Quantitative structure-activity relationships for a series of selective estrogen receptor-beta modulators

The estrogen receptor-beta subtype (ERbeta) is an attractive drug target for the development of novel therapeutic agents for hormone replacement therapy. Hologram quantitative structure-activity relationships (HQSAR) were conducted on a series of 6-phenylnaphthalene and 2-phenylquinoline derivatives, employing values of ERbeta binding affinity. A training set of 65 compounds served to derive the models. The best statistical HQSAR model (q(2) = 0.73 and r(2) = 0.91) was generated using atoms, bonds, connections and donor and acceptor as fragment distinction parameters, and fragment size default (4-7) with hologram length of 199. The model was used to predict the binding affinity of an external test set of 16 compounds, and the predicted values were in good agreement with the experimental results. The final HQSAR model and the information obtained from 2D contribution maps should be useful for the design of novel ERbeta modulators having improved affinity.     

Performance of (consensus) kNN QSAR for predicting estrogenic activity in a large diverse set of organic compounds

A novel method (in the context of quantitative structure–activity relationship (QSAR)) based on the k nearest neighbour (kNN) principle, has recently been introduced for the derivation of predictive structure–activity relationships. Its performance has been tested for estimating the estrogen binding affinity of a diverse set of 142 organic molecules. Highly predictive models have been obtained. Moreover, it has been demonstrated that consensus-type kNN QSAR models, derived from the arithmetic mean of individual QSAR models were statistically robust and provided more accurate predictions than the great majority of the individual QSAR models. Finally, the consensus QSAR method was tested with 3D QSAR and log?P data from a widely used steroid benchmark data set.     

Application of 4D-QSAR studies to a series of raloxifene analogs and design of potential selective estrogen receptor modulators

Four-dimensional quantitative structure-activity relationship (4D-QSAR) analysis was applied on a series of 54 2-arylbenzothiophene derivatives, synthesized by Grese and coworkers, based on raloxifene (an estrogen receptor-alpha antagonist), and evaluated as ERa ligands and as inhibitors of estrogen-stimulated proliferation of MCF-7 breast cancer cells. The conformations of each analogue, sampled from a molecular dynamics simulation, were placed in a grid cell lattice according to three trial alignments, considering two grid cell sizes (1.0 and 2.0 ?). The QSAR equations, generated by a combined scheme of genetic algorithms (GA) and partial least squares (PLS) regression, were evaluated by "leave-one-out" cross-validation, using a training set of 41 compounds. External validation was performed using a test set of 13 compounds. The obtained 4D-QSAR models are in agreement with the proposed mechanism of action for raloxifene. This study allowed a quantitative prediction of compounds' potency and supported the design of new raloxifene analogs.     

QSAR studies on estrogen receptor binding affinity of 2-phenylindoles using first-order valence molecular connectivity

The estrogen receptor binding affinity of 2-phenylindoles is found to be significantly correlated with Kier’s first-order valence molecular connectivity index. The correlation equations obtained provide a much simple rationale to design more potent compounds and help in predicting the potency of new compounds.     

PIFA-mediated synthesis of novel pyrazoloquinolin-4-ones as potential ligands for the estrogen receptor

A facile and efficient preparation of pyrazoloquinolin-4-ones, as potential ligands for the estrogen receptor, via a PIFA [phenyliodine(III)bis(trifluoroacetate)] promoted cyclization reaction with overall yields up to 29% over six steps is described. The employed strategy, based on an electrophilic amidation reaction as the key step of the synthesis, allows the generation of a diverse array of derivatives.     

Synthesis of benzyl- and benzhydrylferrocenes via Friedel-Crafts alkylation of ferrocene. Access to ferrocenyl bisphenols with high affinities for estrogen receptors

Ferrocene reacts with methoxy-substituted benzyl- and benzhydryl alcohols in the presence of trifluoroacetic acid to afford methoxybenzyl- or benzhydrylferrocenes in 47-56% yield. Demethylation of these compound leads to the ferrocenyl phenols and bisphenols. Some of the synthesized compounds display high affinity for estrogen receptors ERα and ERβ.     

