Pharmacophore generation and atom-based 3D-QSAR of novel 2-(4-methylsulfonylphenyl)pyrimidines as COX-2 inhibitors

Cyclooxygenase-2 (COX-2) inhibitors are widely used for the treatment of pain and inflammatory disorders such as rheumatoid arthritis and osteoarthritis. A series of novel 2-(4-methylsulfonylphenyl)pyrimidine derivatives has been reported as COX-2 inhibitors. In order to understand the structural requirement of these COX-2 inhibitors, a ligand-based pharmacophore and atom-based 3D-QSAR model have been developed. A five-point pharmacophore with four hydrogen bond acceptors (A) and one hydrogen bond donor (D) was obtained. The pharmacophore hypothesis yielded a 3D-QSAR model with good partial least-square (PLS) statistics results. The training set correlation is characterized by PLS factors (r ² = 0.642, SD = 0.65, F = 82.7, P = 7.617 e − 12). The test set correlation is characterized by PLS factors (Q ² _ext = 0.841, RMSE = 0.24,Pearson−R = 0.91). A docking study revealed the binding orientations of these inhibitors at active site amino acid residues (Arg513, Val523, Phe518, Ser530, Tyr355, His90) of COX-2 enzyme. The results of ligand-based pharmacophore hypothesis and atom-based 3D-QSAR give detailed structural insights as well as highlights important binding features of novel 2-(4-methylsulfonylphenyl)pyrimidine derivatives as COX-2 inhibitors which can provide guidance for the rational design of novel potent COX-2 inhibitors.     

Identification of new novel scaffold for Aurora A inhibition by pharmacophore modeling and virtual screening

Aurora kinases belong to family of highly conserved serine/threonine protein kinases that are involved in diverse cell cycle events and play a major role in regulation of cell division. Abnormal expression of Aurora kinases may lead to cancer; hence, these are considered as a potential target in cancer treatment. In this research article, we identified three novel Aurora A inhibitors using modern computational tools. A four-point common 3D pharmacophore hypothesis of Aurora A (AurA) inhibitors was developed using a diverse set of 55 thienopyrimidine derivatives. A three-dimensional quantitative structure–activity relationship (3D-QSAR) study was carried out using atom-based alignment of diverse set of 55 molecules to evaluate the structure– activity relationships. Docking and 3D-QSAR studies were performed with the 3D structure of AurA to evaluate the generated pharmacophore. The pharmacophore model and 3D-QSAR results complemented the results of our docking study. The pharmacophore hypothesis, which yields the best results, was used to screen the Zinc ‘clean drug-like’ database. Various database filters such as 3D-arrangement of pharmacophoric features, predicted activity and binding interaction score were used to retrieve hits having potential AurA inhibition activity.     

Integration-mediated prediction enrichment of quantitative model for Hsp90 inhibitors as anti-cancer agents: 3D-QSAR study

The present study describes a systematic 3D-QSAR study consisting of pharmacophore modeling, docking, and integration of ligand-based and structure-based drug design approaches, applied on a dataset of 72 Hsp90 inhibitors as anti-cancer agents. The best pharmacophore model, with one H-bond donor (HBD), one H-bond acceptor (HBA), one hydrophobic_aromatic (Hy_Ar), and two hydrophobic_aliphatic (Hy_Al) features, was developed using the Catalyst/HypoGen algorithm on a training set of 35 compounds. The model was further validated using test set, external set, Fisher’s randomization method, and ability of the pharmacophoric features to complement the active site amino acids. Docking analysis was performed using Hsp90 chaperone (PDB-Id: 1uyf) along with water molecules reported to be crucial for binding and catalysis (Sgobba et al. ChemMedChem 4:1399–1409, 2009). Furthermore, an integration of the ligand-based as well as structure-based drug design approaches was done leading to the integrated model, which was found to be superior over the best pharmacophore model in terms of its predictive ability on internal [integrated model 2: R _(train) = 0.954, R _(test) = 0.888; Hypo-01: R _(train) = 0.912 and R _(test) = 0.819] as well as on external data set [integrated model 2: R _(ext.set) = 0.801; Hypo-01: R _(ext.set) = 0.604].     

