Androgen receptor binding affinity of pesticide "active" formulation ingredients. QSAR evaluation by COREPA method

The COREPA approach for identifying the COmmon REactivity PAttern of biologically similar chemicals was employed to upgrade the recently derived affinity pattern for high androgen receptor (AR) binding affinity. The training set consisted of 28 steroidal and nonsteroidal ligands whose AR binding affinity was determined in competitive binding assays (in terms of pKi). The interatomic distances between nucleophilic sites and their charges providing distinct and non-overlapping integral patterns for active and inactive chemicals were assumed that it was related with the endpoint, which was under study. These stereoelectronic characteristics were used to predict pKi values of pesticide "active" formulation ingredients in an attempt to identify chemicals with potential AR binding affinity.     

An integrated "4-phase" approach for setting endocrine disruption screening priorities--phase I and II predictions of estrogen receptor binding affinity

Recent legislation mandates the US Environmental Protection Agency (EPA) to develop a screening and testing program for potential endocrine disrupting chemicals (EDCs), of which xenoestrogens figure prominently. Under the legislation, a large number of chemicals will undergo various in vitro and in vivo assays for their potential estrogenicity, as well as other hormonal activities. There is a crucial need for priority setting before this strategy can be effectively implemented. Here we report an integrated computational approach to priority setting using estrogen receptor (ER) binding as an example. This approach rationally integrates different predictive computational models into a "Four-Phase" scheme so that it can effectively identify potential estrogenic EDCs based on their predicted ER relative binding affinity (RBA). The system has been validated using an in-house ER binding assay dataset for 232 chemicals that was designed to have both broad structural diversity and a wide range of binding affinities. When applied to 58,000 chemicals identified by Walker et al. as candidates for endocrine disruption screening, some 9100 chemicals were predicted to bind to ER. Of these, only 3600 were expected to bind to ER at RBA values up to 100,000-fold less than that of 17 g -estradiol. The method ruled out 83% of the chemicals as non-binders with a very low rate of false negatives. We believe that the same integrated scheme will be equally applicable to endpoints of other endocrine disrupting mechanisms, e.g. androgen receptor binding.     

Efficient Synthesis of a Water-Soluble Glucoamide Inhibitor Against Human Aldose Reductase by Click Chemistry

While D-glucose is the natural substrate of aldose reductase (AR) in the polyol pathway, the K _m value of D-glucose against AR is large. A glucoamide 1 was designed as a tool to investigate whether AR has a strong affinity for the open form of D-glucose. Glucoamide 1 was synthesized in high yield by modification of the reaction condition for click chemistry. It was found that our modified condition was applicable for highly polar alkynes and gave coupling products in excellent yield (90% to 100%). Although weak inhibitory activity against AR was observed, kinetic studies showed that AR does not accept glucoamide 1 in its active site.     

New pyrazolo[3,4-b]pyridones as selective A(1) adenosine receptor antagonists: synthesis, biological evaluation and molecular modelling studies

A series of ethyl 4-amino-1-(2-chloro-2-phenylethyl)-6-oxo-6,7-dihydro-1H-pyrazolo[3,4-b]pyridine-5-carboxylates () has been synthesized as potential A(1) adenosine receptor (A(1) AR) ligands. Binding affinities of the new compounds were determined for adenosine A(1), A(2A) and A(3) receptors. Compounds and showed good affinity (K(i)= 299 nM and 517 nM, respectively) and selectivity towards A(1) AR, whereas showed good affinity for A(2A) AR (K(i)= 290 nM), higher than towards A(1) AR (K(i)= 1000 nM). The only arylamino derivative of the series displayed high affinity (K(i)= 4.6 nM) and selectivity for A(3) AR. Molecular modelling and 3D-QSAR (CoMFA) studies carried out on the most active compounds gave further support to the pharmacological results.     

Adenosine A 2A receptor agonists: CoMFA-based selection of the most predictive conformation

A step-wise comparative molecular field analysis (CoMFA)-based procedure was applied to a series of 51 2-oxyadenosines in order to select the most predictive conformation for binding to A 2A adenosine receptor (AR). The highest correlation and predictive power were found for conformers with side chain at 2nd position oriented in the direction opposite to the exocyclic amino group on the adenine ring (torsion N1C2OR=120 ) and fully extended. The interaction of ligand and receptor is under steric and electrostatic control. The steric contribution is of a greater importance for the predictivity than the electrostatic one. Hydrophobicity of the compounds investigated does not affect significantly either the affinity to A 2A AR, nor the predictivity of the models.     

