Synthesis and structure-activity relationship studies of CD4 down-modulating cyclotriazadisulfonamide (CADA) analogues

HIV attachment via the CD4 receptor is an important target for developing novel approaches to HIV chemotherapy. Cyclotriazadisulfonamide (CADA) inhibits HIV at submicromolar levels by specifically down-modulating cell-surface and intracellular CD4. An effective five-step synthesis of CADA in 30% overall yield is reported. This synthesis has also been modified to produce more than 50 analogues. Many tail-group analogues have been made by removing the benzyl tail of CADA and replacing it with various alkyl, acyl, alkoxycarbonyl and aminocarbonyl substituents. A series of sidearm analogues, including two unsymmetrical compounds, have also been prepared by modifying the CADA synthesis, replacing the toluenesulfonyl sidearms with other sulfonyl groups. Testing 30 of these compounds in MT-4 cells shows a wide range of CD4 down-modulation potency, which correlates with ability to inhibit HIV-1. Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were constructed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches. The X-ray crystal structures of four compounds, including CADA, show the same major conformation of the central 12-membered ring. The solid-state structure of CADA was energy minimized and used to generate the remaining 29 structures, which were similarly minimized and aligned to produce the 3D-QSAR models. Both models indicate that steric bulk of the tail group, and, to a lesser extent, the sidearms mainly determine CD4 down-modulation potency in this series of compounds.

Algorithmic statistical analysis of electrophysiological data for the investigation of structure-activity relationship in single neurons

We are developing computational tools supporting the detailed analysis of the dependence of neural electrophysiological response on dendritic morphology. We approach this problem by combining simulations of faithful models of neurons (experimental real life morphological data with known models of channel kinetics) with algorithmic extraction of morphological and physiological parameters and statistical analysis. In this paper, we present the novel method for an automatic recognition of spike trains in voltage traces, which eliminates the need for human intervention. This enables classification of waveforms with consistent criteria across all the analyzed traces and so it amounts to reduction of the noise in the data. This method allows for an automatic extraction of relevant physiological parameters necessary for further statistical analysis. In order to illustrate the usefulness of this procedure to analyze voltage traces, we characterized the influence of the somatic current injection level on several electrophysiological parameters in a set of modeled neurons. This application suggests that such an algorithmic processing of physiological data extracts parameters in a suitable form for further investigation of structure-activity relationship in single neurons.

Structure property relationships in electrically conducting copolymers formed from pyrrole and N-methyl pyrrole

A series of copolymers containing differing proportions of pyrrole and N-methyl pyrrole were prepared electrochemically at various temperatures using acetonitrile as the solvent. The resultant electrical conductivity decreases universally with increasing fraction of N-methyl pyrrole. Films prepared with p-toluene sulfonate as the dopant show a marked variation in structural anisotropy as revealed by X-ray scattering with apparent copolymer content. There is a clear trend between the variation in electrical conductivity and this structural anisotropy. Different patterns of behaviour are observed for films prepared using perchlorate as the dopant and this is attributed to the role of the dopant and final structure in determining the relative reactivities of the pyrrole and N-methyl pyrrole monomers. These observations support the concept that the introduction of methyl substituents into a polypyrrole chain results in a twisted chain conformation. The structure and properties of the resultant copolymer films are particularly sensitive to the preparation conditions.

Possible pre-dissociation of diorganotin dihalide complexes: relationship between antitumour activity and structure

An examination of crystallographic data has indicated that the structure/activity relationship for diorganotin dihalide complexes is different from that of other metal dihalides, in that the SnN bond lengths appear to determine the antitumour activity.

Joint multiple dictionary learning for tensor sparse coding

Traditional dictionary learning algorithms are used for finding a sparse representation on high dimensional data by transforming samples into a one-dimensional (1D) vector. This 1D model loses the inherent spatial structure property of data. An alternative solution is to employ Tensor Decomposition for dictionary learning on their original structural form —a tensor— by learning multiple dictionaries along each mode and the corresponding sparse representation in respect to the Kronecker product of these dictionaries. To learn tensor dictionaries along each mode, all the existing methods update each dictionary iteratively in an alternating manner. Because atoms from each mode dictionary jointly make contributions to the sparsity of tensor, existing works ignore atoms correlations between different mode dictionaries by treating each mode dictionary independently. In this paper, we propose a joint multiple dictionary learning method for tensor sparse coding, which explores atom correlations for sparse representation and updates multiple atoms from each mode dictionary simultaneously. In this algorithm, the Frequent-Pattern Tree (FP-tree) mining algorithm is employed to exploit frequent atom patterns in the sparse representation. Inspired by the idea of K-SVD, we develop a new dictionary update method that jointly updates elements in each pattern. Experimental results demonstrate our method outperforms other tensor based dictionary learning algorithms.