Pharmacophore-based screening and drug repurposing exemplified on glycogen synthase kinase-3 inhibitors

The current study was conducted to elaborate a novel pharmacophore model to accurately map selective glycogen synthase kinase-3 (GSK-3) inhibitors, and perform virtual screening and drug repurposing. Pharmacophore modeling was developed using PHASE on a data set of 203 maleimides. Two benchmarking validation data sets with focus on selectivity were assembled using ChEMBL and PubChem GSK-3 confirmatory assays. A drug repurposing experiment linking pharmacophore matching with drug information originating from multiple data sources was performed. A five-point pharmacophore model was built consisting of a hydrogen bond acceptor (A), hydrogen bond donor (D), hydrophobic (H), and two rings (RR). An atom-based 3D quantitative structure–activity relationship (QSAR) model showed good correlative and satisfactory predictive abilities (training set \({R}^{2}= 0.904\); test set: \({Q}^{2}= 0.676\); whole data set: stability \(s = 0.803\)). Virtual screening experiments revealed that selective GSK-3 inhibitors are ranked preferentially by Hypo-1, but fail to retrieve nonselective compounds. The pharmacophore and 3D QSAR models can provide assistance to design novel, potential GSK-3 inhibitors with high potency and selectivity pattern, with potential application for the treatment of GSK-3-driven diseases. A class of purine nucleoside antileukemic drugs was identified as potential inhibitor of GSK-3, suggesting the reassessment of the target range of these drugs.     

基于FFCNN的二维恒星光谱分类

天体光谱处理中的一项基本任务是对大量的恒星光谱进行自动分类。到目前为止,恒星光谱的分类工作多是基于一维光谱数据。该研究打破传统的天体光谱数据处理流程,提出了基于二维恒星光谱分类的方法。在LAMOST(the large sky area multi-object fiber spectroscopic telescope)的数据处理流程中,所有的一维光谱都是由二维光谱抽谱、合并得来。二维光谱是由光谱仪产生的图像,包括蓝端图像和红端图像。基于LAMOST二维光谱数据,提出了特征融合卷积神经网络（FFCNN）分类模型,用于二维恒星光谱的分类。该模型是一个有监督的算法,通过两个CNN模型分别提取蓝端图像和红端图像的特征,然后将二者进行融合得到新的特征,再利用CNN对新特征进行分类。所使用的数据全部来源于LAMOST,我们在LMOST DR7中随机选择了一批源,然后获得了它们的二维光谱。一共有14 840根F,G和K型恒星的二维光谱用于FFCNN模型的训练,其中包括7 420根蓝端光谱和7 420根红端光谱。由于三类恒星光谱的数量并不均衡,在训练的过程中分别为每类恒星光谱设置了不同权重,防止模型出现分类失衡现象。同时,为了加快模型收敛,对二维光谱数据采用Z-score归一化处理。此外,为了充分利用所有样本,提高模型的可靠度,采用五折交叉验证的方法验证模型。3 710根二维光谱用作测试集,使用准确率、精确率、召回率和F1-score来对FFCNN模型的性能进行评价。实验结果显示,F,G和K型恒星的精确率分别达到87.6%,79.2%和88.5%,而且它们超过了一维光谱分类的结果。实验结果证明基于FFCNN的二维恒星光谱分类是一种有效的方法,它也为恒星光谱的处理提供了新的思路和方法。     

Comparative docking and CoMFA analysis of curcumine derivatives as HIV-1 integrase inhibitors

The docking studies and comparative molecular field analysis (CoMFA) were performed on highly active molecules of curcumine derivatives against 3′ processing activity of HIV-1 integrase (IN) enzyme. The optimum CoMFA model was selected with statistically significant cross-validated r² value of 0.815 and non-cross validated r ² value of 0.99. The common pharmacophore of highly active molecules was used for screening of HIV-1 IN inhibitors. The high contribution of polar interactions in pharmacophore mapping is well supported by docking and CoMFA results. The results of docking, CoMFA, and pharmacophore mapping give structural insights as well as important binding features of curcumine derivatives as HIV-1 IN inhibitors which can provide guidance for the rational design of novel HIV-1 IN inhibitors.     

Direct single-layered fabrication of 3D concavo–convex patterns in nano-stereolithography

A nano-surfacing process (NSP) is proposed to directly fabricate three-dimensional (3D) concavo–convex-shaped microstructures such as micro-lens arrays using two-photon polymerization (TPP), a promising technique for fabricating arbitrary 3D highly functional micro-devices. In TPP, commonly utilized methods for fabricating complex 3D microstructures to date are based on a layer-by-layer accumulating technique employing two-dimensional sliced data derived from 3D computer-aided design data. As such, this approach requires much time and effort for precise fabrication. In this work, a novel single-layer exposure method is proposed in order to improve the fabricating efficiency for 3D concavo–convex-shaped microstructures. In the NSP, 3D microstructures are divided into 13 sub-regions horizontally with consideration of the heights. Those sub-regions are then expressed as 13 characteristic colors, after which a multi-voxel matrix (MVM) is composed with the characteristic colors. Voxels with various heights and diameters are generated to construct 3D structures using a MVM scanning method. Some 3D concavo–convex-shaped microstructures were fabricated to estimate the usefulness of the NSP, and the results show that it readily enables the fabrication of single-layered 3D microstructures. PACS 85.40.Hp; 81.16.Nd; 42.82.Cr     

