SAR-oriented discovery of peroxisome proliferator-activated receptor pan agonist with a 4-adamantylphenyl group as a hydrophobic tail

3-(4-Alkoxyphenyl)propanoic acid derivatives were prepared as candidate peroxisome proliferator-activated receptor (PPAR) alpha/delta/gamma pan agonists, based on our previous SAR studies directed toward the development of subtype-selective PPAR agonists. Those studies indicated that the steric bulkiness of substituents introduced at the distal benzene ring had an important influence on PPAR activity. The finding that a 4-adamantyl derivative exhibited not only PPARalpha/delta activity but also significant PPARgamma activity prompted us to search for structurally novel phenylpropanoic acid derivatives with more potent adipocyte differentiation activity than the well-known PPARgamma agonist, rosiglitazone, as well as well-balanced PPARalpha and PPARdelta agonistic activities. A representative phenylpropanoic acid derivative (12) bearing a 4-adamantylphenyl substituent proved to be a well-balanced PPAR-pan agonist with activities to regulate the expression of genes involved in lipid and glucose homeostasis, and should be useful as a candidate drug for the treatment of altered PPAR function.     

Synthesis and structure-activity relationships of berberine analogues as a novel class of low-density-lipoprotein receptor up-regulators

Berberine (BBR, 1) is a novel cholesterol-lowering agent that up-regulates low-density-lipoprotein receptor (LDLR) expression through a mechanism different from that of statins. Because of the unique mode of action and good safety record, BBR provoked our interest to do structure modification at different domains for its cholesterol-lowering activity. Nineteen BBR analogues with substituents on the benzene ring D were synthesized in the present study. The analysis of structure-activity relationship (SAR) indicated that the two methoxyl groups in an ortho-distribution on this benzene ring afforded a good activity. Among the 19 analogues, compound 8j bearing a methoxyl at both 10- and 11-position showed an increased LDLR up-regulatory activity in respect to BBR, and therefore has been selected as a promising cholesterol-lowering drug candidate for further evaluation.     

Interaction of bleomycin A2 with deoxyribonucleic acid: DNA unwinding and inhibition of bleomycin-induced DNA breakage by cationic thiazole amides related to bleomycin A2

The association of the antitumor antibiotic bleomycin A2 with DNA has been investigated by employing several 2-substituted thiazole-4-carboxamides, structurally related to the cationic terminus of the drug. With a 5'-32P-labeled DNA restriction fragment from plasmid pBR322 as substrate, these compounds have been shown to inhibit bleomycin-induced DNA breakage. Analogues possessing 2'-aromatic substituents on the bithiazole ring were more potent inhibitors than those carrying 2'-aliphatic groups, e.g., the acetyl dipeptide A2. The degree of inhibition was similar at all scission sites on DNA, and inclusion of the analogues did not induce bleomycin cleavage at new sites. DNA binding of bithiazole derivatives has also been studied by two complementary topological methods. Two-dimensional gel electrophoresis using a population of DNA topoisomers and DNA relaxation experiments involving calf thymus DNA topoisomerase I and pBR322 DNA reveal that bleomycin bithiazole analogues unwind closed circular duplex DNA. The inhibition and unwinding studies together support recent NMR studies suggesting that both bleomycin A2 and synthetic bithiazole derivatives bind to DNA by an intercalative mechanism. The results are discussed in relation to the DNA breakage properties of bleomycin A2.     

Vavien: an algorithm for prioritizing candidate disease genes based on topological similarity of proteins in interaction networks

Genome-wide linkage and association studies have demonstrated promise in identifying genetic factors that influence health and disease. An important challenge is to narrow down the set of candidate genes that are implicated by these analyses. Protein-protein interaction (PPI) networks are useful in extracting the functional relationships between known disease and candidate genes, based on the principle that products of genes implicated in similar diseases are likely to exhibit significant connectivity/proximity. Information flow?based methods are shown to be very effective in prioritizing candidate disease genes. In this article, we utilize the topology of PPI networks to infer functional information in the context of disease association. Our approach is based on the assumption that PPI networks are organized into recurrent schemes that underlie the mechanisms of cooperation among different proteins. We hypothesize that proteins associated with similar diseases would exhibit similar topological characteristics in PPI networks. Utilizing the location of a protein in the network with respect to other proteins (i.e., the "topological profile" of the proteins), we develop a novel measure to assess the topological similarity of proteins in a PPI network. We then use this measure to prioritize candidate disease genes based on the topological similarity of their products and the products of known disease genes. We test the resulting algorithm, Vavien, via systematic experimental studies using an integrated human PPI network and the Online Mendelian Inheritance in Man (OMIM) database. Vavien outperforms other network-based prioritization algorithms as shown in the results and is available at www.diseasegenes.org.     

