Abstract: Carcinoma of the urinary bladder is the most common malignancy in many tropical and subtropical countries due to endemic infection by Schistosoma hematobium (bilharzia). In the current study, we performed a high-resolution analysis of gene copy number amplifications using array comparative genomic hybridization to compare DNA copy number changes in pools of Schistosoma-associated (SA) and non-Schistosoma-associated (NSA) bladder cancer (BC). Many DNA copy number changes were detected in all studies, with multiple gains and losses of genetic material. The most frequent alterations were gains on 5p15.2 approximately p15.33, 8q13.1, and 11q13, and losses on 8p21.3 approximately p22 and 22q13. Even when SA pools showed no Schistosoma-specific gene copy number profiling as compared to NSA pools, some genes seemed to be gained (ELN on 7q11.23) and some lost (PRKAG3 on 2q35 and PRDM6 on 5q23.2) in SA-SCC. The following genes were gained in all histopathologic categories: SRC (20q11.23), CEBPB (20q13.13), and GPR9 (Xq13.1). Our study did not provide clear evidence of differences in carcinogenesis of SA-BC and NSA-BC.
Abstract: BACKGROUND: Tissue plasminogen activator (tPA) is the major activator of plasminogen in plasma. This serine protease is overexpressed by exocrine pancreas tumour cells, where it promotes tumour cell proliferation, growth, and invasion. Here we have explored the signalling pathways used by tPA to activate the proliferation of pancreatic cancer cells. METHODS: Transcriptional profiling on cDNA micro arrays was used to analyse the pattern of gene expression in response to tPA compared to the response to epidermal growth factor (EGF) and platelet derived growth factor (PDGF). Results were confirmed using different biochemical assays in which specific kinase inhibitors or RNA interference were used. RESULTS: Transcriptional profiling showed that tPA modulates the expression of a set of genes commonly regulated by EGF, but distinct from the major set of genes modulated by PDGF. This suggested that tPA and EGF share common signalling pathways, a conclusion supported by further experimental evidence. Firstly, we found that tPA induced a rapid and transient phosphorylation of the EGFR. Secondly, specific EGFR kinase inhibitors, but not PDGFR kinase inhibitors, abolished the tPA induced phosphorylation of the ERK1/2 kinases and cell proliferation. The mitogenic activity of tPA was also inhibited by siRNA depletion of EGFR, thus confirming the involvement of this receptor in tPA triggered signalling. Thirdly, we show that the signalling and mitogenic effects of tPA require its proteolytic activity, the activity of the metalloprotease-9 and active hb-EGF. CONCLUSION: Our results suggest that tPA induces proliferation by triggering a proteolytic cascade that sequentially activates plasmin, metalloprotease-9 (MMP-9) and hb-EGF. These events are required to activate the EGFR signalling pathway and cell proliferation.
Abstract: Bladder cancer is a common malignancy requiring a high degree of surveillance because of the frequent recurrences and the poor clinical outcome of invasive disease. To date, serum biomarkers for bladder cancer lack optimal sensitivity and specificity to assist in diagnosis and disease categorization. Here, we designed antibody arrays for bladder cancer by selecting antibodies against targets differentially expressed in bladder tumors. Serum protein profiles measured by an antibody array containing 254 antibodies discriminated bladder cancer patients from controls (n = 95) with a correct classification rate of 93.7%. A second independent antibody array containing 144 antibodies revealed that protein profiles provide predictive information by stratifying patients with bladder tumors (n = 37) based on their overall survival (P = 0.0479). In addition, serum proteins, such as c-met, that were top ranked at identifying bladder cancer patients were associated with pathological stage, tumor grade, and survival when validated by immunohistochemistry of tissue microarrays containing bladder tumors (n = 173). This study provides experimental evidence for the use of several integrated technologies strengthening the process of biomarker discovery. Serum protein profiles obtained by antibody arrays represent comprehensive means for bladder cancer diagnosis and clinical outcome stratification, which could potentially assist in selection of cancer patients who would benefit from early, individualized therapeutic intervention.
