A novel method for selection of chymotrypsin inhibitors from a phage peptide library

A novel screening strategy has been developed for the identification of alpha-chymotrypsin inhibitors from a phage peptide library. In this strategy, the standard affinity selection protocol was modified by adding a proteolytic cleavage period to avoid recovery of alpha-chymotrypsin substrates. After four cycles of selection and further activity assay, a group of related peptides were identified by DNA sequencing. These peptides share a consensus sequence motif as (S/T)RVPR(R/H). Then, a corresponding short peptide (Ac-ASRVPRRG-NH2) was synthesized chemically and proved to be an inhibitor of alpha-chymotrypsin. The present work provides a useful way for searching proteinase inhibitors without detailed knowledge of the molecular structure.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

Relationship between peptide selectivities of human transporters associated with antigen processing and HLA class I molecules

Efficiency of presentation of a peptide epitope by a MHC class I molecule depends on two parameters: its binding to the MHC molecule and its generation by intracellular Ag processing. In contrast to the former parameter, the mechanisms underlying peptide selection in Ag processing are poorly understood. Peptide translocation by the TAP transporter is required for presentation of most epitopes and may modulate peptide supply to MHC class I molecules. To study the role of human TAP for peptide presentation by individual HLA class I molecules, we generated artificial neural networks capable of predicting the affinity of TAP for random sequence 9-mer peptides. Using neural network-based predictions of TAP affinity, we found that peptides eluted from three different HLA class I molecules had higher TAP affinities than control peptides with equal binding affinities for the same HLA class I molecules, suggesting that human TAP may contribute to epitope selection. In simulated TAP binding experiments with 408 HLA class I binding peptides, HLA class I molecules differed significantly with respect to TAP affinities of their ligands, As a result, some class I molecules, especially HLA-B27, may be particularly efficient in presentation of cytosolic peptides with low concentrations, while most class I molecules may predominantly present abundant cytosolic peptides.

Selection of a strain of Aspergillus for the production of citric acid from pineapple waste in solid-state fermentation

Aspergillus foetidus ACR I 3996 (=FRR 3558) and three strains of Aspergillus niger ACM 4992 (=ATCC 9142), ACM 4993 (=ATCC 10577), ACM 4994 (=ATCC 12846) were compared for the production of citric acid from pineapple peel in solid-state fermentation. A. niger ACM 4992 produced the highest amount of citric acid, with a yield of 19.4 g of citric acid per 100 g of dry fermented pineapple waste under optimum conditions, representing a yield of 0.74 g citric acid/g sugar consumed. Optimal conditions were 65% (w/w) initial moisture content, 3% (v/w) methanol, 30 degrees C, an unadjusted initial pH of 3.4, a particle size of 2 mm and 5 ppm Fe2+. Citric acid production was best in flasks, with lower yields being obtained in tray and rotating drum bioreactors.

Anthropometric-based selection and sprint kayak training in children

A 12 week kayak training programme was evaluated in children who either had or did not have the anthropometric characteristics identified as being unique to senior elite sprint kayakers. Altogether, 234 male and female school children were screened to select 10 children with and 10 children without the identified key anthropometric characteristics. Before and after training, the children completed an all-out 2 min kayak ergometer simulation test; measures of oxygen consumption, plasma lactate and total work accomplished were recorded. In addition, a 500 m time trial was performed at weeks 3 and 12. The coaches were unaware which 20 children possessed those anthropometric characteristics deemed to favour development of kayak ability. All children improved in both the 2 min ergometer simulation test and 500 m time trial. However, boys who were selected according to favourable anthropometric characteristics showed greater improvement than those without such characteristics in the 2 min ergometer test only. In summary, in a small group of children selected according to anthropometric data unique to elite adult kayakers, 12 weeks of intensive kayak training did not influence the rate of improvement of on-water sprint kayak performance.

Effects of egg load on the host-selection behaviour of Helicoverpa armigera (Hubner) (Lepidoptera : Noctuidae)

We examined the effect of age-specific fecundity, mated status, and egg load on host-plant selection, by Helicoverpa armigera under laboratory conditions. The physiological state of a female moth (number of mature eggs produced) greatly influences her host-plant specificity and propensity to oviposit (oviposition motivation). Female moths were less discriminating against cowpea (a low-ranked host) relative to maize (a high-ranked host) as egg load increased. Similarly, increased egg load led to a greater propensity to oviposit on both cowpea and maize. Distribution of oviposition with age of mated females peaked shortly after mating and declined steadily thereafter until death. Most mated females (88%) carried only a single spermatophore, a few females (12%) contained two. The significance of these findings in relation to host-plant selection by H. armigera, and its management, are discussed.

An exploration of varieties of visual attention: ERP findings

A set of five tasks was designed to examine dynamic aspects of visual attention: selective attention to color, selective attention to pattern, dividing and switching attention between color and pattern, and selective attention to pattern with changing target. These varieties of visual attention were examined using the same set of stimuli under different instruction sets; thus differences between tasks cannot be attributed to differences in the perceptual features of the stimuli. ERP data are presented for each of these tasks. A within-task analysis of different stimulus types varying in similarity to the attended target feature revealed that an early frontal selection positivity (FSP) was evident in selective attention tasks, regardless of whether color was the attended feature. The scalp distribution of a later posterior selection negativity (SN) was affected by whether the attended feature was color or pattern. The SN was largely unaffected by dividing attention across color and pattern. A large widespread positivity was evident in most conditions, consisting of at least three subcomponents which were differentially affected by the attention conditions. These findings are discussed in relation to prior research and the time course of visual attention processes in the brain. (C) 1999 Elsevier Science B.V. All rights reserved.