Comparative molecular field analysis (CoMFA) model using a large diverse set of natural, synthetic and environmental chemicals for binding to the androgen receptor

A large number of natural, synthetic and environmental chemicals are capable of disrupting the endocrine systems of experimental animals, wildlife and humans. These so-called endocrine disrupting chemicals (EDCs), some mimic the functions of the endogenous androgens, have become a concern to the public health. Androgens play an important role in many physiological processes, including the development and maintenance of male sexual characteristics. A common mechanism for androgen to produce both normal and adverse effects is binding to the androgen receptor (AR). In this study, we used Comparative Molecular Field Analysis (CoMFA), a three-dimensional quantitative structure-activity relationship (3D-QSAR) technique, to examine AR-ligand binding affinities. A CoMFA model with r2 = 0.902 and q2 = 0.571 was developed using a large training data set containing 146 structurally diverse natural, synthetic, and environmental chemicals with a 10(6)-fold range of relative binding affinity (RBA). By comparing the binding characteristics derived from the CoMFA contour map with these observed in a human AR crystal structure, we found that the steric and electrostatic properties encoded in this training data set are necessary and sufficient to describe the RBA of AR ligands. Finally, the CoMFA model was challenged with an external test data set; the predicted results were close to the actual values with average difference of 0.637 logRBA. This study demonstrates the utility of this CoMFA model for real-world use in predicting the AR binding affinities of structurally diverse chemicals over a wide RBA range.     

Synthesis,biological evaluation,and molecular docking study of pyridine clubbed 1,3,4-oxadiazoles as potential antituberculars

A series of pyridine clubbed 1,3,4-oxadiazole derivatives were efficiently synthesized, characterized by standard spectral techniques and evaluated for their in vitro antitubercular activity against Mycobacterium tuberculosis (MTB) H₃₇Ra and Mycobacterium bovis BCG in active and dormant state using an established methods. Compounds 5a, 5m, and 5t were identified as the most active compounds against MTB. Molecular docking was performed against MTB enoyl-ACP (CoA) reductase (FabI/ENR/InhA) enzyme to predict the binding modes and affinity. The theoretical predictions from molecular docking could establish a link between the observed biological activity and the binding affinity shedding light into specific bonded and non-bonded interactions influencing the activity. The active compounds were studied for cytotoxicity against three cell lines and were found to be non-cytotoxic. Specificity of these compounds was checked by screening them for their antibacterial activity against four bacterial strains.     

A reactivity pattern for discrimination of ER agonism and antagonism based on 3-D molecular attributes

Various models have been developed to predict the relative binding affinity (RBA) of chemicals to estrogen receptors (ER). These models can be used to prioritize chemicals for further tiered biological testing to assess the potential for endocrine disruption. One shortcoming of models predicting RBA has been the inability to distinguish potential receptor antagonism from agonism, and hence in vivo response. It has been suggested that steroid receptor antagonists are less compact than agonists; thus, ER binding of antagonists may prohibit proper alignment of receptor protein helices preventing subsequent transactivation. The current study tests the theory of chemical bulk as a defining parameter of antagonism by employing a 3-D structural approach for development of reactivity patterns for ER antagonists and agonists. Using a dataset of 23 potent ER ligands (16 agonists, 7 antagonists), molecular parameters previously found to be associated with ER binding affinity, namely global ( E HOMO ) and local (donor delocalizabilities and charges) electron donating ability of electronegative sites and steric distances between those sites, were found insufficient to discriminate ER antagonists from agonists. However, parameters related to molecular bulk, including solvent accessible surface and negatively charged Van der Waal's surface, provided reactivity patterns that were 100% successful in discriminating antagonists from agonists in the limited data set tested. The model also shows potential to discriminate pure antagonists from partial agonist/antagonist structures. Using this exploratory model it is possible to predict additional chemicals for their ability to bind but inactivate the ER, providing a further tool for hypothesis testing to elucidate chemical structural characteristics associated with estrogenicity and anti-estrogenicity.     