Abstract: Genomic copy number changes are frequently found in cancers and they have been demonstrated to contribute to carcinogenesis; and it is widely accepted that tumors with microsatellite instability (MSI) are genetically stable and mostly diploid. In the present study we compared the copy number alterations and the gene-expression profiles of microsatellite stable (MSS) and MSI colorectal tumors. A total number of 31 fresh-frozen primary tumors (16 MSS and 15 MSI) were used. Twenty-eight samples (15 MSS and 13 MSI) were analyzed with metaphase comparative genomic hybridization (CGH), nine of which plus one additional sample (4 MSS and 6 MSI) were further analyzed by cDNA-based array-CGH. Gene expression analysis was performed with six samples [3 MSS and 3 MSI, four of these used in metaphase CGH (mCGH) analysis] to identify differentially expressed genes possibly located in the lost or amplified regions found by CGH, stressing the biological significance of copy number changes. Metaphase and array-CGH analysis of two colon cancer cell lines (HTC116 and SW480, reported as MSI and MSS archetypes) gave comparable results. Alterations found by mCGH in MSS tumors were +20, +8q, -8p and -18q. Interestingly, 1p22, 4q26 and 15q21 were found deleted preferentially in MSS tumors, while 22q13 was found gained in MSI tumors. The regions of alterations identified by array-CGH were gains at 8q24, 16q24.3 and 20q13, and the loss of 5q21, appearing in the both types of tumors. Gene expression analysis revealed genes with specific associations with the copy number changes of the corresponding genomic regions. As a conclusion, colorectal cancer is a heterogeneous disease, demonstrated by the genomic profiles of individual samples. However, our data shows that copy number changes do not occur exclusively in the MSS phenotypes.
Abstract: PURPOSE: Bladder cancer is a common malignancy characterized by a poor clinical outcome when tumors progress into invasive disease. We sought to define genetic signatures characteristic of aggressive clinical behavior in advanced bladder tumors. METHODS: Oligonucleotide arrays were utilized to analyze the transcript profiles of 105 bladder tumors: 33 superficial, 72 invasive lesions, and 52 normal urothelium. Hierarchical clustering and supervised algorithms were used to classify and stratify bladder tumors on the basis of stage, node metastases, and overall survival. Immunohistochemical analyses on bladder cancer tissue arrays (n = 294 cases) served to validate associations between marker expression, staging and outcome. RESULTS: Hierarchical clustering classified normal urothelium, superficial, and invasive tumors with 82.2% accuracy, and stratified bladder tumors on the basis of clinical outcome. Predictive algorithms rendered an 89%-correct rate for tumor staging using genes differentially expressed between superficial and invasive tumors. Accuracies of 82% and 90% were obtained for predicting overall survival when considering all patients with bladder cancer or only patients with invasive disease, respectively. A genetic profile consisting of 174 probes was identified in those patients with positive lymph nodes and poor survival. Two independent Global Test runs confirmed the robust association of this profile with lymph node metastases (P = 7.3(-13)) and overall survival (P = 1.9(-14)) simultaneously. Immunohistochemical analyses on tissue arrays sustained the significant association of synuclein with tumor staging and clinical outcome (P = .002). CONCLUSION: Gene profiling provides a genomic-based classification scheme of diagnostic and prognostic utility for stratifying advanced bladder cancer. Identification of this poor outcome profile could assist in selecting patients who may benefit from more aggressive therapeutic intervention.
Abstract: AMarge is a web tool for the automatic quality assessment of Affymetrix GeneChip data. It is essential to have a trustworthy set of chips in order to derive gene expression data for phenotypic analysis, and AMarge provides a complete and rigorous web-accessible tool to fulfill this need. The quality assessment steps include image plots of weights derived from a robust linear model fit of the data, a 3'/5' RNA digestion plot, and Affymetrix Microarray Suite version 5.0 (MAS 5.0) quality standard procedures. Furthermore, robust multi-array average expression values are generated in order to have a start-up expression set for the subsequent analysis. The results of the complete analysis are summarised and returned as an HTML report. AVAILABILITY: The AMarge web interface is accessible at http://nin.crg.es/cgi-binf/AMargeWeb.cgi. A mirror server is also available at http://bioinformatics.istge.it/AMarge-bin/AMargeWeb.cgi. The software implementing all these methods is part of the Bioconductor project (http://www.bioconductor.org).
