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PubMed2002

Microarray analysis of gene expression patterns during healing of rat corneas after excimer laser photorefractive keratectomy.

PURPOSE: To characterize changes over time in the genomic expression profile of rat corneas after excimer laser photorefractive keratectomy (PRK), in an effort to better understand the cellular response to injury and the dynamic changes that occur in gene expression patterns as a wound heals. METHODS: The corneal gene expression profile of 1176 genes at 3 and 7 days after PRK was determined and compared with untreated corneal gene expression patterns by interrogating commercially available cDNA arrays with labeled target cDNA prepared from pooled total RNA harvested from the respective treatment group of adult male rats. The gene expression patterns were inferred based on the hybridization intensities of the probes on the cDNA arrays. The hybridization signals were globally normalized and filtered. The data were analyzed by using hierarchical and k-means clustering algorithms before and after normalization of variances. RESULTS: Of the 1176 cDNA elements on the array, 588 consistently produced similar results in replicate experiments and comprised the data set analyzed in this work. In total, 73 genes were identified, with expression levels that differed by at least threefold at either 3 or 7 days after PRK. At 3 days after PRK, 70 genes were identified with expression levels that differed by more than threefold, compared with the expression level in untreated animals. The expression of 42 genes increased by threefold or more, whereas expression of 28 genes decreased by threefold or more. By day 7 after PRK, the number of genes displaying more than a threefold difference in expression pattern was reduced to 27 genes, 20 of which showed elevated levels, whereas 7 exhibited decreased levels. Hierarchical clustering of the 588 studied genes produced 10 clusters with correlation coefficients of 0.9 or greater. To determine whether any of the clusters were overrepresented by genes with related functions, the cumulative hypergeometric probability was calculated by obtaining the observed number of functionally related genes within each of the 10 clusters. Seven of the clusters were statistically overrepresented by one or more categories of functionally related genes, such as cell cycle regulators, transcription factors, and metabolic pathway genes. Clustering analysis of 56 genes generally considered to influence corneal wound healing produced 10 gene clusters with correlation coefficients of at least 0.9. Expression of 23 of these 56 genes increased at day 3, then decreased at day 7 to levels similar to those on day 0. These included several growth factors (VEGF, FGF, IGF-I), proteases (PAI-1, PAI-2A) and protease inhibitors (TIMP-2 and TIMP-3). Expression of nine genes increased on both days 3 and 7 compared with expression on day 0 (e.g., TGFB1, TGFBIIR, M6P/IGFR-2), and no genes decreased on both days 3 and 7, compared with day 0. CONCLUSIONS: Microarray analysis of 1176 identified 588 genes with reproducible patterns of expression in rat corneas on days 3 and 7 after PRK and 73 genes with a threefold change in expression compared with untreated corneas. Hierarchical clustering of these 588 genes identified 10 clusters of genes with very similar patterns of expression. Clustering of genes with similar patterns of expression implies a common regulatory pathway for the genes within a cluster, and identifies potential new targets for regulating corneal wound healing.

Animals↗

PubMed2006

Cytosine methylation profiles as a molecular marker in non-small cell lung cancer.

Aberrant promoter methylation is frequently observed in different types of lung cancer. Epigenetic modifications are believed to occur before the clinical onset of the disease and hence hold a great promise as early detection markers. Extensive analysis of DNA methylation has been impeded by methods that are either too labor intensive to allow large-scale studies or not sufficiently quantitative to measure subtle changes in the degree of methylation. We used a novel quantitative DNA methylation analysis technology to complete a large-scale cytosine methylation profiling study involving 47 gene promoter regions in 96 lung cancer patients. Each individual contributed a lung cancer specimen and corresponding adjacent normal tissue. The study identified six genes with statistically significant differences in methylation between normal and tumor tissue (P < 10(-6)). We explored the quantitative methylation data using an unsupervised hierarchical clustering algorithm. The data analysis revealed that methylation patterns differentiate normal from tumor tissue. For validation of our approach, we divided the samples to train a classifier and test its performance. We were able to distinguish normal from lung cancer tissue with >95% sensitivity and specificity. These results show that quantitative cytosine methylation profiling can be used to identify molecular classification markers in lung cancer.

