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PubMed1992

Pharmacokinetics and dosage adjustment of antibiotics during continuous extracorporeal lung assistance and hemofiltration.

Fifty-eight patients undergoing continuous volume-controlled hemofiltration (CVHF) and extracorporeal lung assistance (ECLA) received drug therapy determined by use of a new predictive algorithm in a validation study. Amikacin, netilmicin, tobramycin, ceftriaxone, vancomycin, and teicoplanin doses were given as predicted from clinical parameters. Corrections were necessary in 15 cases (e.g., CVHF 68% and ECLA 82% precision). There were no statistical differences between predicted and monitored drug doses. The correlation coefficient gave r2 = 0.921. Preliminary results from not yet analyzed drugs (ceftriaxone, teicoplanin) fit well into the curve. Because of rapid intraindividual changes, toxic drugs should continue to be monitored.

Acute Kidney Injury↗
PubMed2004

Application of sparse NMR restraints to large-scale protein structure prediction.

The protein structure prediction algorithm TOUCHSTONEX that uses sparse distance restraints derived from NMR nuclear Overhauser enhancement (NOE) data to predict protein structures at low-to-medium resolution was evaluated as follows: First, a representative benchmark set of the Protein Data Bank library consisting of 1365 proteins up to 200 residues was employed. Using N/8 simulated long-range restraints, where N is the number of residues, 1023 (75%) proteins were folded to a C(alpha) root-mean-square deviation (RMSD) from native <6.5 A in one of the top five models. The average RMSD of the models for all 1365 proteins is 5.0 A. Using N/4 simulated restraints, 1206 (88%) proteins were folded to a RMSD <6.5 A and the average RMSD improved to 4.1 A. Then, 69 proteins with experimental NMR data were used. Using long-range NOE-derived restraints, 47 proteins were folded to a RMSD <6.5 A with N/8 restraints and 61 proteins were folded to a RMSD <6.5 A with N/4 restraints. Thus, TOUCHSTONEX can be a tool for NMR-based rapid structure determination, as well as used in other experimental methods that can provide tertiary restraint information.

Algorithms↗
PubMed2006

Requirements for prediction of peptide retention time in reversed-phase high-performance liquid chromatography: hydrophilicity/hydrophobicity of side-chains at the N- and C-termini of peptides are dramatically affected by the end-groups and location.

The value of reversed-phase high-performance liquid chromatography (RP-HPLC) and the field of proteomics would be greatly enhanced by accurate prediction of retention times of peptides of known composition. The present study investigates the hydrophilicity/hydrophobicity of amino acid side-chains at the N- and C-termini of peptides while varying the functional end-groups at the termini. We substituted all 20 naturally occurring amino acids at the N- and C-termini of a model peptide sequence, where the functional end-groups were N(alpha)-acetyl-X- and N(alpha)-amino-X- at the N-terminus and -X-C(alpha)-carboxyl and -X-C(alpha)-amide at the C-terminus. Amino acid coefficients were subsequently derived from the RP-HPLC retention behaviour of these peptides and compared to each other as well as to coefficients determined in the centre of the peptide chain (internal coefficients). Coefficients generated from residues substituted at the C-terminus differed most (between the -X-C(alpha)-carboxyl and -X-C(alpha)-amide peptide series) for hydrophobic side-chains. A similar result was seen for the N(alpha)-acetyl-X- and N(alpha)-amino-X- peptide series, where the largest differences in coefficient values were observed for hydrophobic side-chains. Coefficients derived from substitutions at the C-terminus for hydrophobic amino acids were dramatically different compared to internal coefficients for hydrophobic side-chains, ranging from 17.1 min for Trp to 4.8 min for Cys. In contrast, coefficients derived from substitutions at the N-terminus showed relatively small differences from the internal coefficients. Subsequent prediction of peptide retention time, within an error of just 0.4 min, was achieved by a predictive algorithm using a combination of internal coefficients and coefficients for the C-terminal residues. For prediction of peptide retention time, the sum of the coefficients must include internal and terminal coefficients.

Amino Acid Sequence↗
PubMed1999

Is beta-pleated sheet the molecular conformation which dictates formation of helicoidal cuticle?

