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

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.

Computationally guided discovery of novel non-steroidal AR-GR dual antagonists demonstrating potency against antiandrogen resistance

As a major class of medicine for treating the lethal type of castration-resistant prostate cancer (PCa), long-term use of androgen receptor (AR) antagonists commonly leads to antiandrogen resistance. When AR signaling pathway is blocked by AR-targeted therapy, glucocorticoid receptor (GR) could compensate for AR function especially at the late stage of PCa. AR-GR dual antagonist is expected to be a good solution for this situation. Nevertheless, no effective non-steroidal AR-GR dual antagonist has been reported so far. In this study, an AR-GR dual binder H18 was first discovered by combining structure-based virtual screening and biological evaluation. Then with the aid of computationally guided design, the AR-GR dual antagonist HD57 was finally identified with antagonistic activity towards both AR (IC50 = 0.394 μM) and GR (IC50 = 17.81 μM). Moreover, HD57 could effectively antagonize various clinically relevant AR mutants. Further molecular dynamics simulation provided more atomic insights into the mode of action of HD57. Our research presents an efficient and rational strategy for discovering novel AR-GR dual antagonists, and the new scaffold provides important clues for the development of novel therapeutics for castration-resistant PCa.

Discovery and Optimization of N-Acyl-6-sulfonamide-tetrahydroquinoline Derivatives as Novel Non-Steroidal Selective Glucocorticoid Receptor Modulators

Selective glucocorticoid receptor modulators (SGRMs), which can dissociate the transactivation from the transrepression of the glucocorticoid receptor (GR), are regarded as very promising therapeutics for inflammatory and autoimmune diseases. We previously discovered a SGRM HP-19 based on the passive antagonistic conformation of GR and bioassays. In this study, we further analyzed the dynamic changes of the passive antagonistic state upon the binding of HP-19 and designed and synthesized 62 N-acyl-6-sulfonamide-tetrahydroquinoline derivatives by structural optimization of HP-19. Therein, compound B53 exhibits the best transrepression activity (IC_{50 NF-κB} = 0.009 ± 0.001 μM) comparable with dexamethasone (IC_{50 NF-κB} = 0.005 ± 0.001 μM) and no transactivation activity. B53 can efficiently reduce the expression of inflammatory factors IL-6, IL-1β, TNF-α, and so on and makes a milder adverse effect and is highly specific to GR. Furthermore, B53 is able to significantly relieve dermatitis on a mouse model via oral drug intervention.

Quick and efficient quantitative predictions of androgen receptor binding affinity for screening Endocrine Disruptor Chemicals using 2D-QSAR and Chemical Read-Across

Endocrine Disruptor Chemicals are synthetic or natural molecules in the environment that promote adverse modifications of endogenous hormone regulation in humans and/or in animals. In the present research, we have applied two-dimensional quantitative structure-activity relationship (2D-QSAR) modeling to analyze the structural features of these chemicals responsible for binding to the androgen receptors (logRBA) in rats. We have collected the receptor binding data from the EDKB database (https://www.fda.gov/science-research/endocrine-disruptor-knowledge-base/accessing-edkb-database) and then employed the DTC-QSAR tool, available from https://dtclab.webs.com/software-tools, for dataset division, feature selection, and model development. The final partial least squares model was evaluated using various stringent validation criteria. From the model, we interpreted that hydrophobicity, steroidal nucleus, bulkiness and a hydrogen bond donor at an appropriate position contribute to the receptor binding affinity, while presence of electron rich features like aromaticity and polar groups decrease the receptor binding affinity. Additionally we have also performed chemical Read-Across predictions using Read-Across-v3.1 available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home, and the results for the external validation metrics were found to be better than the QSAR-derived predictions. The best quality of external predictions emerged from the q-RASAR approach which combines both read-across and QSAR. To explore the essential features responsible for the receptor binding, pharmacophore mapping, molecular docking along with molecular dynamics simulation were also performed, and the results are in accordance with the QSAR/q-RASAR findings.