Biomarkers, Tumor↗

PubMed1992

An algorithm for comparing RNA secondary structures and searching for similar substructures.

To access the functional informations carried by RNA molecules at the level of their secondary structure interactions, we propose a comparison method based on a tree edit algorithm which takes into account the tree structure of RNA foldings. Any secondary structure is translated into a tree involving all its elementary substructures; then a shorter condensed tree is built in which any unbranched helix interspersed with bulges and interior loops is taken as a single node. This method includes several parameters: a comparison matrix between structural units, gap penalties, and the scoring between nodes of the condensed trees. Their effects have been analysed using as a model a rapidly divergent domain of the large ribosomal RNA, for which structural variation during evolution is well known. This method allows one to recognize precisely, in large target molecules, definite substructures that present with the query molecules only a limited set of closely related secondary structure features; it is still efficient if intervening features, which can correspond to insertion/deletion of entire stem regions, separate such structural elements. When coupled with a hierarchical clustering algorithm, this method is suitable for classifying RNA molecules according to their secondary structure homologies.

Algorithms↗

PubMed2000

Saturated BLAST: an automated multiple intermediate sequence search used to detect distant homology.

MOTIVATION: Two proteins can have a similar 3-dimensional structure and biological function, but have sequences sufficiently different that traditional protein sequence comparison algorithms do not identify their relationship. The desire to identify such relations has led to the development of more sensitive sequence alignment strategies. One such strategy is the Intermediate Sequence Search (ISS), which connects two proteins through one or more intermediate sequences. In its brute-force implementation, ISS is a strategy that repetitively uses the results of the previous query as new search seeds, making it time-consuming and difficult to analyze. RESULTS: Saturated BLAST is a package that performs ISS in an efficient and automated manner. It was developed using Perl and Perl/Tk and implemented on the LINUX operating system. Starting with a protein sequence, Saturated BLAST runs a BLAST search and identifies representative sequences for the next generation of searches. The procedure is run until convergence or until some predefined criteria are met. Saturated BLAST has a friendly graphic user interface, a built-in BLAST result parser, several multiple alignment tools, clustering algorithms and various filters for the elimination of false positives, thereby providing an easy way to edit, visualize, analyze, monitor and control the search. Besides detecting remote homologies, Saturated BLAST can be used to maintain protein family databases and to search for new genes in genomic databases.

Algorithms↗

PubMed2002

Primer on medical genomics. Part III: Microarray experiments and data analysis.

Genomics has been defined as the comprehensive study of whole sets of genes, gene products, and their interactions as opposed to the study of single genes or proteins. Microarray technology is one of many novel tools that are allowing global and high-throughput analysis of genes and gene products. In addition to an introduction on underlying principles, the current review focuses on the use of both complementary DNA and oligodeoxynucleotide microarrays in gene expression analysis. Genome-wide experiments generate a massive amount of data points that require systematic methods of analysis to extract biologically useful information. Accordingly, the current educational communication discusses different methods of data analysis, including supervised and unsupervised clustering algorithms. Illustrative clinical examples show clinical applications, including (1) identification of candidate genes or pathological pathways (ie, elucidation of pathogenesis); (2) identification of "new" molecular classes of diseases that may be relevant in disease reclassification, prognostication, and treatment selection (ie, class discovery); and (3) use of expression profiles of known disease classes to predict diagnosis and classification of unknown samples (ie, class prediction). The current review should serve as an introduction to the subject for clinician investigators, physicians and medical scientists in training, practicing clinicians, and other students of medicine.

Breast Neoplasms↗

PubMed2005

Transcript patterns associated with ectomycorrhiza development in Eucalyptus globulus and Pisolithus microcarpus.

