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PubMedDate not supplied

Essential latent knowledge for protein-protein interactions: analysis by an unsupervised learning approach.

Protein-protein interactions play a number of central roles in many cellular functions, including DNA replication, transcription and translation, signal transduction, and metabolic pathways. A recent increase in the number of protein-protein interactions has made predicting unknown protein-protein interactions important for the understanding of living cells. However, the protein-protein interactions experimentally obtained so far are often incomplete and contradictory and, consequently, existing computational prediction methods have integrated evidence (latent knowledge of proteins) from different and more reliable sources. Analyzing the relationships between proteins and the latent knowledge is important to understanding the cellular processes. For this analysis, we propose a new probabilistic model for protein-protein interactions by considering the latent knowledge of proteins. We further present an efficient learning algorithm for this model, based on an EM algorithm. Experimental results have shown that in a supervised test setting, the proposed method outperformed five other competing methods by a statistically significant factor in all cases. Using the probability parameters of a trained model, we have further shown the latent knowledge that is essential to predicting protein-protein interactions. Overall, our experimental results confirm that our proposed model is especially effective for analyzing protein-protein interactions from a viewpoint of the latent knowledge of proteins.

Algorithms↗
PubMed2004

Discovery of novel selective inhibitors of human intestinal carboxylesterase for the amelioration of irinotecan-induced diarrhea: synthesis, quantitative structure-activity relationship analysis, and biological activity.

The dose-limiting toxicity of the highly effective anticancer agent 7-ethyl-10-[4-(1-piperidino)-1-piperidino]carbonyloxy-camptothecin (irinotecan; CPT-11) is delayed diarrhea. This is thought to be caused by either bacteria-mediated hydrolysis of the glucuronide conjugate of the active metabolite 7-ethyl-10-hydroxycamptothecin (SN-38) or direct conversion of CPT-11 to SN-38 by carboxylesterases (CE) in the small intestine. After drug administration, a very high level of CPT-11 is present in the bile; this is deposited into the duodenum, the region of the gut with the highest levels of CE activity. Hence, it is likely that direct conversion of the drug to SN-38 is partially responsible for the diarrhea associated with this agent. In an attempt to ameliorate this toxicity, we have applied Target-Related Affinity Profiling to identify novel CE inhibitors that are selective inhibitors of the human intestinal enzyme (hiCE). Seven inhibitors, all sulfonamide derivatives, demonstrated greater than 200-fold selectivity for hiCE compared with the human liver CE hCE1, and none was an inhibitor of human acetylcholinesterase or butyrylcholinesterase. Quantitative structure-activity relationship (QSAR) analysis demonstrated excellent correlations with the predicted versus experimental Ki values (r2 = 0.944) for hiCE. Additionally, design and synthesis of a tetrafluorine-substituted sulfonamide analog, which QSAR indicated would demonstrate improved inhibition of hiCE, validated the computer predictive analyses. These and other phenyl-substituted sulfonamides compounds are regarded as lead compounds for the development of effective, selective CE inhibitors for clinical applications.

Animals↗
PubMed1998

Accuracy of cephalometric and video imaging program Dentofacial Planner Plus in orthognathic surgical planning.

The prediction of profile changes after surgery poses a problem due to the variability of the soft tissue and the differences in soft-tissue translations relative to osseous changes. This study examined the accuracy of computer predictions of such soft-tissue changes. Twenty-five patients with mandibular retrognathia were examined before and after orthognathic surgery. Changes in soft-tissue reference points were correlated to translations of hard-tissue references in the sagittal and vertical planes, and the measurements from these patients were compared to results predicted in preoperative planning by the cephalometric and video imaging program Dentofacial Planner. In surgical treatment involving advancement of the mandible, the mean operative advancement of the osseous pogonion was 6.06 mm. The corresponding movements of soft-tissue references, expressed as percentages relative to the movement of the osseous pogonion in the sagittal plane, were 98.4% for the soft-tissue pogonion, 93.6% for the soft-tissue menton, and 49.0% for the soft-tissue labrale inferior. The same measurements were carried out in the vertical plane and the changes in soft-tissue references were compared to those predicted in preoperative planning using the Dentofacial Planner. The predicted images were perceived as agreeing with the actual image most frequently in the lip and nasal area, while the highest degree of error was seen in the submental region. An overall predictability of more than 80% can be attained by planning mandibular advancement operations for correction of mandibular retrognathia using the Dentofacial Planner.

