Producing 13C NMR, infrared absorption, and electron ionization mass spectrometric data models of the monodechlorination of chlorobenzenes, chlorophenols, and chloroanilines

We have developed four spectroscopic data-activity relationship (SDAR) models of monodechlorination of 32 chlorinated benzene compounds in anaerobic estuarine sediment. The SDAR models were based on combinations of 13C nuclear magnetic resonance (NMR), infrared absorption (IR), and electron ionization mass spectrometric (EI MS) data. The SDAR models segregated the 32 compounds into 17 readily monodechlorinated compounds and 15 not readily monodechlorinated compounds. The SDAR model based on 13C NMR, IR, and EI MS data gave a leave-one-out cross-validation of 93.8%. The SDAR model based on a composite of 13C NMR and IR data gave a leave-one-out cross-validation of 90.6%. The SDAR model based on a composite of IR and EI MS data gave a leave-one-out cross-validation of 84.4%. The SDAR model based on a composite of 13C NMR and EI MS data gave a leave-one-out cross-validation of 84.4%. These reliable SDAR models provide a rapid and simple way to predict whether a chlorinated benzene compound will readily go through monodechlorination. The FDA has filed a patent application on methods of using any combination of spectral data (NMR, MS, UV-vis, IR, and fluorescence, phosphorescence) to model a chemical, physical, or biological endpoint.     

Anti-estrogenic activity of mansorins and mansonones from the heartwood of Mansonia gagei DRUMM

Through an anti-estrogenic bioassay-guided fractionation of the methanol extract of Mansonia gagei, three new coumarins, called mansorins I (1), II (2) and III (3) and a new naphthoquinone, mansonone I (4), were isolated. Their structures were determined based on their NMR data and CD spectroscopy. The anti-estrogenic activity of the fractions and the isolated compounds were investigated using a yeast two-hybrid assay method expressing estrogen receptors alpha (ERalpha) and beta (ERbeta). In addition, an ERalpha competitor screening system (ligand binding screen) was used to verify the binding affinities of the isolated compounds to the estrogen receptor. 1,2-Naphthoquinones (mansonones) showed more binding affinities to ER in both assay systems. All the tested compounds showed higher binding affinities to ERbeta than to ERalpha in the yeast two-hybrid assay. Mansonones F and S showed the most potent estrogen binding and estrogen antagonistic effects.     

Binary quantitative structure-activity relationship (QSAR) analysis of estrogen receptor ligands

The use of high throughput screening (HTS) to identify lead compounds has greatly challenged conventional quantitative structure-activity relationship (QSAR) techniques that typically correlate structural variations in similar compounds with continuous changes in biological activity. A new QSAR-like methodology that can correlate less quantitative assay data (i.e., "active" versus "inactive"), as initially generated by HTS, has been introduced. In the present study, we have, for the first time, applied this approach to a drug discovery problem; that is, the study of the estrogen receptor ligands. The binding affinities of 463 estrogen analogues were transformed into a binary data format, and a predictive binary QSAR model was derived using 410 estrogen analogues as a training set. The model was applied to predict the activity of 53 estrogen analogues not included in the training set. An overall accuracy of 94% was obtained.     

Conformational studies on (17alpha,20Z)-21-(X-Phenyl)-19-norpregna-1, 3,5(10),20-tetraene-3,17beta-diols using 1D and 2D NMR spectroscopy and GIAO calculations of (13)C shieldings

Differences in agonist responses of the novel estrogen receptor ligands (17alpha,20Z)-(p-methoxyphenyl)vinyl estradiol (1), (17alpha, 20Z)-(o-alpha,alpha,alpha-trifluoromethylphenyl)vinyl estradiol (2), and (17alpha,20Z)-(o-hydroxymethylphenyl)vinyl estradiol (3) led us to investigate their solution conformation. In competitive binding assay studies, we observed that several phenyl-substituted (17alpha, 20E/Z)-(X-phenyl)vinyl estradiols exhibited significant estrogen receptor binding, but with variation (RBA (1) = 20; RBA (2) = 23; RBA (3) = 140 where estradiol RBA = 100) depending on the phenyl substitution pattern. Because the 17alpha-phenylvinyl substituent interacts with the key helix-12 of the ligand binding domain, we considered that differences in the preferred conformation of 1-3 could account for their varying binding affinity. 2D NMR experiments at 500 MHz allowed the complete assignment of the (13)C and (1)H spectra of 1-3. The conformations of these compounds in solution were established by 2D and 1D NOESY spectroscopy. A statistical approach of evaluating contributing conformers of 1-3 from predicted (13)C shifts correlated quite well with the NOE data. The 17alpha substituents of 1 and 2 exist in similar conformational equilibria with some differences in relative populations of conformers. In contrast, the 17alpha substituent of 3 exists in a different conformational equilibrium. The similarity in solution conformations of 1 and 2 suggests they occupy a similar receptor volume, consistent with similar RBA values of 20 and 23. Conversely, the different conformational equilibria of 3 may contribute to the significant binding affinity (RBA = 140) of this ligand.     