Novel method for evaluation of chemicals based on ligand-dependent recruitment of GFP labeled coactivator to estrogen receptor displayed on bacterial magnetic particles

We established a novel method to evaluate endocrine disrupting chemicals (EDCs) by assembling the estrogen receptor-ligand binding domain (ERLBD) and GFP labeled coactivator on magnetic nanoparticles. EDC can promote or inhibit coactivator recruitment to the ligand-ERLBD complex. ERLBD was displayed on the surface of nano-sized bacterial magnetic particles (BacMPs) produced by the magnetic bacterium, Magnetospirillum magneticum AMB-1. Our method resulted in 38 molecules of ERLBD molecules on a BacMPs with diameter of 75 nm. Furthermore, ligand-dependent recruitment assays of GFP labeled coactivator to ERLBD-BacMPs was performed by measuring the fluorescence intensity. 17β-estradiol (E2), estriol, diethylstilbestrol, zeralenone (full agonist), octylphenol (partial agonist) and ICI 182,780 (antagonist) were evaluated by this method. Full agonists tested showed increased fluorescence with increasing agonist concentration. Octylphenol had lower fluorescence intensity than E2. ICI 182,780 did not produce any fluorescence. The method developed in this study can evaluate the estrogenic potential of chemicals by discriminating whether they are an ER full agonist, partial agonist, or antagonist. Finally, this method is amenable adaptation into a high throughput format by using automated magnetic separation.     

Preliminary study on application of impregnated synthetic peptide TLC stationary phases for the pre-screening of 5-HT1A ligands

Chromatographic parameters (deltaR(f)), defined as a difference in the migration of tested compound on the control and peptide impregnated silica gel TLC plates, were determined for 42 arylpiperazine derivatives. An amino acid sequence of the peptide used for impregnation was derived from the III transmembrane segment of the 5-HT(1A) receptor in the close vicinity of aspartic acid (Asp 166) residue. It was found that the deltaR(f) values obtained in a model employing tetrapeptide P4LA (ADVL), as well as the calculated logP correlate with 5-HT(1A) receptor affinity of the studied compounds.     

Parabolic quantitative structure-activity relationships and photodynamic therapy: application of a three-compartment model with clearance to the in vivo quantitative structure-activity relationships of a congeneric series of pyropheophorbide derivatives used as photosensitizers for photodynamic therapy

An open three-compartment pharmacokinetic model was applied to the in vivo quantitative structure-activity relationship (QSAR) data of a homologous series of pyropheophorbide photosensitizers for photodynamic therapy (PDT). The physical model was a lipid compartment sandwiched between two identical aqueous compartments. The first compartment was assumed to clear irreversibly at a rate K0. The measured octanol-water partition coefficients, P(i) (where i is the number of carbons in the alkyl chain) and the clearance rate K0 determined the clearance kinetics of the drugs. Solving the coupled differential equations of the three-compartment model produced clearance kinetics for each of the sensitizers in each of the compartments. The third compartment was found to contain the target of PDT. This series of compounds is quite lipophilic. Therefore these drugs are found mainly in the second compartment. The drug level in the third compartment represents a small fraction of the tissue level and is thus not accessible to direct measurement by extraction. The second compartment of the model accurately predicted the clearance from the serum of mice of the hexyl ether of pyropheophorbide a, one member of this series of compounds. The diffusion and clearance rate constants were those found by fitting the pharmacokinetics of the third compartment to the QSAR data. This result validated the magnitude and mechanistic significance of the rate constants used to model the QSAR data. The PDT response to dose theory was applied to the kinetic behavior of the target compartment drug concentration. This produced a pharmacokinetic-based function connecting PDT response to dose as a function of time postinjection. This mechanistic dose-response function was fitted to published, single time point QSAR data for the pheophorbides. As a result, the PDT target threshold dose together with the predicted QSAR as a function of time postinjection was found.     

