Prediction of dual agents as an activator of mutant p53 and inhibitor of Hsp90 by docking,molecular dynamic simulation and virtual screening

Heat shock protein90s (Hsp90s) play a crucial role in the development of cancer, and their inhibitors are a main target for tumor suppression. P53 also is a tumor suppressor, but in cancer cells, mutations in the p53 gene lead to the inactivation and accumulation of protein. For instance, the ninth p53 cancer mutation, Y220C, destabilizes the p53 core domain. Small molecules have been assumed to bind to Y220C DNA-binding domain and reactivate cellular mutant p53 functions. In this study, one of the mutant p53 activators is suggested as an Hsp90 inhibitor according to a pyrazole scaffold. To confirm a new ligand as a dual agent, molecular docking and molecular dynamic simulations were performed on both proteins (p53 and Hsp90). Molecular dynamic simulations were also conducted to evaluate the obtained results on the other two pyrazole structures, one known as Hsp90 inhibitor and the other as the reported mutant p53 activator. The findings indicate that the new ligand was stable in the active site of both proteins. Finally, a virtual screening was performed on ZINC database, and a set of new dual agents was proposed according to the new ligand scaffold.     

Insight into analysis of interactions of saquinavir with HIV-1 protease in comparison between the wild-type and G48V and G48V/L90M mutants based on QM and QM/MM calculations

Saquinavir (SQV) was the first HIV-1 PR inhibitor licensed for clinical use and widely used for acquired immunodeficiency syndrome (AIDS) therapy. Its effectiveness, however, has been hindered by the emergence of resistant mutations. The two most important HIV-1 PR mutants are G48V and G48V/L90M. Inhibition studies of SQV on these mutants demonstrated 13.5- and 419-fold reductions of susceptibility, respectively. In this study, an analysis of energetic binding affinity between saquinavir and the HIV-1 PR wild-type and these two mutants has been performed in detail based on density functional theory and the hybrid quantum mechanical/molecular mechanical (QM/MM) calculations. We have found that the interaction of SQV with flap residue 48 of the mutants is significantly perturbed, as shown by the reduced stability of binding between SQV and residue 48 for the G48V and G48V/L90M mutants over the wild-type. This was associated with conformational changes of the inhibitor and the enzyme, leading to the loss of hydrogen bonding between the binding subsite P2 and the backbone carbonyl of residue 48. Moreover, the G48V/L90M mutations cause the repositioning of the residues close to residues 48 and 90, at important locations as a part of the flap and catalytic regions, respectively. The repositioning of these residues consequently perturbed the binding affinity of SQV in the pocket as indicated by the decreasing interaction energies. In addition to the loss of inhibitor/enzyme binding, it is interesting to observe that the mutation leads significantly to an increase of the stability of the enzyme.     

Physiological mechanism underlying the improvement in visuospatial performance due to 30% oxygen inhalation

This study investigated the effect of 30% oxygen inhalation on visuospatial cognitive performance, blood oxygen saturation, and heart rate. Six male (25.8(mean)+/-1.0(SD) years) and six female (23.8+/-1.9 years) college students participated in this experiment. Two psychological tests were developed to measure the performance level of visuospatial cognition. The experiment consisted of two runs: one was a visuospatial cognition task under normal air (21% oxygen) condition and the other under hyperoxic air (30% oxygen) condition. The experimental sequence in each run consisted of four phases, that were Rest1 (1min), Control (1min), Task (4min), and Rest2 (4min). Blood oxygen saturation and heart rate were measured throughout the course of four phases. The analysis of behavioral performance with 30% oxygen administration when compared to 21% oxygen revealed that the mean performance was improved. When supplied 30% oxygen in the air, the blood oxygen saturation was increased while the heart rate was decreased compared to those under 21% oxygen condition. We conclude that 30% oxygen inhalation enhanced visuospatial performance by the increased the oxygen saturation in the blood.     

