Discovery of estrogen receptor modulators: a review of virtual screening and SAR efforts

Importance of the field: Virtual screening (VS) coupled with structural biology is a significantly important approach to increase the number and enhance the success of projects in lead identification stage of drug discovery process. Recent advances and future directions in estrogen therapy have resulted in great demand for identifying the potential estrogen receptor (ER) modulators with more activity and selectivity. Areas covered in this review: This review presents the current state of the art in VS and structure-activity relationship of ER modulators in recent discovery, and discusses the strengths and weaknesses of the technology. What the reader will gain: Readers will gain an overview of the current platforms of in silico screening for discovery of ER modulators; they will learn which structural information is significantly correlated with the bioactivity of ER modulators and what novel strategies should be considered for the creation of more effective chemical structures. Take home message: With the goal of reducing toxicity and/or improving efficacy, challenges to the successful modeling of endocrine agents are proposed, providing new paradigms for the design of ER inhibitors.     

Use of an induced fit receptor structure in virtual screening

Structured-based drug design has traditionally relied on a single receptor structure as a target for docking and screening studies. However, it has become increasingly clear that in many cases where protein flexibility is an issue, it is critical to accurately model ligand-induced receptor movement in order to obtain high enrichment factors. We present a novel protein-ligand docking method that accounts for both ligand and receptor flexibility and accurately predicts the conformation of protein-ligand binding complexes. This method can generate viable receptor ensembles that can be used in virtual database screens.     

Structure-based virtual screening: an overview

Enormous advances in genomics have resulted in a large increase in the number of potential therapeutic targets that are available for investigation. This growth in potential targets has increased the demand for reliable target validation, as well as technologies that can identify rapidly several quality lead candidates. Virtual screening, and in particular receptor-based virtual screening, has emerged as a reliable, inexpensive method for identifying leads. Although still an evolving method, advances in computational techniques have enabled virtual screening to have a positive impact on the discovery process. Here, the current strengths and weaknesses of the technology are discussed, and emphasis is placed on aspects of the work-flow of a virtual screening campaign, from preparation through to post-screening analysis.     

Virtual screening of the estrogen receptor

Background: For > 30 years, the estrogen receptor (ER) has been the most important biomarker in breast cancer, principally because of its role in indicating the potential of patients to benefit from endocrine therapy. The search for modulators of ER (selective estrogen receptor modulators) through the use of computational methods such as virtual screening (VS) has redefined the area. Objective: We demonstrate how this receptor has become a key target in the computational (docking and scoring, pharmacophore) arena for algorithm development and validation. The use of quantitative structure–activity relationship for estimation of binding affinity to ER is also discussed, and finally all examples of lead identification through VS are exemplified using several VS campaigns carried out to identify environmental endocrine disruptors. Method: This review comprehensively details all current applications of virtual screening to the estrogen receptor and demonstrates how its use has pushed the boundaries of VS in general. Conclusion: The widespread application of the estrogen receptor to VS has allowed identification of numerous pitfalls within the process flow of VS such as library generation, correct validation procedures for docking/scoring functions, and inclusion of receptor flexibility.     

Nuclear hormone receptor targeted virtual screening

Virtual library screening (VLS) is emerging as a valuable drug lead discovery tool. ICM-VLS implementation of this technology was evaluated on a benchmark set of nuclear hormone receptors (NRs), an important therapeutic target family. Over 5000 structurally diverse compounds, including 78 known NR ligands, were screened against 18 crystal structures and one computer model of 10 NR ligand binding domains in their active or inactive states. The results confirm the ability of the VLS method to generate highly focused subsets of the input chemical library, enriched 33- to 100-fold for all but one receptor studied. However, receptor flexibility remains to be fully addressed, and the choice of the specific conformation used for screening may determine the success of the exercise. We observe that for a particular ligand VLS can often identify the correct target within the receptor family, although the technology is unable to reliably discriminate between the closely related receptor isoforms. Additionally, our results suggest that VLS may be applied successfully without an experimental structure of the receptor by using a homology model. These data represent a realistic snapshot of the state-of-the-art of NR-targeted VLS and define the recent progress and the remaining limitations of the technology.     

The virtual heart as a platform for screening drug cardiotoxicity

To predict the safety of a drug at an early stage in its development is a major challenge as there is a lack of in vitro heart models that correlate data from preclinical toxicity screening assays with clinical results. A biophysically detailed computer model of the heart, the virtual heart, provides a powerful tool for simulating drug–ion channel interactions and cardiac functions during normal and disease conditions and, therefore, provides a powerful platform for drug cardiotoxicity screening. In this article, we first review recent progress in the development of theory on drug–ion channel interactions and mathematical modelling. Then we propose a family of biomarkers that can quantitatively characterize the actions of a drug on the electrical activity of the heart at multi‐physical scales including cellular and tissue levels. We also conducted some simulations to demonstrate the application of the virtual heart to assess the pro‐arrhythmic effects of cisapride and amiodarone. Using the model we investigated the mechanisms responsible for the differences between the two drugs on pro‐arrhythmogenesis, even though both prolong the QT interval of ECGs. Several challenges for further development of a virtual heart as a platform for screening drug cardiotoxicity are discussed.