Identification of dual Acetyl-CoA carboxylases 1 and 2 inhibitors by pharmacophore based virtual screening and molecular docking approach

Acetyl-CoA carboxylase (ACC) is a crucial metabolic enzyme that plays a vital role in obesity-induced type 2 diabetes and fatty acid metabolism. To identify dual inhibitors of Acetyl-CoA carboxylase1 and Acetyl-CoA carboxylase2, a pharmacophore modelling approach has been employed. The best HypoGen pharmacophore model for ACC2 inhibitors (Hypo1_ACC2) consists of one hydrogen bond acceptor, one hydrophobic aliphatic and one hydrophobic aromatic feature, whereas the best pharmacophore (Hypo1_ACC1) for ACC1 consists of one additional hydrogen-bond donor (HBD) features. The best pharmacophore hypotheses were validated by various methods such as test set, decoy set and Cat-Scramble methodology. The validated pharmacophore models were used to screen several small-molecule databases, including Specs, NCI, ChemDiv and Natural product databases to identify the potential dual ACC inhibitors. The virtual hits were then subjected to several filters such as estimated $\text{ IC}_{50}$ value, quantitative estimation of drug-likeness and molecular docking analysis. Finally, three novel compounds with diverse scaffolds were selected as potential starting points for the design of novel dual ACC inhibitors.     

以AgCl和1,2-二(4-吡啶)乙烷为原料合成的二维无机-有机杂化聚合物的晶体结构及荧光性质(英文)

以AgCl与柔性配体1,2-二(4-吡啶)乙烷(bpe)为原料,在1∶1的甲醇-水混合溶剂中超声反应合成了一个新的无机-有机杂化聚合物[Ag3Cl3(BPE)2]n(1),并对该配合物进行了元素分析、红外光谱分析、热重分析、发光测试以及晶体结构研究。配合物属于三斜晶系,P1空间群,a=0.998 8(2)nm,b=1.115 1(2)nm,c=1.269 5(3)nm,α=64.27(3)°,β=85.71(3)°,γ=86.70(3)°,V=1.269 7(5)nm3,Z=2。单晶结构分析表明,该化合物1含有一维的(Ag6Cl6)n链,双氮配体BPE进一步连接该一维链形成了二维双层结构。固体发光性能测试表明,该化合物在385 nm光激发下能发出峰值为525 nm的黄光。此外,热分析表明,该化合物热稳定性可达到170℃。     

Determination of the strong phase in D0-->K+pi- using quantum-correlated measurements

We exploit the quantum coherence between pair-produced D0 and D[over]0 in psi(3770) decays to study charm mixing, which is characterized by the parameters x and y, and to make a first determination of the relative strong phase delta between D0-->K+pi- and D[over]0-->K+pi-. Using 281 pb(-1) of e+e- collision data collected with the CLEO-c detector at Ecm=3.77 GeV, as well as branching fraction input and time-integrated measurements of RM identical with (x2 + y2)/2 and RWS identical with Gamma(D0-->K+pi-)/Gamma(D[over]0-->K+pi-) from other experiments, we find cosdelta=1.03(-0.17)(+0.31)+/-0.06, where the uncertainties are statistical and systematic, respectively. By further including other mixing parameter measurements, we obtain an alternate measurement of cosdelta=1.10+/-0.35+/-0.07, as well as x sindelta=(4.4(-1.8)(+2.7)+/-2.9)x10(-3) and delta=(22(-12-11)(+11+9)) degrees .     

Discovery of small molecular inhibitors for interleukin-33/ST2 protein–protein interaction: a virtual screening,molecular dynamics simulations and binding free energy calculations

The interleukin-1 receptor like ST2 has emerged as a potential drug discovery target since it was identified as the receptor of the novel cytokine IL-33, which is involved in many inflammatory and autoimmune diseases. For the treatment of such IL-33-related disorders, efforts have been made to discover molecules that can inhibit the protein–protein interactions (PPIs) between IL-33 and ST2, but to date no drug has been approved. Although several anti-ST2 antibodies have entered clinical trials, the exploration of small molecular inhibitors is highly sought-after because of its advantages in terms of oral bioavailability and manufacturing cost. The aim of this study was to discover ST2 receptor inhibitors based on its PPIs with IL-33 in crystal structure (PDB ID: 4KC3) using virtual screening tools with pharmacophore modeling and molecular docking. From an enormous chemical space ZINC, a potential series of compounds has been discovered with stronger binding affinities than the control compound from a previous study. Among them, four compounds strongly interacted with the key residues of the receptor and had a binding free energy?<????20 kcal/mol. By intensive calculations using data from molecular dynamics simulations, ZINC59514725 was identified as the most potential candidate for ST2 receptor inhibitor in this study.