Discovery of 2-(1-(3-Chloro-4-cyanophenyl)-1H-pyrazol-3-yl)acetamides as Potent, Selective, and Orally Available Antagonists Targeting the Androgen Receptor

The androgen receptor (AR) antagonists are efficient therapeutics for the treatment of prostate cancer (PCa). All the approved AR antagonists to date are targeted to the ligand-binding pocket (LBP) of AR and have suffered from various drug resistances, whereas AR antagonist targeting non-LBP site of AR is conceived as a promising strategy. Through the scaffold hopping of AR LBP antagonists, the 2-chloro-4-(1H-pyrazol-1-yl)benzonitrile was designed as a new core structure for AR antagonists. A total of 46 compounds were synthesized and biologically evaluated to disclose compounds 2f, 2k, and 4c, exhibiting potent AR antagonistic activities (IC₅₀ up to 69 nM), force against antiandrogen resistance, and untraditional targeting site of probably AR binding function 3. Therein, 4c exhibited effective tumor growth inhibition in LNCaP xenograft study upon oral administration. This work provides a novel chemical scaffold for AR antagonists and offers new perspective for the development of PCa therapy.

Al-tameemi Z, AL-Zobaidy MJ. In silico comparison between the mutated and wild-type androgen receptors and their influence on the selection of optimum androgenic receptor blockers for the treatment of prostate cancer

Background: Prostate cancer is a disease that occurs in men aged more than 50 years. In Iraq, 8.89 men per 100,000 population suffer from prostate cancer, with the incidence being 14,016 cases and mortality being 6,367 cases. Despite advances in treatment against prostate cancer, it can become resistant to drugs. Therefore, the aim of current study was to search and identify binding sites for the repositioning of drugs by computational methods (docking).  Methods: Based on the protein structure of the wild androgen receptor, the analysis parameters (22x22x22 on the X, Y, and Z axes) were established. Results: The interactions of the natural ligands with androgen receptor were 10.0 (testosterone) and 10.8 (dihydrotestosterone) while mutated androgen receptor (T877A) had a low affinity with testosterone and dihydrotestosterone (-5.3 and -6.7, respectively). In the interactions of both receptors with the reported inhibitors (antagonists), a decrease with Bicalutamide (-8.3 and -4.3, respectively) and an increase in affinity with Flutamide and Nilutamide (-7.7 and 8.6, wild AR; -8.7 and -9.3 AR T877A) were observed. As for Enzalutamide and Apalutamide (second-generation antagonists), the change was minimal between wild androgen receptor and T877A (-7.6 and -7.7; -7.3 and -7.3, respectively). The change in the affinity of the ligands with androgen receptor and androgen receptor T877A shows how a mutation alters the bonds between these molecules. Conclusion: The identification of key sites and potent inhibitors against abnormal androgen receptor functions will enrich prostate cancer treatments.

Discovery of novel MIF inhibitors that attenuate microglial inflammatory activation by structures-based virtual screening and in vitro bioassays

Macrophage migration inhibitory factor (MIF) is a pluripotent pro-inflammatory cytokine and is related to acute and chronic inflammatory responses, immune disorders, tumors, and other diseases. In this study, an integrated virtual screening strategy and bioassays were used to search for potent MIF inhibitors. Twelve compounds with better bioactivity than the prototypical MIF-inhibitor ISO-1 (IC₅₀ = 14.41 μM) were identified by an in vitro enzymatic activity assay. Structural analysis revealed that these inhibitors have novel structural scaffolds. Compound 11 was then chosen for further characterization in vitro, and it exhibited marked anti-inflammatory efficacy in LPS-activated BV-2 microglial cells by suppressing the activation of nuclear factor kappa B (NF-κB) and mitogen-activated protein kinases (MAPKs). Our findings suggest that MIF may be involved in the regulation of microglial inflammatory activation and that small-molecule MIF inhibitors may serve as promising therapeutic agents for neuroinflammatory diseases.

