Agent-based modeling of the context dependency in T cell recognition

Antigen recognition by T cells is a key event in the adaptive immune response. T cells scan the surface of antigen-presenting cells (APCs) or target cells for specific peptides bound to MHC molecules. In the physiological setting, a typical APC presents tens of thousands of diverse endogenous self-derived peptides complexed to MHC (pMHC complexes). When 'foreign' peptides are presented, they constitute a small fraction of the total surface peptide repertoire. As T cells seem to be capable of discerning minute amounts of 'foreign' peptides among a complex background of self-peptides, endogenous peptides are generally assumed to play no role in recognition. However, recent results suggest that these background peptides may alter the sensitivity of T cells to foreign peptides. Current experimental limitations preclude analysis of peptide mixtures approaching physiological complexity, making it difficult to further address the role of complex background peptides. In this paper, we present a computational model to test how complex, varied peptide populations on an APC could potentially modulate a T cell's ability to detect the presence of small numbers of agonist peptides among a diverse population. We use the model to investigate the notion that under physiological conditions, T cell recognition of foreign peptides is context dependent, that is, T cells process signals gathered from all pMHC interactions, not just from a few agonist peptides while ignoring all others.     

Parameterization and classification of the protein universe via geometric techniques

We present a scheme for the classification of 3487 non-redundant protein structures into 1207 non-hierarchical clusters by using recurring structural patterns of three to six amino acids as keys of classification. This results in several signature patterns, which seem to decide membership of a protein in a functional category. The patterns provide clues to the key residues involved in functional sites as well as in protein-protein interaction. The discovered patterns include a "glutamate double bridge" of superoxide dismutase, the functional interface of the serine protease and inhibitor, interface of homo/hetero dimers, and functional sites of several enzyme families. We use geometric invariants to decide superimposability of structural patterns. This allows the parameterization of patterns and discovery of recurring patterns via clustering. The geometric invariant-based approach eliminates the computationally explosive step of pair-wise comparison of structures. The results provide a vast resource for the biologists for experimental validation of the proposed functional sites, and for the design of synthetic enzymes, inhibitors and drugs.     

Disc-electrophoresis of albumin and globulin fractions from dormant achenes of Lasthenia

Albumin and globulin fractions were extracted from dormant seeds of all 20 taxa of Lasthenia. After disc-electrophoresis on basic 7% acrylamide gels, mean R_p values, coefficients of variation and 95% confidence intervals were computed for both types of protein bands. Dendrograms were produced using similarity coefficients, indicating interspecific affinities among the taxa which differ from the sectional taxonomy of the genus. Protein data concerning certain problematical relationships are compared with published taxonomical and chemical data.     

How different from random are docking predictions when ranked by scoring functions?

Docking algorithms predict the structure of protein–protein interactions. They sample the orientation of two unbound proteins to produce various predictions about their interactions, followed by a scoring step to rank the predictions. We present a statistical assessment of scoring functions used to rank near‐native orientations, applying our statistical analysis to a benchmark dataset of decoys of protein–protein complexes and assessing the statistical significance of the outcome in the Critical Assessment of PRedicted Interactions (CAPRI) scoring experiment. A P value was assigned that depended on the number of near‐native structures in the sampling. We studied the effect of filtering out redundant structures and tested the use of pair‐potentials derived using ZDock and ZRank. Our results show that for many targets, it is not possible to determine when a successful reranking performed by scoring functions results merely from random choice. This analysis reveals that changes should be made in the design of the CAPRI scoring experiment. We propose including the statistical assessment in this experiment either at the preprocessing or the evaluation step. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Higher-order interhelical spatial interactions in membrane proteins

Higher-order interactions are important for protein folding and assembly. We introduce the concept of interhelical three-body interactions as derived from Delaunay triangulation and alpha shapes of protein structures. In addition to glycophorin A, where triplets are strongly correlated with protein stability, we found that tight interhelical triplet interactions exist extensively in other membrane proteins, where many types of triplets occur far more frequently than in soluble proteins. We developed a probabilistic model for estimating the value of membrane helical interaction triplet (MHIT) propensity. Because the number of known structures of membrane proteins is limited, we developed a bootstrap method for determining the 95% confidence intervals of estimated MHIT values. We identified triplets that have high propensity for interhelical interactions and are unique to membrane proteins, e.g. AGF, AGG, GLL, GFF and others. A significant fraction (32%) of triplet types contains triplets that may be involved in interhelical hydrogen bond interactions, suggesting the prevalent and important roles of H-bond in the assembly of TM helices. There are several well-defined spatial conformations for triplet interactions on helices with similar parallel or antiparallel orientations and with similar right-handed or left-handed crossing angles. Often, they contain small residues and correspond to the regions of the closest contact between helices. Sequence motifs such as GG4 and AG4 can be part of the three-body interactions that have similar conformations, which in turn can be part of a higher-order cooperative four residue spatial motif observed in helical pairs from different proteins. In many cases, spatial motifs such as serine zipper and polar clamp are part of triplet interactions. On the basis of the analysis of the archaeal rhodopsin family of proteins, tightly packed triplet interactions can be achieved with several different choices of amino acid residues.     

Comprehensive evaluation of multiple cropping systems on upland red soil

According to the principles and methods of ecology and system engineering,we set up an evaluation indicator system for multi-component and multiple crop-ping systems,evaluated the comprehensive benefits of multi-component and multiple cropping systems using grey relation clustering analysis and screened out the opti-mized model based on research done in the upland red soil in Jiangxi Agricultural University from 1984 to 2004.The results show that the grey relation degree of "cabbage/ potato/maize-sesame" was the highest among 23 multi-component and multiple cropping systems and was clustered into the optimized system.This indicates that "cabbage/potato/maize - sesame" can bring the best social,economic and ecological benefits,increase product yield and farmers' income and promote sustainable development of agricultural production.Therefore,it is suitable for promotion on upland red soil.The grey rela-tion degree of "canola/Chinese milk vetch/maize/mung bean/maize" was second,which is suitable for imple-mentation at the city outskirts.In conclusion,these two planting patterns are expected to play important roles in the reconstruction of the planting structure and optimiza-tion of the planting patterns on upland red soil.