Adult↗
PubMed2006

Phosphoproteomics toolbox: computational biology, protein chemistry and mass spectrometry.

Protein phosphorylation is important for regulation of most biological functions and up to 50% of all proteins are thought to be modified by protein kinases. Increased knowledge about potential phosphorylation of a protein may increase our understanding of the molecular processes in which it takes part. Despite the importance of protein phosphorylation, identification of phosphoproteins and localization of phosphorylation sites is still a major challenge in proteomics. However, high-throughput methods for identification of phosphoproteins are being developed, in particular within the fields of bioinformatics and mass spectrometry. In this review, we present a toolbox of current technology applied in phosphoproteomics including computational prediction, chemical approaches and mass spectrometry-based analysis, and propose an integrated strategy for experimental phosphoproteomics.

Computational Biology↗
PubMed1996

Genomic organization of a mouse MHC class II region including the H2-M and Lmp2 loci.

The region encompassing the Ma, Mb1, Mb2, and Lmp2 genes of the mouse class II major histocompatibility complex (MHC) was sequenced. Since this region contains clusters of genes required for efficient class I and class II antigen presentation, it was interesting to search for putative additional genes in the 21 kilobase gap between the Mb1 and Lmp2 genes. Computer predictions of coding regions and CpG islands, exon trapping experiments, and cross-species comparison with the corresponding human sequence indicate that no additional functional gene is present in that stretch. However, computer analysis revealed the possible existence of an alternative 3' exon for Mb1. Except for the fact that the mouse MHC contains two Mb genes, the genomic organization of the H2-M loci was found to be almost identical to the organization of the human HLA-DM genes. The promoter regions of the Ma and Mb genes also resemble classical class II promoters, containing typical S, X, and Y boxes. Like the human genes, the three H2-M genes displayed very limited polymorphism when we compared the cDNA sequences from six haplotypes. Finally, comparison of DMB with Mb1 and Mb2, both at the genomic level and in their coding regions, suggests that the Mb gene was recently duplicated, probably only in certain rodents.

Animals↗
PubMed2005

Improving functional annotation of non-synonomous SNPs with information theory.

Automated functional annotation of nsSNPs requires that amino-acid residue changes are represented by a set of descriptive features, such as evolutionary conservation, side-chain volume change, effect on ligand-binding, and residue structural rigidity. Identifying the most informative combinations of features is critical to the success of a computational prediction method. We rank 32 features according to their mutual information with functional effects of amino-acid substitutions, as measured by in vivo assays. In addition, we use a greedy algorithm to identify a subset of highly informative features. The method is simple to implement and provides a quantitative measure for selecting the best predictive features given a set of features that a human expert believes to be informative. We demonstrate the usefulness of the selected highly informative features by cross-validated tests of a computational classifier, a support vector machine (SVM). The SVM's classification accuracy is highly correlated with the ranking of the input features by their mutual information. Two features describing the solvent accessibility of "wild-type" and "mutant" amino-acid residues and one evolutionary feature based on superfamily-level multiple alignments produce comparable overall accuracy and 6% fewer false positives than a 32-feature set that considers physiochemical properties of amino acids, protein electrostatics, amino-acid residue flexibility, and binding interactions.

Analysis of Variance↗
PubMed2006

Computational framework for the prediction of transcription factor binding sites by multiple data integration.