基于Gabor特征与BP神经网络的屏幕显示自动校验系统

针对人工校验视频监控设备屏幕显示(OSD)效率低下、人力物力资源耗费大的问题,提出一种OSD自动校验系统,取代传统的人工校验方式。系统首先综合多种数理统计特征进行OSD定位,然后利用改进的Otsu算法进行精确字符分割并二值化,最后通过基于Gabor特征离线训练的改进型BP神经网络进行字符识别。实验结果表明,在确保92.7%识别率的前提下,该系统识别一帧OSD平均耗时53ms。     

Preparation of an electrochemical PNA biosensor for detection of target DNA sequence and single nucleotide mutation on p53 tumor suppressor gene corresponding oligonucleotide

Development of an electrochemical biosensor based on peptide nucleic acid (PNA) probe for detection of target DNA sequence and single nucleotide mutation in p53 tumor suppressor gene corresponding oligonucleotide using methylene blue (MB) as an electrochemical indicator is described. The interaction between MB and short sequence of p53, one of the most important tumor suppressor genes due to its dysfunction in the majority of human cancers, was studied by differential pulse voltammety (DPV). Probe modified electrode was prepared by self-assembled monolayer (SAM) formation of thiolated PNA molecules on the surface of gold electrode (GE). The hybridization of PNA probe with target DNA was performed in solution to form PNA-DNA hybrid on the surface of the GE. A significant increase in the reduction signal of MB was observed upon hybridization of the probe with the complementary DNA. The selectivity of the biosensor was studied using noncomplementary oligonucleotides. Furthermore, our results confirmed the ability of the sensor to detect single base mismatch in the sample oligonucleotide. The influence of probe concentration on the effective discrimination against noncomplementary sequence and point mutation was also investigated. Diagnostic performance of the biosensor is described and the detection limit is found 6.82 × 10⁻¹⁰ M. The electrochemical impedance spectroscopy was also employed to further investigate the sensor function.     

A Comparison of Mamdani and Sugeno Fuzzy Based Packet Scheduler for MANET with a Realistic Wireless Propagation Model

 The mobile nature of the nodes in a wireless mobile ad-hoc network (MANET) and the error prone link connectivity between nodes pose many challenges. These include frequent route changes, high packet loss, etc. Such problems increase the end-toend delay and decrease the throughput. This paper proposes two adaptive priority packet scheduling algorithms for MANET based on Mamdani and Sugeno fuzzy inference system. The fuzzy systems consist of three input variables: data rate, signal-to-noise ratio (SNR) and queue size. The fuzzy decision system has been optimised to improve its efficiency. Both fuzzy systems were verified using the Matlab fuzzy toolbox and the performance of both algorithms were evaluated using the riverbed modeler (formally known as OPNET modeler). The results were compared to an existing fuzzy scheduler under various network loads, for constant-bit-rate (CBR) and variable-bit-rate (VBR) traffic. The measuring metrics which form the basis for performance evaluation are end-to-end delay, throughput and packet delivery ratio. The proposed Mamdani and Sugeno scheduler perform better than the existing scheduler for CBR traffic. The end-to-end delay for Mamdani and Sugeno scheduler was reduced by an average of 52% and 54%, respectively. The performance of the throughput and packet delivery ratio for CBR traffic are very similar to the existing scheduler because of the characteristic of the traffic. The network was also at full capacity. The proposed schedulers also showed a better performance for VBR traffic. The end-to-end delay was reduced by an average of 38% and 52%, respectively. Both the throughput and packet delivery ratio (PDR) increased by an average of 53% and 47%, respectively. The Mamdani scheduler is more computationally complex than the Sugeno scheduler, even though they both showed similar network performance. Thus, the Sugeno scheduler is more suitable for real-time applications.     