小鼠对不同拓扑性质图形的识别

视觉感知的一系列研究都支持大范围拓扑感知的理论．拓扑性质作为整体性质,是视觉感知的基础．视觉对图形拓扑特征差异的感知要优先于对局部特征差异的感知．采用Y迷宫研究了小鼠对不同拓扑性质图形的识别．训练小鼠学习识别圆环和实心矩形这一对拓扑性质不同的图形,之后用拓扑特征相同或不同的其他图形测试小鼠,这些图形包括空心矩形、实心圆、缺口的圆环、缺口的空心矩形．实验结果表明,学会识别圆环(奖励)和实心矩形(无奖励)的小鼠无法区分实心圆和实心矩形以及圆环和空心矩形,但是能够分别从缺口圆环、缺口的空心矩形、实心圆与空心矩形组成的图形对中识别出空心矩形．因此证实了小鼠的视觉系统能够感知拓扑特征的差异并且具有对拓扑性质的概括能力．结果为拓扑知觉对视觉系统来说是基本的这一假设提供了证据．     

Functional coherence in domain interaction networks

MOTIVATION: Extracting functional information from protein-protein interactions (PPI) poses significant challenges arising from the noisy, incomplete, generic and static nature of data obtained from high-throughput screening. Typical proteins are composed of multiple domains, often regarded as their primary functional and structural units. Motivated by these considerations, domain-domain interactions (DDI) for network-based analyses have received significant recent attention. This article performs a formal comparative investigation of the relationship between functional coherence and topological proximity in PPI and DDI networks. Our investigation provides the necessary basis for continued and focused investigation of DDIs as abstractions for functional characterization and modularization of networks. RESULTS: We investigate the problem of assessing the functional coherence of two biomolecules (or segments thereof) in a formal framework. We establish essential attributes of admissible measures of functional coherence, and demonstrate that existing, well-accepted measures are ill-suited to comparative analyses involving different entities (i.e. domains versus proteins). We propose a statistically motivated functional similarity measure that takes into account functional specificity as well as the distribution of functional attributes across entity groups to assess functional similarity in a statistically meaningful and biologically interpretable manner. Results on diverse data, including high-throughput and computationally predicted PPIs, as well as structural and computationally inferred DDIs for different organisms show that: (i) the relationship between functional similarity and network proximity is captured in a much more (biologically) intuitive manner by our measure, compared to existing measures and (ii) network proximity and functional similarity are significantly more correlated in DDI networks than in PPI networks, and that structurally determined DDIs provide better functional relevance as compared to computationally inferred DDIs.     

Topological comparison of two helix destabilizing proteins: ribonuclease A and the gene 5 DNA binding protein

A topological comparison of the two helix destabilizing proteins, pancreatic ribonuclease A and the gene 5 DNA binding protein of bacteriophage fd has been completed utilizing the available high resolution tertiary structures of each protein. The results indicate these two proteins are structurally if not also evolutionarily related. Regions of closet topological equivalence occur between beta loops directly involved in nucleotide binding or are required for the maintenance of their respective oligonucleotide binding channels. In addition, there is a similar placement of critical amino acid side chains about the binding site. Further evidence for this structural relationship is obtained by comparison of structural data for the mode of complexation of polynucleotides to each protein. The results of topological comparison suggest the essential property shared by helix destabilizing proteins, whether specialized DNA binding proteins such as G5BP or proteins with other primary functional roles, like ribonuclease A, is the presence of an elongated oligonucleotide binding channel. Although ribonuclease A and G5BP are structurally related, it seems likely any protein with this structural feature will exhibit a helix destabilizing capacity. This conclusion is supported by the diversity of molecular characteristics shown by other proteins having this activity.     