Abstract: OBJECTIVES: To determine the impact of different levels of RNA degradation on gene expression measurements and to ascertain if the gene expression profile obtained from bladder washing (BW) correlates to that obtained from the related bladder tumour (BT). METHODS: BT and BW RNAs from the same patient were heat shocked to obtain three RNA degradation states, which were compared with intact RNAs from healthy bladders by using complementary DNA (cDNA) microarrays. All samples were amplified by means of a T3N9-based transcription method. In addition, four of the differentially expressed genes in microarrays related to bladder cancer (KRT20, IGF2, GSN, and CCL2) were analyzed in 36 tumoural and 14 control BW samples by quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR). RESULTS: A high percentage of overlapping differentially expressed genes were detected between BT arrays (85-91%) and between BW arrays (78-93%). Furthermore, the similarity between BW and BT arrays was relatively high and independent of the RNA degradation state (52-60%). Finally, expression differences for the four selected genes were confirmed in the vast majority of extended BW samples tested by qRT-PCR. CONCLUSIONS: Our results showed that partially degraded RNA samples analyzed by cDNA microarrays yielded gene expression profiles comparable to those obtained using intact RNA. Moreover, BW RNA exhibited gene expression patterns similar to those identified in the BT, indicating that BW is an appropriate sample for studying gene expression profiles of BT using cDNA microarrays. In addition, qRT-PCR results further support the suitability of BW for gene expression profiling and its potential use for routine diagnostics.
Abstract: BACKGROUND: We use an approach based on Factor Analysis to analyze datasets generated for transcriptional profiling. The method groups samples into biologically relevant categories, and enables the identification of genes and pathways most significantly associated to each phenotypic group, while allowing for the participation of a given gene in more than one cluster. Genes assigned to each cluster are used for the detection of pathways predominantly activated in that cluster by finding statistically significant associated GO terms. We tested the approach with a published dataset of microarray experiments in yeast. Upon validation with the yeast dataset, we applied the technique to a prostate cancer dataset. RESULTS: Two major pathways are shown to be activated in organ-confined, non-metastatic prostate cancer: those regulated by the androgen receptor and by receptor tyrosine kinases. A number of gene markers (HER3, IQGAP2 and POR1) highlighted by the software and related to the later pathway have been validated experimentally a posteriori on independent samples. CONCLUSION: Using a new microarray analysis tool followed by a posteriori experimental validation of the results, we have confirmed several putative markers of malignancy associated with peptide growth factor signalling in prostate cancer and revealed others, most notably ERRB3 (HER3). Our study suggest that, in primary prostate cancer, HER3, together or not with HER4, rather than in receptor complexes involving HER2, could play an important role in the biology of these tumors. These results provide new evidence for the role of receptor tyrosine kinases in the establishment and progression of prostate cancer.
Abstract: To identify gene expression changes along progression of bladder cancer, we compared the expression profiles of early-stage and advanced bladder tumors using cDNA microarrays containing 17,842 known genes and expressed sequence tags. The application of bootstrapping techniques to hierarchical clustering segregated early-stage and invasive transitional carcinomas into two main clusters. Multidimensional analysis confirmed these clusters and more importantly, it separated carcinoma in situ from papillary superficial lesions and subgroups within early-stage and invasive tumors displaying different overall survival. Additionally, it recognized early-stage tumors showing gene profiles similar to invasive disease. Different techniques including standard t-test, single-gene logistic regression, and support vector machine algorithms were applied to identify relevant genes involved in bladder cancer progression. Cytokeratin 20, neuropilin-2, p21, and p33ING1 were selected among the top ranked molecular targets differentially expressed and validated by immunohistochemistry using tissue microarrays (n = 173). Their expression patterns were significantly associated with pathological stage, tumor grade, and altered retinoblastoma (RB) expression. Moreover, p33ING1 expression levels were significantly associated with overall survival. Analysis of the annotation of the most significant genes revealed the relevance of critical genes and pathways during bladder cancer progression, including the overexpression of oncogenic genes such as DEK in superficial tumors or immune response genes such as Cd86 antigen in invasive disease. Gene profiling successfully classified bladder tumors based on their progression and clinical outcome. The present study has identified molecular biomarkers of potential clinical significance and critical molecular targets associated with bladder cancer progression.