Over 100 sequences for cuticular proteins are now available, but there have been no formal analyses of how these sequences might contribute to the helicoidal architecture of cuticle or to the interaction of these proteins with chitin. A secondary structure prediction scheme (Hamodrakas, S.J., 1988. A protein secondary structure prediction scheme for the IBM PC and compatibles. CABIOS 4, 473-477) that combines six different algorithms predicting alpha-helix, beta-strands and beta-turn/loops/coil has been used to predict the secondary structure of chorion proteins and experimental confirmation has established its utility (Hamodrakas, S.J., 1992. Molecular architecture of helicoidal proteinaceous eggshells. In: Case, S.T. (Ed.), Results and Problems in Cell Differentiation, Vol. 19, Berlin-Heidelberg, Springer Verlag, pp. 116-186 and references therein). We have used this same scheme with eight cuticular protein sequences associated with hard cuticles and nineteen from soft cuticles. Secondary structure predictions were restricted to a conserved 68 amino acid region that begins with a preponderance of hydrophilic residues and ends with a 33 amino acid consensus region, first identified by Rebers and Riddiford (Rebers, J.F., Riddiford, L.M., 1988. Structure and expression of a Manduca sexta larval cuticle gene homologous to Drosophila cuticle genes. J. Mol. Biol. 203, 411-423). Both classes of sequences showed a preponderance of beta-pleated sheet, with four distinct strands in the proteins from 'hard' cuticles and three from 'soft'. In both cases, tyrosine and phenylalanine were found on one face within a sheet, an optimal location for interaction with chitin. We propose that this beta-sheet dictates formation of helicoidal cuticle.

Amino Acid Sequence↗
PubMed2005

Protein structure estimation from minimal restraints using Rosetta.

RosettaNMR combines the Rosetta de novo structure prediction method with limited NMR experimental data for rapid estimation of protein structure. The de novo Rosetta algorithm predicts protein three-dimensional structures using only sequence information by combining short fragments selected from known protein structures on the basis of local sequence similarity. These fragments are assembled using a Monte Carlo strategy to generate models that reproduce empirical statistics describing nonlocal protein structure such as overall compactness, hydrophobic burial, and beta-strand pairing. By incorporating chemical shift, nuclear Overhauser enhancement, and?or residual dipolar coupling restraints that are insufficient on their own to determine the protein global fold, the RosettaNMR method correctly estimates the global fold of a variety of different proteins, generating models that are that are generally 4?A or better Calpha root-mean-square deviation to the high-resolution experimental structures. Here we review the capabilities of the RosettaNMR approach, describe the underlying methods, and provide practical tips for applying the technique to structure estimation problems.

Algorithms↗
PubMed2000

Prediction of protein structural classes and subcellular locations.

The structural class and subcellular location are the two important features of proteins that are closely related to their biological functions. With the rapid increase in new protein sequences entering into data banks, it is highly desirable to develop a fast and accurate method for predicting the attributes of these features for them. This can expedite the functionality determination of new proteins and the process of prioritizing genes and proteins identified by genomics efforts as potential molecular targets for drug design. Various prediction methods have been developed during the last two decades. This review is devoted to presenting a systematic introduction and comparison of the existing methods in respect to the prediction algorithm and classification scheme. The attention is focused on the state-of-the-art, which is featured by the covarient-discriminant algorithm developed very recently, as well as some new classification schemes for protein structural classes and subcellular locations. Particularly, addressed are also the physical chemistry foundation of the existing prediction methods, and the essence why the covariant-discriminant algorithm is so powerful.

Algorithms↗
PubMed2003

Genetic and molecular evidence that the Pseudomonas syringae type III effector protein AvrRpt2 is a cysteine protease.

Upon delivery to the plant cell during infection, the Pseudomonas syringae effector protein AvrRpt2 undergoes proteolytic processing, enhances pathogen virulence and causes the elimination of the Arabidopsis RIN4 protein. A structure-prediction method was employed in order to investigate possible biochemical functions of AvrRpt2. Results of a secondary structure prediction algorithm suggest that the functional C-terminal portion of AvrRpt2 is a cysteine protease. Mutation of predicted catalytic residues within this portion of AvrRpt2 abolished in planta processing, elimination of Arabidopsis RIN4, and the ability to trigger an RPS2-specific resistance response. These data indicate that AvrRpt2 is most likely a sequence divergent cysteine protease whose activity is required for elimination of RIN4 during infection.

Amino Acid Sequence↗
PubMed1987

Lecithin:cholesterol acyltransferase. Functional regions and a structural model of the enzyme.