Linked Articles

This article is part of a themed section on Chinese Innovation in Cardiovascular Drug Discovery. To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2015.172.issue-23

Abbreviations

AE

allosteric effector

APD

action potential duration

APD₉₀

APD at 90% repolarization

APs

action potentials

BCL

basic cycle length

CV

conduction velocity

CVR

conduction velocity restitution

ERP

effective refractory period

GR

guarded receptor

HH

Hodgkin–Huxley

I_CaL

L‐type Ca²⁺ current

I_Kr

delayed rectifier K⁺ channel current

I_Ktof

fast component of the cardiac transient outward current

I_Na

Na⁺ channel current

LQTs

long QT syndrome

MR

modulated receptor

QTc

corrected QT interval

VW

vulnerable window

WL

wavelength

Tables of Links

Estrogen receptor interaction with specific histones: Binding to genomic DNA and an estrogen response element

Chromosomal proteins that impart high affinity and specificity to the binding of the estrogen receptor (ER) to DNA are termed estrogen receptor binding factors (ERBFs). Certain partially purified chromosomal protein fractions obtained from rabbit uterine chromatin by extraction with various molarities of GdnHCl when reconstituted to double-stranded DNA demonstrated high affinity binding for the ER. We report the purification and characterization of ERBFs in the chromosomal protein fraction extracted with 4 M GdnHCl (CP4) after large scale purification. These protein fractions were further purified by CL-Sepharose 6B column chromatography which resolved fractions from CP4 that recognized the ER bound by estrogen only or antiestrogen only. Thus, these hydrophobic chromosomal proteins enhanced the binding of the ER to reconstituted chromatin. To further investigate the interaction of ERBFs with ER, gel mobility shift assays were performed. The highly purified CP4 fraction with ERBF activity in the binding assay with reconstituted chromatin caused an increase in the formation of the retarded ER-estrogen responsive element (ERE) band. Thus, chromatin contains specific ERBFs for ER bound by estrogen which enhance the binding of ER to genomic DNA and a target ERE sequence. Further purification of the CL-Sepharose fraction with ERBF activity was achieved by preparative SDS—PAGE. ERBF activity was attributed to proteins with approximate molecular weights of 16,000, 13,000, and 12,000 and a pI of >9.0. Peptides were partially sequenced by Edman degradation and were found to have identity with histones H2B and H4. A 17 kDa protein without ERBF activity was identified as H3. Since these histones were not readily extracted from chromatin with 3 M NaCl or 1–3 M GdnHCl, we postulate that some ERBFs may be histone variants or modified histones that display a very high affinity for DNA and ER.     

Soft docking and multiple receptor conformations in virtual screening

Protein conformational change is an important consideration in ligand-docking screens, but it is difficult to predict. A simple way to account for protein flexibility is to soften the criterion for steric fit between ligand and receptor. A more comprehensive but more expensive method would be to sample multiple receptor conformations explicitly. Here, these two approaches are compared. A "soft" scoring function was created by attenuating the repulsive term in the Lennard-Jones potential, allowing for a closer approach between ligand and protein. The standard, "hard" Lennard-Jones potential was used for docking to multiple receptor conformations. The Available Chemicals Directory (ACD) was screened against two cavity sites in the T4 lysozyme. These sites undergo small but significant conformational changes on ligand binding, making them good systems for soft docking. The ACD was also screened against the drug target aldose reductase, which can undergo large conformational changes on ligand binding. We evaluated the ability of the scoring functions to identify known ligands from among the over 200 000 decoy molecules in the database. The soft potential was always better at identifying known ligands than the hard scoring function when only a single receptor conformation was used. Conversely, the soft function was worse at identifying known leads than the hard function when multiple receptor conformations were used. This was true even for the cavity sites and was especially true for aldose reductase. To test the multiple-conformation method predictively, we screened the ACD for molecules that preferentially docked to the expanded conformation of aldose reductase, known to bind larger ligands. Six novel molecules that ranked among the top 0.66% of hits from the multiple-conformation calculation, but ranked relatively poorly in the soft docking calculation, were tested experimentally for enzyme inhibition. Four of these six inhibited the enzyme, the best with an IC(50) of 8 microM. Although ligands can get better scores in soft docking, the same is also true for decoys. The improved ranking of such decoys can come at the expense of true ligands.     