Abstract: The selection of a sample of diverse compounds is a common strategy for exploring large molecular libraries. However, the success of such approach depends on the selection of relevant molecular descriptors and the use of appropriate sampling methods. In the context of pharmaceutical research, the molecular descriptors should be based on physicochemical properties related with the pharmacological behaviour of the compounds. In this sense, the alignment-free GRIND and VolSurf molecular descriptors are promising candidates since they have been successfully used in the modelling of both pharmacodynamic and pharmacokinetic properties of drugs. This work describes the use of such descriptors in the diversity sampling of a library of primary amines and compares the results with those obtained in a previous study that used quantum-mechanical descriptors. As in the previous work, principal component (PC) analysis was applied to reduce the dimensionality and remove redundant information of the original descriptors, and the compounds were sampled on the basis of k-means clustering on the space of the selected PCs. The results of the present study show that VolSurf and GRIND provide similar quality sampling regarding global features of the molecules such as hydrophilicity, however the topology of the compounds is considered differently. The similarity between particular compounds strongly depends on the original descriptors used. However all the sample selections done in the PC space after k-means clustering provide the same apparent diversity in comparison to the whole dataset. The results indicate that there is no best set of descriptors on a diversity basis. The selection of descriptors must be based on the drug features to be investigated.
Abstract: The present study introduces a new strategy of selection of a maximum diversity sample of n compounds from N available in a molecular database. This strategy can be useful in pharmacological screening, combinatorial chemistry or parallel synthesis planning. It consists of first describing the compounds by means of parameters derived from quantum mechanical computations (water solvation deltaG, benzene solvation deltaG, octanol solvation deltaG, dipolar moment), as well as standard molecular parameters such as solvent-accessible surface area and molecular weight. Solvation parameters are used because of the importance of this phenomenon in the pharmacological behaviour. Redundant information in the description of the compounds is eliminated by using principal components (PC) instead of the original descriptors. Based on the similarity between the N compounds in the PC space, they are classified into n groups by k-means cluster analysis. The compounds that are nearest to the centroid of each cluster constituted the maximum diversity sample. When practical difficulties exist for the use of one of the proposed compounds, another also close to the cluster centroid can substitute for it. This strategy has been tested in the selection of a sample of 50 amines from the 923 available in the Aldrich catalogue. The results have been contrasted with those obtained from an optimal, distance-based experimental design, resulting in an 86% of agreement between both approaches. An R(2)-like diversity coefficient has been used to assess the quality of the proposed solutions.
Abstract: All protein sequences from 19 complete chloroplast genomes (cpDNA) have been studied using a new computational method able to analyze functional correlations among series of protein sequences contained in complete proteomes. First, all open reading frames (ORFs) from the cpDNAs, comprising a total of 2266 protein sequences, were compared against the 3168 proteins from Synechocystis PCC6803 complete genome to find functionally related orthologous proteins. Additionally, all cpDNA genomes were pairwise compared to find orthologous groups not present in cyanobacteria. Annotations in the cluster of othologous proteins database and CyanoBase were used as reference for the functional assignments. Following this protocol, new functional assignments were made for ORFs of unknown function and for ycfs (hypothetical chloroplast frames), which still lack a functional assignment. Using this information, a matrix of functional relationships was derived from profiles of the presence and/or absence of orthologous proteins; the matrix included 1837 proteins in 277 orthologous clusters. A factor analysis study of this matrix, followed by cluster analysis, allowed us to obtain accurate phylogenetic reconstructions and the detection of genes probably involved in speciation as phylogenetic correlates. Finally, by grouping common evolutionary patterns, we show that it is possible to determine functionally linked protein networks. This has allowed us to suggest putative associations for some unknown ORFs.
Abstract: The prostaglandin-endoperoxide H synthase-1 (PGHS- 1) and prostaglandin-endoperoxide H synthase-2 (PGHS-2) are the targets of nonsteroidal anti-inflammatory drugs (NSAIDs). It appears that the high degree of selectivity for inhibition of PGHS-2 shown by certain compounds is the result of two mechanisms (time-dependent, time-independent inhibition), by which they interact with each isoform. Molecular models of the complexes formed by indomethacin, sulindac, fenamates, 2-phenylpropionic acids and selective cyclooxygenase-2 (COX-2) inhibitors with the cyclooxygenase active site of human PGHS-2 have been built, paying particular attention to water molecules that participate in the hydrogen-bonding network at the polar active site entrance. The stability of the complexes has been assessed by molecular dynamics simulations and interaction energy decomposition analysis, and their biological significance has been discussed in light of available X-ray crystallographic and kinetic results. The selective PGHS-2 inhibitors exploit the extra space of a side-pocket in the active site of PGHS-2 that is not found in PGHS-1. The results suggest that active site hydration together with residues Tyr355, Glu524, Arg120 and Arg513 are crucial to understand the time-dependent inhibition mechanism. A marked relationship between the isoform selectivity and tightly interactions with residues into the side pocket bordered by Val523 is also found.
