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PubMed2000

Computational predictions of binding affinities to dihydrofolate reductase: synthesis and biological evaluation of methotrexate analogues.

The relative binding affinities to human dihydrofolate reductase of four new potential antifolates, containing ester linkages between the two aromatic systems, were estimated by free energy perturbation simulations. The ester analogue, predicted to exhibit the highest binding affinity to human dihydrofolate reductase, and a reference ester (more structurally related to methotrexate) were synthesized. As deduced from the measured IC(50) values, the calculated ranking of the ligands was correct although a greater difference in affinity was indicated by the experimental measurements. Among the new antifolates the most potent inhibitor exhibited a similar pharmacokinetic profile to methotrexate but lacked activity in a complex antiarthritic model in rat in vivo.

Animals↗
PubMed2001

Design, synthesis, computational prediction, and biological evaluation of ester soft drugs as inhibitors of dihydrofolate reductase from Pneumocystis carinii.

A series of lipophilic soft drugs structurally related to the nonclassical dihydrofolate reductase (DHFR) inhibitors trimetrexate and piritrexim have been designed, synthesized, and evaluated in DHFR assays, with special emphasis on the inhibition of P. carinii DHFR. The best inhibitors, encompassing an ester bond in the bridge connecting the two aromatic systems, were approximately 10 times less potent than trimetrexate and piritrexim. The metabolites were designed to be poor inhibitors. Furthermore, molecular dynamics simulations of three ligands in complex with DHFR from Pneumocystis carinii and from the human enzyme were conducted in order to better understand the factors determining the selectivity. A correct ranking of the relative inhibition of DHFR was achieved utilizing the linear interaction energy method. The soft drugs are intended for local administration. One representative ester was selected for a pharmacokinetic study in rats where it was found to undergo fast metabolic degradation to the predicted inactive metabolites.

Animals↗
PubMed2006

Synthesis of anthranylaldoxime derivatives as estrogen receptor ligands and computational prediction of binding modes.

N-Me-anthranylaldoximes possess a hydrogen-bonded pseudocyclic A' ring in place of the typical phenolic A-ring that is characteristic of most estrogen receptor (ER) ligands. We have investigated the role played by substituents introduced into either one or both of the peripheral 3- and 4-phenyl rings in modulating ER binding affinity. An efficient synthetic strategy was employed for the preparation of differentially substituted 3- and 4-aryl derivatives that involved exploiting the different reactivity of bromo- versus chloro-aryl groups in palladium-catalyzed cross-couplings. The binding data showed that ERalpha affinity could be improved by a single p-OH group in the 4-phenyl ring, whereas the same substitution on the 3-phenyl ring caused a dramatic reduction of ERbeta affinity. The most ERalpha-selective compound was the one with two p-OH groups on both phenyl substituents. To rationalize these results, ligand docking followed by molecular mechanics Poisson-Boltzmann/surface area (MM-PBSA) studies were carried out. These analyses suggested a molecular basis for the interaction of these compounds with the ERs and enabled the development of models able to predict the mode of ligand binding.

Benzene Derivatives↗
PubMed2003

Haplotype variation in bovine Toll-like receptor 4 and computational prediction of a positively selected ligand-binding domain.

Toll-like receptor 4 (TLR4) is a cell-surface receptor that activates innate and adaptive immune responses. Because it recognizes a broad class of pathogen-associated molecular patterns presented by lipopolysaccharides and lipoteichoic acid, TLR4 is a candidate gene for resistance to a large number of diseases. In particular, mouse models suggest TLR4 as a candidate gene for resistance to major agents in bovine respiratory disease and Johne's disease. The coding sequence of bovine TLR4 is divided into three exons, with intron/exon boundaries and intron sizes similar to those of human TLR4 transcript variant 1. We amplified each exon in 40 individuals from 11 breeds and screened the sequence for single-nucleotide polymorphisms (SNPs). We identified 32 SNPs, 28 of which are in the coding sequence, for an average of one SNP per 90 bp of coding sequence. Eight SNPs were nonsynonymous and potentially alter specificity of pathogen recognition or efficiency of signaling. To evaluate the functional importance of these SNPs, we used codon-substitution models to detect diversifying selection in an extracellular region that may physically interact with ligands. One nonsynonymous SNP is located within this region, and other substitutions are in adjacent regions that may interact with coreceptor molecules. The 32 SNPs were found in 20 haplotypes that can be assigned to geographic ranges of origin. Haplotype-tagging SNP analysis indicated that 12 SNPs need to be genotyped to distinguish these 20 haplotypes. These data provide a basic understanding of bovine TLR4 sequence variation and supply haplotype markers for disease association studies.

