagonistic activities toward ERα and/or GR. According to the mechanistic modeling, the pure agonistic and pure antagonistic activities were attributed to a single type of protein conformation induced by BPs-ERα and/or BPs-GR interactions, whereas the mixed agonistic/antagonistic activities were attributed to multiple conformations that concomitantly exist. After interacting with BPs, the active conformation recruits coactivator to induce agonistic activity and the blocked conformation inhibits coactivator to induce antagonistic activity, whereas the concomitantly-existing multiple conformations (active, blocked and competing conformations) recruit coactivator, recruit corepressor and/or inhibit coactivator to dually induce the agonistic and antagonistic activities. Therefore, the in silico modeling in this study can not only predict ERα and GR disrupting activities but also, especially, identify the potential mechanisms. This mechanistic study breaks the current bottleneck of computational toxicology and can be widely used to prioritize potential estrogen/glucocorticoid disruptor for experimental testing in both pre-clinic and clinic studies.

Insights into the interaction mechanisms of estrogen-related receptor alpha (ERRα) with ligands via molecular dynamics simulations

Estrogen-related receptor alpha (ERRα), a member of nuclear receptors (NRs), participates in energy metabolism. Recent experiments identified that several agonists to increase the activity of ERRα, which have a therapeutic effect in improving insulin sensitivity and lowering blood glucose levels. However, the detailed molecular mechanism about how the ligands affect the structure of ERRα remains elusive. To better understand the conformational change of ERRα complexed with agonists and inverse agonists, unbiased molecular dynamics (MD) simulations were performed on the ligand binding domain of ERRα (ERRα-LBD) bound with different ligands. According to the results, the ERRα-agonist interactions were more stable in the presence of the peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α). More importantly, we observed that the binding of inverse agonists would decrease the stability of helix 12 (H12) of ERRα. Moreover, we suggested that Phe232 and Phe414 should be key residues in the interaction pathway from ligands to H12, which provided a possible explanation about how ligands impact the structure of ERRα. These results would provide insights into the design of novel and efficient agonists of ERRα to treat metabolic diabetes.Communicated by Ramaswamy H. Sarma.

Advances in the computational development of androgen receptor antagonists

The androgen receptor is a ligand-dependent transcriptional factor and an essential therapeutic target for prostate cancer. Competitive binding of antagonists to the androgen receptor can alleviate aberrant activation of the androgen receptor in prostate cancer. In recent years, computer-aided drug design has played an essential part in the discovery of novel androgen receptor antagonists. This review summarizes the recent advances in the discovery of novel androgen receptor antagonists through computer-aided drug design approaches; and discusses the applications of molecular modeling techniques to understand the resistance mechanisms of androgen receptor antagonists at the molecular level.

PCAViz: An Open-Source Python/JavaScript Toolkit for Visualizing Molecular Dynamics Simulations in the Web Browser

Molecular dynamics (MD) simulations reveal molecular motions at atomic resolution. Recent advances in high-performance computing now enable microsecond-long simulations capable of sampling a wide range of biologically relevant events. But the disk space required to store an MD trajectory increases with simulation length and system size, complicating collaborative sharing and visualization. To overcome these limitations, we created PCAViz, an open-source toolkit for sharing and visualizing MD trajectories via the web browser. PCAViz includes two components: the PCAViz Compressor, which compresses and saves simulation data; and the PCAViz Interpreter, which decompresses the data in users’ browsers and feeds it to any of several browser-based molecular-visualization libraries (e.g., 3Dmol.js, NGL Viewer, etc.). An easy-to-install WordPress plugin enables “plug-and-play” trajectory visualization. PCAViz will appeal to a broad audience of researchers and educators. The source code is available at http://durrantlab.com/pcaviz/, and the WordPress plugin is available via the official WordPress Plugin Directory.

How Effectively Can Adaptive Sampling Methods Capture Spontaneous Ligand Binding?

Molecular dynamics (MD) simulations that capture the spontaneous binding of drugs and other ligands to their target proteins can reveal a great deal of useful information, but most drug-like ligands bind on time scales longer than those accessible to individual MD simulations. Adaptive sampling methods―in which one performs multiple rounds of simulation, with the initial conditions of each round based on the results of previous rounds―offer a promising potential solution to this problem. No comprehensive analysis of the performance gains from adaptive sampling is available for ligand binding, however, particularly for protein–ligand systems typical of those encountered in drug discovery. Moreover, most previous work presupposes knowledge of the ligand’s bound pose. Here we outline existing methods for adaptive sampling of the ligand-binding process and introduce several improvements, with a focus on methods that do not require prior knowledge of the binding site or bound pose. We then evaluate these methods by comparing them to traditional, long MD simulations for realistic protein–ligand systems. We find that adaptive sampling simulations typically fail to reach the bound pose more efficiently than traditional MD. However, adaptive sampling identifies multiple potential binding sites more efficiently than traditional MD and also provides better characterization of binding pathways. We explain these results by showing that protein–ligand binding is an example of an exploration–exploitation dilemma. Existing adaptive sampling methods for ligand binding in the absence of a known bound pose vastly favor the broad exploration of protein–ligand space, sometimes failing to sufficiently exploit intermediate states as they are discovered. We suggest potential avenues for future research to address this shortcoming.