Abstract: The prostaglandin endoperoxide H synthase-1 (PGHS-1) and prostaglandin endoperoxide H synthase-2 (PGHS-2) are the targets of non-steroidal anti-inflammatory drugs (NSAIDs). The high degree of selectivity for inhibition of PGHS-2 shown by certain compounds appears to stem from two mechanisms (time-dependent, time-independent inhibition) by which they interact with each isoform. Molecular models of the complexes between indomethacin, fenamates, 2-phenylpropionic acids and the selective cyclooxygenase-2 (COX-2) inhibitors, with the cyclooxygenase active site of human PGHS-2 have been built by combining homology modelling, conformational searching and automated docking techniques. The stability of the resulting complexes has been assessed by molecular dynamics simulations combined with extended linear response calculations. The results allow us to identify regions of biological significance consistent with both X-ray crystallographic and kinetic results. The selective PGHS-2 inhibitors exploit the extra space of a side-pocket in the active site of PGHS-2 that is not found in PGHS-1. The results obtained point out a marked relationship between the experimental affinity and the electrostatic interaction energy alone for a series of NSAIDs. Analysis of the structural and the energetic data provides evidence supporting that network of hydrogen bonds between Tyr355, Glu524, Arg120 and Arg513 might be involved in mediating the binding of the time-dependent inhibitors of PGHS-2.
Abstract: In a search for molecular markers of progression in prostate cancer by means of differential display, we have identified a new gene, which we have designated PTOV1. Semiquantitative RT-PCR has established that nine out of 11 tumors overexpress PTOV1 at levels significantly higher than benign prostatic hyperplasia or normal prostate tissue. The human PTOV1 protein consists almost entirely of two repeated blocks of homology of 151 and 147 amino acids, joined by a short linker peptide, and is encoded by a 12-exon gene localized in chromosome 19q13.3. A Drosophila melanogaster PTOV1 homolog also contains two tandemly arranged PTOV blocks. A second gene, PTOV2, was identified in humans and Drosophila, coding for proteins with a single PTOV homology block and unrelated amino- and carboxyl-terminal extensions. A 1.8-Kb PTOV1 transcript was detected abundantly in normal human brain, heart, skeletal muscle, kidney and liver, and at low levels in normal prostate. Immunocytochemical analysis and expression of chimeric GFP-PTOV1 proteins in cultured cells showed a predominantly perinuclear localization of PTOV1. In normal prostate tissue and in prostate adenomas, PTOV1 was undetectable or expressed at low levels, whereas nine out of 11 prostate adenocarcinomas showed a strong immunoreactivity, with a focal distribution in areas of carcinoma and prostatic intraepithelial neoplasia. Therefore, PTOV1 is a previously unknown gene, overexpressed in early and late stages of prostate cancer. The PTOV homology block represents a new class of conserved sequence blocks present in human, rodent and fly proteins.
Abstract: SUMMARY: MIPSIM is a computational package designed to analyse and compare 3D distributions of molecular interaction potentials (MIP) of series of biomolecules.
Abstract: Many heterocyclic amines (HCA) present in cooked food exert a genotoxic activity when they are metabolised (N-oxidated) by the human cytochrome P450 1A2 (CYP1A2h). In order to rationalize the observed differences in activity of this enzyme on a series of 12 HCA, 3D-QSAR methods were applied on the basis of models of HCA-CYP1A2h complexes. The CYP1A2h enzyme model has been previously reported and was built by homology modeling based on cytochrome P450 BM3. The complexes were automatically generated applying the AUTODOCK software and refined using AMBER. A COMBINE analysis on the complexes identified the most important enzyme-ligand interactions that account for the differences in activity within the series. A GRID/GOLPE analysis was then performed on just the ligands, in the conformations and orientations found in the modeled complexes. The results from both methods were concordant and confirmed the advantages of incorporating structural information from series of ligand-receptor complexes into 3D-QSAR methodologies.