Animals↗
PubMed2004

Computational prediction of 7-ethoxyresorufin-O-diethylase (EROD) and luciferase (luc) inducing potency for 75 congeners of chloronaphthalene.

Based on available toxicological data and matrix of structural descriptors 7-ethoxyresorufin-O-diethylase (EROD) and luciferase (luc) inducing potency for 75 congeners of chloronaphthalene was predicted using quantitative structure-activity relationships (QSAR) strategy. The most active congeners in EROD and luciferase bioassays were CN congeners nos. 75 and 67. Some empirical rules describing toxic PCNs were formulated.

Chlorine Compounds↗
PubMed2006

JVirGel 2.0: computational prediction of proteomes separated via two-dimensional gel electrophoresis under consideration of membrane and secreted proteins.

MOTIVATION: After the publication of JVirGel 1.0 in 2003 we got many requests and suggestions from the proteomics community to further improve the performance of the software and to add additional useful new features. RESULTS: The integration of the PrediSi algorithm for the prediction of signal peptides for the Sec-dependent protein export into JVirGel 2.0 allows the exclusion of most exported preproteins from calculated proteomic maps and provides the basis for the calculation of Sec-based secretomes. A tool for the identification of transmembrane helices carrying proteins (JCaMelix) and the prediction of the corresponding membrane proteome was added. Finally, in order to directly compare experimental and calculated proteome data, a function to overlay and evaluate predicted and experimental two-dimensional gels was included. AVAILABILITY: JVirGel 2.0 is freely available as precompiled package for the installation on Windows or Linux operating systems. Furthermore, there is a completely platform-independent Java version available for download. Additionally, we provide a Java Server Pages based version of JVirGel 2.0 which can be operated in nearly all web browsers. All versions are accessible at http://www.jvirgel.de

Algorithms↗
PubMed2006

Lipoprotein computational prediction in spirochaetal genomes.

Lipoproteins are of great interest in understanding the molecular pathogenesis of spirochaetes. Because spirochaete lipobox sequences exhibit more plasticity than those of other bacteria, application of existing prediction algorithms to emerging sequence data has been problematic. In this paper a novel lipoprotein prediction algorithm is described, designated SpLip, constructed as a hybrid of a lipobox weight matrix approach supplemented by a set of lipoprotein signal peptide rules allowing for conservative amino acid substitutions. Both the weight matrix and the rules are based on a training set of 28 experimentally verified spirochaetal lipoproteins. The performance of the SpLip algorithm was compared to that of the hidden Markov model-based LipoP program and the rules-based algorithm Psort for all predicted protein-coding genes of Leptospira interrogans sv. Copenhageni, L. interrogans sv. Lai, Borrelia burgdorferi, Borrelia garinii, Treponema pallidum and Treponema denticola. Psort sensitivity (13-35 %) was considerably less than that of SpLip (93-100 %) or LipoP (50-84 %) due in part to the requirement of Psort for Ala or Gly at the -1 position, a rule based on E. coli lipoproteins. The percentage of false-positive lipoprotein predictions by the LipoP algorithm (8-30 %) was greater than that of SpLip (0-1 %) or Psort (4-27 %), due in part to the lack of rules in LipoP excluding unprecedented amino acids such as Lys and Arg in the -1 position. This analysis revealed a higher number of predicted spirochaetal lipoproteins than was previously known. The improved performance of the SpLip algorithm provides a more accurate prediction of the complete lipoprotein repertoire of spirochaetes. The hybrid approach of supplementing weight matrix scoring with rules based on knowledge of protein secretion biochemistry may be a general strategy for development of improved prediction algorithms.

Algorithms↗
PubMed2006

Computational prediction of cis-regulatory modules from multispecies alignments using Galaxy, Table Browser, and GALA.

One major goal of genomics is to identify all the functional sequences in genomes, including sequences that regulate the expression of genes. Sequence conservation is a good, albeit imperfect, guide to these functional elements. We describe how to use publicly available servers (Galaxy, the UCSC Table Browser, and GALA) to find genomic sequences whose alignments (from blastZ and multiZ) show properties associated with cis-regulatory modules, such as high conservation score, high regulatory potential score, and conserved transcription factor binding sites. Links to these servers can be accessed at http://www.bx.psu.edu/ and http://genome.ucsc.edu/.