Novel synthesised flavone derivatives provide significant insight into the structural features required for enhanced anti-proliferative activity

With many cancers showing resistance to current chemotherapies, the search for novel anti-cancer agents is attracting considerable attention. Natural flavonoids have been identified as useful leads in such programmes. However, since an in-depth understanding of the structural requirements for optimum activity is generally lacking, further research is required before the full potential of flavonoids as anti-proliferative agents can be realised. Herein a broad library of 76 methoxy and hydroxy flavones, and their 4-thio analogues, was constructed and their structure-activity relationships for anti-proliferative activity against the breast cancer cell lines MCF-7 (ER+ve), MCF-7/DX (ER+ve, anthracycline resistant) and MDA-MB-231 (ER-ve) were probed. Within this library, 42 compounds were novel, and all compounds were afforded in good yields and > 95% purity. The most promising lead compounds, specifically the novel hydroxy 4-thioflavones 15f and 16f, were further evaluated for their anti-proliferative activities against a broader range of cancer cell lines by the National Cancer Institute (NCI), USA and displayed significant growth inhibition profiles (e.g Compound-15f: MCF-7 (GI50 = 0.18 μM), T-47D (GI50 = 0.03 μM) and MDA-MB-468 (GI50 = 0.47 μM) and compound-16f: MCF-7 (GI50 = 1.46 μM), T-47D (GI50 = 1.27 μM) and MDA-MB-231 (GI50 = 1.81 μM). Overall, 15f and 16f exhibited 7-46 fold greater anti-proliferative potency than the natural flavone chrysin (2d). A systematic structure-activity relationship study against the breast cancer cell lines highlighted that free hydroxyl groups and the B-ring phenyl groups were essential for enhanced anti-proliferative activities. Substitution of the 4-C=O functionality with a 4-C=S functionality, and incorporation of electron withdrawing groups at C4’ of the B-ring phenyl, also enhanced activity. Molecular docking and mechanistic studies suggest that the anti-proliferative effects of flavones 15f and 16f are mediated via ER-independent cleavage of PARP and downregulation of GSK-3β for MCF-7 and MCF-7/DX cell lines. For the MDA-MB-231 cell line, restoration of the wild-type p53 DNA binding activity of mutant p53 tumour suppressor gene was indicated.

Lease maturity and initial rent: is there a term structure for UK commercial property leases?

This paper investigates the relationship between lease maturity and rent in commercial property. Over the last decade market-led changes to lease structures, the threat of government intervention and the associated emergence of the Codes of Practice for commercial leases have stimulated growing interest in pricing of commercial property leases. Seminal work by Grenadier (1995) derived a set of hypotheses about the pricing of different lease lengths in different market conditions. Whilst there is a compelling theoretical case for and a strong intuitive expectation of differential pricing of different lease maturities, to date the empirical evidence is inconclusive. Two Swedish studies have found mixed results (Gunnelin and Soderbergh 2003 and Englund et al 2003). In only half the cases is the null hypothesis that lease length has no effect rejected. In the UK, Crosby et al (2003) report counterintuitive results. In some markets, they find that short lease terms are associated with low rents, whilst in others they are associated with high rents. Drawing upon a substantial database of commercial lettings in central London (West End and City of London) over the last decade, we investigate the relationship between rent and lease maturity. In particular, we test whether a building quality variable omitted in previous studies provides empirical results that are more consistent with the theoretical and intuitive a priori expectations. It is found that initial leases rates are upward sloping with the lease term and that this relationship is constant over time.