Comparative proteomic analysis of low stage and high stage endometrioid ovarian adenocarcinomas

Ovarian cancer, the second most common gynecological malignancy, accounts for 3% of all cancers among women in the United States, and has a high mortality rate, largely because existing therapies for widespread disease are rarely curative. Ovarian endometrioid adenocarcinoma (OEA) accounts for about 20% of the overall incidence of all ovarian cancer. We have used proteomics profiling to characterize low stage (FIGO stage 1 or 2) versus high stage (FIGO stage 3 or 4) human OEAs. In general, the low stage tumors lacked p53 mutations and had frequent CTNNB1, PTEN, and/or PIK3CA mutations. The high stage tumors had mutant p53, were usually high grade, and lacked mutations predicted to deregulate Wnt/β‐catenin and PI3K/Pten/Akt signaling. We utilized 2‐D liquid‐based separation/mass mapping techniques to elucidate molecular weight and pI measurements of the differentially expressed intact proteins. We generated 2‐D protein mass maps to facilitate the analysis of protein expression between both the low stage and high stage tumors. These mass maps (over a pI range of 5.6–4.6) revealed that the low stage OEAs demonstrated protein over‐expression at the lower pI ranges (pI 4.8–4.6) in comparison to the high stage tumors, which demonstrated protein over‐expression in the higher pI ranges (pI 5.4–5.2). These data suggest that both low and high stage OEAs have characteristic pI signatures of abundant protein expression probably reflecting, at least in part, the different signaling pathway defects that characterize each group. In this study, the low stage OEAs were distinguishable from high stage tumors based upon the proteomic profiles. Interestingly, when only high‐grade (grade 2 or 3) OEAs were included in the analysis, the tumors still tended to cluster according to stage, suggesting that the altered protein expression was not solely dependent upon tumor cell differentiation. Further, these protein profiles clearly distinguish OEA from other types of ovarian cancer at the protein level.     

An inverse docking approach for identifying new potential anti-cancer targets

Inverse docking is a relatively new technique that has been used to identify potential receptor targets of small molecules. Our docking software package MDock is well suited for such an application as it is both computationally efficient, yet simultaneously shows adequate results in binding affinity predictions and enrichment tests. As a validation study, we present the first stage results of an inverse-docking study which seeks to identify potential direct targets of PRIMA-1. PRIMA-1 is well known for its ability to restore mutant p53's tumor suppressor function, leading to apoptosis in several types of cancer cells. For this reason, we believe that potential direct targets of PRIMA-1 identified in silico should be experimentally screened for their ability to inhibit cancer cell growth. The highest-ranked human protein of our PRIMA-1 docking results is oxidosqualene cyclase (OSC), which is part of the cholesterol synthetic pathway. The results of two followup experiments which treat OSC as a possible anti-cancer target are promising. We show that both PRIMA-1 and Ro 48-8071, a known potent OSC inhibitor, significantly reduce the viability of BT-474 and T47-D breast cancer cells relative to normal mammary cells. In addition, like PRIMA-1, we find that Ro 48-8071 results in increased binding of p53 to DNA in BT-474 cells (which express mutant p53). For the first time, Ro 48-8071 is shown as a potent agent in killing human breast cancer cells. The potential of OSC as a new target for developing anticancer therapies is worth further investigation.     

Improved genetic algorithm inspired by biological evolution

The process of mutation has been studied extensively in the field of biology and it has been shown that it is one of the major factors that aid the process of evolution. Inspired by this a novel genetic algorithm (GA) is presented here. Various mutation operators such as small mutation, gene mutation and chromosome mutation have been applied in this genetic algorithm. In order to facilitate the implementation of the above-mentioned mutation operators a modified way of representing the variables has been presented. It resembles the way genetic information is coded in living beings. Different mutation operators pose a challenge as regards the determination of the optimal rate of mutation. This problem is overcome by using adaptive mutation operators. The main purpose behind this approach was to improve the efficiency of GAs and to find widely distributed Pareto-optimal solutions. This algorithm was tested on some benchmark test functions and compared with other GAs. It was observed that the introduction of these mutations do improve the genetic algorithms in terms of convergence and the quality of the solutions.     