An integrated "4-phase" approach for setting endocrine disruption screening priorities--phase I and II predictions of estrogen receptor binding affinity

Recent legislation mandates the US Environmental Protection Agency (EPA) to develop a screening and testing program for potential endocrine disrupting chemicals (EDCs), of which xenoestrogens figure prominently. Under the legislation, a large number of chemicals will undergo various in vitro and in vivo assays for their potential estrogenicity, as well as other hormonal activities. There is a crucial need for priority setting before this strategy can be effectively implemented. Here we report an integrated computational approach to priority setting using estrogen receptor (ER) binding as an example. This approach rationally integrates different predictive computational models into a "Four-Phase" scheme so that it can effectively identify potential estrogenic EDCs based on their predicted ER relative binding affinity (RBA). The system has been validated using an in-house ER binding assay dataset for 232 chemicals that was designed to have both broad structural diversity and a wide range of binding affinities. When applied to 58,000 chemicals identified by Walker et al. as candidates for endocrine disruption screening, some 9100 chemicals were predicted to bind to ER. Of these, only 3600 were expected to bind to ER at RBA values up to 100,000-fold less than that of 17beta-estradiol. The method ruled out 83% of the chemicals as non-binders with a very low rate of false negatives. We believe that the same integrated scheme will be equally applicable to endpoints of other endocrine disrupting mechanisms, e.g. androgen receptor binding.     

Photo-Induced Switchable Binding Behavior of Bridged Bis(β-cyclodextrin) with an Azobenzene Dicarboxylate Linker

A bridged bis(β-cyclodextrin) (1) with an azobenzene dicarboxylate linker was synthesized, and its binding behavior with a fluorescent dye, acridine red (AR), was investigated by means of fluorescence spectroscopy. Due to the photo-induced conversion of the azobenzene dicarboxylate linker from the trans-conformer to the cis-conformer, 1 exhibits a different binding behavior before and after UV light irradiation, giving a stronger binding ability towards AR in the cis form. This switchable binding behavior of 1 may open a new channel to the design of azobenzene-linked dimeric receptors as photo-induced molecular devices.     

Design,Synthesis, and Biological Evaluation of Tetra-Substituted Thiophenes as Inhibitors of p38α MAPK

p38α mitogen-activated protein kinase (MAPK) plays a role in several cellular processes and consequently has been a therapeutic target in inflammatory diseases, cancer, and cardiovascular disease. A number of known p38α MAPK inhibitors contain vicinal 4-fluorophenyl/4-pyridyl rings connected to either a 5- or 6-membered heterocycle. In this study, a small library of substituted thiophene-based compounds bearing the vicinal 4-fluorophenyl/4-pyridyl rings was designed using computational docking as a visualisation tool. Compounds were synthesised and evaluated in a fluorescence polarisation binding assay. The synthesised analogues had a higher binding affinity to the active phosphorylated form of p38α MAPK than the inactive nonphosphorylated form of the protein. 4-(2-(4-fluorophenyl)thiophen-3-yl)pyridine had a K_i value of 0.6 μm to active p38α MAPK highlighting that substitution of the core ring to a thiophene retains affinity to the enzyme and can be utilised in p38α MAPK inhibitors. This compound was further elaborated using a substituted phenyl ring in order to probe the second hydrophobic pocket. Many of these analogues exhibited low micromolar affinity to active p38α MAPK. The suppression of neonatal rat fibroblast collagen synthesis was also observed suggesting that further development of these compounds may lead to potential therapeutics having cardioprotective properties.     

Spectroscopic Study of Azo- and Azoxycrowns Binding with Cations of Similar Ionic Radius

The complexation of 13- and 16-memberedazo- and azoxycrowns with metal cations of similarionic diameter (Na⁺ and Ca²⁺; and K⁺,Ba²⁺, Ag⁺ and Pb²⁺) was studied byuv/visible spectroscopic titration in acetonitrile andMeOH. In MeOH the 13-membered azo- and azoxycrowns 1 and 2 are weakly and non-selectively bound tohard cations of similar ionic diameter, but differentcharge (Na⁺ and Ca²⁺). At the same time thebinding to the soft cation Ag⁺ of larger sizethan the macrocycle cavity is considerably stronger.In contrast to solutions in acetonitrile no bindingwith the small Li⁺ cation was found.The 16-membered azocrowns 3 and 4 alsodiscriminate silver cation in MeOH withlog K = 3.65 ± 0.1 for both compounds.Unexpectedly low bindingwith the hard barium divalent cation of similar size(log K = 1.55 ± 0.4 and 1.95 ± 0.2, respectively)was found for these compounds. Similarly to13-membered compounds no binding with the smallLi⁺ cation was detected. A reverse order ofselectivity was observed for these crowns inacetonitrile with binding constant for association of3 with Ba²⁺ (log K 5.3) considerablyhigher than for other cations. The previously observedstrong binding with the smaller Li⁺ and Na⁺cations is confirmed.     