Regulated gene expression is an important mechanism for controlling ectomycorrhizal symbiosis development. This study aimed to elucidate the coordination between development of mycorrhiza and the differential gene expression in both partners. We analysed RNA levels from sequential samples of symbiotic tissues of Eucalyptus globulus bicostata and the basidiomycete Pisolithus microcarpus progressing through ectomycorrhiza development using cDNA arrays. We derived groups of coordinately expressed genes using hierarchical and nonhierarchical clustering algorithms. Five major distinct temporal patterns of induction/repression were observed with distinct groups of early, middle-, and late-transcriptionally responsive genes to symbiosis formation. At earliest stages, the differentially expressed fungal genes included cell wall symbiosis-regulated proteins, hydrophobins and mannoproteins, whereas transcripts coding for defense-related proteins were upregulated in plant tissues. Middle- and late-transcriptionally responsive genes coded enzymes of glycolysis, tricarboxylic acid cycle and amino acid biosynthesis, as well as protein synthesis, hormone metabolism and signal transduction components. This investigation confirms and extends earlier results which found that changes in morphology associated with mycorrhizal development were accompanied by changes in transcript patterns, but no ectomycorrhiza-specific genes were detected.

Basidiomycota↗

PubMed1992

A new approach to analysis of synchronized sympathetic nerve activity.

Renal sympathetic nerve activity (RSNA) recorded from the multifiber preparation is a continuously fluctuating variable in terms of period and amplitude, reflecting a coordinated tonic level of output from the vasomotor center. Yet current methods of analysis cannot simultaneously measure both of these parameters. A new accurate technique for assessing changes in global sympathetic activity is required. We made a novel application of a computerized peak detection algorithm (Cluster program) to recordings of synchronized sympathetic nerve discharges. The procedure was applied to this new area to retrieve information about the characteristics of synchronized RSNA. Peaks in synchronized RSNA activity were detected from short-term (20 ms) integrated recordings in which voltage changes had been digitized at 200 Hz and stored on computer. The program scanned the data series for significant increases followed by significant decreases in a small cluster of voltage values. The program permits the input of the cluster sample sizes for the test peaks and pre- and postpeak nadirs and also the minimum height to be defined as a peak. Once each synchronized RSNA peak had been detected, its corresponding amplitude, width, and peak-to-peak interval were calculated. The program successfully characterized RSNA in a group of eight cats and yielded results comparable to other analysis techniques. The peak-to-peak interval period showed two modes of synchronized discharge, one related to the cardiac cycle and a faster 8- to 14-Hz frequency. The synchronized peak amplitude and width showed unimodal frequency distributions. The relationship between each of the three variables was examined; only the peak height and width were significantly related to each other.(ABSTRACT TRUNCATED AT 250 WORDS)

Algorithms↗

PubMed2003

Spike cluster analysis in neocortical localization related epilepsy yields clinically significant equivalent source localization results in magnetoencephalogram (MEG).

OBJECTIVE: In magnetoencephalogram (MEG) recordings of patients with epilepsy several types of sharp transients with different spatiotemporal distributions are commonly present. Our objective was to develop a computer based method to identify and classify groups of epileptiform spikes, as well as other transients, in order to improve the characterization of irritative areas in the brain of epileptic patients. METHODS: MEG data centered on selected spikes were stored in signal matrices of C channels by T time samples. The matrices were normalized and euclidean distances between spike representations in vector space R(CxT) were input to a Ward's hierarchical clustering algorithm. RESULTS: The method was applied to MEG data from 4 patients with localization-related epilepsy. For each patient, distinct spike subpopulations were found with clearly different topographical field maps. Inverse computations to selected spike subaverages yielded source solutions in agreement with seizure classification and location of structural lesions, if present, on magnetic resonance images. CONCLUSIONS: With the proposed method a reliable categorization of epileptiform spikes is obtained, that can be applied in an automatic way. Computation of subaverages of similar spikes enhances the signal-to-noise ratio of spike field maps and allows for more accurate reconstruction of sources generating the epileptiform discharges.

Adult↗

PubMed2002

Global gene expression analysis of gastric cancer by oligonucleotide microarrays.

