Prediction of protein deamidation rates from primary and three-dimensional structure

A method for the quantitative estimation of instability with respect to deamidation of the asparaginyl (Asn) residues in proteins is described. The procedure involves the observation of several simple aspects of the three-dimensional environment of each Asn residue in the protein and a calculation that includes these observations, the primary amino acid residue sequence, and the previously reported complete set of sequence-dependent rates of deamidation for Asn pentapeptides. This method is demonstrated and evaluated for 23 proteins in which 31 unstable and 167 stable Asn residues have been reported and for 7 unstable and 63 stable Asn residues that have been reported in 61 human hemoglobin variants. The relative importance of primary structure and three-dimensional structure in Asn deamidation is estimated.

Force and kinetic barriers to unzipping of the DNA double helix

A theory of the unzipping of double-stranded DNA is presented and is compared to recent micromanipulation experiments. It is shown that the interactions that stabilize the double helix and the elastic rigidity of single strands simply determine the sequence-dependent ≈12-pN force threshold for DNA strand separation. Using a semimicroscopic model of the binding between nucleotide strands, we show that the greater rigidity of the strands when formed into double-stranded DNA, relative to that of isolated strands, gives rise to a potential barrier to unzipping. The effects of this barrier are derived analytically. The force to keep the extremities of the molecule at a fixed distance, the kinetic rates for strand unpairing at fixed applied force, and the rupture force as a function of loading rate are calculated. The dependence of the kinetics and of the rupture force on molecule length is also analyzed.

The folding mechanism of larger model proteins: role of native structure.

The folding mechanism of a 125-bead heteropolymer model for proteins is investigated with Monte Carlo simulations on a cubic lattice. Sequences that do and do not fold in a reasonable time are compared. The overall folding behavior is found to be more complex than that of models for smaller proteins. Folding begins with a rapid collapse followed by a slow search through the semi-compact globule for a sequence-dependent stable core with about 30 out of 176 native contacts which serves as the transition state for folding to a near-native structure. Efficient search for the core is dependent on structural features of the native state. Sequences that fold have large amounts of stable, cooperative structure that is accessible through short-range initiation sites, such as those in anti-parallel sheets connected by turns. Before folding is completed, the system can encounter a second bottleneck, involving the condensation and rearrangement of surface residues. Overly stable local structure of the surface residues slows this stage of the folding process. The relation of the results from the 125-mer model studies to the folding of real proteins is discussed.

Foldons, protein structural modules, and exons.

Foldons, which are kinetically competent, quasi-independently folding units of a protein, may be defined using energy landscape analysis. Foldons can be identified by maxima in a scan of the ratio of a contiguous segment's energetic stability gap to the energy variance of that segment's molten globule states, reflecting the requirement of minimal frustration. The predicted foldons are compared with the exons and structural modules for 16 of the 30 proteins studied. Statistical analysis indicates a strong correlation between the energetically determined foldons and Go's geometrically defined structural modules, but there are marked sequence-dependent effects. There is only a weak correlation of foldons to exons. For gammaII-crystallin, myoglobin, barnase, alpha-lactalbumin, and cytochrome c the foldons and some noncontiguous clusters of foldons compare well with intermediates observed in experiment.

Inhibition of Plasmodium falciparum malaria using antisense oligodeoxynucleotides.

We studied inhibition of growth of the malaria parasite Plasmodium falciparum in in vitro culture using antisense (AS) oligodeoxynucleotides (ODNs) against different target genes. W2 and W2mef strains of drug-resistant parasites were exposed to AS ODNs over 48 hr, and growth was determined by microscopic examination and [3H]hypoxanthine incorporation. At ODN concentrations of 1 microM, phosphorothioate (PS) ODNs inhibited growth in a target-independent manner. However, between 0.5 and 0.005 microM, ODNs against dihydrofolate reductase, dihydropteroate synthetase, ribonucleotide reductase, the schizont multigene family, and erythrocyte binding antigen EBA175 significantly inhibited growth compared with a PS AS ODN against human immunodeficiency virus, two AS ODNs containing eight mismatches, or the sense strand controls (P < 0.0001). The IC50 was approximately 0.05 microM, whereas that for non-sequence-specific controls was 15-fold higher. PS AS ODNs against DNA polymerase alpha showed less activity than that for other targets, whereas a single AS ODN against triose-phosphate isomerase did not differ significantly from controls. We conclude that at concentrations below 0.5 microM, PS AS ODNs targeted against several malarial genes significantly inhibit growth of drug-resistant parasites in a nucleotide sequence-dependent manner. This technology represents an alternative method for identifying malarial genes as potential drug targets.

