Synthesis of new mono and bis amides projected as potential histone deacetylase (HDAC) inhibitors

In our ongoing efforts to discover new potent histone deacetylase (HDAC) inhibitors as promising anticancer candidates, we designed and synthesized a small collection of 3-substituted amines possessing macro heterocyclic skeletons bearing variable-length tails. As a metal binder domain, all the compounds possess an amide function suitable for Zn²⁺ chelation in the enzyme active site. A combination of solution and solid phase techniques were employed to synthesize the compounds and, as the key synthetic step to obtain the rings, a ring closing metathesis (RCM) reaction was adopted. The putative affinity of the compounds for the histone deacetylase-like protein (HDLP) model receptor active site was explored through docking calculations, and we also report preliminary studies on their pharmacological properties.     

Proteomic profiling of human colon cancer cells treated with the histone deacetylase inhibitor belinostat

The anticancer drug belinostat is a hydroxamate histone deacetylase inhibitor that has shown significant antitumour activity in various tumour models and also in clinical trials. In this study, we utilized a proteomic approach in order to evaluate the effect of this drug on protein expression in the human colon cancer cell line HCT116. Protein extracts from untreated HCT116 cells, and cells grown for 24 h in the presence of 1 and 10 μM belinostat were analysed by 2‐D gel electrophoresis. Proteins were visualized by colloidal Coomassie blue staining and quantitative analysis of gel images revealed 45 unique differentially expressed proteins that were identified by LC‐MSMS analysis. Among these proteins, of particular interest are the downregulated proteins nucleophosmin and stratifin, and the upregulated proteins nucleolin, gelsolin, heterogeneous nuclear ribonucleoprotein K, annexin 1, and HSP90B that all were related to the proto‐oncogene proteins p53, Myc, activator protein 1, and c‐fos protein. The modulation of these proteins is consistent with the observations that belinostat is able to inhibit clonogenic cell growth of HCT116 cells and the biological role of these proteins will be discussed.     

3D-QSAR and molecular modeling of HIV-1 integrase inhibitors

Three-dimensional quantitative structure-activity relationship (3D QSAR) methods were applied on a series of inhibitors of HIV-1 integrase with respect to their inhibition of 3-processing and 3-end joining steps in vitro.The training set consisted of 27 compounds belonging to the class of thiazolothiazepines. The predictive ability of each model was evaluated using test set I consisting of four thiazolothiazepines and test set II comprised of seven compounds belonging to an entirely different structural class of coumarins. Maximum Common Substructure (MCS) based method was used to align the molecules and this was compared with other known methods of alignment. Two methods of 3D QSAR: comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were analyzed in terms of their predictive abilities. CoMSIA produced significantly better results for all correlations. The results indicate a strong correlation between the inhibitory activity of these compounds and the steric and electrostatic fields around them. CoMSIA models with considerable internal as well as external predictive ability were obtained. A poor correlation obtained with hydrophobic field indicates that the binding of thiazolothiazepines to HIV-1 integrase is mainly enthalpic in nature. Further the most active compound of the series was docked into the active site using the crystal structure of integrase. The binding site was formed by the amino acid residues 64-67, 116, 148, 151-152, 155-156, and 159. The comparison of coefficient contour maps with the steric and electrostatic properties of the receptor shows high level of compatibility.     

从药物的三维分子结构预测人体小肠吸收

在口服药物的发展过程中，人体小肠吸收的预测是候选药物设计、优化和选择的一个主要目标.VolSurf/GRID计算方法作为一个新的工具被用来预测被测化合物的人体小肠吸收，以及测定人体小肠吸收所必需的重要的分子特征.被测化合物包括112个结构不同的类似药物的化合物.使用偏最小二乘判别分析方法在实验数据和人体小肠吸收的理论分子特征之间建立相关性.建立的两个模型之间具有较高的一致性.小肠吸收实验数据与分子特征之间好的相关性（r2=0.82, q2=0.67）表明,从化合物的三维分子结构能够预测人体小肠吸收.有利于人体小肠吸收的药物分子特征包括,分子量中心与亲水区重心的不平衡性，较大的疏水区域以及分子内较少的氢键给体.     

A Sensitive Electrochemical Biosensor for Detection of Histone Deacetylase Activity Using an Acetylated Peptide

A sensitive electrochemical biosensor was developed for activity detection of histone deacetylase sirtuin2 (SIRT2) using an acetylated peptide substrate. This substrate could be recognized by anti‐acetylated peptide antibody, which could be detected using secondary antibody conjugated alkaline phosphatase which provided an amplified electrochemical signal. In the presence of SIRT2, the substrate was deacetylated, resulting in a decreased electrochemical signal that was correlated to the concentration of SIRT2. Under optimized conditions, the biosensor exhibited a wide linear range from 1 nM to 500 nM with a detection limit of 0.1 nM. The proposed biosensor was also used for detection of SIRT2 inhibitor.     