To gain molecular understanding of carcinogenesis, progression, and diversity of gastric cancer, 22 primary human advanced gastric cancer tissues and 8 noncancerous gastric tissues were analyzed by high-density oligonucleotide microarray in this study. Based on expression analysis of approximately 6800 genes, a two-way clustering algorithm successfully distinguished cancer tissues from noncancerous tissues. Subsequently, genes that were differentially expressed in cancer and noncancerous tissues were identified; 162 and 129 genes were highly expressed (P < 0.05) >2.5-fold in cancer tissues and noncancerous tissues, respectively. In cancer tissues, genes related to cell cycle, growth factor, cell motility, cell adhesion, and matrix remodeling were highly expressed. In noncancerous tissues, genes related to gastrointestinal-specific function and immune response were highly expressed. Furthermore, we identified several genes associated with lymph node metastasis including Oct-2 or histological types including Liver-Intestine Cadherin. These results provide not only a new molecular basis for understanding biological properties of gastric cancer, but also useful resources for future development of therapeutic targets and diagnostic markers for gastric cancer.

Cluster Analysis↗

PubMed1977

A typology of parasuicide.

Parasuicide is not a single syndrome. Subtypes at present recognized are based largely on clinically derived stereotypes. When considering a series of patients, the clinician is unable to handle more than a few attributes at a time. This paper describes the application of three very different clustering algorithms to a material of 350 treated parasuicide patients. Mathematically, three types emerge. Clinically, two of these are interpretable and make sense. The types established are: I (n = 107) a group not characterized by any of the variables we examined; this group is a puzzle, mainly because the reasons for the parasuicidal act are not clear. II (n = 132) a depressed, alienated group with high life-endangerment. III (n = III) a group whose act was highly operant: they felt alienated and were angry with others. These groups did not differ significantly on demographic variables. The usefulness of this typology, particularly for management, after-care and prevention, has now to be assessed.

Anger↗

PubMed2006

Construction of phylogenetic trees by kernel-based comparative analysis of metabolic networks.

BACKGROUND: To infer the tree of life requires knowledge of the common characteristics of each species descended from a common ancestor as the measuring criteria and a method to calculate the distance between the resulting values of each measure. Conventional phylogenetic analysis based on genomic sequences provides information about the genetic relationships between different organisms. In contrast, comparative analysis of metabolic pathways in different organisms can yield insights into their functional relationships under different physiological conditions. However, evaluating the similarities or differences between metabolic networks is a computationally challenging problem, and systematic methods of doing this are desirable. Here we introduce a graph-kernel method for computing the similarity between metabolic networks in polynomial time, and use it to profile metabolic pathways and to construct phylogenetic trees. RESULTS: To compare the structures of metabolic networks in organisms, we adopted the exponential graph kernel, which is a kernel-based approach with a labeled graph that includes a label matrix and an adjacency matrix. To construct the phylogenetic trees, we used an unweighted pair-group method with arithmetic mean, i.e., a hierarchical clustering algorithm. We applied the kernel-based network profiling method in a comparative analysis of nine carbohydrate metabolic networks from 81 biological species encompassing Archaea, Eukaryota, and Eubacteria. The resulting phylogenetic hierarchies generally support the tripartite scheme of three domains rather than the two domains of prokaryotes and eukaryotes. CONCLUSION: By combining the kernel machines with metabolic information, the method infers the context of biosphere development that covers physiological events required for adaptation by genetic reconstruction. The results show that one may obtain a global view of the tree of life by comparing the metabolic pathway structures using meta-level information rather than sequence information. This method may yield further information about biological evolution, such as the history of horizontal transfer of each gene, by studying the detailed structure of the phylogenetic tree constructed by the kernel-based method.

Archaeal Proteins↗

PubMed2003

Expression profiles of non-small cell lung cancers on cDNA microarrays: identification of genes for prediction of lymph-node metastasis and sensitivity to anti-cancer drugs.