Role of hERG potassium channel assays in drug development

Numerous structurally and functionally unrelated drugs block the hERG potassium channel. HERG channels are involved in cardiac action potential repolarization, and reduced function of hERG lengthens ventricular action potentials, prolongs the QT interval in an electrocardiogram, and increases the risk for potentially fatal ventricular arrhythmias. In order to reduce the risk of investing resources in a drug candidate that fails preclinical safety studies because of QT prolongation, it is important to screen compounds for activity on hERG channels early in the lead optimization process. A number of hERG assays are available, ranging from high throughput binding assays on stably expressed recombinant channels to very time consuming electrophysiological examinations in cardiac myocytes. Depending on the number of compounds to be tested, binding assays or functional assays measuring membrane potential or Rb(+) flux, combined with electrophysiology on a few compounds, can be used to efficiently develop the structure-function relationship of hERG interactions.     

Role of hERG potassium channel assays in drug development

Numerous structurally and functionally unrelated drugs block the hERG potassium channel. HERG channels are involved in cardiac action potential repolarization, and reduced function of hERG lengthens ventricular action potentials, prolongs the QT interval in an electrocardiogram, and increases the risk for potentially fatal ventricular arrhythmias. In order to reduce the risk of investing resources in a drug candidate that fails preclinical safety studies because of QT prolongation, it is important to screen compounds for activity on hERG channels early in the lead optimization process. A number of hERG assays are available, ranging from high throughput binding assays on stably expressed recombinant channels to very time consuming electrophysiological examinations in cardiac myocytes. Depending on the number of compounds to be tested, binding assays or functional assays measuring membrane potential or Rb+ flux, combined with electrophysiology on a few compounds, can be used to efficiently develop the structure-function relationship of hERG interactions.     

Classification of doubly wound nucleotide binding topologies using automated loop searches

A classification is presented of doubly wound α/β nucleotide binding topologies, whose binding sites are located in the cleft formed by a topological switch point. In particular, the switch point loop nearest the N-terminus is used to identify specific structural classes of binding protein. This yields seven structurally distinct loop conformations, which are subsequently used as motifs for scanning the Protein Data Bank. The searches, which are effective at identifying functional relationships within a large database of structures, reveal a remarkable and previously unnoticed similarity between the coenzyme binding sites of flavodoxin and tryptophan synthetase, even though there is no sequence or topological similarity between them.     

Topological Comparison of Two Helix Destabilizing Proteins: Ribonuclease A and the Gene 5 DNA Binding Protein

Abstract

A topological comparison of the two helix destabilizing proteins, pancreatic ribonuclease A and the gene S DNA binding protein of bacteriophage fd has been completed utilizing the available high resolution tertiary structures of each protein. The results indicate these two proteins are structurally if not also evolutionarily related. Regions of closest topological equivalence occur between beta loops directly involved in nucleotide binding or are required for the maintenance of their respective oligonucleotide binding channels. In addition, there is a similar placement of critical amino acid side chains about the binding site. Further evidence for this structural relationship is obtained by comparison of structural data for the mode of complexation of polynucleotides to each protein. The results of topological comparison suggest the essential property shared by helix destabilizing proteins, whether specialized DNA binding proteins such as G5BP or proteins with other primary functional roles, like ribonuclease A, is the presence of an elongated oligonucleotide binding channel. Although ribonuclease A and G5BP are structurally related, it seems likely any protein with this structural feature will exhibit a helix destabilizing capacity. This conclusion is supported by the diversity of molecular characteristics shown by other proteins having this activity.     