A new method to forecast of Escherichia coli promoter gene sequences: Integrating feature selection and Fuzzy-AIRS classifier system

We have investigated the real-world task of recognizing biological concepts in DNA sequences in this work. Recognizing promoters in strings that represent nucleotides (one of A, G, T, or C) has been performed using a novel approach based on feature selection (FS) and Artificial Immune Recognition System (AIRS) with Fuzzy resource allocation mechanism (Fuzzy-AIRS), which is first proposed by us. The aim of this study is to improve the prediction accuracy of Escherichia coli promoter gene sequences using a novel system based on FS and Fuzzy-AIRS. The E. coli promoter gene sequences dataset has 57 attributes and 106 samples including 53 promoters and 53 non-promoters. The proposed system consists of two parts. Firstly, we have reduced the dimension of E. coli promoter gene sequences dataset from 57 attributes to 4 attributes by means of FS process. Second, Fuzzy-AIRS classifier algorithm has been run to predict the E. coli promoter gene sequences. The robustness of the proposed method is examined using prediction accuracy, sensitivity and specificity analysis, k-fold cross-validation method and confusion matrix. Whilst only Fuzzy-AIRS classifier has obtained 50% prediction accuracy using 10-fold cross-validation, the proposed system has obtained 90% prediction accuracy in the same conditions. These obtained results have indicated that the proposed system obtain the success rate in recognizing promoters in strings that represent nucleotides.     

Main Effect Fine-tuning of the Mutation Operator and the Neighbourhood Function for Uncapacitated Facility Location Problems

In both genetic algorithms (GAs) and simulated annealing (SA), solutions can be represented by gene representation. Mutation operator in GA and neighborhood function in SA are used to explore the solution space. They usually select genes for performing mutation. The rate of selection of genes can be called mutation rate. However, randomly selecting genes may not be the best way for both algorithms. This paper describes how to estimate the main effect in genes representation. The resulting estimates cannot only be used to understand the domination of gene representation, but also employed to fine-tune the mutation rate in both the mutation operator in the GA and the neighborhood function in the SA. It has been demonstrated the use of the proposed methods for solving uncapacitated facility location problems and discuss the examination of the proposed methods with some useful comparisons with both the latest developed GA and SA for solving this problem. For many well-known benchmark problems, the proposed methods yield better results in solution quality than the previously used methods.     

电子细胞模型Analog-Cell中基因表达调控的模拟实现

电子细胞模型的研究是人工生命的重要研究领域之一,Analog-Cell是国内第1个电子细胞图形模型,用于在分子水平上图形化的模拟真核细胞的基因表达过程.扩展的Analog-Cell添加了在基因表达过程中起重要作用的酶和调控因子,利用状态控制机制,设计并实现了转录、mRNA的加工和翻译3个阶段中基因表达调控的主要反应的算法,并结合模拟示例展示了这些算法的运行结果.模拟实验结果表明,设计的算法符合生物学原理,使Analog-Cell具备了一定的图形化模拟基因表达调控反应的能力.最后,指出了上述工作给Analog-Cell带来的新优势,并对下一步工作进行了展望.     

2-(4-甲氧基苯基)亚肼基乙酸与乙醛酸反应密度泛函理论研究

本文应用量子化学密度泛函理论(DFT)研究了2-(4-甲氧基苯基)亚肼基乙酸与乙醛酸的反应机理及动力学行为,并研究了不同取代基对反应的影响.在RB3LYP/6-31G*水平上,优化了各反应通道的反应物、中间体、过渡态及产物的几何构型,计算了各驻点的振动频率、零点能和电荷分布.计算结果表明,该反应有2条反应通道,分别生成(2Z)和(2E)-3(4-甲氧基苯基二氮烯基)丙烯酸.产物发生了键长的平均化和电荷的重新分布.两反应通道具有相同的反应入口,Z式产物为主要产物,2-(4-甲氧基苯基)亚肼基乙酸中苯环对位被给电子基团取代,有利于反应进行.     