DrugRep: an automatic virtual screening server for drug repurposing

Computationally identifying new targets for existing drugs has drawn much attention in drug repurposing due to its advantages over de novo drugs, including low risk, low costs, and rapid pace. To facilitate the drug repurposing computation, we constructed an automated and parameter-free virtual screening server, namely DrugRep, which performed molecular 3D structure construction, binding pocket prediction, docking, similarity comparison and binding affinity screening in a fully automatic manner. DrugRep repurposed drugs not only by receptor-based screening but also by ligand-based screening. The former automatically detected possible binding pockets of the receptor with our cavity detection approach, and then performed batch docking over drugs with a widespread docking program, AutoDock Vina. The latter explored drugs using seven well-established similarity measuring tools, including our recently developed ligand-similarity-based methods LigMate and FitDock. DrugRep utilized easy-to-use graphic interfaces for the user operation, and offered interactive predictions with state-of-the-art accuracy. We expect that this freely available online drug repurposing tool could be beneficial to the drug discovery community. The web site is http://cao.labshare.cn/drugrep/.     

Identification of nonpeptide CCR5 receptor agonists by structure-based virtual screening

A three-dimensional model of the chemokine receptor CCR5 has been built to fulfill structural peculiarities of its alpha-helix bundle and to distinguish known CCR5 antagonists from randomly chosen drug-like decoys. In silico screening of a library of 1.6 million commercially available compounds against the CCR5 model by sequential filters (drug-likeness, 2-D pharmacophore, 3-D docking, scaffold clustering) yielded a hit list of 59 compounds, out of which 10 exhibited a detectable binding affinity to the CCR5 receptor. Unexpectedly, most binders tested in a functional assay were shown to be agonists of the CCR5 receptor. A follow-up database query based on similarity to the most potent binders identified three new CCR5 agonists. Despite a moderate affinity of all nonpeptide ligands for the CCR5 receptor, one of the agonists was shown to promote efficient receptor internalization, which is a process therapeutically favorable for protection against HIV-1 infection.     

Pharmacophore-based virtual screening versus docking-based virtual screening： a benchmark comparison against eight targets

Aim:

This study was conducted to compare the efficiencies of two virtual screening approaches, pharmacophore-based virtual screening (PBVS) and docking-based virtual screening (DBVS) methods.

Methods:

All virtual screens were performed on two data sets of small molecules with both actives and decoys against eight structurally diverse protein targets, namely angiotensin converting enzyme (ACE), acetylcholinesterase (AChE), androgen receptor (AR), D-alanyl-D-alanine carboxypeptidase (DacA), dihydrofolate reductase (DHFR), estrogen receptors α (ERα), HIV-1 protease (HIV-pr), and thymidine kinase (TK). Each pharmacophore model was constructed based on several X-ray structures of protein-ligand complexes. Virtual screens were performed using four screening standards, the program Catalyst for PBVS and three docking programs (DOCK, GOLD and Glide) for DBVS.

Results:

Of the sixteen sets of virtual screens (one target versus two testing databases), the enrichment factors of fourteen cases using the PBVS method were higher than those using DBVS methods. The average hit rates over the eight targets at 2% and 5% of the highest ranks of the entire databases for PBVS are much higher than those for DBVS.

Conclusion:

The PBVS method outperformed DBVS methods in retrieving actives from the databases in our tested targets, and is a powerful method in drug discovery.     

Effect of an homo-aza-steroidal ester on estrogen receptor

A new modified steroid esterified with the cytotoxic moiety, p-[N,N-bis(2-chloroethyl)amino]phenyl-acetic acid, has been synthesized and tested for interaction with estrogen receptor and cytotoxic activity on the MCF-7 cell line.     

Identification of putative estrogen receptor-mediated endocrine disrupting chemicals using QSAR- and structure-based virtual screening approaches