Homology modeling,force field design,and free energy simulation studies to optimize the activities of histone deacetylase inhibitors

As an effort to develop therapeutics for cancer treatments, a number of effective histone deacetylase inhibitors with structural diversity have been discovered. To gain insight into optimizing the activity of an identified lead compound, a computational protocol sequentially involving homology modeling, docking experiments, molecular dynamics simulation, and free energy perturbation calculations was applied for rationalizing the relative activities of known histone deacetylase inhibitors. With the newly developed force field parameters for the coordination environment of the catalytic zinc ion in hand, the computational strategy proved to be successful in predicting the rank orders for 12 derivatives of three hydroxamate-based inhibitor scaffolds with indole amide, pyrrole, and sulfonamide moieties. The results showed that the free energy of an inhibitor in aqueous solution should be an important factor in determining the binding free energy. Hence, in order to enhance the inhibitory activity by adding or substituting a chemical group, the increased stabilization in solution due to the structural changes must be overcome by a stronger enzyme-inhibitor interaction. It was also found that to optimize inhibitor potency, the hydrophobic head of an inhibitor should be elongated or enlarged so that it can interact with Pro29 and His28 that are components of the flexible loop at the top of the active site.     

酪氨酸激酶抑制剂的比较分子场分析

采用比较分子场分析(CoMFA)方法研究了一组嘧啶类衍生物酪氨酸激酶抑制剂活性与结构的关系.所得模型不仅能够很好地预报训练集中的化合物的活性,而且还可以准确地预报预报集中的化合物活性.通过分析分子场等值面图在空间的分布,可以观察到叠加分子周围的立体和静电特征对化合物活性的影响.     

比较分子场分析方法研究的最新进展*

比较分子场分析方法(CoM FA ) 是目前在三维定量构效关系(3D2Q SAR) 中应用最为广泛的方法之一。但传统的比较分子场分析方法在具体的实现过程中还存在着一些缺陷和不足, 包括分子场势能函数的选择, 活性构象的确定, 分子的叠合以及分子场变量的选取等等。本文结合我们科研组的工作, 就近几年CoM FA 方法的最新进展做了较为详细的阐述, 同时对CoM FA 的发展前景及其在药物设计中的应用进行了展望。     

非肽类凝血酶抑制剂的比较分子力场分析

在血栓症和止血疗法中凝血酶起重要的生物调节作用，凝血酶抑制剂由于基溶 血栓作用成为药物设计的热点，对非肽类芳基磺酸酯系列凝血酶抑制剂进行了三维 定量构效关系研究。用Autodock方法和比较分子力场分析相结合构建了该类分子的 定量构效关系模型，得到三维等值线图。模型的传统相关系数r~2=0.956，交叉验 证系数q~2=0.681, F_(4,16) = 85.985，标准偏差S = 0.158。该模型为凝血酶抑 制剂的进一步结构改造提供了有益的启示。     

Pharmacophore identification by molecular modeling and chemometrics: The case of HMG-CoA reductase inhibitors

Summary A methodology based on molecular modeling and chemometrics is applied to identify the geometrical pharmacophore and the stereoelectronic requirements for the activity in a series of inhibitors of 3-hydroxy 3-methylglutaryl coenzyme A (HMG-CoA) reductase, an enzyme involved in cholesterol biosynthesis. These inhibitors present two common structural features—a 3,5-dihydroxy heptanoic acid which mimics the active portion of the natural substrate HMG-CoA and a lipophilic region which carries both polar and bulky groups. A total of 432 minimum energy conformations of 11 homologous compounds showing different levels of biological activity are calculated by the molecular mechanics MM2 method. Five atoms are selected as representatives of the relevant fragments of these compounds and three interatomic distances, selected among 10 by means of a Principal Component Analysis (PCA), are used to describe the three-dimensional disposition of these atoms. A cluster analysis procedure, performed on the whole set of conformations described by these three distances, allows the selection of one cluster whose centroid represents a geometrical model for the HMG-CoA reductase pharmacophore and the conformations included are candidates as binding conformations. To obtain a refinement of the geometrical model and to have a better insight into the requirements for the activity of these inhibitors, the Molecular Electrostatic Potential (MEP) distributions are determined by the MNDO semiempirical method.     