Conformational studies of novel estrogen receptor ligands by 1D and 2D NMR spectroscopy and computational methods

The solution conformations of the novel estrogen receptor ligands (17α,20E)‐(p‐trifluoromethylphenyl)vinylestradiol ( 1 ) and (17α,20E)‐(o‐trifluoromethylphenyl)vinylestradiol ( 2 ) were investigated in 2D and 1D NOESY studies and by comparison of ¹³C NMR chemical shifts with theoretical shieldings. The ¹H and ¹³C assignments of 1 and 2 were determined by DEPT, COSY and HMQC experiments. The conformations of the 17α‐phenylvinyl substituents of 1 and 2 are of interest because of their differing receptor binding affinities and effects in in vivo uterotrophic growth assays. A statistical method of evaluating contributing conformers of 1 and 2 from predicted ¹³C shifts of possible structures correlated fairly well with conformational conclusions derived from the NOE data. The 17α substituents of 1 and 2 apparently exist in similar conformational equilibria, suggesting that while 1 and 2 would occupy a similar receptor volume, interactions with the protein may shift the equilibrium and thereby influence the expression of the ligand. Copyright © 2003 John Wiley & Sons, Ltd.     

Towards a rational spacer design for bivalent inhibition of estrogen receptor

Estrogen receptors are known drug targets that have been linked to several kinds of cancer. The structure of the estrogen receptor ligand binding domain is available and reveals a homodimeric layout. In order to improve the binding affinity of known estrogen receptor inhibitors, bivalent compounds have been developed that consist of two individual ligands linked by flexible tethers serving as spacers. So far, binding affinities of the bivalent compounds do not surpass their monovalent counterparts. In this article, we focus our attention on the molecular spacers that are used to connect the individual ligands to form bivalent compounds, and describe their thermodynamic contribution during the ligand binding process. We use computational methods to predict structural and entropic parameters of different spacer structures. We find that flexible spacers introduce a number of effects that may interfere with ligand binding and possibly can be connected to the low binding affinities that have been reported in binding assays. Based on these findings, we try to provide guidelines for the design of novel molecular spacers.     

胰蛋白酶和苯酰氨类抑制剂结合自由能的预测

用基于线性响应近似的自由能预测方法计算胰蛋白酶和苯酰氨类抑制剂的结合 自由能。计算结果表明,单参数,双参数和三参数模型具有相似的线性回归系数, 但三参数和双参数模型的交互验证回归系数要明显优于单参数模型。从预测能力来 看,双参数模型和三参数模型都能够很好地预测测试集中抑制剂的结合自由能,其 中双参数模型预测的结果要略优于三参数模型的预测结果。对测试集中的抑制剂, 双参数模型预测得到的预测自由能和实际自由能之间平均绝对误差仅为1.15 kJ/mol。自由能计算模型以及分子动力学轨迹能很好地解释抑制剂结构和活性的 关系,为药物设计提供了重要的结构信息。     

(13)C NMR quantitative spectrometric data-activity relationship (QSDAR) models of steroids binding the aromatase enzyme

