Structure-based prediction of binding peptides to MHC class I molecules: application to a broad range of MHC alleles

Specific binding of antigenic peptides to major histocompatibility complex (MHC) class I molecules is a prerequisite for their recognition by cytotoxic T-cells. Prediction of MHC-binding peptides must therefore be incorporated in any predictive algorithm attempting to identify immunodominant T-cell epitopes, based on the amino acid sequence of the protein antigen. Development of predictive algorithms based on experimental binding data requires experimental testing of a very large number of peptides. A complementary approach relies on the structural conservation observed in crystallographically solved peptide-MHC complexes. By this approach, the peptide structure in the MHC groove is used as a template upon which peptide candidates are threaded, and their compatibility to bind is evaluated by statistical pairwise potentials. Our original algorithm based on this approach used the pairwise potential table of Miyazawa and Jernigan (Miyazawa S, Jernigan RL, 1996, J Mol Biol 256:623-644) and succeeded to correctly identify good binders only for MHC molecules with hydrophobic binding pockets, probably because of the high emphasis of hydrophobic interactions in this table. A recently developed pairwise potential table by Betancourt and Thirumalai (Betancourt MR, Thirumalai D, 1999, Protein Sci 8:361-369) that is based on the Miyazawa and Jernigan table describes the hydrophilic interactions more appropriately. In this paper, we demonstrate how the use of this table, together with a new definition of MHC contact residues by which only residues that contribute exclusively to sequence specific binding are included, allows the development of an improved algorithm that can be applied to a wide range of MHC class I alleles.     

Prediction of amino acid sequence from structure

We have developed a method for the prediction of an amino acid sequence that is compatible with a three-dimensional backbone structure. Using only a backbone structure of a protein as input, the algorithm is capable of designing sequences that closely resemble natural members of the protein family to which the template structure belongs. In general, the predicted sequences are shown to have multiple sequence profile scores that are dramatically higher than those of random sequences, and sometimes better than some of the natural sequences that make up the superfamily. As anticipated, highly conserved but poorly predicted residues are often those that contribute to the functional rather than structural properties of the protein. Overall, our analysis suggests that statistical profile scores of designed sequences are a novel and valuable figure of merit for assessing and improving protein design algorithms.     

Evaluation of PSI-BLAST alignment accuracy in comparison to structural alignments

The PSI-BLAST algorithm has been acknowledged as one of the most powerful tools for detecting remote evolutionary relationships by sequence considerations only. This has been demonstrated by its ability to recognize remote structural homologues and by the greatest coverage it enables in annotation of a complete genome. Although recognizing the correct fold of a sequence is of major importance, the accuracy of the alignment is crucial for the success of modeling one sequence by the structure of its remote homologue. Here we assess the accuracy of PSI-BLAST alignments on a stringent database of 123 structurally similar, sequence-dissimilar pairs of proteins, by comparing them to the alignments defined on a structural basis. Each protein sequence is compared to a nonredundant database of the protein sequences by PSI-BLAST. Whenever a pair member detects its pair-mate, the positions that are aligned both in the sequential and structural alignments are determined, and the alignment sensitivity is expressed as the percentage of these positions out of the structural alignment. Fifty-two sequences detected their pair-mates (for 16 pairs the success was bi-directional when either pair member was used as a query). The average percentage of correctly aligned residues per structural alignment was 43.5+/-2.2%. Other properties of the alignments were also examined, such as the sensitivity vs. specificity and the change in these parameters over consecutive iterations. Notably, there is an improvement in alignment sensitivity over consecutive iterations, reaching an average of 50.9+/-2.5% within the five iterations tested in the current study.     

A liquid crystalline medium for measuring residual dipolar couplings over a wide range of temperatures

A mixture of dilauroyl phosphatidylcholine (DLPC) and 3-(cholamidopropyl)dimethylammonio-2-hydroxyl-1-propane sulfonate (CHAPSO) in water forms disc shaped bicelles that become ordered at high magnetic fields over a wide range of temperatures. As illustrated for the FK506 binding protein (FKBP), large residual dipolar couplings can be measured for proteins dissolved in low concentrations (5% w/v) of a DLPC/CHAPSO medium at a molar ratio of 4.2:1. This system is especially useful for measuring residual dipolar couplings for molecules that are only stable at low temperatures.     