To investigate genes involved in pulmonary carcinogenesis and those related to sensitivity of nonsmall cell lung cancers (NSCLCs) to therapeutic drugs, we performed cDNA microarray analysis of 37 NSCLCs after laser-capture microdissection of cancer cells from primary tumors. A clustering algorithm applied to the expression data easily distinguished two major histological types of non-small cell lung cancer, adenocarcinoma and squamous cell carcinoma. Subsequent analysis of the 18 adenocarcinomas identified 40 genes whose expression levels could separate cases with lymph-node metastasis from those without metastasis. In addition, we compared the expression data with measurements of the sensitivity of surgically dissected NSCLC specimens to six anti-cancer drugs (docetaxel, paclitaxel, irinotecan, cisplatin, gemcitabine, and vinorelbine), as measured by the CD-DST (collagen gel droplet embedded culture-drug sensitivity test) method. We found significant associations between expression levels of dozens of genes and chemosensitivity of NSCLCs. Our results provide valuable information for eventually identifying predictive markers and novel therapeutic target molecules for this type of cancer.

Adenocarcinoma↗

PubMed2004

Automatized clustering and functional geometry of human parietofrontal networks for language, space, and number.

Human functional MRI studies frequently reveal the joint activation of parietal and of lateral and mesial frontal areas during various cognitive tasks. To analyze the geometrical organization of those networks, we used an automatized clustering algorithm that parcels out sets of areas based on their similar profile of task-related activations or deactivations. This algorithm allowed us to reanalyze published fMRI data (Simon, O., Mangin, J.F., Cohen, L., Le Bihan, D., Dehaene, S., 2002. Topographical layout of hand, eye, calculation, and language-related areas in the human parietal lobe. Neuron 33, 475-487) and to reproduce the previously observed geometrical organization of activations for saccades, attention, grasping, pointing, calculation, and language processing in the parietal lobe. Further, we show that this organization extends to lateral and mesial prefrontal regions. Relative to the parietal lobe, the prefrontal functional geometry is characterized by a partially symmetrical anteroposterior ordering of activations, a decreased representation of effector-specific tasks, and a greater emphasis on higher cognitive functions of attention, higher-order spatial representation, calculation, and language. Anatomically, our results in humans are closely homologous to the known connectivity of parietal and frontal regions in the macaque monkey.

Animals↗

PubMed1993

Alterations in luteinizing hormone secretory activity in women with insulin-dependent diabetes mellitus and secondary amenorrhea.

To investigate hypothalamic and/or pituitary abnormalities in women with poorly controlled insulin-dependent diabetes mellitus (IDDM) and secondary amenorrhea, we measured serum LH every 10 min for 24 h and for 2 additional h after the administration of exogenous GnRH in 8 women with IDDM and amenorrhea and compared these to data from 15 eumenorrheic nondiabetic women. LH pulses were characterized by the pulse detection algorithm Cluster, and secretory episodes were evaluated using the multiple parameter deconvolution procedure Deconv. Cluster analysis revealed fewer LH pulses per 24 h (14.3 +/- 1.2 vs. 19.9 +/- 0.6; P < 0.001; mean +/- SEM), a greater peak width (63 +/- 4.9 vs. 44 +/- 2.2 min; P < 0.01), and greater peak area (136 +/- 17 vs. 89 +/- 13 IU/L.min; P < 0.01) in the diabetic women. Analysis with Deconv revealed fewer LH secretory episodes per 24 h in the diabetic women (14.4 +/- 0.9 vs. 20.4 +/- 0.5; P < 0.001) and no statistical difference in LH half-lives. The IDDM women responded to a 10-micrograms GnRH bolus with LH pulses of larger total (51 +/- 15.9 vs. 15 +/- 1.4 IU/L; P < 0.01) and incremental (29 +/- 7.6 vs. 9 +/- 1.2; P < 0.001) amplitude. In summary, we observed that amenorrheic diabetic women have fewer LH pulses/secretory episodes than normal women. However, they respond well to exogenous GnRH, suggesting that compromise of the GnRH pulse generator, rather than pituitary dysfunction, is responsible for their menstrual dysfunction.

Adult↗

PubMed2005

Signature of B-CLL with different prognosis by Shrunken centroids of surface antigen expression profiling.