Effects of data characteristics on the results of reserve selection algorithms

We tested the effects of four data characteristics on the results of reserve selection algorithms. The data characteristics were nestedness of features (land types in this case), rarity of features, size variation of sites (potential reserves) and size of data sets (numbers of sites and features). We manipulated data sets to produce three levels, with replication, of each of these data characteristics while holding the other three characteristics constant. We then used an optimizing algorithm and three heuristic algorithms to select sites to solve several reservation problems. We measured efficiency as the number or total area of selected sites, indicating the relative cost of a reserve system. Higher nestedness increased the efficiency of all algorithms (reduced the total cost of new reserves). Higher rarity reduced the efficiency of all algorithms (increased the total cost of new reserves). More variation in site size increased the efficiency of all algorithms expressed in terms of total area of selected sites. We measured the suboptimality of heuristic algorithms as the percentage increase of their results over optimal (minimum possible) results. Suboptimality is a measure of the reliability of heuristics as indicative costing analyses. Higher rarity reduced the suboptimality of heuristics (increased their reliability) and there is some evidence that more size variation did the same for the total area of selected sites. We discuss the implications of these results for the use of reserve selection algorithms as indicative and real-world planning tools.

Bird responses at inherent and induced edges in the Murray Mallee, South Australia. 2. Nest predation as an edge effect

We assayed nest predation as an edge effect, using artificial ground nests, at inherent (naturally occurring) and induced (human-created) edges, in the Murray Mallee, South Australia. Nests were constructed at distances between 0-120 m away from habitat edges. The relative predation rate on nests generally increased close to induced edges with a significant difference (P < 0.05) recorded for two out of five experiments. Predation rate at inherent edges was similar from the edge to the interior, and was lower than that recorded at induced edges. Our results suggest that increased predator numbers, activity or efficiency at locating nests occurred close to the induced edges at our study sites.

A rapid selection/amplification procedure for high-level expression of recombinant protein in a metal-amplifiable mammalian expression system

We describe a strategy for the selection and amplification of foreign gene expression in Chinese hamster ovary (CHO) cells employing a metallothionein gene-containing expression vector. This report describes an amplification procedure that results in an enrichment of clones exhibiting high levels of recombinant protein production and reduces the labour required for screening recombinant cell lines.

Role of chemical cues from cotton in mediating host selection and oviposition behaviour in Helicoverpa armigera (Hubner) (Lepidoptera : Noctuidae)

We investigated the role of chemoreception in the host selection and oviposition behaviour of Helicoverpa armigera in the laboratory using five cotton genotypes and synthetic volatile terpenes. Female moths oviposited on substrates treated with methanol, ethanol, acetone and pentane extracts of leaves, squares and flowers of the cotton genotypes. Phytochemicals soluble in pentane were the most efficient in eliciting oviposition behaviour. In a two-way bioassay, pentane extracts of leaves or squares of a Multiple Host-plant Resistance genotype (MHR11), Deltapine commercial (DP90), and Smith Red Leaf (SRL) received significantly more eggs than solvent-treated controls. Extracts of squares of the native genotype Gossypium nelsonii did not receive more eggs. Females preferred DP90 and MHR11 to SRL and G. nelsonii. Female moths also laid more eggs on pentane extracts of MHR11 flowers than MHR11 leaves from preflowering, early flowering and peak-flowering plants. In a flight chamber, female moths used olfactory cues at short range to mediate oviposition and discrimination between host plants. Egg-laying, mated females were attracted at a distance (1.5 m) to volatile compounds released by whole plants and odours emanating from filter papers treated with synthetic volatile terpenes. Individually, the terpenes did not stimulate any significant oviposition response. However, there was a significant oviposition response to a mixture of equal volumes of the terpenes (trans-beta-caryophyllene, alpha-pinene, beta-pinene, myrcene, beta-bisabolol, and alpha-humulene). Conversely, antennectomised (moths with transected antennae), egg-laying, mated females did not stimulate any significant oviposition response. The significance of these findings in relation to H. armigera hostplant selection are discussed.

Conformational selection of inhibitors and substrates by proteolytic enzymes: Implications for drug design and polypeptide processing

Inhibitors of proteolytic enzymes (proteases) are emerging as prospective treatments for diseases such as AIDS and viral infections, cancers, inflammatory disorders, and Alzheimer's disease. Generic approaches to the design of protease inhibitors are limited by the unpredictability of interactions between, and structural changes to, inhibitor and protease during binding. A computer analysis of superimposed crystal structures for 266 small molecule inhibitors bound to 48 proteases (16 aspartic, 17 serine, 8 cysteine, and 7 metallo) provides the first conclusive proof that inhibitors, including substrate analogues, commonly bind in an extended beta-strand conformation at the active sites of all these proteases. Representative superimposed structures are shown for (a) multiple inhibitors bound to a protease of each class, (b) single inhibitors each bound to multiple proteases, and (c) conformationally constrained inhibitors bound to proteases. Thus inhibitor/substrate conformation, rather than sequence/composition alone, influences protease recognition, and this has profound implications for inhibitor design. This conclusion is supported by NMR, CD, and binding studies for HIV-1 protease inhibitors/ substrates which, when preorganized in an extended conformation, have significantly higher protease affinity. Recognition is dependent upon conformational equilibria since helical and turn peptide conformations are not processed by proteases. Conformational selection explains the resistance of folded/structured regions of proteins to proteolytic degradation, the susceptibility of denatured proteins to processing, and the higher affinity of conformationally constrained 'extended' inhibitors/substrates for proteases. Other approaches to extended inhibitor conformations should similarly lead to high-affinity binding to a protease.

Methods for prediction of peptide binding to MHC molecules: A comparative study

Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.