Discovery of Novel Androgen Receptor Ligands by Structure-based Virtual Screening and Bioassays

Androgen receptor (AR) is a ligand-activated transcription factor that plays a pivotal role in the development and progression of many severe diseases such as prostate cancer, muscle atrophy, and osteoporosis. Binding of ligands to AR triggers the conformational changes in AR that may affect the recruitment of coactivators and downstream response of AR signaling pathway. Therefore, AR ligands have great potential to treat these diseases. In this study, we searched for novel AR ligands by performing a docking-based virtual screening (VS) on the basis of the crystal structure of the AR ligand binding domain (LBD) in complex with its agonist. A total of 58 structurally diverse compounds were selected and subjected to LBD affinity assay, with five of them (HBP1-3, HBP1-17, HBP1-38, HBP1-51, and HBP1-58) exhibiting strong binding to AR-LBD. The IC₅₀ values of HBP1-51 and HBP1-58 are 3.96 µM and 4.92 µM, respectively, which are even lower than that of enzalutamide (Enz, IC₅₀ = 13.87 µM), a marketed second-generation AR antagonist. Further bioactivity assays suggest that HBP1-51 is an AR agonist, whereas HBP1-58 is an AR antagonist. In addition, molecular dynamics (MD) simulations and principal components analysis (PCA) were carried out to reveal the binding principle of the newly-identified AR ligands toward AR. Our modeling results indicate that the conformational changes of helix 12 induced by the bindings of antagonist and agonist are visibly different. In summary, the current study provides a highly efficient way to discover novel AR ligands, which could serve as the starting point for development of new therapeutics for AR-related diseases.

A magic drug target: Androgen receptor

Androgen receptor (AR) is closely associated with a group of hormone-related diseases including the cancers of prostate, breast, ovary, pancreas, etc and anabolic deficiencies such as muscle atrophy and osteoporosis. Depending on the specific type and stage of the diseases, AR ligands including not only antagonists but also agonists and modulators are considered as potential therapeutics, which makes AR an extremely interesting drug target. Here, we at first review the current understandings on the structural characteristics of AR, and then address why and how AR is investigated as a drug target for the relevant diseases and summarize the representative antagonists and agonists targeting five prospective small molecule binding sites at AR, including ligand-binding pocket, activation function-2 site, binding function-3 site, DNA-binding domain, and N-terminal domain, providing recent insights from a target and drug development view. Further comprehensive studies on AR and AR ligands would bring fruitful information and push the therapy of AR relevant diseases forward.

Molecular Dynamics Simulations Revealed the Regulation of Ligands to the Interactions between Androgen Receptor and Its Coactivator

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.

Endocrine Disruption at the Androgen Receptor: Employing Molecular Dynamics and Docking for Improved Virtual Screening and Toxicity Prediction

The androgen receptor (AR) is a key target for the development of drugs targeting hormone-dependent prostate cancer, but has also an important role in endocrine disruption. Reliable prediction of the binding of ligands towards the AR is therefore of great relevance. Molecular docking is a powerful computational method for exploring small-ligand binding to proteins. It can be applied for virtual screening experiments but also for predicting molecular initiating events in toxicology. However, in case of AR, there is no antagonist-bound crystal structure yet available. Our study demonstrates that molecular docking approaches are not able to satisfactorily screen for AR antagonists because of this reason. Therefore, we applied Molecular Dynamics simulations to generate antagonist AR structures and showed that this leads to a vast improvement for the docking of AR antagonists. We benchmarked the ability of these antagonist AR structures discriminate between AR antagonists and decoys using an ensemble docking approach and obtained promising results with good enrichment. However, distinguishing AR antagonists from agonists with high confidence is not possible with the current approach alone.

Structural Changes Due to Antagonist Binding in Ligand Binding Pocket of Androgen Receptor Elucidated Through Molecular Dynamics Simulations

When a small molecule binds to the androgen receptor (AR), a conformational change can occur which impacts subsequent binding of co-regulator proteins and DNA. In order to accurately study this mechanism, the scientific community needs a crystal structure of the Wild type AR (WT-AR) ligand binding domain, bound with antagonist. To address this open need, we leveraged molecular docking and molecular dynamics (MD) simulations to construct a structure of the WT-AR ligand binding domain bound with antagonist bicalutamide. The structure of mutant AR (Mut-AR) bound with this same antagonist informed this study. After molecular docking analysis pinpointed the suitable binding orientation of a ligand in AR, the model was further optimized through 1 μs of MD simulations. Using this approach, three molecular systems were studied: (1) WT-AR bound with agonist R1881, (2) WT-AR bound with antagonist bicalutamide, and (3) Mut-AR bound with bicalutamide. Our structures were very similar to the experimentally determined structures of both WT-AR with R1881 and Mut-AR with bicalutamide, demonstrating the trustworthiness of this approach. In our model, when WT-AR is bound with bicalutamide, Val716/Lys720/Gln733, or Met734/Gln738/Glu897 move and thus disturb the positive and negative charge clumps of the AF2 site. This disruption of the AF2 site is key for understanding the impact of antagonist binding on subsequent co-regulator binding. In conclusion, the antagonist induced structural changes in WT-AR detailed in this study will enable further AR research and will facilitate AR targeting drug discovery.