With the aim of identifying the immunophenotypic profile of B-cell chronic lymphocytic leukemia (B-CLL) subsets with different prognosis, we investigated by flow cytometry the expression of 36 surface antigens in 123 cases, all with survivals. By analyzing results with unsupervised (hierarchical and K-means clustering) algorithms, three distinct immunophenotypic groups (I, II, and III) were identified, group I (51/123) with longer survivals, as compared to the group II (36/123) and III (36/123). The immunophenotypic signatures of these groups, as determined by applying the nearest Shrunken centroids method as class predictor, were characterized by the coordinated and differential expression of 12 surface markers, that is, group I: above-average expression of CD62L, CD54, CD49c, and CD25, below-average expression of CD38; group II: above-average expression of CD38, CD49d, CD29, and CD49e; and group III: below-average expression of the above markers, overexpression of CD23, CD20, SmIg, and CD79b. As opposed to groups II-III, group I B-CLLs lacked expression of ZAP-70 and activation-induced cytidine deaminase in the majority of cases, while more frequently had mutated IgV(H) genes and IgV(H) mutations consistent with antigen-driven selection. Our findings contribute to improve the immunophenotypical identification of disease subsets with different prognosis and suggest a set of surface antigens to be employed as prognosticators in routine diagnostic/prognostic procedures.

Adult↗

PubMed1997

Patterns of secretion of GnRH, LH and FSH during the postovulatory period in mares: mechanisms prolonging the LH surge.

To study the mechanisms responsible for the unusually slow decline of the ovulatory LH surge in mares, secretion patterns of GnRH, LH and FSH were monitored in pituitary venous blood collected every 2 or 5 min for 10.5-18.0 h from five mares on the third (n = 4) or fifth day after ovulation (first sampling period). To determine the effectiveness of progesterone negative feedback, mares were then given a luteolytic dose of a prostaglandin analogue (PGF2 alpha) and pituitary venous sampling (every 2 or 5 min for 16 h) recommenced 20-22 h later (second sampling period). During the declining arm of the LH surge, large peaks (detected by the Cluster algorithm) of concurrent LH and FSH secretion occurred infrequently, with four peaks being detected in a combined sampling period of 75 h. Outside the peaks, LH or FSH secretion continued (as assessed by a pituitary to jugular-venous concentration ratio > or = 1.25) during 46% +/- 13 or 40% +/- 10, respectively, of the sampling period. GnRH immunoactivity was detected during each spontaneous gonadotrophin peak, but at other times was generally at assay sensitivity. After PGF2 alpha, plasma progesterone fell (ng ml-1, mean +/- SEM; first sampling period: 8.6 +/- 0.8; second; 2.0 +/- 0.3; P = 0.001) and the frequency of LH (P < 0.05) and FSH (P < 0.02) peaks rose, with 28 peaks detected for each hormone in a total of 80 h sampling. Peaks in LH were smaller during the second period, with decreases observed in maximum (P = 0.027) and mean (P = 0.025) secretion rates. Maximum GnRH secretion rate during peaks also declined (P = 0.010); however, the decrement (-30 +/- 6%) was less than that in maximum LH secretion rate (-82 +/- 5%; P = 0.040), suggesting that other factors contribute to the reduced LH peak amplitude. In summary, gonadotrophin peak frequency during the downswing of the surge in mares is slow, as in the midluteal phase, and the slow rate of decline in peripheral gonadotrophin concentrations is due, at least in part, to continued secretion between pulses. Moreover, progesterone negative feedback is highly effective in early dioestrus, in that lessening it without complete removal markedly accelerates gonadotrophin pulse frequency.

Animals↗

PubMed1996

Regional brain tissue composition in children with hydrocephalus. Relationships with cognitive development.