Characterization of magnetically oriented phospholipid micelles for measurement of dipolar couplings in macromolecules

Weak alignment of solute molecules with the magnetic field can be achieved in a dilute liquid crystalline medium, consisting of an aqueous mixture of dimyristoyl-phosphatidylcholine (DMPC) and dihexanoyl-phosphatidylcholine (DHPC). For a certain range of molar ratios, DMPC and DHPC can form large, disc-shaped particles, commonly referred to as bicelles (Sanders and Schwonek, 1992), which cooperatively align in the magnetic field and induce a small degree of alignment on asymmetrically shaped solute molecules. As a result, dipolar couplings between pairs of ¹H, ¹³C or ¹⁵N nuclei are no longer averaged to zero by rotational diffusion and they can be readily measured, providing valuable structural information. The stability of these liquid crystals and the degree of alignment of the solute molecules depend strongly on experimental variables such as the DMPC:DHPC ratio and concentration, the preparation protocol of the DMPC/DHPC mixtures, as well as salt, temperature, and pH. The lower temperature limit for which the liquid crystalline phase is stable can be reduced to 20 °C by using a ternary mixture of DHPC, DMPC, and 1-myristoyl-2-myristoleoyl-sn-glycero-3-phosphocholine, or a binary mixture of DHPC and ditridecanoyl-phosphatidylcholine. These issues are discussed, with an emphasis on the use of the medium for obtaining weak alignment of biological macromolecules.     

Prediction of functional residues in water channels and related proteins.

In this paper, we present an updated classification of the ubiquitous MIP (Major Intrinsic Protein) family proteins, including 153 fully or partially sequenced members available in public databases. Presently, about 30 of these proteins have been functionally characterized, exhibiting essentially two distinct types of channel properties: (1) specific water transport by the aquaporins, and (2) small neutral solutes transport, such as glycerol by the glycerol facilitators. Sequence alignments were used to predict amino acids and motifs discriminant in channel specificity. The protein sequences were also analyzed using statistical tools (comparisons of means and correspondence analysis). Five key positions were clearly identified where the residues are specific for each functional subgroup and exhibit high dissimilar physico-chemical properties. Moreover, we have found that the putative channels for small neutral solutes clearly differ from the aquaporins by the amino acid content and the length of predicted loop regions, suggesting a substrate filter function for these loops. From these results, we propose a signature pattern for water transport.     

Dependence of alignment direction on magnitude of strain in esophageal smooth muscle cells

The response of cells in vitro to mechanical forces has been the subject of much research using devices to exert controlled mechanical stimulation on cultured cells or isolated tissue. In this study, esophageal smooth muscle cells were seeded on flexible polyurethane membranes to form a confluent cell layer. The cells were then subjected to uniform cyclic stretch of varying magnitudes at a frequency of approximately five cycles per minute in a custom made mechatronic bioreactor, providing similar strains experienced in the in vivo mechanical environment of the esophagus. The results show that the orientation response is dependent on the magnitude of cyclic stretch applied. Smooth muscle cells showed parallel alignment to the force direction at low cyclic strains (2%) compared to the hill‐valley morphology of static controls. At higher strains (5% and 10% magnitude), the cells exhibited a consistent alignment perpendicular to the strain. To our knowledge, this is the first time that the alignment direction's dependence on strain magnitude has been demonstrated. MTS analysis indicated that cell metabolism was reduced when mechanical strain was applied, and proliferation was inhibited by mechanical strain. Protein expression indicates a decrease in smooth muscle α‐actin, indicative of changes in cell phenotype, an increase in vimentin, which is associated with increased cell motility, and an increase in desmin, indicating differentiation in stimulated cells. Biotechnol. Bioeng. 2009;102: 1703–1711. © 2008 Wiley Periodicals, Inc.     

A Quantitative Measure of Field Illumination

In this paper, we describe a statistically based algorithm to quantify the uniformity of illumination in an optical light microscopy imaging system that outputs a single quality factor (QF) score. The importance of homogeneous field illumination in quantitative light microscopy is well understood and often checked. However, there is currently no standard automatic quantitative measure of the uniformity of the field illumination. Images from 89 different laser-scanning confocal microscopes (LSCMs), which were collected as part of an international study on microscope quality assessment, were used as a “training” set to build the algorithm. To validate the algorithm and verify its robustness, images from 33 additional microscopes, including LSCM and wide-field (WF) microscopes, were used. The statistical paradigm used for developing the quality scoring scale was a regression approach to supervised learning. Three intensity profiles across each image—2 corner-to-corner diagonals and a center horizontal—were used to generate pixel-intensity data. All of the lines passed through the center of the image. The intensity profile data then were converted into a single-field illumination QF score in the range of 0–100, with 0 having extreme variation, and therefore, essentially unusable, and 100 having no deviation, i.e., straight lines with a constant uniform intensity. Empirically, a QF ≥ 83 was determined to be the minimum acceptable value based on manufacturer acceptance tests and reasonably achievable values. This new QF is an invaluable metric to ascertain objectively and easily the uniformity of illumination quality, provide a traceable reference for monitoring field uniformity over time, and make a direct comparison among different microscopes. The QF can also be used as an indicator of system failure and the need for alignment or service of the instrument.