Discovery of N-(4-(Benzyloxy)-phenyl)-sulfonamide Derivatives as Novel Antagonists of the Human Androgen Receptor Targeting the Activation Function 2

Androgen receptor (AR) antagonists have been widely used for the treatment of prostate cancer (PCa). As a link between the AR and its transcriptional function, the activation function 2 (AF2) region has recently been revealed as a novel targeting site for developing AR antagonists. Here, we reported a series of N-(4-(benzyloxy)-phenyl)-sulfonamide derivatives as new-scaffold AR antagonists targeting the AR AF2. Therein, compound T1-12 showed excellent AR antagonistic activity (IC50 = 0.47 μM) and peptide displacement activity (IC50 = 18.05 μM). Furthermore, the in vivo LNCaP xenograft study confirmed that T1-12 offered effective inhibition on tumor growth when administered intratumorally. The study represents the first successful attempt to identify a small molecule targeting the AR AF2 with submicromolar AR antagonistic activity by structure-based virtual screening and provides important clues for the development of novel therapeutics for PCa treatment.

Discovery of a novel nonsteroidal selective glucocorticoid receptor modulator by virtual screening and bioassays

Synthetic glucocorticoids (GCs) have been widely used in the treatment of a broad range of inflammatory diseases, but their clinic use is limited by undesired side effects such as metabolic disorders, osteoporosis, skin and muscle atrophies, mood disorders and hypothalamic-pituitary-adrenal (HPA) axis suppression. Selective glucocorticoid receptor modulators (SGRMs) are expected to have promising anti-inflammatory efficacy but with fewer side effects caused by GCs. Here, we reported HT-15, a prospective SGRM discovered by structure-based virtual screening (VS) and bioassays. HT-15 can selectively act on the NF-κB/AP1-mediated transrepression function of glucocorticoid receptor (GR) and repress the expression of pro-inflammation cytokines (i.e., IL-1β, IL-6, COX-2, and CCL-2) as effectively as dexamethasone (Dex). Compared with Dex, HT-15 shows less transactivation potency that is associated with the main adverse effects of synthetic GCs, and no cross activities with other nuclear receptors. Furthermore, HT-15 exhibits very weak inhibition on the ratio of OPG/RANKL. Therefore, it may reduce the side effects induced by normal GCs. The bioactive compound HT-15 can serve as a starting point for the development of novel therapeutics for high dose or long-term anti-inflammatory treatment.

Discovery of novel antagonists targeting the DNA binding domain of androgen receptor by integrated docking-based virtual screening and bioassays

Androgen receptor (AR), a ligand-activated transcription factor, is a master regulator in the development and progress of prostate cancer (PCa). A major challenge for the clinically used AR antagonists is the rapid emergence of resistance induced by the mutations at AR ligand binding domain (LBD), and therefore the discovery of novel anti-AR therapeutics that can combat mutation-induced resistance is quite demanding. Therein, blocking the interaction between AR and DNA represents an innovative strategy. However, the hits confirmed targeting on it so far are all structurally based on a sole chemical scaffold. In this study, an integrated docking-based virtual screening (VS) strategy based on the crystal structure of the DNA binding domain (DBD) of AR was conducted to search for novel AR antagonists with new scaffolds and 2-(2-butyl-1,3-dioxoisoindoline-5-carboxamido)-4,5-dimethoxybenzoicacid (Cpd39) was identified as a potential hit, which was competent to block the binding of AR DBD to DNA and showed decent potency against AR transcriptional activity. Furthermore, Cpd39 was safe and capable of effectively inhibiting the proliferation of PCa cell lines (i.e., LNCaP, PC3, DU145, and 22RV1) and reducing the expression of the genes regulated by not only the full-length AR but also the splice variant AR-V7. The novel AR DBD-ARE blocker Cpd39 could serve as a starting point for the development of new therapeutics for castration-resistant PCa.

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.