Synthesis of a dendritic estrogen cluster:A potential tool for studies of nuclear versus extranuclear pathways of estrogen actions

A novel estrogen dendrimer has been synthesized through a combination of divergent and convergent approaches in 9 practical steps and in good yields.It was characterized and confirmed by elemental analysis,FT-IR,MS,¹H NMR,¹³C NMR.The dendrimer contains 16 estrone units and is potentially a useful tool for the studies of estrogen actions.     

Systematic evaluation of structure-activity relationships of the riminophenazine class and discovery of a C2 pyridylamino series for the treatment of multidrug-resistant tuberculosis

Clofazimine, a member of the riminophenazine class of drugs, is the cornerstone agent for the treatment of leprosy. This agent is currently being studied in clinical trials for the treatment of multidrug-resistant tuberculosis to address the urgent need for new drugs that can overcome existing and emerging drug resistance. However, the use of clofazimine in tuberculosis treatment is hampered by its high lipophilicity and skin pigmentation side effects. To identify a new generation of riminophenazines that is less lipophilic and skin staining, while maintaining efficacy, we have performed a systematic structure-activity relationship (SAR) investigation by synthesizing a variety of analogs of clofazimine and evaluating their anti-tuberculosis activity. The study reveals that the central tricyclic phenazine system and the pendant aromatic rings are important for anti-tuberculosis activity. However, the phenyl groups attached to the C2 and N5 position of clofazimine can be replaced by a pyridyl group to provide analogs with improved physicochemical properties and pharmacokinetic characteristics. Replacement of the phenyl group attached to the C2 position by a pyridyl group has led to a promising new series of compounds with improved physicochemical properties, improved anti-tuberculosis potency, and reduced pigmentation potential.     

Accurate prediction of relative binding affinities of a series of HIV-1 protease inhibitors using semi-empirical quantum mechanical charge

A major challenge in computer-aided drug design is the accurate estimation of ligand binding affinity. Here, a new approach that combines the adaptive steered molecular dynamics (ASMD) and partial atomic charges calculated by semi-empirical quantum mechanics (SQMPC), namely ASMD-SQMPC, is suggested to predict the ligand binding affinities, with 24 HIV-1 protease inhibitors as testing examples. In the ASMD-SQMPC, the relative binding free energy (ΔG) is reflected by the average maximum potential of mean force (<PMF>_max) between bound and unbound states. The correlation coefficient (R²) between the <PMF>_max and experimentally determined ΔG is 0.86, showing a significant improvement compared with the conventional ASMD (R² = 0.52). Therefore, this study provides an efficient approach to predict the relative ΔG and reveals the significance of precise partial atomic charges in the theoretical simulations.     

Absolute and relative binding affinity of cucurbit[7]uril towards a series of cationic guests

We determined the relative binding constants (K_rel) for guests 1–19 towards cucurbit[7]uril by ¹H NMR competition experiments in 100 mM Na₃PO₄-buffered D₂O. In these experiments, we use guest 11 as the reference guest because of its strong binding towards CB[7] and its advantageous spectroscopic properties (e.g. slow exchange on NMR timescale and distinct resonances for key protons). To convert the determined K_rel values to absolute binding constants, we performed a direct UV–vis titration of 1 with CB[7] to determine K_a for CB[7]√1. The trends in the determined values of K_rel and K_a are discussed with respect to the importance of the concentration of metal ions in the buffer, the influence of hydroxyl groups located at the portals or inside the CB[7] cavity, geometry of the guest (e.g. regioisomers), the number of guest C atoms and secondary electrostatic interactions.     