Hair analysis for drugs of abuse XXI. Effect of para-substituents on benzene ring of methamphetamine on drug incorporation into rat hair

In order to study the effect of para-substituents on the benzene ring of methamphetamine on drug incorporation into hair from blood, the plasma AUCs and hair concentrations of 7 methamphetamines [methamphetamine(MA), p-hydroxymethamphetamine(OHMA), p-bromomethamphetamine (BMA), p-aminomethamphetamine (AMA), p-nitromethamphetamine (NMA), p-methoxymethamphetamine (MOMA) and 3,4-methylenedioxymethamphetamine (MDMA)] plus propylhexedrine(PHX) in DA rats was determined after intraperitoneal injection at 5 mg/kg, with single dose for the plasma AUC and 10 doses for the hair concentration. Drug incorporation rates into hair (ICRs) were calculated by dividing each hair concentration by each plasma AUC. Comparing the highest value (NMA) to the lowest one (OHMA), the ICR of NMA was 31.7 times larger than that of OHMA. Using the ICR of MA which has no substitute on the benzene ring as a base point, nitro, bromo, methylenedioxy, methoxy and amino groups raised the drug incorporation into rat hair in this order. On the other hand, hydroxy substitution showed a negative effect on the ICR. In comparison between the ICRs of MA and PHX, it was found that the benzene ring shows higher affinity to melanin and less lipophilicity than the cyclohexyl ring. Our results showed that there is a relatively strong effect of the functional groups on drug incorporation into hair. The combination of melanin affinity and lipophilicity are clearly correlated with their ICR.     

Density functional theory investigation of cocaine water complexes

Twenty cocaine–water complexes were studied using density functional theory (DFT) B3LYP/6-311++G** level to understand their geometries, energies, vibrational frequencies, charge transfer and topological parameters. Among the 20 complexes, 12 are neutral and eight are protonated in the cocaine-water complexes. Based on the interaction energy, the protonated complexes are more stable than the neutral complexes. In both complexes, the most stable structure involves the hydrogen bond with water at nitrogen atom in the tropane ring and C?=?O groups in methyl ester. Carbonyl groups in benzoyl and methyl ester is the most reactive site in both forms and it is responsible for the stability order. The calculated topological results show that the interactions involved in the hydrogen bond are electrostatic dominant. Natural bond orbital (NBO) analysis confirms the presence of hydrogen bond and it supports the stability order. Atoms in molecules (AIM) and NBO analysis confirms the C-H?·?·?·?O hydrogen bonds formed between the cocaine-water complexes are blue shifted in nature.     

Structural alerts for predicting clastogenic activity of pro-oxidant flavonoid compounds: quantitative structure-activity relationship study

Flavonoids have been reported to exert multiple biological effects that include acting as pro-oxidants at very high doses. The authors determined a structural alert to identify the clastogenic activity of a series of flavonoids with pro-oxidant activity. The methodology was based on a quantitative structure-activity relationship (QSAR) study. Specifically, the authors developed a virtual screening method for a clastogenic model using the topological substructural molecular design (TOPS-MODE) approach. It represents a useful platform for the automatic generation of structural alerts, based on the calculation of spectral moments of molecular bond matrices appropriately weighted, taking into account the hydrophobic, electronic, and steric molecular features. Therefore, it was possible to establish the structural criteria for maximal clastogenicity of pro-oxidant flavonoids: the presence of a 3-hydroxyl group and a 4-carbonyl group in ring C, the maximal number of hydroxyl groups in ring B, the presence of methoxyl and phenyl groups, the absence of a 2,3-double bond in ring C, and the presence of 5,7 hydroxyl groups in ring A. The presented clastogenic model may be useful for screening new pro-oxidant compounds. This alert could help in the design of new and efficient flavonoids, which could be used as bioactive compounds in nutraceuticals and functional food.     

Identification of potential host proteins for influenza A virus based on topological and biological characteristics by proteome-wide network approach

A proteome-wide network approach was performed to characterize significant patterns of influenza A virus (IAV)-human interactions, and to further identify potentially valuable targets for prophylactic and therapeutic interventions. Topological analysis demonstrated a strong tendency for IAV to interplay with highly connected and central proteins located in sparsely connected sub-networks. Additionally, functional analysis based on biological process revealed a number of functional groups overrepresented for IAV interactions, in which regulation of cell death and apoptosis, and phosphorus metabolic process is the most highly enriched. In order to investigate whether these topological and biological features are significant enough to distinguish IAV targets from human proteome, a discrimination model was constructed based on these features using support vector machine coupled with genetic algorithm. The average result of overall prediction accuracy is 71.04% by leave-one-out across validation test. The optimized classifier was then applied to 9706 human proteins. As a result, 1418 novel genes were identified from human interactome, some of which were experimentally validated by others' works to be important for IAV infection. The findings presented in this study might be important in discovering new drug targets for therapeutic treatments as well as revealing topological features and functional properties specific for viral infection.     

