A computational analysis of substrate binding strength by phosphorylase kinase and protein kinase A

Protein kinases exhibit various degrees of substrate specificity. The large number of different protein kinases in the eukaryotic proteomes makes it impractical to determine the specificity of each enzyme experimentally. To test if it were possible to discriminate potential substrates from non-substrates by simple computational techniques, we analysed the binding enthalpies of modelled enzyme-substrate complexes and attempted to correlate it with experimental enzyme kinetics measurements. The crystal structures of phosphorylase kinase and cAMP-dependent protein kinase were used to generate models of the enzyme with a series of known peptide substrates and non-substrates, and the approximate enthalpy of binding assessed following energy minimization. We show that the computed enthalpies do not correlate closely with kinetic measurements, but the method can distinguish good substrates from weak substrates and non-substrates. Copyright (C) 2002 John Wiley Sons, Ltd.

Computational immunology: The coming of age

The explosive growth in biotechnology combined with major advancesin information technology has the potential to radically transformimmunology in the postgenomics era. Not only do we now have readyaccess to vast quantities of existing data, but new data with relevanceto immunology are being accumulated at an exponential rate. Resourcesfor computational immunology include biological databases and methodsfor data extraction, comparison, analysis and interpretation. Publiclyaccessible biological databases of relevance to immunologists numberin the hundreds and are growing daily. The ability to efficientlyextract and analyse information from these databases is vital forefficient immunology research. Most importantly, a new generationof computational immunology tools enables modelling of peptide transportby the transporter associated with antigen processing (TAP), modellingof antibody binding sites, identification of allergenic motifs andmodelling of T-cell receptor serial triggering.

Estimation of crystalline phase present in the glucose crystal-solution mixture by water activity measurement

The amount of crystalline fraction present in monohydrate glucose crystal-solution mixture up to 110% crystal in relation to solution (crystal:solution=110:100) was determined by water activity measurement. It was found that the water activity had a strong linear correlation (R-2=0.994) with the amount of glucose present above saturation. Difference in the water activities of the crystal-solution mixture (a(w1)) and the supersaturated solution (a(w2)) by re-dissolving the crystalline fraction allowed calculation of the amount of crystalline phase present (DeltaG) in the mixture by an equation DeltaG=846.97(a(w1)-a(w2)). Other methods such as Raoult's, Norrish and Money-Born equations were also tested for the prediction of water activity of supersaturated glucose solution. (C) 2003 Swiss Society of Food Science and Technology. Published by Elsevier Science Ltd. All rights reserved.

Computational tools for the study of allergens

Allergy is a major cause of morbidity worldwide. The number of characterized allergens and related information is increasing rapidly creating demands for advanced information storage, retrieval and analysis. Bioinformatics provides useful tools for analysing allergens and these are complementary to traditional laboratory techniques for the study of allergens. Specific applications include structural analysis of allergens, identification of B- and T-cell epitopes, assessment of allergenicity and cross-reactivity, and genome analysis. In this paper, the most important bioinformatic tools and methods with relevance to the study of allergy have been reviewed.

Modelling the Distribution of Ischaemic Stroke-Specific Survival Time Using an EM-based Mixture Approach with Random Effects Adjustment

A two-component survival mixture model is proposed to analyse a set of ischaemic stroke-specific mortality data. The survival experience of stroke patients after index stroke may be described by a subpopulation of patients in the acute condition and another subpopulation of patients in the chronic phase. To adjust for the inherent correlation of observations due to random hospital effects, a mixture model of two survival functions with random effects is formulated. Assuming a Weibull hazard in both components, an EM algorithm is developed for the estimation of fixed effect parameters and variance components. A simulation study is conducted to assess the performance of the two-component survival mixture model estimators. Simulation results confirm the applicability of the proposed model in a small sample setting. Copyright (C) 2004 John Wiley Sons, Ltd.

Computational methods for prediction of T-cell epitopes - a framework for modelling, testing, and applications

Computational models complement laboratory experimentation for efficient identification of MHC-binding peptides and T-cell epitopes. Methods for prediction of MHC-binding peptides include binding motifs, quantitative matrices, artificial neural networks, hidden Markov models, and molecular modelling. Models derived by these methods have been successfully used for prediction of T-cell epitopes in cancer, autoimmunity, infectious disease, and allergy. For maximum benefit, the use of computer models must be treated as experiments analogous to standard laboratory procedures and performed according to strict standards. This requires careful selection of data for model building, and adequate testing and validation. A range of web-based databases and MHC-binding prediction programs are available. Although some available prediction programs for particular MHC alleles have reasonable accuracy, there is no guarantee that all models produce good quality predictions. In this article, we present and discuss a framework for modelling, testing, and applications of computational methods used in predictions of T-cell epitopes. (C) 2004 Elsevier Inc. All rights reserved.