Preliminary modelling as the first stage of targeted organic synthesis

The review aims to present a classification and applicability analysis of methods for preliminary molecular modelling for targeted organic, catalytic and biocatalytic synthesis. The following three main approaches are considered as a primary classification of the methods: modelling of the target – ligand coordination without structural information on both the target and the resulting complex; calculations based on experimentally obtained structural information about the target; and dynamic simulation of the target – ligand complex and the reaction mechanism with calculation of the free energy of the reaction. The review is meant for synthetic chemists to be used as a guide for building an algorithm for preliminary modelling and synthesis of structures with specified properties.

The bibliography includes 353 references.

Analysis of the binding modes of the first- and second-generation antiandrogens with respect to F876L mutation

Androgen receptor (AR) is an important target for the treatment of prostate cancer, and mutations in the AR have an important impact on the resistance of existing drugs. In this work, we performed molecular dynamics simulations of the existing marketed antiandrogens flutamide, nilutamide, bicalutamide, enzalutamide, apalutamide, darolutamide, and its main metabolite ORM15341 in complex with the wild-type and F876L mutant AR. We calculated the residue-specific binding free energy contribution of the wild-type and mutant ARs with the AS-IE method and analyzed the hotspot residues and the binding free energy contributions of specific residues before and after the mutation. In addition, we analyzed the total binding obtained by adding residue binding energy contributions and compared the results with experimental values. The obtained residue-specific binding information should be very helpful in understanding the mechanism of drug resistance with respect to specific mutations and in the design of new generation drugs against possible new mutations.

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.

Paradoxical androgen receptor regulation by small molecule enantiomers

Small molecules that target the androgen receptor (AR) are the mainstay of therapy for lethal castration-resistant prostate cancer (CRPC), yet existing drugs lose their efficacy during continued treatment. This evolution of resistance is due to heterogenous mechanisms which include AR mutations causing the identical drug to activate instead of inhibit the receptor. Understanding in molecular detail the paradoxical phenomenon wherein an AR antagonist is transformed into an agonist by structural mutations in the target receptor is thus of paramount importance. Herein, we describe a reciprocal paradox: opposing antagonist and agonist AR regulation determined uniquely by enantiomeric forms of the same drug structure. The antiandrogen BMS-641988, which has (R)-chirality at C-5 encompasses a previously uncharacterized (S)-stereoisomer that is, surprisingly, a potent agonist of AR, as demonstrated by transcriptional assays supported by cell imaging studies. This duality was reproduced in a series of novel compounds derived from the BMS-641988 scaffold. Coupled with in silico modeling studies, the results inform an AR model that explains the switch from potent antagonist to high-affinity agonist in terms of C-5 substituent steric interactions with helix 12 of the ligand binding site. They imply strategies to overcome AR drug resistance and demonstrate that insufficient enantiopurity in this class of AR antagonist can confound efforts to correlate structure with function.

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.

Integrating Machine Learning-Based Virtual Screening With Multiple Protein Structures and Bio-Assay Evaluation for Discovery of Novel GSK3β Inhibitors

Glycogen synthase kinase-3β (GSK3β) is associated with various key biological processes, and it has been considered as a critical therapeutic target for the treatment of many diseases. However, it is a big challenge to develop ATP-competition GSK3β inhibitors because of the high sequence homology with other kinases. In this work, a novel parallel virtual screening strategy based on multiple GSK3β protein structures, integrating molecular docking, complex-based pharmacophore, and naive Bayesian classification, was developed to screen a large chemical database, the 50 compounds with top-scores then underwent a luminescent kinase assay, which led to the discovery of two GSK3β inhibitor hits. The high screening enrichment rate indicates the reliability and practicability of the integrated protocol. Finally, molecular docking and molecular dynamics simulation were employed to investigate the binding modes of the GSK3β inhibitors, and some “hot residues” critical to GSK3β affinity were highlighted. The present study may provide some valuable guidance for the development of novel GSK3β inhibitors.