Simultaneous Anodic Stripping Voltammetric Determination of Pb and Cd,Using a Vibrating Gold Microwire Electrode,Assisted by Chemometric Techniques

Simultaneous anodic stripping voltammetric determination of Pb and Cd is restricted on gold electrodes as a result of the overlapping of these two peaks. This work describes the quantitative determination of a binary mixture system of Pb and Cd, at low concentration levels (up to 15.0 and 10.0 µg L^?1 for Pb and Cd, respectively) by differential pulse anodic stripping voltammetry (DPASV; deposition time of 30 s), using a green electrode (vibrating gold microwire electrode) without purging in a chloride medium (0.5 M NaCl) under moderate acidic conditions (HCl 1.0 mM), assisted by chemometric tools. The application of multivariate curve resolution alternating least squares (MCR‐ALS) for the resolution and quantification of both metals is shown. The optimized MCR‐ALS models showed good prediction ability with concentration prediction errors of 12.4 and 11.4 % for Pb and Cd, respectively. The quantitative results obtained by MCR‐ALS were compared to those obtained with partial least squares (PLS) and classical least squares (CLS) regression methods. For both metals, PLS and MCR‐ALS results are comparable and superior to CLS. For Cd, as a result of the peak shift problem, the application of CLS was unsuitable. MCR‐ALS provides additional advantage compared to PLS since it estimates the pure response of the analytes signal. Finally, the built up multivariate calibration models, based either in MCR‐ALS or PLS regression, allowed to quantify concentrations of Pb and Cd in surface river water samples, with satisfactory results.     

Multi-way partial least squares modeling of water quality data

A 10 years surface water quality data set pertaining to a polluted river was analyzed using partial least squares (PLS) regression models. Both the unfold-PLS and N-PLS (tri-PLS and quadri-PLS) models were calibrated through leave-one out cross-validation method. These were applied to the multivariate, multi-way data array with a view to assess and compare their predictive capabilities for biochemical oxygen demand (BOD) of river water in terms of their relative mean squares error of cross-validation, prediction and variance captured. The sum of squares of residuals and leverages were computed and analyzed to identify the sites, variables, years and months which may have influence on the constructed model. Both the tri- and quadri-PLS models yielded relatively low validation error as compared to unfold-PLS and captured high variance in model. Moreover, both of these methods produced acceptable model precision and accuracy. In case of tri-PLS the root mean squares errors were 1.65 and 2.17 for calibration and prediction, respectively; whereas these were 2.58 and 1.09 for quadri-PLS. At a preliminary level it seems that BOD can be predicted but a different data arrangement is needed. Moreover, analysis of the scores and loadings plots of the N-PLS models could provide information on time evolution of the river water quality.     

A combined molecular modeling study on gelatinases and their potent inhibitors

Zinc‐dependent matrix metalloproteinase (MMP) family is considered to be an attractive target because of its important role in many physiological and pathological processes. In the present work, a molecular modeling study combining protein‐, ligand‐ and complex‐based computational methods was performed to analyze a new series of β‐N‐biaryl ether sulfonamide hydroxamates as potent inhibitors of gelatinase A (MMP‐2) and gelatinase B (MMP‐9). Firstly, the similarities and differences between the binding sites of MMP‐2 and MMP‐9 were analyzed through sequence alignment and structural superimposition. Secondly, in order to extract structural features influencing the activities of these inhibitors, quantitative structure‐activity relationship (QSAR) models using genetic algorithm‐multiple linear regression (GA‐MLR), comparative molecular field (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were developed. The proposed QSAR models could give good predictive ability for the studied inhibitors. Thirdly, docking study was employed to further explore the binding mode between the ligand and protein. The results from all the above analyses could provide the information about the similarities and differences of the binding mode between the MMP‐2, MMP‐9 and their potent inhibitors. The obtained results can provide very useful information for the design of new potential inhibitors. © 2009 Wiley Periodicals, Inc. J Comput Chem 2010     

Simultaneous kinetic spectrophotometric determination of cyanide and thiocyanate using the partial least squares (PLS) regression

The partial least squares (PLS-1) calibration model based on spectrophotometric measurement, for the simultaneous determination of CN⁻ and SCN⁻ ions is described. The method is based on the difference in the rate of the reaction between CN⁻ and SCN⁻ ions with chloramine-T in a pH 4.0 buffer solution and at 30 °C. The produced cyanogen chloride (CNCl) reacts with pyridine and the product condenses with barbituric acid and forms a final colored product. The absorption kinetic profiles of the solutions were monitored by measuring absorbance at 578 nm in the time range 20-180 s after initiation of the reaction with 2 s intervals. The experimental calibration matrix for partial least squares (PLS-1) calibration was designed with 31 samples. The cross-validation method was used for selecting the number of factors. The results showed that simultaneous determination could be performed in the range 10.0-900.0 and 50.0-1200.0 ng mL⁻¹ for CN⁻ and SCN⁻ ions, respectively. The proposed method was successfully applied to the simultaneous determination of cyanide and thiocyanate in water samples.     