Evaluation and application of multiple scoring functions for a virtual screening experiment

In order to identify novel chemical classes of factor Xa inhibitors, five scoring functions (FlexX, DOCK, GOLD, ChemScore and PMF) were engaged to evaluate the multiple docking poses generated by FlexX. The compound collection was composed of confirmed potent factor Xa inhibitors and a subset of the LeadQuest screening compound library. Except for PMF the other four scoring functions succeeded in reproducing the crystal complex (PDB code: 1FAX). During virtual screening the highest hit rate (80%) was demonstrated by FlexX at an energy cutoff of -40 kJ/mol, which is about 40-fold over random screening (2.06%). Limited results suggest that presenting more poses of a single molecule to the scoring functions could deteriorate their enrichment factors. A series of promising scaffolds with favorable binding scores was retrieved from LeadQuest. Consensus scoring by pair-wise intersection failed to enrich the hit rate yielded by single scorings (i.e. FlexX). We note that reported successes of consensus scoring in hit rate enrichment could be artificial because their comparisons were based on a selected subset of single scoring and a markedly reduced subset of double or triple scoring. The findings presented in this report are based upon a single biological system and support further studies.     

Integrating medicinal chemistry, organic/combinatorial chemistry, and computational chemistry for the discovery of selective estrogen receptor modulators with Forecaster, a novel platform for drug discovery

As part of a large medicinal chemistry program, we wish to develop novel selective estrogen receptor modulators (SERMs) as potential breast cancer treatments using a combination of experimental and computational approaches. However, one of the remaining difficulties nowadays is to fully integrate computational (i.e., virtual, theoretical) and medicinal (i.e., experimental, intuitive) chemistry to take advantage of the full potential of both. For this purpose, we have developed a Web-based platform, Forecaster, and a number of programs (e.g., Prepare, React, Select) with the aim of combining computational chemistry and medicinal chemistry expertise to facilitate drug discovery and development and more specifically to integrate synthesis into computer-aided drug design. In our quest for potent SERMs, this platform was used to build virtual combinatorial libraries, filter and extract a highly diverse library from the NCI database, and dock them to the estrogen receptor (ER), with all of these steps being fully automated by computational chemists for use by medicinal chemists. As a result, virtual screening of a diverse library seeded with active compounds followed by a search for analogs yielded an enrichment factor of 129, with 98% of the seeded active compounds recovered, while the screening of a designed virtual combinatorial library including known actives yielded an area under the receiver operating characteristic (AU-ROC) of 0.78. The lead optimization proved less successful, further demonstrating the challenge to simulate structure activity relationship studies.     

Structure‐property relationships for a series of amorphous partially aliphatic polyimides

High molecular weight, soluble, amorphous, partially aliphatic polyimides were successfully synthesized using an ester acid high‐temperature solution imidization route, which allows one to control desired glass‐transition (T_g) and processing temperatures. This method involves the prereaction of aromatic dianhydrides with ethanol and a tertiary amine catalyst to form ester acids, followed by the addition of diamines. Subsequent thermal reaction forms fully cyclized polyimides. This reaction pathway eliminates the need for anhydrous solvents and overcomes the problem of salt formation commonly observed for nucleophilic, more‐basic aliphatic amines when utilizing the traditional polyamic acid synthesis route. The molar ratio of aromatic‐to‐aliphatic diamines was varied to generate a series of copolyimides with the chosen dianhydride and tailor the physical properties for specific adhesive applications. This series of copolyimides was characterized by their molecular weight, T_g, thermal stability, coefficient of thermal expansion, refractive index, and dielectric constant. Structure‐property relationships were established. The γ and β sub‐T_g viscoelastic properties were researched to understand their molecular origins. © 2002 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 40: 1503–1512, 2002     

Quantitative structure activity relationship (QSAR) studies on a series of imidazole derivatives as novel ORL1 receptor antagonists

QSAR studies were performed on a series of imidazole derivatives as novel Orl1 receptor antagonists. Imidazole derivatives have been analyzed in relation to their physicochemical and molecular properties. The activities of the compounds were found to be significantly correlated with the physicochemical parameters such as density (D), surface tension (St), index of refraction (Ior), balaban index (J) and partition coefficient (Log P). It was found that the presence of group at R₁ position was conducive for the inhibitory activity. The results are critically discussed on the basis of regression data and cross validation techniques. Poglani factor Q and the results of LOO (leave one out) method confirms the reliability and predictability of the proposed models.