Abstract: UEV proteins are enzymatically inactive variants of the E2 ubiquitin-conjugating enzymes that regulate noncanonical elongation of ubiquitin chains. In Saccharomyces cerevisiae, UEV is part of the RAD6-mediated error-free DNA repair pathway. In mammalian cells, UEV proteins can modulate c-FOS transcription and the G2-M transition of the cell cycle. Here we show that the UEV genes from phylogenetically distant organisms present a remarkable conservation in their exon-intron structure. We also show that the human UEV1 gene is fused with the previously unknown gene Kua. In Caenorhabditis elegans and Drosophila melanogaster, Kua and UEV are in separated loci, and are expressed as independent transcripts and proteins. In humans, Kua and UEV1 are adjacent genes, expressed either as separate transcripts encoding independent Kua and UEV1 proteins, or as a hybrid Kua-UEV transcript, encoding a two-domain protein. Kua proteins represent a novel class of conserved proteins with juxtamembrane histidine-rich motifs. Experiments with epitope-tagged proteins show that UEV1A is a nuclear protein, whereas both Kua and Kua-UEV localize to cytoplasmic structures, indicating that the Kua domain determines the cytoplasmic localization of Kua-UEV. Therefore, the addition of a Kua domain to UEV in the fused Kua-UEV protein confers new biological properties to this regulator of variant polyubiquitination.
Abstract: PGHS-1 and PGHS-2 are the targets of nonsteroidal anti-inflammatory drugs (NSAIDs). It appears that the high degree of selectivity for inhibition of PGHS-2 shown by certain compounds is the result of two mechanisms (time-dependent and time-independent inhibition), by which they interact with each isoform. The fenamic acids can be divided into competitive inhibitors of substrate binding and competitive inhibitors that cause time-dependent losses of cyclooxygenase activity. The cyclooxygenase activity was measured by oxygen consumption following preincubation of the enzyme and the inhibitor for increasing periods of time. The rate constants associated with binding inhibition kinetics and structure-activity relationships were calculated for a large number of fenamates, diclofenac and indomethacin. The K1* values are similar but the individual rate constants are markedly different: K1 is two-fold lower, and k2 is six-fold slower for diclofenac than for indomethacin. All the active time-dependent compounds show MEPs with a negative conical surface, with their vertex on the minimum of the carboxyl group, which extends around the first aromatic ring to the central region. The conical surface keeps an open angle of 61 degrees or larger, and a close contact surface with the residues Ala527, Ileu523, Val349, and Ser530, in the zones surrounding the bridging amino group and the chlorine atoms for meclofenamate and diclofenac, or in the region around the carbonyl group for indomethacin. The K1* and IC50 values indicate that the interactions that promote the slow binding kinetics must be examined in relation to the reaction energies of formation (delta Hr) of an ionic bond between the deprotonated carboxylic acid group of acid NSAIDs with the monocationic guanidinum group of Arg120, the free energies of solvation in aqueous solution, and the molecular volumes measured. Presumably indomethacin, diclofenac and meclofenamate cause the enzyme to undergo a subtle conformational change to a form that binds compounds even more tightly, with some slight structural changes confined to reorientations of the Arg277 and Gln358 side chains. These results show that the model has reliably chosen regions of biological significance consistent with both the X-ray crystallographic and kinetic results.
Abstract: The open reading frame YGL087c in the budding yeast Saccharomyces cerevisiae genome encodes a polypeptide highly similar to the human UEV (ubiquitin-conjugating E2 enzyme variant) proteins, which have been proposed to belong to a family of putative dominant negative ubiquitin regulators. Deletion of the YGL087c open reading frame yields viable cells which are sensitive to UV irradiation or methyl methanesulfonate, but not to hydroxyurea. This phenotype is reminiscent of that of rad mutants and suggests that the YGL087c-encoded protein functions in a process related to tolerance to DNA damage. We also show that the mutant phenotype is fully complemented by expression of the human UEV-1A cDNA and we propose that UEV-1 proteins could also have a role in protecting higher eukaryotic cells from DNA damaging agents.