Optimal estimation of one-parameter quantum channels

We explore the task of optimal quantum channel identification and in particular, the estimation of a general one-parameter quantum process. We derive new characterizations of optimality and apply the results to several examples including the qubit depolarizing channel and the harmonic oscillator damping channel. We also discuss the geometry of the problem and illustrate the usefulness of using entanglement in process estimation.

Optimal quantum measurements for phase-shift estimation in optical interferometry

Quantum information theory, applied to optical interferometry, yields a 1/n scaling of phase uncertainty Delta phi independent of the applied phase shift phi, where n is the number of photons in the interferometer. This 1/n scaling is achieved provided that the output state is subjected to an optimal phase measurement. We establish this scaling law for both passive (linear) and active (nonlinear) interferometers and identify the coefficient of proportionality. Whereas a highly nonclassical state is required to achieve optimal scaling for passive interferometry, a classical input state yields a 1/n scaling of phase uncertainty for active interferometry.

Estimation of the pore size of the large-conductance mechanosensitive ion channel of Escherichia coli

The open channel diameter of Escherichia coli recombinant large-conductance mechanosensitive ion channels (MscL) was estimated using the model of Hille (Hille, B. 1968. Pharmacological modifications of the sodium channels of frog nerve. J. Gen. Physiol. 51:199-219)that relates the pore size to conductance. Based on the MscL conductance of 3.8 nS, and assumed pore lengths, a channel diameter of 34 to 46 Angstrom was calculated. To estimate the pore size experimentally, the effect of large organic ions on the conductance of MscL was examined. Poly-L-lysines (PLLs) with a diameter of 37 Angstrom or larger significantly reduced channel conductance, whereas spermine (similar to 15 Angstrom), PLL19 (similar to 25 Angstrom) and 1,1'-bis-(3-(1'-methyl-(4,4'-bipyridinium)-1-yl)-propyl)-4,4'-bipyridinium (similar to 30 Angstrom) had no effect. The smaller organic ions putrescine, cadaverine, spermine, and succinate all permeated the channel. We conclude that the open pore diameter of the MscL is similar to 40 Angstrom, indicating that the MscL has one of the largest channel pores yet described. This channel diameter is consistent with the proposed homohexameric model of the MscL.

Long-term survivor mixture model with random effects: application to a multi-centre clinical trial of carcinoma

A mixture model incorporating long-term survivors has been adopted in the field of biostatistics where some individuals may never experience the failure event under study. The surviving fractions may be considered as cured. In most applications, the survival times are assumed to be independent. However, when the survival data are obtained from a multi-centre clinical trial, it is conceived that the environ mental conditions and facilities shared within clinic affects the proportion cured as well as the failure risk for the uncured individuals. It necessitates a long-term survivor mixture model with random effects. In this paper, the long-term survivor mixture model is extended for the analysis of multivariate failure time data using the generalized linear mixed model (GLMM) approach. The proposed model is applied to analyse a numerical data set from a multi-centre clinical trial of carcinoma as an illustration. Some simulation experiments are performed to assess the applicability of the model based on the average biases of the estimates formed. Copyright (C) 2001 John Wiley & Sons, Ltd.

Estimation of body water compartments in cirrhosis by multiple-frequency bioelectrical-impedance analysis

Estimation of total body water by measuring bioelectrical impedance at a fixed frequency of 50 kHz is useful in assessing body composition in healthy populations. However, in cirrhosis, the distribution of total body water between the extracellular and intracellular compartments is of greater clinical importance. We report an evaluation of a new multiple-frequency bioelectrical-impedance analysis technique (MFBIA) that may quantify the distribution of total body water in cirrhosis. In 21 cirrhotic patients and 21 healthy control subjects, impedance to the Row of current was measured at frequencies ranging from 4 to 1012 kHz. These measurements were used to estimate body water compartments and then compared with total body water and extracellular water determined by isotope methodology. In cirrhotic patients, extracellular water and total body water (as determined by isotope methods) were well predicted by MFBIA (r = 0.73 and 0.89, respectively).;However, the 95% confidence intervals of the limits of agreement between MFBIA and the isotope methods were +/- 14% and +/-9% for cirrhotics (extracellular water and total body water, respectively) and +/-9% and +/-9% for cirrhotics without ascites. The 95% confidence intervals estimated from the control group were +/-10% and +/-5% for extracellular water and total body water, respectively. Thus, despite strong correlations between MFBIA and isotope measurements, the relatively large limits of agreement with accepted techniques suggest that the MFBIA technique requires further refinement before it can be routinely used to determine the nutritional assessment of individual cirrhotic patients. Nutrition 2001,17.31-34. (C)Elsevier Science Inc. 2001.