基于动态集合进化算法的弱变异测试用例集生成

为解决基于集合进化算法（SEA）的弱变异测试用例集生成过程中个体规模固定和执行开销大的问题,提出一种基于动态集合进化算法（DSEA）的弱变异测试用例集生成方法。以测试用例集为个体,生成覆盖所有变异分支的弱变异测试用例集。在进化过程中,集合精简算子根据最优个体的最小子集及其未覆盖变异分支数量计算所需测试用例集的最小规模,并基于该最小规模调整种群中所有个体的规模,以生成最小规模的弱变异测试用例集,同时设计了适用于评估以测试用例集为个体的适应度函数。实验结果表明,动态集合进化算法指导弱变异测试用例集生成,获得的测试用例集规模比个体初始规模平均约简了50.15%,执行时间比集合进化的弱变异测试用例集生成最多降低了74.58%。因此,动态集合进化算法为最小规模的弱变异测试用例集生成和提升算法速度提供了一种解决方案。     

一种用于图形渲染的高性能SpMV专用加速器结构

图形渲染中涉及的几何变换、投影变换、视口变换等需要大量稀疏矩阵向量乘法(Sparse Matrix-Vector Multiplication,SpM V)运算,如何实现SpMV高性能计算成为了图形处理器设计中的关键性问题之一,然而,当前的SpMV运算存在并行度较差,资源占用较多等问题.为提升硬件运算的性能,本文基于矩阵列向量的线性组合,充分利用数据的并行性,设计了一种专用加速器结构.实验表明,在XC6VLX550T开发板上与其他两种结构相比,速度分别能够提高28%、37%,资源占用率分别减少约48%、18%,应用于图形渲染中的变换操作后,速度分别能够提高28%、30%,资源占用率分别最高减少约48%、60%.     

Cross-sectional analysis of BMI and some lifestyle variables in Flemish vegetarians compared with non-vegetarians

Epidemiological studies on vegetarians indicate that appropriately planned vegetarian diets are associated with certain health benefits, which may lower mortality and morbidity. A healthy lifestyle, such as regular physical activity and avoidance of harmful practices, such as smoking and heavy drinking, could also influence these positive health-related outcomes in vegetarians. This study reports BMI, smoking and drinking habits, engagement in physical activity, medication use and subjective health perception in a vegetarian population (women: n = 206, mean age 37.0 +/- 12.3 years; men: n = 120, mean age 42.3 +/- 15.9 years) as compared with a reference Belgian population (women: n = 4993, mean age 49.8 +/- 18.0 years; men: n = 4666, mean age 48.0 +/- 17.1 years). When considering the vegetarian group as a whole, the vegetarians had a lower mean BMI compared with the reference population (respectively 22.1 +/- 3.1 kg/m2 compared with 24.6 +/- 4.8 kg/m2 for women (p < 0.001) and respectively 22.6 +/- 3.6 kg/m2 compared with 25.7 +/- 4.0 kg/m2 for men (p < 0.001)). Vegetarians smoked less than subjects of the reference group (13.5% compared with 28.5% respectively; p < 0.001). During weekdays the percentage of subjects consuming alcoholic drinks in the two populations was comparable (32.8 in the vegetarian and 35.8 in the reference population; p = 0.159). During the weekend, more subjects of the reference population drank alcohol compared with the vegetarian subjects (70.2% vs. 58.6% respectively; p = 0.026). More vegetarians were involved in intensive physical activity (over 4 h per week) compared with the reference population (36.8% vs. 17.3% respectively; p < 0.001), while fewer vegetarians were involved in moderate physical activity (up to 4 h per week) compared with subjects of the reference group (28.2% and 51.0% respectively; p < 0.001). Percentages of subjects involved in no physical activity were comparable in both groups (vegetarians 34.9 vs. reference subjects 31.8; p = 0.625). Use of prescribed medication was lower among the vegetarians (25.5% compared with 47.3% in the reference population; p < 0.001), while use of non-prescribed drugs was comparable between both groups (34.1% in the vegetarian group and 28.2% in the reference group; p = 0.580). More vegetarian subjects perceived their health to be good to very good compared with the subjects of the reference population (90.4% vs. 77.2% respectively; p < 0.001). The significant difference for the BMI values when comparing the vegetarian males and females with the reference population cannot be completely explained by the evaluated lifestyle characteristics. However, the lower BMI values in vegetarians are in agreement with the literature.     