Quantitative Determination of the Components in Corn and Tobacco Samples by Using Near-Infrared Spectroscopy and Multiblock Partial Least Squares

Multiblock partial least squares (MB-PLS) are applied for determination of corn and tobacco samples by using near-infrared diffuse reflection spectroscopy. In the model, the spectra are separated into several sub-blocks along the wavenumber, and different latent variable number was used for each sub-block. Compared with ordinary PLS, the importance and the contribution of each sub-block can be balanced by super-weights and the usage of different latent variable numbers. Therefore, the prediction obtained by the MB-PLS model is superior to that of the ordinary PLS, especially for the large data sets of tobacco samples with a large number of variables.     

Multivariate curve resolution modeling of liquid chromatography-mass spectrometry data in a comparative study of the different endogenous metabolites behavior in two tomato cultivars treated with carbofuran pesticide

A metabonomic study based on the application of multivariate curve resolution and alternating least squares (MCR-ALS) to three-way data sets obtained by liquid chromatography coupled to mass spectrometry detection (LC-MS) was carried out for Rambo and Raf tomato cultivars treated with carbofuran pesticide. Samples were picked up during a 21 days period after treatment and analyzed by LC-MS in scan mode, along with the corresponding blank samples. Then, MCR-ALS was applied to the three-way data sets using column wise augmented matrices, and the evolutionary profiles as a function of the time after treatment were estimated for the metabolites present in both cultivars, as well as their corresponding pure spectra estimations. A comparative study using those estimations showed that some of these metabolites followed different behavior for the different cultivars after treatment. Since all treated and untreated Rambo and Raf samples were picked up according to the same sampling protocol and in a similar state of maturation, any difference in the behavior between profiles can be interpreted as an effect due to the presence of pesticide and to the kind of cultivar. Based on this hypothesis, several PLS-DA approaches were tested to check if it would be possible to classify samples by using the metabolites MCR estimations. Results showed that PLS-DA models for classification of treated or non-treated (blank) samples were the best ones obtained (98.44% of correct classifications for the validation set), which supports the stress effects related to carbofuran treatment. In addition, excellent discrimination among the four groups could be attained (89.06% of correct classifications for the validation set).     

Combinative neural network and its applications

A new approach named combinative neural network (CN) using partial least squares (PLS) analysis to modify the hidden layer in the multi-layered feed forward (MLFF) neural networks (NN) was proposed in this paper. The significant contributions of PLS in the proposed CN are to reorganize the outputs of hidden nodes such that the correlation of variables could be circumvented, to make the network meet the non-linear relationship best between the input and output data of the NN, and to eliminate the risk of over-fitting problem at the same time. The performance of the proposed approach was demonstrated through two examples, a well defined nonlinear approximation problem, and a practical nonlinear pattern classification problem with unknown relationship between the input and output data. The results were compared with those by conventional MLFF NNs. Good performance and time-saving implementation make the proposed method an attractive approach for non-linear mapping and classification.     

Molecular modeling and structural analysis of some tetrahydroindazole and cyclopentanepyrazole derivatives as COX-2 inhibitors

In an attempt to rationalize the search for new potential anti-inflammatory compounds on the COX-2 enzyme, we carried out an in silico protocol that successfully combines the prediction of physicochemical and pharmacokinetic properties, molecular docking, molecular dynamic simulation, and free energy calculation. Starting from a small library of compounds synthesized previously, it was found that 70% of the compounds analyzed satisfy with the associated values to physicochemical principles as key evaluation parameters for the drug-likeness; all the compounds presented good gastrointestinal absorption and cerebral permeability and they showed an interaction with the Arg 106 residue of the COX-2 isoenzyme. Finally, it was obtained that compound 3ab has a binding mode, binding energy, and stability in the active site of COX-2 like the reference drug celecoxib, suggesting that this compound could become a powerful candidate in the inhibition of the COX-2 enzyme. In addition, we realized the crystallographic analysis of compounds 3j, 3r, and 3t defining the crystal parameters and the Packing interactions.