Identification of endocrine disrupting chemicals is one of the important goals of environmental chemical hazard screening. We report on the development of validated in silico predictors of chemicals likely to cause estrogen receptor (ER)-mediated endocrine disruption to facilitate their prioritization for future screening. A database of relative binding affinity of a large number of ERα and/or ERβ ligands was assembled (546 for ERα and 137 for ERβ). Both single-task learning (STL) and multi-task learning (MTL) continuous quantitative structure–activity relationship (QSAR) models were developed for predicting ligand binding affinity to ERα or ERβ. High predictive accuracy was achieved for ERα binding affinity (MTL R² = 0.71, STL R² = 0.73). For ERβ binding affinity, MTL models were significantly more predictive (R² = 0.53, p < 0.05) than STL models. In addition, docking studies were performed on a set of ER agonists/antagonists (67 agonists and 39 antagonists for ERα, 48 agonists and 32 antagonists for ERβ, supplemented by putative decoys/non-binders) using the following ER structures (in complexes with respective ligands) retrieved from the Protein Data Bank: ERα agonist (PDB ID: 1L2I), ERα antagonist (PDB ID: 3DT3), ERβ agonist (PDB ID: 2NV7), and ERβ antagonist (PDB ID: 1L2J). We found that all four ER conformations discriminated their corresponding ligands from presumed non-binders. Finally, both QSAR models and ER structures were employed in parallel to virtually screen several large libraries of environmental chemicals to derive a ligand- and structure-based prioritized list of putative estrogenic compounds to be used for in vitro and in vivo experimental validation.     

On-line formation, separation, and estrogen receptor affinity screening of cytochrome P450-derived metabolites of selective estrogen receptor modulators.

We have developed a fully automated bioreactor coupled to an on-line receptor affinity detection system. This analytical system provides detailed information on pharmacologically active metabolites of selective estrogen receptor modulators (SERMs) generated by cytochromes P450 (P450s). We demonstrated this novel concept by investigating the metabolic activation of tamoxifen and raloxifene by P450-containing pig and rat liver microsomes. The high resolution screening (HRS) system is based on the coupling of a P450-bioreactor to an HPLC-based estrogen receptor alpha (ERalpha) affinity assay. P450-derived metabolites of the SERMs were generated in the bioreactor, subsequently trapped on-line with solid phase extraction, and finally separated with gradient HPLC. Upon elution, the metabolites were screened on affinity for ERalpha with an on-line HRS assay. With this HRS system, we were able to follow, in a time-dependent manner, the formation of ERalpha-binding metabolites of tamoxifen and raloxifene. By analyzing the bioaffinity chromatograms with liquid chromatography-tandem mass spectrometry, structural information of the pharmacologically active metabolites was obtained as well. For tamoxifen, 15 active and 6 nonactive metabolites were observed, of which 5 were of primary, 10 of secondary, and 6 of an as yet unknown order of metabolism. Raloxifene was biotransformed in three primary and three secondary metabolites. MS/MS analysis revealed that three of the observed active metabolites of raloxifene were not described before. The present automated on-line HRS system coupled to a P450-containing bioreactor and an ERalpha-affinity detector proved very efficient, sensitive, and selective in metabolic profiling of SERMs.     

Recent development and application of virtual screening in drug discovery: an overview

Virtual screening, especially the structure-based virtual screening, has emerged as a reliable, cost-effective and time-saving technique for the discovery of lead compounds. Here, the basic ideas and computational tools for virtual screening have been briefly introduced, and emphasis is placed on aspects of recent development of docking-based virtual screening, scoring functions in molecular docking and ADME/Tox-based virtual screening in the past three years (2000 to 2003). Moreover, successful examples are provided to further demonstrate the effectiveness of virtual screening in drug discovery.     

补体C5a受体拮抗剂体外筛选平台的建立

目的建立稳定的补体C5a受体(C5aR)拮抗剂筛选平台。方法采集人外周静脉抗凝血,与不同浓度C5a、脂多糖及PMX-53孵育10～30 min。通过流式细胞术检测中性粒细胞表面CD11b的表达,溶菌酶检测试剂盒观察中性粒细胞分泌溶菌酶的能力变化,罗丹明-123检测中性粒细胞呼吸爆发的变化,ELISA检测细胞上清液中白细胞介素(IL)-8的表达变化,Western Blotting检测胞外信号调节激酶(ERK)、蛋白激酶B(AKB或AKT)含量及其磷酸化水平的变化,考察补体C5a刺激及使用阳性药物PMX-53后对各生化指标的影响。结果 C5a刺激人外周血可增强中性粒细胞CD11b的表达,促进溶菌酶释放和IL-8的分泌,激发呼吸爆发,上调ERK、AKT的含量和磷酸化水平,阳性药物PMX-53则能显著抑制C5a的上述生物学效应。结论成功建立C5aR拮抗剂人全血体外筛选平台,为C5aR拮抗剂筛选及功能研究奠定了基础。     

Benzoxepin-derived estrogen receptor modulators: a novel molecular scaffold for the estrogen receptor

We present and examine the efficacy of a novel benzoxepin-based scaffold for modulation of the human estrogen receptor. Receptor tolerance of this new molecular scaffold is examined through presentation of experimentally determined antiproliferative effects on human MCF-7 breast tumor cells and measured binding affinities. The effect of functional group substitution on the benzoxepin scaffold is explored through a brief computational structure-activity relationship investigation with molecular simulation.