Control of gene expression is essential to the establishment and maintenance of all cell types, and its dysregulation is involved in pathogenesis of several diseases. Accurate computational predictions of transcription factor regulation may thus help in understanding complex diseases, including mental disorders in which dysregulation of neural gene expression is thought to play a key role. However, biological mechanisms underlying the regulation of gene expression are not completely understood, and predictions via bioinformatics tools are typically poorly specific. We developed a bioinformatics workflow for the prediction of transcription factor binding sites from several independent datasets. We show the advantages of integrating information based on evolutionary conservation and gene expression, when tackling the problem of binding site prediction. Consistent results were obtained on a large simulated dataset consisting of 13050 in silico promoter sequences, on a set of 161 human gene promoters for which binding sites are known, and on a smaller set of promoters of Myc target genes. Our computational framework for binding site prediction can integrate multiple sources of data, and its performance was tested on different datasets. Our results show that integrating information from multiple data sources, such as genomic sequence of genes' promoters, conservation over multiple species, and gene expression data, indeed improves the accuracy of computational predictions.

Animals↗
PubMed2006

Prediction of the functional class of lipid binding proteins from sequence-derived properties irrespective of sequence similarity.

Lipid binding proteins play important roles in signaling, regulation, membrane trafficking, immune response, lipid metabolism, and transport. Because of their functional and sequence diversity, it is desirable to explore additional methods for predicting lipid binding proteins irrespective of sequence similarity. This work explores the use of support vector machines (SVMs) as such a method. SVM prediction systems are developed using 14,776 lipid binding and 133,441 nonlipid binding proteins and are evaluated by an independent set of 6,768 lipid binding and 64,761 nonlipid binding proteins. The computed prediction accuracy is 78.9, 79.5, 82.2, 79.5, 84.4, 76.6, 90.6, 79.0, and 89.9% for lipid degradation, lipid metabolism, lipid synthesis, lipid transport, lipid binding, lipopolysaccharide biosynthesis, lipoprotein, lipoyl, and all lipid binding proteins, respectively. The accuracy for the nonmember proteins of each class is 99.9, 99.2, 99.6, 99.8, 99.9, 99.8, 98.5, 99.9, and 97.0%, respectively. Comparable accuracies are obtained when homologous proteins are considered as one, or by using a different SVM kernel function. Our method predicts 86.8% of the 76 lipid binding proteins nonhomologous to any protein in the Swiss-Prot database and 89.0% of the 73 known lipid binding domains as lipid binding. These findings suggest the usefulness of SVMs for facilitating the prediction of lipid binding proteins. Our software can be accessed at the SVMProt server (http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi).

Algorithms↗
PubMed1998

Ligand binding affinity prediction by linear interaction energy methods.

A recent method for estimating ligand binding affinities is extended. This method employs averages of interaction potential energy terms from molecular dynamics simulations or other thermal conformational sampling techniques. Incorporation of systematic deviations from electrostatic linear response, derived from free energy perturbation studies, into the absolute binding free energy expression significantly enhances the accuracy of the approach. This type of method may be useful for computational prediction of ligand binding strengths, e.g., in drug design applications.

Binding Sites↗
PubMedDate not supplied

Accuracy and precision of computer-simulated tissue temperatures in individual human intracranial tumours treated with interstitial hyperthermia.

Accurate knowledge of tissue temperature is necessary for effective delivery of clinical hyperthermia in the treatment of malignant tumours. This report compares computer-predicted versus measured intratumoral temperatures in 11 human subjects with intracranial tumours, treated with a conceptually simple 'conductive' interstitial hyperthermia system. Interstitial hyperthermia was achieved by the use of parallel arrays of implanted, electrically heated catheters. The tissue was warmed by thermal conduction and blood convection. Simulation of intratumoral temperatures was achieved by solving a modified bioheat transfer equation on a digital computer using a finite difference method. Comparison of intratumoral temperatures from simulations and measured values differed by about +/- 0.75 degrees C. Further analysis of computed temperature distributions between catheters revealed a rapidly computable relationship between the local minimum tumour temperature and nearby catheter power and temperature that accounts for effects of varying blood flow. These findings suggest that 'on-line' prediction and control of local minimum tumour temperatures are feasible with the conductive interstitial technique.

Adult↗
PubMed1985

Localization of epitopes of herpes simplex virus type 1 glycoprotein D.