Five quantitative spectroscopic data-activity relationships (QSDAR) models for 50 steroidal inhibitors binding to aromatase enzyme have been developed based on simulated (13)C nuclear magnetic resonance (NMR) data. Three of the models were based on comparative spectral analysis (CoSA), and the two other models were based on comparative structurally assigned spectral analysis (CoSASA). A CoSA QSDAR model based on five principal components had an explained variance (r(2)) of 0.78 and a leave-one-out (LOO) cross-validated variance (q(2)) of 0.71. A CoSASA model that used the assigned (13)C NMR chemical shifts from a steroidal backbone at five selected positions gave an r(2) of 0.75 and a q(2) of 0.66. The (13)C NMR chemical shifts from atoms in the steroid template position 9, 6, 3, and 7 each had correlations greater than 0.6 with the relative binding activity to the aromatase enzyme. All five QSDAR models had explained and cross-validated variances that were better than the explained and cross-validated variances from a five structural parameter quantitative structure-activity relationship (QSAR) model of the same compounds. QSAR modeling suffers from errors introduced by the assumptions and approximations used in partial charges, dielectric constants, and the molecular alignment process of one structural conformation. One postulated reason that the variances of QSDAR models are better than the QSAR models is that (13)C NMR spectral data, based on quantum mechanical principles, are more reflective of binding than the QSAR model's calculated electrostatic potentials and molecular alignment process. The QSDAR models provide a rapid, simple way to model the steroid inhibitor activity in relation to the aromatase enzyme.     

Ultrafiltration tandem mass spectrometry of estrogens for characterization of structure and affinity for human estrogen receptors

Although hormone replacement therapy (HRT) is used by post-menopausal women for the relief of menopausal symptoms and the potential reduction of osteoporosis, HRT also increases their risk of Alzheimer's disease, stroke, breast cancer, and endometrial cancer. Since the majority of these effects are associated primarily with estrogen binding to only one of the estrogen receptors (ER), new assays are needed that can more efficiently evaluate ER-binding and identify ligands selective for ER-alpha and ER-beta. High performance liquid chromatography-tandem mass spectrometry (LC-MS-MS) was combined with ultrafiltration as a new method to investigate the relative binding of compounds to the ERs and to evaluate the structures of these estrogens. Mixtures of estradiol and six equine estrogens, including equilin, equilenin, 8,9-dehydroestrone, and their 17beta-hydroxyl derivatives, were assayed simultaneously to determine their relative binding to human ER-alpha and ER-beta. Estrogens containing a 17beta-OH group were found to have higher relative affinities for the estrogen receptors than their ketone analogs. In addition, 17beta-EN showed selectivity for binding to ER-beta over ER-alpha. The results were compared to the IC50 values obtained by using a conventional radiolabled estradiol competitive binding assay. Finally, the utility of negative ion electrospray tandem mass spectrometry for the unambiguous identification of these estrogen isomers was investigated. Several characteristic recyclization pathways during tandem mass spectrometry were identified, which might be useful for distinguishing related estrogens.     

Design and Synthesis of Novel Nonsteroidal Phytoestrogen‐based Probes as Potential Biomarker: Evaluation of Anticancer Activity and Docking Studies

Two series of novel flavones and flavone‐tanaproget conjugates were designed, synthesized, ¹²⁵I­radiolabeled, and evaluated for their antiproliferative activity against human cancer cell lines (MCF‐7, MDA‐MB‐231, and HeLa). They exhibited good‐to‐excellent in vitro antiproliferative activity. For improving the receptor‐binding affinity of synthesized compounds, flavone‐tanaproget moieties were linked together through alkyl‐alkenyl chain spacer, and the butyl chain was substituted at C‐3 position of oxa‐ and aza‐flavones to enhance the lypophilicity of the molecule. These compounds are hypothesized to bind with estrogen and progesterone receptors by docking studies, and binding affinities were shown to increase significantly compared with the reference ligands.     

Simple method for identification of skeletons of aporphine alkaloids from 13C NMR data using artificial neural networks

This paper describes the use of artificial neural networks as a theoretical tool in the structural determination of alkaloids from (13)C NMR chemical shift data, aiming to identify skeletal types of those compounds. For that, 162 aporphine alkaloids belonging to 12 different skeletons were codified with their respective (13)C NMR chemical shifts. Each skeleton pertaining to aporphine alkaloid type was used as output, and the (13)C NMR chemical shifts were used as input data of the net. Analyzing the obtained results, one can then affirm the skeleton to which each one of these compounds belongs with high degree of confidence (over 97%). The relation between the correlation coefficient and the number of epochs and the architecture of net (3-layer MLP or 4-layer MLP) were analyzed, too. The analysis showed that the results predicted by the 3-layer MLP networks trained with a number of the epochs higher than 900 epochs are the best ones. The artificial neural nets were shown to be a simple and efficient tool to solve structural elucidation problems making use of (13)C NMR chemical shift data, even when a similarity between the searched skeletons occurs, offering fast and accurate results to identification of skeletons of organic compounds.     