Structure–function analysis of D9N and N291S mutations in human lipoprotein lipase using molecular modelling

Lipoprotein lipase (LPL) plays a central role in lipid metabolism. The D9N and N291S mutations in the LPL gene are associated with elevated triglyceride and decreased HDL-cholesterol levels. Published in vitro expression studies suggest that these two mutations are associated with reduced LPL enzymatic activity. We sought to gain further insight on the impact of these two mutations on the LPL structure and function by molecular modelling techniques. Homology modelling was used to develop a three-dimensional (3D) structure of LPL from human pancreatic lipase. Two separate LPL models for the D9N and N291S substitutions were constructed and compared with the wild type LPL for differences in hydrophobicity, atomic burial, hydrogen bond pattern, and atomic mobility. In comparison to the wild type model, the 9N model was associated with significantly increased atomic mobility of its neighboring residues, but the catalytic site was not affected. The region near residue 9 in the upper part of the N-domain was considered a candidate site for protein–protein interaction. In the N291S model, alterations in H-bonds and constrained atomic mobility were among conformational changes in the region where the substitution had occurred. These are hypothesized to cause an increase in the rate of dissociation in LPL dimerization, subsequently affecting the LPL enzymatic activity. We also modelled the C-domain of apoCII, the obligatory cofactor of LPL, from 2D NMR data and docked the model with LPL to explore their interaction site. These docking experiments suggest that the C-domain of apoCII interacts with the interface of N- and C-domains of LPL and part of the lid structure that covers the catalytic site. In summary, we provide molecular modelling data on two well-known mutations in the LPL gene to help explain the published in vitro expression findings and propose a possible LPL-apoCII interaction site. Our data indicate that molecular modelling of LPL mutations could provide a valuable tool to understand the effects of a mutation on the structure–function of this important enzyme.     

基于GEP的最小二乘支持向量机模型参数选择

针对最小二乘支持向量机的多参数寻优问题,提出了一种基于基因表达式编程的最小二乘支持向量机参数优选方法.该算法将最小二乘支持向量机参数(C,σ)样本作为GEP的基因,按其变异算子随着进化代数和染色体所含基因数目动态变化的机制执行,其收敛速度和精确度大大提高.并与基于粒子群算法和遗传算法参数优选方法比较,通过标准测试函数验证了该算法的拟合误差最低.最后用其建立氧化铝生产蒸发过程参数预测模型,应用工业生产数据进行验证,实验结果表明该方法有效且获得了满意的效果.     

Aberrant expression of glycosylation in juvenile gastrointestinal stromal tumors

Most adult gastrointestinal stromal tumors (GIST) are thought to be caused by activating mutations in the KIT or PDGFRA gene. However, many juvenile GIST lack either mutation and are considered to develop with a different pathogenesis. To investigate the molecular characteristics of juvenile GIST, we analyzed the proteome difference in phosphorylated protein between adult and juvenile GIST. Eleven GIST samples (seven adult cases and four juvenile cases lacking either mutation) were analyzed by using immunostaining and LC-MS/MS. Comparative analysis of tyrosine-phosphorylated protein levels showed that juvenile GIST possessed phosphorylated KIT in spite of lacking mutation in the KIT gene. Moreover, downstream signals of KIT were also activated as in adult GIST. Although, SDS-PAGE gels showed that there was a difference of each KIT bands between adult and juvenile GIST, they became the same after removal of N-glycans or sialic acids. Moreover, one of the most typical enzymes, ST6Gal1, which transfers Neu5Ac residues in α2-6 linkage to Gal β1-4GlcNAc units on N-glycans, is significantly less expressed in juvenile GIST. This suggests that the difference in KIT is generated by post-translational modification and may play a role in the progression of juvenile GIST.