We previously defined eight groups of monoclonal antibodies which react with distinct epitopes of herpes simplex virus glycoprotein D (gD). One of these, group VII antibody, was shown to react with a type-common continuous epitope within residues 11 to 19 of the mature glycoprotein (residues 36 to 44 of the predicted sequence of gD). In the current investigation, we have localized the sites of binding of two additional antibody groups which recognize continuous epitopes of gD. The use of truncated forms of gD as well as computer predictions of secondary structure and hydrophilicity were instrumental in locating these epitopes and choosing synthetic peptides to mimic their reactivity. Group II antibodies, which are type common, react with an epitope within residues 268 to 287 of the mature glycoprotein (residues 293 to 312 of the predicted sequence). Group V antibodies, which are gD-1 specific, react with an epitope within residues 340 to 356 of the mature protein (residues 365 to 381 of the predicted sequence). Four additional groups of monoclonal antibodies appear to react with discontinuous epitopes of gD-1, since the reactivity of these antibodies was lost when the glycoprotein was denatured by reduction and alkylation. Truncated forms of gD were used to localize these four epitopes to the first 260 amino acids of the mature protein. Competition experiments were used to assess the relative positions of binding of various pairs of monoclonal antibodies. In several cases, when one antibody was bound, there was no interference with the binding of an antibody from another group, indicating that the epitopes were distinct. However, in other cases, there was competition, indicating that these epitopes might share some common amino acids.

Antibodies, Monoclonal↗
PubMed2003

Position specific variation in the rate of evolution in transcription factor binding sites.

BACKGROUND: The binding sites of sequence specific transcription factors are an important and relatively well-understood class of functional non-coding DNAs. Although a wide variety of experimental and computational methods have been developed to characterize transcription factor binding sites, they remain difficult to identify. Comparison of non-coding DNA from related species has shown considerable promise in identifying these functional non-coding sequences, even though relatively little is known about their evolution. RESULTS: Here we analyse the genome sequences of the budding yeasts Saccharomyces cerevisiae, S. bayanus, S. paradoxus and S. mikatae to study the evolution of transcription factor binding sites. As expected, we find that both experimentally characterized and computationally predicted binding sites evolve slower than surrounding sequence, consistent with the hypothesis that they are under purifying selection. We also observe position-specific variation in the rate of evolution within binding sites. We find that the position-specific rate of evolution is positively correlated with degeneracy among binding sites within S. cerevisiae. We test theoretical predictions for the rate of evolution at positions where the base frequencies deviate from background due to purifying selection and find reasonable agreement with the observed rates of evolution. Finally, we show how the evolutionary characteristics of real binding motifs can be used to distinguish them from artefacts of computational motif finding algorithms. CONCLUSION: As has been observed for protein sequences, the rate of evolution in transcription factor binding sites varies with position, suggesting that some regions are under stronger functional constraint than others. This variation likely reflects the varying importance of different positions in the formation of the protein-DNA complex. The characterization of the pattern of evolution in known binding sites will likely contribute to the effective use of comparative sequence data in the identification of transcription factor binding sites and is an important step toward understanding the evolution of functional non-coding DNA.

Artifacts↗
PubMed1986

Prediction of outcome and the management of severe head injuries: the attitudes of neurosurgeons.

We gave a questionnaire to a multinational group of 59 neurosurgeons to discover their views about certain aspects of predictions of outcome after severe head injury. Although there was wide variation in the opinions expressed, a majority of clinicians agreed that estimations of prognosis are possible within 3 days of severe head injury, that these estimates influence some of their management decisions, and that computer predictions should be at least as reliable as those of an experienced clinician. The findings suggest that clinicians may be receptive to the use of computerized predictions of outcome, but also indicate that many other factors influence difficult clinical decisions.

Attitude of Health Personnel↗
PubMed2025

TripLexicon: prediction and analysis of gene regulatory RNA-DNA interactions.