Structural relationships of homologous proteins as a fundamental principle in homology modeling

Protein structure prediction is based mainly on the modeling of proteins by homology to known structures; this knowledgebased approach is the most promising method to date. Although it is used in the whole area of protein research, no general rules concerning the quality and applicability of concepts and procedures used in homology modeling have been put forward yet. Therefore, the main goal of the present work is to provide tools for the assessment of accuracy of modeling at a given level of sequence homology. A large set of known structures from different conformational and functional classes, but various degrees of homology was selected. Pairwise structure superpositions were performed. Starting with the definition of the structurally conserved regions and determination of topologically correct sequence alignments, we correlated geometrical properties with sequence homology (defined by the 250 PAM Dayhoff Matrix) and identity. It is shown that both the topological differences of the protein backbones and the relative positions of corresponding side chains diverge with decreasing sequence identity. Below 50% identity, the deviation in regions that are structurally not conserved continually increases, thus implying that with decreasing sequence identity modeling has to take into account more and more structurally diverging loop regions that are difficult to predict. © 1993 Wiley-Liss, Inc.     

Predicting candidate genes based on combined network topological features: a case study in coronary artery disease

Predicting candidate genes using gene expression profiles and unbiased protein-protein interactions (PPI) contributes a lot in deciphering the pathogenesis of complex diseases. Recent studies showed that there are significant disparities in network topological features between non-disease and disease genes in protein-protein interaction settings. Integrated methods could consider their characteristics comprehensively in a biological network. In this study, we introduce a novel computational method, based on combined network topological features, to construct a combined classifier and then use it to predict candidate genes for coronary artery diseases (CAD). As a result, 276 novel candidate genes were predicted and were found to share similar functions to known disease genes. The majority of the candidate genes were cross-validated by other three methods. Our method will be useful in the search for candidate genes of other diseases.     

基于功能一致性和网络拓扑属性预测冠心病致病基因

基于功能一致性利用蛋白质互作网络挖掘潜在的疾病致病基因,对于了解疾病致病机理和改进临床治疗至关重要．基于基因功能一致性和其在蛋白质互作网络中的拓扑属性将基因与疾病之间建立关联,对疾病风险位点内的基因进行了致病风险预测,并通过GO及KEGG功能富集分析方法进一步筛选,预测出新的致病基因．预测出了51个新的冠心病致病基因,分析发现大部分基因参与了冠心病的致病过程．为疾病基因的挖掘提出一个新的思路,从而有助于复杂疾病致病机理的研究．     

Development and validation of a robust QSAR model for prediction of carcinogenicity of drugs

Carcinogenicity is one of the toxicological endpoints causing the highest concern. Also, the standard bioassays in rodents used to assess the carcinogenic potential of chemicals and drugs are extremely long, costly and require the sacrifice of large numbers of animals. For these reasons, we have attempted development of a global quantitative structure-activity relationship (QSAR) model using a data set of 1464 compounds (the Galvez data set available from http://www.uv.es/-galvez/tablevi.pdf), including many marketed drugs for their carcinogenesis potential. Though experimental toxicity testing using animal models is unavoidable for new drug candidates at an advanced stage of drug development, yet the developed global QSAR model can in silico predict the carcinogenicity of new drug compounds to provide a tool for initial screening of new drug candidate molecules with reduced number of animal testing, money and time. Considering large number of data points with diverse structural features used for model development (n(training) = 732) and model validation (n(test) = 732), the model developed in this study has an encouraging statistical quality (leave-one-out Q2 = 0.731, R2pred = 0.716). Our developed model suggests that higher lipophilicity values and conjugated ring systems, thioketo and nitro groups contribute positively towards drug carcinogenicity. On the contrary, tertiary and secondary nitrogens, phenolic, enolic and carboxylic OH fragments and presence of three-membered rings reduce the carcinogenicity. Branching, size and shape are found to be crucial factors for drug-induced carcinogenicity. One may consider all these points to reduce carcinogenic potential of the molecules.