OBJECTIVE: To determine whether children with shunted hydrocephalus show variations in regional brain tissue composition that relate to cognitive functions. DESIGN: Nonequivalent control group. PATIENTS AND METHODS: Magnetic resonance imaging (MRI) and cognitive skills assessments were obtained on 28 children, 6 to 9 years of age, with shunted hydrocephalus and 13 normal control subjects comparable in age, gender, ethnicity, and socioeconomic status. Three consecutive MRI slices below the vertex were segmented using a fuzzy clustering algorithm to separate pixels into gray matter, white matter, and cerebrospinal fluid (CSF) in quadrants representing left and right anterior and posterior brain regions. The cognitive skills assessments included the Wechsler Intelligence Scale for Children-Revised verbal and performance IQ scores, neuropsychological composites of language and visuospatial skills, a measure of visuomotor dexterity, and 2 measures of problem-solving abilities. The MRI data were analyzed in a group x tissue x hemisphere x region analysis of variance. Spearman rho correlations were computed within the hydrocephalus group between the MRI and cognitive measures. RESULTS: Children with hydrocephalus showed reductions in overall gray matter percentages and corresponding increased CSF percentages that were more pronounced in posterior than anterior regions of both hemispheres. White matter percentages were reduced in children with hydrocephalus only in the left posterior quadrant. Correlations of posterior, but not anterior, CSF and gray matter percentages were significant with verbal and performance IQ scores and language, visuospatial, and visuomotor dexterity skills, but not with problem-solving abilities. Children with hydrocephalus who had proportionately greater posterior than anterior CSF percentages had significantly poorer visuomotor dexterity and visuospatial skills than did hydrocephalic children with proportionate CSF percentages. CONCLUSION: Regional variations in brain tissue composition in children with shunted hydrocephalus correlate with a variety of cognitive and visuomotor functions.

Agenesis of Corpus Callosum↗

PubMed1996

Exploration of the conformational space of oxytocin and arginine-vasopressin using the electrostatically driven Monte Carlo and molecular dynamics methods.

Conformational analysis of the neurohypophyseal hormones oxytocin (OT) and arginine-vasopressin (AVP) has been carried out using two different computational approaches and three force fields, namely by the Electrostatically Driven Monte Carlo (EDMC) method, with the Empirical Conformational Energy Program for Peptides (ECEPP/3) force field or with the ECEPP/3 force field plus a hydration-shell model, and by simulated-annealing molecular dynamics with the Consistent Valence Force Field (CVFF). The low-energy conformations obtained for both hormones were classified using the minimal-tree clustering algorithm and characterized according to the locations of beta-turns in the cyclic moieties. Calculations with the CVFF force field located conformations with a beta-turn at residues 3 and 4 as the lowest energy ones both for OT and for AVP. In the ECEPP/3 force field the lowest energy conformation of OT contained a beta-turn at residues 2 and 3, conformations with this location of the turn being higher in energy for AVP. The latter difference can be attributed to the difference in the size of the side chain in position 3 of the sequences: the bulkier phenylalanine residue of AVP in combination with the bulky Tyr2 residue hinders the formation of a turn at residues 2 and 3. Conformations of OT and AVP with a turn at residues 3,4 were in the best agreement with the x-ray structures of deaminooxytocin and pressinoic acid (the cyclic moiety of vasopressin), respectively, and with the nmr-derived distance constraints. Generally, the low-energy conformations obtained with the hydration-shell model were in a better agreement with the experimental data than the conformations calculated in vacuo. It was found, however, that the obtained low-energy conformations do not satisfy all of the nmr-derived distance constraints and the nuclear Overhauser effect pattern observed in nmr studies can be fully explained only by assuming a dynamic equilibrium between conformations with beta-turns at residues 2,3, 3,4, and 4,5. The low-energy structures of OT with a beta-turn at residues 2,3 have the disulfide ring conformations close to the model proposed recently for a potent bicyclic antagonist of OT [M. D. Shenderovich et al. (1994) Polish Journal of Chemistry, Vol. 25, pp. 921-927], although the native hormone differs from the bicyclic analogue by the conformation of the C-terminal tripeptide. This finding confirms the hypothesis of different receptor-bound conformations of agonists and antagonists of OT.

Amino Acid Sequence↗