Selective inhibition mechanism of RVX-208 to the second bromodomain of bromo and extraterminal proteins: insight from microsecond molecular dynamics simulations

RVX-208 is a recently reported inhibitor of bromo and extraterminal (BET) family proteins (including BRD2-4 and BRDT) with selectivity for the second bromodomain (BD2), currently in phase III clinical trials. Despite of its promising antitumor activity, due to the conserved folds of the first and second bromodomains (BD1 and BD2), the detailed selectivity mechanism of RVX-208 towards BD2 over BD1 is still unknown. To elucidate selective inhibition mechanism of RVX-208 to BD2, microsecond molecular dynamics simulations were performed in this study for BRD2-BD1, BRD2-BD2 and BRD4-BD1 with and without RVX-208, respectively. Binding free energy calculations show that there exists strongest interaction between RVX-208 and BRD2-BD2. Leu383 and Asn429 are two most important residues of BRD2-BD2 for binding to RVX-208. Structural network analysis reveals that RVX-208 can shorten the communication path of ZA and BC loops in BRD2-BD2 pocket, making pocket more suitable to accommodate RVX-208. Additionally, different behaviors of His433 (Asp160 in BRD2-BD1) and Val435 (Ile162 in BRD2-BD1) in BRD2-BD2 are key factors responsible for selective binding of RVX-208 to BRD2-BD2. The proposed selective inhibition mechanism of RVX-208 to BRD2-BD2 can be helpful for rational design of novel selective inhibitors of the second bromodomain of BET family proteins.

Structural Properties of Human IAPP Dimer in Membrane Environment Studied by All-Atom Molecular Dynamics Simulations

The aggregation of human islet amyloid polypeptide (hIAPP) can damage the membrane of the β-cells in the pancreatic islets and induce type 2 diabetes (T2D). Growing evidences indicated that the major toxic species are small oligomers of IAPP. Due to the fast aggregation nature, it is hard to characterize the structures of IAPP oligomers by experiments, especially in the complex membrane environment. On the other side, molecular dynamics simulation can provide atomic details of the structure and dynamics of the aggregation of IAPP. In this study, all-atom bias-exchange metadynamics (BE-Meta) and unbiased molecular dynamics simulations were employed to study the structural properties of IAPP dimer in the membranes environments. A number of intermediates, including α-helical states, β-sheet states, and fully disordered states, are identified. The formation of N-terminal β-sheet structure is prior to the C-terminal β-sheet structure towards the final fibril-like structures. The α-helical intermediates have lower propensity in the dimeric hIAPP and are off-pathway intermediates. The simulations also demonstrate that the β-sheet intermediates induce more perturbation on the membrane than the α-helical and disordered states and thus pose higher disruption ability.

Molecular mechanism of R-bicalutamide switching from androgen receptor antagonist to agonist induced by amino acid mutations using molecular dynamics simulations and free energy calculation

R-bicalutamide, a first generation antiandrogen, was used to treat prostate cancer for decades. Although it is very effective at the beginning, resistance appears after 2-3 years of treatment. Mutation of androgen receptor (AR) is considered a main reason for drug resistance. It is reported that AR W741C, W741L, W741C_T877A, T877A, F876L, F876L_T877A and L701H mutations can convert R-bicalutamide from AR antagonist to agonist, but the switching mechanisms are not clear. In this study, molecular dynamics simulations and molecular mechanics generalized Born surface area (MM-GBSA) calculations were performed to analyze the interaction mechanisms between R-bicalutamide and wild type/mutant ARs. The results indicate that helix H12, which lies on the top of AR LBD like a cover, plays a vital role in R-bicalutamide binding. When interacting with AR, the B-ring of R-bicalutamide pushes H12 aside, distorting the coactivator binding site (AF2) resulting in the inactivation of transcription. Several residue mutations appear to enlarge the distance between the B-ring of R-bicalutamide and H12, reducing steric clash, which is conducive to a closed H12 conformation, leading to the formation of the coactivator binding site AF2 and increased transcription. Hydrogen bond and per-residue free energy decomposition analyses are also investigated to explore the interacting mechanisms, and M895 is found to be a key residue in the antagonist mechanism. The obtained molecular mechanisms will aid rational screening and design of novel AR antagonists, even to mutant AR.