1H and 13C NMR spectra, structure and physicochemical features of phenyl acridine-9-carboxylates and 10-methyl-9-(phenoxycarbonyl)acridinium trifluoromethanesulphonates--alkyl substituted in the phenyl fragment

The 1H and 13C NMR spectra of twelve phenyl acridine-9-carboxylates--alkyl-substituted in the phenyl fragment--and their 10-methyl-9-(phenoxycarbonyl)acridinium salts dissolved in CD3CN, CD3OD, CDCl3 and DMSO-d6 were recorded in order to examine the influence of the structure of these compounds and the properties of the solvents on chemical shifts and 1H-(1)H coupling constants. Experimental data were compared with 1H and 13C chemical shifts predicted at the GIAO/DFT level of theory for DFT(B3LYP)/6-31G** optimised geometries of molecules, as well as with values of 1H chemical shifts and 1H-(1)H coupling constants, estimated using ACD/HNMR database software to ensure that the assignment was correct. To investigate the relations between chemical shifts and selected structural or physicochemical characteristics of the target compounds, the values of several of these parameters were determined at the DFT or HF levels of theory. The HOMO and LUMO energies obtained at the HF level yielded the ionisation potentials and electron affinities of molecules. The DFT method provided atomic partial charges, dipole moments, LCAO coefficients of pz LUMO of selected C atoms, and angles reflecting characteristic structural features of the compounds. It was found that the experimentally determined 1H and 13C chemical shifts of certain atoms relate to the predicted dipole moments, the angles between the acridine and phenyl moieties, and the LCAO coefficients of the pz LUMO of the C atoms believed to participate in the initial step of the oxidation of the target compounds. The spectral and physicochemical characteristics of the target compounds were investigated in the context of their chemiluminogenic ability.     

Estrogen-derived steroidal metal complexes: agents for cellular delivery of metal centers to estrogen receptor-positive cells

Targeted cellular delivery of drugs to specific tissues is an important goal in biomedical chemistry. Achieving this requires harnessing and applying molecular-level recognition events prevalent in (or specific to) the desired tissue type. Tissues rich in estrogen receptors (ERs), which include many types of breast cancer, accumulate molecules that have high binding affinities for these receptors. Therefore, molecules that (i) bind to the ER, (ii) have favorable cellular transport properties, and (iii) contain a second functionality (such as a center that may be used for diagnostic imaging or medical therapy) are exciting synthetic targets in the field of drug delivery. To this end, we have prepared a range of metallo-estrogens based on 17alpha-ethynylestradiol and examined their binding to the ER both as isolated receptor and in whole cell assays (ER positive MCF-7 cells). Estrogens functionalized with metal binding units are prepared by palladium-catalyzed cross-coupling reactions and a wide range of metal centers introduced readily. All the compounds prepared and tested exhibit effective binding to the estrogen receptor and are delivered across the cell membrane into MCF-7 cells. In the whole cell assays, despite their monocationic nature, the palladium and platinum complexes prepared exhibit similar (and even enhanced) receptor binding affinities compared to their corresponding neutral free ligands. It is unprecedented for a higher ER binding affinity to be observed for a cationic complex than for its metal-free ligand.     