Periodicity of strong nucleosome positioning sites around the chicken adult beta-globin gene may encode regularly spaced chromatin.

Positioned nucleosomes contribute to both the structure and the function of the chromatin fiber and can play a decisive role in controlling gene expression. We have mapped, at high resolution, the translational positions adopted by limiting amounts of core histone octamers reconstituted onto 4.4 kb of DNA comprising the entire chicken adult beta-globin gene, its enhancer, and flanking sequences. The octamer displays extensive variation in its affinity for different positioning sites, the range exhibited being about 2 orders of magnitude greater than that of the initial binding of the octamer. Strong positioning sites are located 5' and 3' of the globin gene and in the second intron but are absent from the coding regions. These sites exhibit a periodicity (approximately 200 bp) similar to the average spacing of nucleosomes on the inactive beta-globin gene in vivo, which could indicate their involvement in packaging the gene into higher-order chromatin structure. Overlapping, alternative octamer positioning sites commonly exhibit spacings of 20 and 40 bp, but not of 10 bp. These short-range periodicities could reflect features of the core particle structure contributing to the pronounced sequence-dependent manner in which the core histone octamer interacts with DNA.

Crystal structure of a DNA decamer showing a novel pseudo four-way helix-helix junction.

The crystal structure of the decanucleotide d(CGCAATTGCG)2 has been solved by a combination of molecular replacement and heavy-atom procedures and has been refined to an R factor of 20.2% at 2.7 A. It is not a fully base-paired duplex but has a central core of eight Watson-Crick base pairs flanked by unpaired terminal guanosines and cytosines. These participate in hydrogen-bonding arrangements with adjacent decamer duplexes in the crystal lattice. The unpaired guanosines are bound in the G+C regions of duplex minor grooves. The cytosines have relatively high mobility, even though they are constrained to be in one region where they are involved in base-paired triplets with G.C base pairs. The 5'-AATT sequence in the duplex region has a narrow minor groove, providing further confirmation of the sequence-dependent nature of groove width.

Strand specificity in the transcriptional targeting of recombination at immunoglobulin switch sequences.

B-lymphocyte-specific class switch recombination is known to occur between pairs of 2- to 10-kb switch regions located immediately upstream of the immunoglobulin constant heavy-chain genes. Others have shown that the recombination is temporally correlated with the induction of transcription at the targeted switch regions. To determine whether this temporal correlation is due to a mechanistic linkage, we have developed an extrachromosomal recombination assay that closely recapitulates DNA deletional class switch recombination. In this assay, the rate of recombination is measured between 24 and 48 hr posttransfection. We find that recombinants are generated in a switch sequence-dependent manner. Recombination occurs with a predominance within B-cell lines representative of the mature B-cell stage and within a subset of pre-B-cell lines. Transcription stimulates the switch sequence-dependent recombination. Importantly, transcription activates recombination only when directed in the physiologic orientation but has no effect when directed in the nonphysiologic orientation.

GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA

Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA structure and flexibility may also play a role in protein-DNA interactions, the simultaneous exploration of sequence-and structure-based hypotheses about the composition of binding sites and the ordering of features in a regulatory region should be considered as well. The consideration of structural features requires the development of new detection tools that can deal with data types other than primary sequence. Results: GANN ( available at http://bioinformatics.org.au/gann) is a machine learning tool for the detection of conserved features in DNA. The software suite contains programs to extract different regions of genomic DNA from flat files and convert these sequences to indices that reflect sequence and structural composition or the presence of specific protein binding sites. The machine learning component allows the classification of different types of sequences based on subsamples of these indices, and can identify the best combinations of indices and machine learning architecture for sequence discrimination. Another key feature of GANN is the replicated splitting of data into training and test sets, and the implementation of negative controls. In validation experiments, GANN successfully merged important sequence and structural features to yield good predictive models for synthetic and real regulatory regions. Conclusion: GANN is a flexible tool that can search through large sets of sequence and structural feature combinations to identify those that best characterize a set of sequences.