The amino acid sequence of human lecithin:cholesterol acyltransferase has been determined by degradation and alignment of peptides obtained from tryptic and staphylococcal digestions and the cleavage with cyanogen bromide and consisted of 416 amino acid residues. All of the tryptic peptides of lecithin:cholesterol acyltransferase were isolated and sequenced. Peptides resulting from digestion by staphylococcal protease, cyanogen bromide cleavage, or the combination of the two methods were employed to find overlapping segments. The N terminus of human lecithin:cholesterol acyltransferase was determined to be phenylalanine by sequencing the whole protein up to 40 residues while the C terminus was identified as glutamic acid through carboxypeptidase Y cleavage. Cys50 and Cys74 and Cys313 and Cys356 were identified as the two disulfide bridges while the free sulfhydryl groups were located at positions 31 and 184. The N-glycosylated sites of the protein were assigned to asparagines at positions 20, 84, 272, and 384. The active site of lecithin:cholesterol acyltransferase was identified as serine on position 181 according to its homology with other serine-type esterases which have a common structure of glycine-variable amino acid-active serine-variable amino acid-glycine (Gly-X-Ser-X-Gly) with the variable amino acids disrupting the homology. No long internal repeats or homologies with apolipoproteins were found. The secondary structure is consistent with the results of predictive algorithms. A simple model of the enzyme is proposed on the basis of available chemical data and predictive methods.

Amino Acid Sequence↗
PubMed2003

Renal cell carcinoma: new prognostic factors?

PURPOSE OF REVIEW: There are limited independent predictors of survival in patients with renal cell carcinoma. Factors related to the tumor, host and treatment may help us to predict prognosis to a certain extent. Prognostic indicators would enable selection of patients who can benefit from adjuvant therapy and thus should be enrolled in clinical trials. This review highlights developments in the identification of current prognosticators for patients with renal cell carcinoma. RECENT FINDINGS: Tumor stage, grade and patient-performance status are the known prognostic indicators in renal cell carcinoma. Besides these parameters, many molecular and cytogenetic markers were evaluated recently. Unfortunately, none of these parameters appear to be a better predictive prognostic factor than the usual staging and grading. Therefore, efforts to identify new markers for tumor proliferation and progression are still ongoing. It was recently reported that low carbonic anhydrase 9 staining may be an independent poor prognostic factor in patients with renal cell carcinoma. Moreover, there is increasing interest in prognostic indices and predictive algorithms for survival. Staging systems that combine the pathological features with additional prognostic variables have been constructed to predict outcome. The UCLA Integrated Staging System seems to be superior to staging alone in differentiating patients' survival. SUMMARY: Although the literature reviewed contains numerous promising clinical, histological, molecular and cytogenetic parameters, none of them has yet been shown to have an independent prognostic value

Adult↗
PubMed1997

Predicting differential antigen-antibody contact regions based on solvent accessibility.

A novel computational approach was examined for predicting epitopes from primary structures of the seven immunologically distinct botulinum neurotoxins (BoNT/A-G) and tetanus toxin (TeTX). An artificial neural network [Rost and Sander (1994), Proteins 20, 216] was used to estimate residue solvent accessibilities in multiple aligned sequences. A similar network trained to predict secondary structures was also used to examine this protein family, whose tertiary fold is presently unknown. The algorithm was validated by showing that it was 80% accurate in determining the secondary structure of avian egg-white lysozyme and that it correctly identified highly solvent-exposed residues that correspond to the major contact regions of lysozyme-antibody cocrystals. When sequences of the heavy (H) chains of TeTX and BoNT/A-G were analyzed, this algorithm predicted that the most highly exposed regions were clustered at the sequentially nonconserved N- and C-termini [Lebeda and Olson (1994), Proteins 20, 293]. The secondary structures and the remaining highly solvent-accessible regions were, in contrast, predicted to be conserved. In experiments reported by others, H-chain fragments that induced immunological protection against BoNT/A overlap with these predicted most highly exposed regions. It is also known that the C-terminal halves of the TeTX and BoNT/A H-chains interfere with holotoxin binding to ectoacceptors on nerve endings. Thus, the present results provide a theoretical framework for predicting the sites that could assist in the development of genetically engineered vaccines and that could interact with neurally located toxin ectoacceptors. Finally, because the most highly solvent-exposed regions were not well conserved, it is hypothesized that nonconserved, potential contact sites partially account for the existence of different dominant binding regions for type-specific neutralizing antibodies.