Protein-ligand NOE matching: a high-throughput method for binding pose evaluation that does not require protein NMR resonance assignments

Given the three-dimensional (3D) structure of a protein, the binding pose of a ligand can be determined using distance restraints derived from assigned intra-ligand and protein-ligand nuclear Overhauser effects (NOEs). A primary limitation of this approach is the need for resonance assignments of the ligand-bound protein. We have developed an approach that utilizes data from 3D 13C-edited, 13C/15N-filtered HSQC-NOESY spectra for evaluating ligand binding poses without requiring protein NMR resonance assignments. Only the 1H NMR assignments of the bound ligand are essential. Trial ligand binding poses are generated by any suitable method (e.g., computational docking). For each trial binding pose, the 3D 13C-edited, 13C/15N-filtered HSQC-NOESY spectrum is predicted, and the predicted and observed patterns of protein-ligand NOEs are matched and scored using a fast, deterministic bipartite graph matching algorithm. The best scoring (lowest "cost") poses are identified. Our method can incorporate any explicit restraints or protein assignment data that are available, and many extensions of the basic procedure are feasible. Only a single sample is required, and the method can be applied to both slowly and rapidly exchanging ligands. The method was applied to three test cases: one complex involving muscle fatty acid-binding protein (mFABP) and two complexes involving the leukocyte function-associated antigen 1 (LFA-1) I-domain. Without using experimental protein NMR assignments, the method identified the known binding poses with good accuracy. The addition of experimental protein NMR assignments improves the results. Our "NOE matching" approach is expected to be widely applicable; i.e., it does not appear to depend on a fortuitous distribution of binding pocket residues.     

双酰腙钳形受体分子的合成及阴离子识别研究

在微波辐射下快速、高产率地合成了一系列含有四唑环的双酰腙受体,并对其进行了元素分析、红外以及核磁共振氢谱和碳谱表征.利用紫外-可见吸收光谱及1HNMR考察了其与F-,Cl-,Br-和I-卤素阴离子的相互作用.紫外滴定实验表明4a较4b,4c对F-有更好的识别作用.Job曲线表明,主体4a与F-间形成1∶1型氢键络合物.通过1HNMR滴定及质子溶剂效应进一步证明了该受体分子与阴离子以氢键作用相结合.     

Exploring the active site of human factor Xa protein by NMR screening of small molecule probes

A collection of small molecules (MW < 350 Da) was screened for binding to human factor Xa using saturation transfer difference NMR spectroscopy to detect binding. The NMR screening experiments identified four hits. Binding isotherms constructed from NMR linewidth data showed that the binding affinities of the hits were all in the 30-210 microM range. Competition binding experiments showed that three of the ligands were displaced by a known microM inhibitor of factor Xa. The success of the method for identifying new ligands and the relevance of this information to the design of new factor Xa inhibitors are discussed.     

Halogen effect on structure and 13C NMR chemical shift of 3,6‐disubstituted‐N‐alkyl carbazoles

Structures of selected 3,6‐dihalogeno‐N‐alkyl carbazole derivatives were calculated at the B3LYP/6‐311++G(3df,2pd) level of theory, and their ¹³C nuclear magnetic resonance (NMR) isotropic shieldings were predicted using density functional theory (DFT). The model compounds contained 9H, N‐methyl and N‐ethyl derivatives. The relativistic effect of Br and I atoms on nuclear shieldings was modeled using the spin–orbit zeroth‐order regular approximation (ZORA) method. Significant heavy atom shielding effects for the carbon atom directly bonded with Br and I were observed (~?10 and ~?30 ppm while the other carbon shifts were practically unaffected). The decreasing electronegativity of the halogen substituent (F, Cl, Br, and I) was reflected in both nonrelativistic and relativistic NMR results as decreased values of chemical shifts of carbon atoms attached to halogen (C3 and C6) leading to a strong sensitivity to halogen atom type at 3 and 6 positions of the carbazole ring. The predicted NMR data correctly reproduce the available experimental data for unsubstituted N‐alkylcarbazoles. Copyright © 2013 John Wiley & Sons, Ltd.     

X-ray photoelectron spectra and structure of 2-(2-phenylhydrazono) acetoacetanilide

2-(2-Phenylhydrazono)acetoacetanilide, itsN-methyl derivatives, and model compounds were studied by X-ray photoelectron spectroscopy. The chemical shifts were obtained from the¹³C NMR spectra. A correlation between the calculated charges, the binding energies on N atoms, and the¹³C NMR chemical shifts was found. The analysis of the XPS data and the¹³C NMR chemical shifts led to the conclusion that crystalline 2-(2-phenylhydrazono)acetoacetanilide exists mainly in the oxo hydrazone form. Translated fromIzvestiya Akademii Nauk. Seriya Khimicheskaya, No. 3, pp. 488–491, March, 1999.