MOTIVATION: Non-coding RNA (ncRNA) plays a crucial role in gene regulation, including by forming sequence-specific RNA-DNA interactions at gene regulatory elements. One form of interaction takes place via the formation of RNA:DNA:DNA triple helices (triplexes). Accurate computational prediction of triplex formation from nucleotide sequences is an important tool in ncRNA research but remains somewhat inaccessible and complex. To address this, we created TripLexicon, a web-based interface for accessing and analyzing predicted gene regulatory RNA-DNA interactions in human and mouse. RESULTS: Predicted interactions can be accessed from RNA-, DNA-, and region-centric perspectives. For each RNA transcript, visualizations at genome and nucleotide resolution are available, providing insight into target genes and regions, as well as putative functional domains of the transcript. Predicted target genes can immediately be subjected to ontology and pathway enrichment analysis, providing rapid insight into potential functions mediated by the RNA-DNA interactions of the queried transcript. DNA and region queries are designed to identify potentially important ncRNA interactors at sites of interest. AVAILABILITY AND IMPLEMENTATION: TripLexicon is accessible at https://triplexicon.uni-frankfurt.de. This website is free and open to all users and there is no login requirement. All data and code is uploaded to Zenodo: https://zenodo.org/records/17143608 and the code for the webserver is available on Github: https://github.com/SchulzLab/TripLexicon.

Software↗
PubMed1999

Identification of a human homolog of the Drosophila rotated abdomen gene (POMT1) encoding a putative protein O-mannosyl-transferase, and assignment to human chromosome 9q34.1.

We have isolated a human gene homologous to Drosophila melanogaster rotated abdomen, rt, a poorly viable recessive mutation causing a clockwise twisted abdomen in affected flies due to defects in embryonic muscle development. The human gene, like rt, encodes a protein with high homology to the yeast mannosyl-transferases (Pmts) and has been named POMT1. POMT1 is expressed as a 3.1-kb transcript in all tissues tested, with highest levels in testis and fetal brain. Alternative splicing of several exons in all tissues predicts the generation of several protein isoforms. The most common mRNA variant encodes a 725-aa protein with 40% identity and 62.5% similarity to rt, as well as 30.5% identity and 54% similarity to yeast Pmts. Computer prediction of protein sorting suggests that the POMT1 product could be an integral protein of the endoplasmic reticulum membrane. Given the strong conservation of protein motifs between POMT1 and the yeast Pmts, POMT1 may function as a mannosyl-transferase involved in O-mannosylation of proteins, being the first of such a class found in mammals. The POMT1 locus has been assigned to human chromosome 9q34.1 by somatic cell hybrids, radiation hybrids, and linkage analysis. On the basis of the rt phenotype, POMT1 could be a candidate for uncharacterized genetic disorders of the muscular system, such as some forms of congenital muscular dystrophy or congenital myopathy.

Amino Acid Sequence↗
PubMed2001

Methods for modeling particle deposition as a function of age.

The purpose of this paper is to review the application of mathematical models of inhaled particle deposition to people of various ages. The basic considerations of aerosol physics, biological characteristics and model structure are presented along with limitations inherent in modern modeling techniques. Application of the models to children and senescent adults has been largely based on extrapolating anatomical and physiological data from young adults to match the changes observed during growth and aging. Sample results are included for total particle deposition and deposition in the bronchial and pulmonary regions. The models proposed provide particle deposition predictions that are consistent with the scant measurements available. The models discussed appear to be on firm theoretical grounds, but they are largely limited in application to simple aerosols and average individuals. Also, additional validation of the computational predictions is needed.

Adolescent↗
PubMed2005

Solvation and structure of LiAlH(4) in ethereal solvents.

The nature of the solute species present in ethereal solutions of LiAlH(4) is of crucial importance for understanding the mechanisms for the reduction of ketones and other functional groups by LiAlH(4). We have employed a combination of theoretical and experimental techniques to investigate the structure of LiAlH(4) in ethereal solutions. Using complexation agents, we measured the IR spectra of LiAlH(4) and AlH(4)(-) in tetrahydrofuran (THF). Hybrid quantum-classical (QM-MM) simulations have also been carried out to compute the IR spectra of associated and dissociated LiAlH(4) species and the free-energy profile for the dissociation process in solution. Our experimental estimate of the dissociation constant in THF is 0.021 +/- 0.002, while the predicted computational value corresponding to a model dimethyl ether solvent is 0.001. The free-energy profile shows only one minimum corresponding to a contact ion pair at a Li-Al separation distance of 3.0 A. These results are consistent with the fact that LiAlH(4) is essentially associated in ethereal solutions forming contact ion pairs.

Aluminum Compounds↗