Algorithms↗
PubMed2006

Memory efficient folding algorithms for circular RNA secondary structures.

BACKGROUND: A small class of RNA molecules, in particular the tiny genomes of viroids, are circular. Yet most structure prediction algorithms handle only linear RNAs. The most straightforward approach is to compute circular structures from 'internal' and 'external' substructures separated by a base pair. This is incompatible, however, with the memory-saving approach of the Vienna RNA Package which builds a linear RNA structure from shorter (internal) structures only. RESULT: Here we describe how circular secondary structures can be obtained without additional memory requirements as a kind of 'post-processing' of the linear structures. AVAILABILITY: The circular folding algorithm is implemented in the current version of the of RNAfold program of the Vienna RNA Package, which can be downloaded from http://www.tbi.univie.ac.at/RNA/

Algorithms↗
PubMed1997

Predicting helical segments in proteins by a helix-coil transition theory with parameters derived from a structural database of proteins.

A novel helix-coil transition theory has been developed. This new theory contains more types of interactions than similar theories developed earlier. The parameters of the models were obtained from a database of 351 nonhomologous proteins. No manual adjustment of the parameters was performed. The interaction parameters obtained in this manner were found to be physically meaningful, consistent with current understanding of helix stabilizing/destabilizing interactions. Novel insights into helix stabilizing/destabilizing interactions have also emerged from this analysis. The theory developed here worked well in sorting out helical residues from amino acid sequences. If the theory was forced to make prediction on every residue of a given amino acid sequence, its performance was the best among ten other secondary structural prediction algorithms in distinguishing helical residues from nonhelical ones. The theory worked even better if one only required it to make prediction on residues that were "predictable" (identifiable by the theory); > 90% predictive reliability could be achieved. The helical residues or segments identified by the helix-coil transition theory can be used as secondary structural contraints to speed up the prediction of the three-dimensional structure of a protein by reducing the dimension of a computational protein folding problem. Possible further improvements of this helix-coil transition theory are also discussed.

Algorithms↗
PubMed1997

Stages and processes of change as predictors of drug use among methadone maintenance patients.

In this study the authors evaluated the predictive validity of stages-of-change and processes-of- change measures among methadone maintenance patients. One month after treatment entry, participants completed questionnaires providing stage and process scale scores regarding readiness to discontinue polydrug use. Participants also completed an algorithm assigning them to a stage category on the basis of their stated intentions regarding quitting. The algorithm predicted urinalysis results during a 12-week posttest period; however, only 1 stage scale (contemplation) and no process scales correlated significantly with outcome. In a hierarchical regression, stage and process scale scores significantly improved prediction of posttest abstinence beyond that afforded by baseline drug-free urine rates, but this effect was attributable to the contemplation scale alone. Despite their widespread use, stage and process scales have yet to demonstrate clearly predictive validity.

Adult↗
PubMed2000

Application of multiple sequence alignment profiles to improve protein secondary structure prediction.

The effect of training a neural network secondary structure prediction algorithm with different types of multiple sequence alignment profiles derived from the same sequences, is shown to provide a range of accuracy from 70.5% to 76.4%. The best accuracy of 76.4% (standard deviation 8.4%), is 3.1% (Q(3)) and 4.4% (SOV2) better than the PHD algorithm run on the same set of 406 sequence non-redundant proteins that were not used to train either method. Residues predicted by the new method with a confidence value of 5 or greater, have an average Q(3) accuracy of 84%, and cover 68% of the residues. Relative solvent accessibility based on a two state model, for 25, 5, and 0% accessibility are predicted at 76.2, 79.8, and 86. 6% accuracy respectively. The source of the improvements obtained from training with different representations of the same alignment data are described in detail. The new Jnet prediction method resulting from this study is available in the Jpred secondary structure prediction server, and as a stand-alone computer program from: http://barton.ebi.ac.uk/. Proteins 2000;40:502-511.

Algorithms↗
PubMed2005

An integrative approach to CTL epitope prediction: a combined algorithm integrating MHC class I binding, TAP transport efficiency, and proteasomal cleavage predictions.