Abstract: By means of differential RNA display, we have isolated a cDNA corresponding to transcripts that are down-regulated upon differentiation of the goblet cell-like HT-29-M6 human colon carcinoma cell line. These transcripts encode proteins originally identified as CROC-1 on the basis of their capacity to activate transcription of c-fos. We show that these proteins are similar in sequence, and in predicted secondary and tertiary structure, to the ubiquitin-conjugating enzymes, also known as E2. Despite the similarities, these proteins lack a critical cysteine residue essential for the catalytic activity of E2 enzymes and, in vitro, they do not conjugate or transfer ubiquitin to protein substrates. These proteins constitute a distinct subfamily within the E2 protein family and are highly conserved in phylogeny from yeasts to mammals. Therefore, we have designated them UEV (ubiquitin-conjugating E2 enzyme variant) proteins, defined as proteins similar in sequence and structure to the E2 ubiquitin-conjugating enzymes but lacking their enzymatic activity (HW/GDB-approved gene symbol, UBE2V). At least two human genes code for UEV proteins, and one of them, located on chromosome 20q13.2, is expressed as at least four isoforms, generated by alternative splicing. All human cell types analyzed expressed at least one of these isoforms. Constitutive expression of exogenous human UEV in HT-29-M6 cells inhibited their capacity to differentiate upon confluence and caused both the entry of a larger proportion of cells in the division cycle and an accumulation in G2-M. This was accompanied with a profound inhibition of the mitotic kinase, cdk1. These results suggest that UEV proteins are involved in the control of differentiation and could exert their effects by altering cell cycle distribution.
Abstract: The three-dimensional modelling of proteins is a useful tool to fill the gap between the number of sequenced proteins and the number of experimentally known 3D structures. However, when the degree of homology between the protein and the available 3D templates is low, model building becomes a difficult task and the reliability of the results depends critically on the correctness of the sequence alignment. For this reason, we have undertaken the modelling of human cytochrome P450 1A2 starting by a careful analysis of several sequence alignment strategies (multiple sequence alignments and the TOPITS threading technique). The best results were obtained using TOPITS followed by a manual refinement to avoid unlikely gaps. Because TOPITS uses secondary structure predictions, several methods that are available for this purpose (Levin, Gibrat, DPM, NnPredict, PHD, SOPM and NNSP) have also been evaluated on cytochromes P450 with known 3D structures. More reliable predictions on alpha-helices have been obtained with PHD, which is the method implemented in TOPITS. Thus, a 3D model for human cytochrome P450 1A2 has been built using the known crystal coordinates of P450 BM3 as the template. The model was refined using molecular mechanics computations. The model obtained shows a consistent location of the substrate recognition segments previously postulated for the CYP2 family members. The interaction of caffeine and a carcinogenic aromatic amine (MeIQ), which are characteristic P450 1A2 substrates, has been investigated. The substrates were solvated taking into account their molecular electrostatic potential distributions. The docking of the solvated substrates in the active site of the model was explored with the AUTODOCK programme, followed by molecular mechanics optimisation of the most interesting complexes. Stable complexes were obtained that could explain the oxidation of the considered substrates by cytochrome P450 1A2 and could offer an insight into the role played by water molecules.
Abstract: The new nonsteroidal antiinflammatory drug (NSAID) arylacetic amfenac (2-amino-3-benzoylphenylacetic acid) and 19 substituted derivatives were studied in order to correlate the biological activities with the structure-related parameters. The geometry of amfenac in neutral and anionic form was totally optimized, starting from standard geometries and crystallographic data, using semiempirical AM1 and MNDO quantum-mechanical methods. Conformational analysis shows the existence of a rigid structure for rotations of the acetic acid chain (alpha degrees) and the central carbonyl group (gamma degrees) around the bonds with the phenylamine ring, whereas the carboxyl group (beta degrees) and the phenyl ring of the benzoyl group (delta degrees) can rotate almost freely. Electrostatic potential maps were analyzed and showed that the electrostatic orientation effect seems to make an important contribution to the binding of the active compounds to prostaglandin synthase. An electrostatic orientation model of the binding site is proposed. The frontier orbital charge distribution was also described for each compound. On the other hand, steric, electronic and hydrophobic (log P) parameters were calculated and QSAR analysis showed that the most significant parameter for the antiinflammatory activity was the pi-electron density of the HOMO orbital in the second aromatic ring. These results suggest a possible electronic charge transfer between the aromatic fragments and the receptor.