Cooperative molecular recognition of dyes by two bis(β-cyclodextrin)s with aromatic,sulfur-containing,diamine tethers

The molecular binding behavior of two bis(β-cyclodextrin (CD))s, that is, 4,4′-diaminodiphenylsulfone-bridged bis(β-CD) 2 and 4,4′-diaminodiphenyldisulfide-bridged bis(β-CD) 3 with some representative organic dyes, i.e., acridine red (AR), neutral red (NR), ammonium 8-anilino-1-naphthalenesulfonate (ANS), sodium 2-(p-toluidinyl)naphthalenesulfonate (TNS), rhodamine B (RhB), and brilliant green (BG), has been investigated at 25 °C in phosphate buffer (pH 7.20) by ultraviolet, fluorescence and 2D NMR spectroscopy. The fluorescence of ANS, TNS, AR, and NR are enhanced, whereas that of RhB is quenched, by inclusion complexation with both host compounds. The results obtained show bridged bis(β-CD)s 2 and 3 with dye guests give higher complex stability constants (K _S) than those of the native β-CD 1, through cooperative binding of two hydrophobic CD cavities with one guest. In addition, the K _S values of all guests with host 3 are much larger than those with 2 except for NR as guest. The 2D ¹H NOESY spectrum of host 3 and RhB was acquired to confirm the cooperative binding mode. The molecular binding ability of dyes by hosts 1–3 are discussed from the viewpoint of the size and shape-fitting relationship between host and guest.     

X-Ray Crystallography and Free Energy Calculations Reveal the Binding Mechanism of A2A Adenosine Receptor Antagonists

We present a robust protocol based on iterations of free energy perturbation (FEP) calculations, chemical synthesis, biophysical mapping and X-ray crystallography to reveal the binding mode of an antagonist series to the A_2A adenosine receptor (AR). Eight A_2AAR binding site mutations from biophysical mapping experiments were initially analyzed with sidechain FEP simulations, performed on alternate binding modes. The results distinctively supported one binding mode, which was subsequently used to design new chromone derivatives. Their affinities for the A_2AAR were experimentally determined and investigated through a cycle of ligand-FEP calculations, validating the binding orientation of the different chemical substituents proposed. Subsequent X-ray crystallography of the A_2AAR with a low and a high affinity chromone derivative confirmed the predicted binding orientation. The new molecules and structures here reported were driven by free energy calculations, and provide new insights on antagonist binding to the A_2AAR, an emerging target in immuno-oncology.     

X‐Ray Crystallography and Free Energy Calculations Reveal the Binding Mechanism of A2A Adenosine Receptor Antagonists

We present a robust protocol based on iterations of free energy perturbation (FEP) calculations, chemical synthesis, biophysical mapping and X‐ray crystallography to reveal the binding mode of an antagonist series to the A_2A adenosine receptor (AR). Eight A_2AAR binding site mutations from biophysical mapping experiments were initially analyzed with sidechain FEP simulations, performed on alternate binding modes. The results distinctively supported one binding mode, which was subsequently used to design new chromone derivatives. Their affinities for the A_2AAR were experimentally determined and investigated through a cycle of ligand‐FEP calculations, validating the binding orientation of the different chemical substituents proposed. Subsequent X‐ray crystallography of the A_2AAR with a low and a high affinity chromone derivative confirmed the predicted binding orientation. The new molecules and structures here reported were driven by free energy calculations, and provide new insights on antagonist binding to the A_2AAR, an emerging target in immuno‐oncology.     

Effects-based chemical category approach for prioritization of low affinity estrogenic chemicals

Regulatory agencies are charged with addressing the endocrine disrupting potential of large numbers of chemicals for which there is often little or no data on which to make decisions. Prioritizing the chemicals of greatest concern for further screening for potential hazard to humans and wildlife is an initial step in the process. This paper presents the collection of in vitro data using assays optimized to detect low affinity estrogen receptor (ER) binding chemicals and the use of that data to build effects-based chemical categories following QSAR approaches and principles pioneered by Gilman Veith and colleagues for application to environmental regulatory challenges. Effects-based chemical categories were built using these QSAR principles focused on the types of chemicals in the specific regulatory domain of concern, i.e. non-steroidal industrial chemicals, and based upon a mechanistic hypothesis of how these non-steroidal chemicals of seemingly dissimilar structure to 17ß-estradiol (E2) could interact with the ER via two distinct binding types. Chemicals were also tested to solubility thereby minimizing false negatives and providing confidence in determination of chemicals as inactive. The high-quality data collected in this manner were used to build an ER expert system for chemical prioritization described in a companion article in this journal.