DeepAtomicCharge: a new graph convolutional network-based architecture for accurate prediction of atomic charges

Atomic charges play a very important role in drug-target recognition. However, computation of atomic charges with high-level quantum mechanics (QM) calculations is very time-consuming. A number of machine learning (ML)-based atomic charge prediction methods have been proposed to speed up the calculation of high-accuracy atomic charges in recent years. However, most of them used a set of predefined molecular properties, such as molecular fingerprints, for model construction, which is knowledge-dependent and may lead to biased predictions due to the representation preference of different molecular properties used for training. To solve the problem, we present a new architecture based on graph convolutional network (GCN) and develop a high-accuracy atomic charge prediction model named DeepAtomicCharge. The new GCN architecture is designed with only the atomic properties and the connection information between the atoms in molecules and can dynamically learn and convert molecules into appropriate atomic features without any prior knowledge of the molecules. Using the designed GCN architecture, substantial improvement is achieved for the prediction accuracy of atomic charges. The average root-mean-square error (RMSE) of DeepAtomicCharge is 0.0121 e, which is obviously more accurate than that (0.0180 e) reported by the previous benchmark study on the same two external test sets. Moreover, the new GCN architecture needs much lower storage space compared with other methods, and the predicted DDEC atomic charges can be efficiently used in large-scale structure-based drug design, thus opening a new avenue for high-performance atomic charge prediction and application.

Zinc-mediated conformational preselection mechanism in the allosteric control of DNA binding to the zinc transcriptional regulator (ZitR)

The zinc transcriptional regulator (ZitR) functions as a metalloregulator that fine tunes transcriptional regulation through zinc-dependent DNA binding. However, the molecular mechanism of zinc-driven allosteric control of the DNA binding to ZitR remains elusive. Here, we performed enhanced sampling accelerated molecular dynamics simulations to figure out the mechanism, revealing the role of protein dynamics in the zinc-induced allosteric control of DNA binding to ZitR. The results suggest that zinc-free ZitR samples distinct conformational states, only a handful of which are compatible with DNA binding. Remarkably, zinc binding reduces the conformational plasticity of the DNA-binding domain of ZitR, promoting the population shift in the ZitR conformational ensemble towards the DNA binding-competent conformation. Further co-binding of DNA to the zinc–ZitR complex stabilizes this competent conformation. These findings suggest that ZitR–DNA interactions are allosterically regulated in a zinc-mediated conformational preselection manner, highlighting the importance of conformational dynamics in the regulation of transcription factor family.

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.

Macrophages affect immune inflammation and proliferation in benign prostatic hyperplasia via androgen receptor and CD40/CD40L signaling pathway

OBJECTIVE

Considering the association of macrophage migration inhibitory factor with development of prostate diseases, this study aims to explore the effect and mechanism of macrophages (MAs) in inflammation and proliferation of benign prostate hyperplasia (BPH) cells.

METHODS

Totally 85 prostate tissues (75 from BPH patients and 10 from brain death patients) were collected for determination of biomarkers of T lymphocyte (CD4 and CD8), B lymphocyte (CD20) and MAs (CD68), as well as androgen receptor (AR) and CD40/CD40L. MAs stimulated by phorbol myristate acetate (PMA) were cultured with BPH cells (BPH-1), followed by AR inhibitor or anti-CD40 L antibody treatment. Proliferation and cell apoptosis were observed by MTT assay, colony formation assay and flow cytometer. Expressions of apoptotic related proteins and MAPK signaling pathway-related proteins were determined by qRT-PCR and Western blot.

RESULTS

BPH tissues had increased expressions of AR, CD40 and CD40 L, as well as elevated expressions of inflammation biomarkers (CD4, CD8, CD20 and CD68) in comparison to normal prostate tissues. MAs could increase the expressions of lymphocytes and inflammation biomarkers, in addition to promoting cell proliferation and inhibiting cell apoptosis. Cell proliferation and inflammation reaction could be attenuated by anti-CD40 L antibody and AR inhibitor in a concentration dependent manner through inhibiting the phosphorylation of JNK, ERK1/2 and p38.