Reverse immunogenetic approaches attempt to optimize the selection of candidate epitopes, and thus minimize the experimental effort needed to identify new epitopes. When predicting cytotoxic T cell epitopes, the main focus has been on the highly specific MHC class I binding event. Methods have also been developed for predicting the antigen-processing steps preceding MHC class I binding, including proteasomal cleavage and transporter associated with antigen processing (TAP) transport efficiency. Here, we use a dataset obtained from the SYFPEITHI database to show that a method integrating predictions of MHC class I binding affinity, TAP transport efficiency, and C-terminal proteasomal cleavage outperforms any of the individual methods. Using an independent evaluation dataset of HIV epitopes from the Los Alamos database, the validity of the integrated method is confirmed. The performance of the integrated method is found to be significantly higher than that of the two publicly available prediction methods BIMAS and SYFPEITHI. To identify 85% of the epitopes in the HIV dataset, 9% and 10% of all possible nonamers in the HIV proteins must be tested when using the BIMAS and SYFPEITHI methods, respectively, for the selection of candidate epitopes. This number is reduced to 7% when using the integrated method. In practical terms, this means that the experimental effort needed to identify an epitope in a hypothetical protein with 85% probability is reduced by 20-30% when using the integrated method. The method is available at http://www.cbs.dtu.dk/services/NetCTL. Supplementary material is available at http://www.cbs.dtu.dk/suppl/immunology/CTL.php.

ATP-Binding Cassette Transporters↗
PubMed1993

Determining protein loop conformation using scaling-relaxation techniques.

We recently developed a rapid loop closure algorithm in which bond lengths are scaled to constrain the ends of a segment to match a known distance and then gradually relaxed to their standard values, with boundary constraints maintained. Although the algorithm predicted the Zif286 zinc-finger loop to within approximately 2 A, it had a serious limitation that made its more general use tentative: it omitted the atomic environment of the loop. Here we report an extension of the algorithm to take into account the protein environment surrounding a given loop from the outset of the conformational search and show that it predicts structure with an efficiency and accuracy that could not be achieved without continuous environmental inclusion. The algorithm should be widely applicable to structure determination when complete experimental information is unavailable.

Algorithms↗
PubMed2004

The distribution of 10-Year risk for coronary heart disease among US adults: findings from the National Health and Nutrition Examination Survey III.

OBJECTIVES: We sought to establish the distribution of the 10-year risk for coronary heart disease (CHD) among U.S. adults. BACKGROUND: Risk assessment for CHD was developed to provide clinicians with a tool to estimate the absolute risk of developing CHD. More recently, risk assessment is increasingly being incorporated into guidelines for diagnostic testing and treatment. Yet, little is known about the 10-year risk distribution for CHD among adults in the U.S. based on these risk assessment tools. METHODS: We applied the risk prediction algorithm used by the National Cholesterol Education Program Adult Treatment Panel III guidelines to data from 13769 participants (representing 157366716 U.S. adults) age 20 to 79 years in the Third National Health and Nutrition Examination Survey (1988 to 1994). RESULTS: Among participants without self-reported CHD (heart attack and angina pectoris), stroke, peripheral vascular disease, and diabetes, 81.7% (140 million adults) had a 10-year risk for CHD of <10%, 15.5% (23 million adults) of 10% to 20%, and 2.9% (4 million adults) of >20%. The proportion of the participants with a 10-year risk for CHD of >20% increased with advancing age and was higher among men than among women but varied little with race or ethnicity. CONCLUSIONS: Our results help to define the distribution of 10-year risk for CHD among U.S. adults.

Adult↗
PubMed2005

Prediction of underwater sound levels from rain and wind.

Wind and rain generated ambient sound from the ocean surface represents the background baseline of ocean noise. Understanding these ambient sounds under different conditions will facilitate other scientific studies. For example, measurement of the processes producing the sound, assessment of sonar performance, and helping to understand the influence of anthropogenic generated noise on marine mammals. About 90 buoy-months of ocean ambient sound data have been collected using Acoustic Rain Gauges in different open-ocean locations in the Tropical Pacific Ocean. Distinct ambient sound spectra for various rainfall rates and wind speeds are identified through a series of discrimination processes. Five divisions of the sound spectra associated with different sound generating mechanisms can be predicted using wind speed and rainfall rate as input variables. The ambient sound data collected from the Intertropical Convergence Zone are used to construct the prediction algorithms, and are tested on the data from the Western Pacific Warm Pool. This physically based semi-empirical model predicts the ambient sound spectra (0.5-50 kHz) at rainfall rates from 2-200 mm/h and wind speeds from 2 to 14 m/s.

Journal Article↗