Inventory parameter management and focused continuous improvement for repetitive batch manufacturers

What this thesis proposes is a methodology to assist repetitive batch manufacturers in the adoption of certain aspects of the Lean Production principles. The methodology concentrates on the reduction of inventory through the setting of appropriate batch sizes, taking account of the effect of sequence dependent set-ups and the identification and elimination of bottlenecks. It uses a simple Pareto and modified EBQ based analysis technique to allocate items to period order day classes based on a combination of each item's annual usage value and set-up cost. The period order day classes the items are allocated to are determined by the constraints limits in the three measured dimensions, capacity, administration and finance. The methodology overcomes the limitations associated with MRP in the area of sequence dependent set-ups, and provides a simple way of setting planning parameters taking this effect into account by concentrating on the reduction of inventory through the systematic identification and elimination of bottlenecks through set-up reduction processes, so allowing batch sizes to reduce. It aims to help traditional repetitive batch manufacturers in a route to continual improvement by: Highlighting those areas where change would bring the greatest benefits. Modelling the effect of proposed changes. Quantifying the benefits that could be gained through implementing the proposed changes. Simplifying the effort required to perform the modelling process. It concentrates on increasing flexibility through managed inventory reduction through rationally decreasing batch sizes, taking account of sequence dependent set-ups and the identification and elimination of bottlenecks. This was achieved through the development of a software modelling tool, and validated through a case study approach.

Optimization of physical distribution problem in logistics management

Physical distribution plays an imporant role in contemporary logistics management. Both satisfaction level of of customer and competitiveness of company can be enhanced if the distribution problem is solved optimally. The multi-depot vehicle routing problem (MDVRP) belongs to a practical logistics distribution problem, which consists of three critical issues: customer assignment, customer routing, and vehicle sequencing. According to the literatures, the solution approaches for the MDVRP are not satisfactory because some unrealistic assumptions were made on the first sub-problem of the MDVRP, ot the customer assignment problem. To refine the approaches, the focus of this paper is confined to this problem only. This paper formulates the customer assignment problem as a minimax-type integer linear programming model with the objective of minimizing the cycle time of the depots where setup times are explicitly considered. Since the model is proven to be MP-complete, a genetic algorithm is developed for solving the problem. The efficiency and effectiveness of the genetic algorithm are illustrated by a numerical example.

Functionalized carbon nanotube nanoelectrodes for biomolecular recognition

The objective of this research is to develop nanoscale ultrasensitive transducers for detection of biological species at molecular level using carbon nanotubes as nanoelectrodes. Rapid detection of ultra low concentration or even single DNA molecules are essential for medical diagnosis and treatment, pharmaceutical applications, gene sequencing as well as forensic analysis. Here the use of functionalized single walled carbon nanotubes (SWNT) as nanoscale detection platform for rapid detection of single DNA molecules is demonstrated. The detection principle is based on obtaining electrical signal from a single amine terminated DNA molecule which is covalently bridged between two ends of an SWNT separated by a nanoscale gap. The synthesis, fabrication, chemical functionalization of nanoelectrodes and DNA attachment were optimized to perform reliable electrical characterization these molecules. Using this detection system fundamental study on charge transport in DNA molecule of both genomic and non genomic sequences is performed. We measured an electrical signal of about 30 pA through a hybridized DNA molecule of 80 base pair in length which encodes a portion of sequence of H5N1 gene of avian Influenza A virus. Due the dynamic nature of the DNA molecules the local environment such as ion concentration, pH and temperature significantly influence its physical properties. We observed a decrease in DNA conductance of about 33% in high vacuum conditions. The counterion variation was analyzed by changing the buffer from sodium acetate to tris(hydroxymethyl) aminomethane, which resulted in a two orders of magnitude increase in the conductivity of the DNA. The fabrication of large array of identical SWNT nanoelectrodes was achieved by using ultralong SWNTs. Using these nanoelectrode array we have investigated the sequence dependent charge transport in DNA. A systematic study performed on PolyG - PolyC sequence with varying number of intervening PolyA - PolyT pairs showed a decrease in electrical signal from 180 pA (PolyG - PolyC) to 30 pA with increasing number of the PolyA - PolyT pairs. This work also led to the development of ultrasensitive nanoelectrodes based on enzyme functionalized vertically aligned high density multiwalled CNTs for electrochemical detection of cholesterol. The nanoelectrodes exhibited selectively detection of cholesterol in the presence of common interferents found in human blood.