Synthesis, crystal structure, magnetic behavior and thermal property of three polynuclear complexes: [M(dca)(2)(H2O)2](n)center dot(hmt)(n) [M = Mn(II), Co(II)] and [Co(dca)(2)(bpds)](n) [dca, dicyanamide; hint, hexamethylenetetramine; bpds, 4,4 '-bipyridyl disulfide]

Three mu(1.5)-dicyanamide bridged Mn(II) and Co(II) complexes having molecular formula [Mn(dca)(2)(H2O)(2)](n)center dot(hmt)(n) (1), [Co(dca)(2) (H2O)(2)](n)center dot(hmt)(n) (2) and [Co(dca)(2)(bpds)](n) (3) [dca = dicyanamide; hmt = hexamethylenetetramine; bpds = 4,4'-bipyridyl disulfide] have been synthesized and characterized by single crystal X-ray diffraction study, low temperature (300-2 K) magnetic measurement and thermal behavior. The X-ray diffraction analysis of 1 and 2 reveals that they are isostructural, comprising of 1D coordination polymers [M(dca)(2)(H2O)(2)](n) [M = Mn(II), Co(II) for 1 and 2. respectively] with uncoordinated hmt molecules located among the chains. The [M(dca)(2)(H2O)(2)](n) chains and the lattice hint molecules are connected through H-bonds resulting in a 3D supramolecular architecture. The octahedral N4O2 chromophore surrounding the metal ion forms via two trans located water oxygens and four nitrogens from four nitrile dca. Complex 3 is a 1D chain formed by two mu(1.5)-dca and one bridging bpds. The octahedral N-6 coordination sphere surrounding the cobalt ions comprises four nitrogens from dca and two from bpds. Low temperature magnetic study indicates small antiferromagnetic coupling for all the complexes. Best fit parameters for 1: J = -0.17 cm(-1), g = -2.03 with R = 6.1 x 10(-4), for 2, J = -0.50 cm(-1), and for 3, J = -0.95 cm(-1). (c) 2005 Elsevier B.V. All rights reserved.

Asset allocation, cross-class correlation and the structure of property returns

Practical applications of portfolio optimisation tend to proceed on a “top down” basis where funds are allocated first at asset class level (between, say, bonds, cash, equities and real estate) and then, progressively, at sub-class level (within property to sectors, office, retail, industrial for example). While there are organisational benefits from such an approach, it can potentially lead to sub-optimal allocations when compared to a “global” or “side-by-side” optimisation. This will occur where there are correlations between sub-classes across the asset divide that are masked in aggregation – between, for instance, City offices and the performance of financial services stocks. This paper explores such sub-class linkages using UK monthly stock and property data. Exploratory analysis using clustering procedures and factor analysis suggests that property performance and equity performance are distinctive: there is little persuasive evidence of contemporaneous or lagged sub-class linkages. Formal tests of the equivalence of optimised portfolios using top-down and global approaches failed to demonstrate significant differences, whether or not allocations were constrained. While the results may be a function of measurement of market returns, it is those returns that are used to assess fund performance. Accordingly, the treatment of real estate as a distinct asset class with diversification potential seems justified.

The relationship between diffuse spectral reflectance of the soil and its cation exchange capacity is scale-dependent

Diffuse reflectance spectroscopy (DRS) is increasingly being used to predict numerous soil physical, chemical and biochemical properties. However, soil properties and processes vary at different scales and, as a result, relationships between soil properties often depend on scale. In this paper we report on how the relationship between one such property, cation exchange capacity (CEC), and the DRS of the soil depends on spatial scale. We show this by means of a nested analysis of covariance of soils sampled on a balanced nested design in a 16 km × 16 km area in eastern England. We used principal components analysis on the DRS to obtain a reduced number of variables while retaining key variation. The first principal component accounted for 99.8% of the total variance, the second for 0.14%. Nested analysis of the variation in the CEC and the two principal components showed that the substantial variance components are at the > 2000-m scale. This is probably the result of differences in soil composition due to parent material. We then developed a model to predict CEC from the DRS and used partial least squares (PLS) regression do to so. Leave-one-out cross-validation results suggested a reasonable predictive capability (R2 = 0.71 and RMSE = 0.048 molc kg− 1). However, the results from the independent validation were not as good, with R2 = 0.27, RMSE = 0.056 molc kg− 1 and an overall correlation of 0.52. This would indicate that DRS may not be useful for predictions of CEC. When we applied the analysis of covariance between predicted and observed we found significant scale-dependent correlations at scales of 50 and 500 m (0.82 and 0.73 respectively). DRS measurements can therefore be useful to predict CEC if predictions are required, for example, at the field scale (50 m). This study illustrates that the relationship between DRS and soil properties is scale-dependent and that this scale dependency has important consequences for prediction of soil properties from DRS data