Animals↗
PubMed1993

Analysis of computer-predicted antibody inducing epitope on Japanese encephalitis virus.

Theoretical methods to delineate antibody inducing epitopes have been employed to predict antigenic determinants on envelope glycoprotein (gpE) of Japanese encephalitis (JE), West Nile (WN) and Dengue (DEN) I-IV viruses. A predicted region on JE virus gpE 74CPTTGEAHNEKRAD87 was synthesized, conjugated to KLH (KLH-peptide) and used in immunization of mice. A mouse monoclonal antibody (MoAb IVB4) reactive to the peptide was also found to react with native JE virus gpE. Characterization of the idiotypic (ID) determinants with the help of polyclonal domain-specific anti-ID antibodies revealed that polyclonal anti-KLH-peptide antibodies and MoAb IVB4 are flavivirus-cross-reactive to Hx and NHx domains, respectively. The region 74-87 in JE virus gpE has been mapped as a linking area between Hx and NHx domains. Reactivity of the peptide with sera from JE patients and vaccinees also indicated the feasibility of using predicted peptides for diagnostic and prophylastic purposes.

Amino Acid Sequence↗
PubMed2001

Top 200 medicines: can new actions be discovered through computer-aided prediction?

Computer-aided prediction of the biological activity spectra by the program PASS was applied to a set of 130 pharmaceuticals from the list of the Top 200 medicines. The known pharmacological effects were found in the predicted activity spectra in 93.2% of cases. Additionally, the probability of some supplementary effects was also predicted to be significant, including angiogenesis inhibition, bone formation stimulation, possible use in cognition disorders treatment, multiple sclerosis treatment, etc. These predictions, if confirmed experimentally, may become a cause for a new application of pharmaceuticals from the Top 200 list. Most of known side and toxic effects were also predicted by PASS. PASS predictions at earlier R & D stages may thus provide a basis for finding new "leads" among already launched drugs and may help direct more attention to those particular effects of pharmaceuticals in clinical use which become apparent only in a small part of the population and require additional precautions.

Drug Prescriptions↗
PubMed2006

Bayesian data mining of protein domains gives an efficient predictive algorithm and new insight.

Identification of structural domains in uncharacterized protein sequences is important in the prediction of protein tertiary folds and functional sites, and hence in designing biologically active molecules. We present a new predictive computational method of classifying a protein into single, two continuous or two discontinuous domains using Bayesian Data Mining. The algorithm requires only the primary sequence and computer-predicted secondary structure. It incorporates correlation patterns between certain 3-dimensional motifs and some local helical folds found conserved in the vicinity of protein domains with high statistical confidence. The prediction of domain-class by this computationally simple and fast method shows good accuracy of prediction-average accuracies 83.3% for single domain, 60% for two continuous and 65.7% for two discontinuous domain proteins. Experiments on the large validation sample show its performance to be significantly better than that of DGS and DomSSEA. Computations of Bayesian probabilities show important features in terms of correlation of certain conserved patterns of secondary folds and tertiary motifs and give new insight. Applications for improved accuracy of predicting domain boundary points relevant to protein structural and functional modeling are also highlighted.

Algorithms↗
PubMed1995

Reliability of computer-generated prediction tracing.

The reliability of a commercially available computer prediction program (Quick Ceph II) was evaluated using pretreatment and posttreatment cephalograms of 30 patients who were treated during an active period of growth. The computer prediction was compared with the actual treatment result, and the growth forecast with the computer program was compared with the growth forecast using a manual method. Using paired student's t-tests, predictions for 5 of the 10 variables measured were found to be statistically reliable. Comparing the relative accuracy of growth prediction in terms of absolute values, the computer came closer to the actual result in four of the nine variables, while the manual method came closer in three variables. Predictions for the other two variables were virtually the same using both methods. The manual method of prediction was sufficient to give a reasonably good graphic representation of growth changes to create a VTO. However, the computer offers the added advantages of quicker access to information and somewhat greater accuracy in producing the tracing, as well as its use in patient education.

Adolescent↗
PubMed2004

A brief review of computational gene prediction methods.

With the development of genome sequencing for many organisms, more and more raw sequences need to be annotated. Gene prediction by computational methods for finding the location of protein coding regions is one of the essential issues in bioinformatics. Two classes of methods are generally adopted: similarity based searches and ab initio prediction. Here, we review the development of gene prediction methods, summarize the measures for evaluating predictor quality, highlight open problems in this area, and discuss future research directions.

Computational Biology↗