Graphical abstract

     

Sample optimization and identification of signal patterns of amino acid side chains in 2D RFDR spectra of the alpha-spectrin SH3 domain

Future structural investigations of proteins by solid-state CPMAS NMR will rely on uniformly labeled protein samples showing spectra with an excellent resolution. NMR samples of the solid alpha-spectrin SH3 domain were generated in four different ways, and their (13)C CPMAS spectra were compared. The spectrum of a [u-(13)C, (15)N]-labeled sample generated by precipitation shows very narrow (13)C signals and resolved scalar carbon-carbon couplings. Linewidths of 16-19 Hz were found for the three alanine C(beta )signals of a selectively labeled [70% 3-(13)C]alanine-enriched SH3 sample. The signal pattern of the isoleucine, of all prolines, valines, alanines, and serines, and of three of the four threonines were identified in 2D (13)C-(13)C RFDR spectra of the [u-(13)C, (15)N]-labeled SH3 sample. A comparison of the (13)C chemical shifts of the found signal patterns with the (13)C assignment obtained in solution shows an intriguing match.     

Experimental realization of a model glass former in 2D

We have studied binary two-dimensional (2D) mixtures of superparamagnetic colloidal particles interacting through magnetic dipole moments, which were induced by an external magnetic field B. By tuning B the effective system temperature could be widely adjusted. Time-dependent particle coordinates measured by video-microscopy provide radial pair-distribution functions, mean-square displacements as well as evidence for heterogeneous dynamics. Characteristic features of 3D glass formers are observed experimentally in 2D for the first time.     

Direct MR arthrography of the shoulder: 2D vs. 3D gradient-echo imaging.

The aim of this study was to determine the value of a fat suppressed 3D gradient-echo sequence (GRE) data set in comparison to a 2D GRE sequence in direct MR arthrography of the shoulder. For this purpose we examined 50 consecutive patients with subacute or chronic disorders of the shoulder using a 1.5 T scanner: Transverse T1-weighted 2D (slice thickness 4 mm) and 3D GRE (slice thickness 1.5 mm reconstructed from 3 mm), oblique coronal T2- and T1-weighted turbo spin-echo (TSE) and sagittal T1-weighted TSE with fat saturation were applied. Visual image analysis of anatomical and pathological structures was performed by two independent observers. A correlation to surgical results was available in 21 patients. Transverse GRE sequences were well suited for analysis of the anterior/posterior labrum, the middle glenohumeral ligament, and cartilage. 3D GRE with fat suppression was slightly superior to 2D GRE without fat suppression in the evaluation of the anterior/posterior labrum, and the middle glenohumeral ligament, whereas for cartilage no significant differences were found between both sequences. Concerning pathological findings, in most of the cases 2D delivered the same results as 3D. In conclusion, a T1-weighted 3D GRE data set with fat saturation in transverse orientation may be useful for evaluation of the anterior/posterior labrum, and the middle glenohumeral ligament. However, similar measured slice thickness of 3 mm-even if interpolated to 1.5 mm-compared to a 2D sequence with 4 mm does not provide significant diagnostic advantages.     

3D combinational curves for accuracy and performance analysis of positive biometrics identification

The receiver operating characteristic (ROC) curve has been widely used as an evaluation criterion to measure the accuracy of biometrics system. Unfortunately, such an ROC curve provides no indication of the optimum threshold and cost function. In this paper, two kinds of 3D combinational curves are proposed: the 3D combinational accuracy curve and the 3D combinational performance curve. The 3D combinational accuracy curve gives a balanced view of the relationships among FAR (false alarm rate), FRR (false rejection rate), threshold t, and Cost. Six 2D curves can be derived from the 3D combinational accuracy curve: the conventional 2D ROC curve, 2D curve of (FRR, t), 2D curve of (FAR, t), 2D curve of (FRR, Cost), 2D curve of (FAR, Cost), and 2D curve of (t, Cost). The 3D combinational performance curve can be derived from the 3D combinational accuracy curve which can give a balanced view among Security, Convenience, threshold t, and Cost. The advantages of using the proposed 3D combinational curves are demonstrated by iris recognition systems where the experimental results show that the proposed 3D combinational curves can provide more comprehensive information of the system accuracy and performance.