CONCLUSION

MAs regulate AR and CD40/CD40L expression to promote the inflammation and proliferation as well as inhibiting apoptosis of BPH-1 cells through activation of the MAPK signaling pathway. This conclusion may provide a therapeutic strategy for BPH patients.

Investigation of Crystal Structures in Structure-Based Virtual Screening for Protein Kinase Inhibitors

Protein kinases are important drug targets in several therapeutic areas ,and structure-based virtual screening (SBVS) is an important strategy in discovering lead compounds for kinase targets. However, there are multiple crystal structures available for each target, and determining which one is the most favorable is a key step in molecular docking for SBVS due to the ligand induce-fit effect. This work aimed to find the most desirable crystal structures for molecular docking by a comprehensive analysis of the protein kinase database which covers 190 different kinases from all eight main kinase families. Through an integrated self-docking and cross-docking evaluation, 86 targets were eventually evaluated on a total of 2608 crystal structures. Results showed that molecular docking has great capability in reproducing conformation of crystallized ligands and for each target, the most favorable crystal structure was selected, and the AGC family outperformed the other family targets based on RMSD comparison. In addition, RMSD values, GlideScore, and corresponding bioactivity data were compared and demonstrated certain relationships. This work provides great convenience for researchers to directly select the optimal crystal structure in SBVS-based kinase drug design and further validates the effectiveness of molecular docking in drug discovery.

Identification of novel inhibitor of protein tyrosine phosphatases delta: structure-based pharmacophore modeling, virtual screening, flexible docking, molecular dynamics simulation, and post-molecular dynamics analysis

Owing to their unique functions in regulating the synapse activity of protein tyrosine phosphatases delta (PTPδ) that has drawn special attention for developing drugs to autism spectrum disorders (ASDs). In this study, the PTPδ pharmacophore was first established by the structure-based pharmacophore method. Subsequently, 10 compounds contented Lipinski's rule of five was acquired by the virtual screening of the PTPδ pharmacophore against ZINC and PubChem databases. Then, the 10 identified molecules were discovered that had better binding affinity than a known PTPδ inhibitors compound SCHEMBL16375396. Two compounds SCHEMBL16375408 and ZINC19796658 with high binding score, low toxicity were gained. They were observed by docking analysis and molecular dynamics simulations that the novel potential inhibitors not only possessed the same function as SCHEMBL16375396 did in inhibiting PTPδ, but also had more favorable conformation to bind with the catalytic active regions. This study provides a new method for identify PTPδ inhibitor for the treatment of ASDs disease.Communicated by Ramaswamy H. Sarma.

Effective prediction model and determination of binding residues influential for inhibitors targeting HIV-1 integrase-LEDGF/p75 interface by employing solvent accessible surface area energy as key determinant

Development of a highly accurate prediction model for protein-ligand inhibition has been a major challenge in drug discovery. Herein, we describe a novel predictive model for the inhibition of HIV-1 integrase (IN)-LEDGF/p75 protein-protein interaction. The model was constructed using energy parameters approximated from molecular dynamics (MD) simulations and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. Chemometric analysis using partial least squares (PLS) regression revealed that solvent accessible surface area energy (ΔG_SASA) is the major determinant parameter contributing greatly to the prediction accuracy. PLS prediction model on the ΔG_SASA values collected from 41 complexes yielded a strong correlation between the predicted and the actual inhibitory activities (R² = 0.9666, RMSEC of pIC₅₀ values = 0.0890). Additionally, for the test set of 14 complexes, the model performed satisfactorily with very low pIC₅₀ errors (Q² = 0.5168, RMSEP = 0.3325). A strong correlation between the buried surface areas on the IN protein, when bound with IN-LEDGF/p75 inhibitors, and the respective ΔG_SASA values was also obtained. Furthermore, the current method could identify 'hot spots'of amino acid residues highly influential to the inhibitory activity prediction. This could present fruitful implications in binding site determination and future inhibitor developments targeting protein-protein interactions.Communicated by Ramaswamy H. Sarma.

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.