Investigation of generation -recombination noise and related processes in aluminum gallium arsenide TEGFETs and Hall structures with quantum wells

Experimental and theoretical studies regarding noise processes in various kinds of AlGaAs/GaAs heterostructures with a quantum well are reported. The measurement processes, involving a Fast Fourier Transform and analog wave analyzer in the frequency range from 10 Hz to 1 MHz, a computerized data storage and processing system, and cryostat in the temperature range from 78 K to 300 K are described in detail. The current noise spectra are obtained with the “three-point method”, using a Quan-Tech and avalanche noise source for calibration. ^ The properties of both GaAs and AlGaAs materials and field effect transistors, based on the two-dimensional electron gas in the interface quantum well, are discussed. Extensive measurements are performed in three types of heterostructures, viz., Hall structures with a large spacer layer, modulation-doped non-gated FETs, and more standard gated FETs; all structures are grown by MBE techniques. ^ The Hall structures show Lorentzian generation-recombination noise spectra with near temperature independent relaxation times. This noise is attributed to g-r processes in the 2D electron gas. For the TEGFET structures, we observe several Lorentzian g-r noise components which have strongly temperature dependent relaxation times. This noise is attributed to trapping processes in the doped AlGaAs layer. The trap level energies are determined from an Arrhenius plot of log (τT2) versus 1/T as well as from the plateau values. The theory to interpret these measurements and to extract the defect level data is reviewed and further developed. Good agreement with the data is found for all reported devices. ^

Criação de estabilidade numa linha de produção de argamassas em pó

Com as constantes mudanças de mercado, as empresas enfrentam cada vez mais obstáculos para se manterem competitivas e inovadoras, para isso procuram formas de sobreviver seguindo filosofias e utilizando ferramentas que permita atingir os seus objetivos. A filosofia Lean é uma filosofia seguida por muitas empresas que pretendam criar valor eliminando desperdícios. O objetivo deste projeto passa pela implementação de ferramentas Lean de modo a criar estabilidade no processo produtivo, eliminando desperdícios e criando valor. Com foco neste objetivo estudou-se as principais fontes de variabilidade no processo produtivo nos 4M’s (Máquina, Método, Mão-de-Obra e Máquina). Após essa análise foram implementadas ações de melhoria como os 5S, criação de sistemas visuais, redução do tempos de setup e tempos de espera, introdução de kanbans e padronização dos métodos de trabalho.Com a implementação destas medidas foi possível tornar o processo produtivo mais estável e flexível, com capacidade para responder às constantes alterações de mercado.

Proposta de implementação de uma metodologia SMED numa metalomecânica

O presente trabalho é o resultado de um projecto experimental que teve como principal objetivo a redução dos tempos de setup, através da implementação da metodologia Single Minute Exchange of Die (SMED) em equipamentos de eletroerosão (EDM) por fio e penetração. Para garantir o sucesso da implementação, após uma revisão bibliográfica centrada no tema SMED, estabelece-se uma metodologia, numa lógica de melhoria contínua análoga a um ciclo PDCA. A metodologia estabelecida envolve as seguintes fases: caracterização da situação inicial, observação, recolha de dados, análise dos dados e implementação SMED. A caracterização da situação inicial visa qualificar a situação encontrada e identificar a zona de atuação - equipamentos em estudo. A observação do processo produtivo é suportada pela ferramenta fluxograma do processo, por sua vez, a recolha de dados visa a avaliação inicial e nessa perspectiva recorre-se à abordagem OEE. Na fase de análise dos dados são introduzidas as ferramentas de análise VSM e diagrama de causa e efeito que auxiliam a identificação de um conjunto de acções de melhoria, a realizar previamente à fase de implementação SMED, culminando assim uma fase PRÉ-SMED. Reunidas as condições ideais iniciou-se a implementação efectiva da metodologia SMED obtendo-se reduções do tempo total de setup superiores a 60%. O presente estudo permite concluir que podem surgir diferenças significativas em diversas aplicações SMED, enfatizando a importância de uma fase PRÉ-SMED de modo a potenciar os resultados alcançados com uma implementação SMED.