Venkatarajan S. Mathura

Major linear IgE epitopes of mountain cedar pollen allergen Jun a 1 map to the pectate lyase catalytic site.

Resolution of the 3D structures and IgE epitopes of allergens may identify common or conserved features of allergens. Jun a 1, the predominant allergen in mountain cedar pollen, was chosen as a model for identifying common structural and functional features among a group of plant allergens. In this study, synthetic, overlapping peptides of Jun a 1 and sera from patients allergic to mountain cedar pollen were used to identify linear epitopes. A 3D model of Jun a 1 was produced using the Bacillus subtiles pectate lyase (PL) as a template and validated with biophysical measurements. This allowed mappings of four IgE binding sites on Jun a 1. Two of the epitopes mapped to turns or loops on the surface of the model structure. The other two epitopes mapped to the beta-sheet region, homologous to the catalytic site of PL. This region of Jun a 1 is highly conserved in the group 1 allergens from other cedar trees as well as microbial PLs. The finding that two out of three major IgE epitopes map to highly conserved catalytic regions of group 1 cedar allergens may help to explain the high degree of cross-reactivity between cedar pollen allergens and might represent a pattern of reactivity common to other allergens with catalytic activity.

Using property based sequence motifs and 3D modeling to determine structure and functional regions of proteins.

Homology modeling has become an essential tool for studying proteins that are targets for medical drug design. This paper describes the approach we developed that combines sequence decomposition techniques with distance geometry algorithms for homology modeling to determine functionally important regions of proteins. We show here the application of these techniques to targets of medical interest chosen from those included in the CASP5 (Critical Assessment of Techniques for Protein Structure Prediction) competition, including the dihydroneopterin aldolase from Mycobacterium tuberculosis, RNase III of Thermobacteria maritima, and the NO-transporter nitrophorin from saliva of the bedbug Cimex lectularius. Physical chemical property (PCP) motifs, identified in aligned sequences with our MASIA program, can be used to select among different alignments returned by fold recognition servers. They can also be used to suggest functions for hypothetical proteins, as we illustrate for target T188. Once a suitable alignment has been made with the template, our modeling suite MPACK generates a series of possible models. The models can then be selected according to their match in areas known to be conserved in protein families. Alignments based on motifs can improve the structural matching of residues in the active site. The quality of the local structure of our 3D models near active sites or epitopes makes them useful aids for drug and vaccine design. Further, the PCP motif approach, when combined with a structural filter, can be a potent way to detect areas involved in activity and to suggest function for novel genome sequences.

Molego-based definition of the architecture and specificity of metal-binding sites

Decomposing proteins into “molegos,” building blocks that are conserved in sequence and 3D‐structure, can identify functional elements. To demonstrate the specificity of the decomposition method, the PCPMer program suite was used to numerically define physical chemical property motifs corresponding to the molegos that make up the metal‐containing active sites of three distinct enzyme families, from the dimetallic phosphatases, DNase 1 related nucleases/phosphatases, and dioxygenases. All three superfamilies bind metal ions in a β‐strand core region but differ in the number and type of ions needed for activity. The motifs were then used to automatically identify proteins in the ASTRAL40 database that contained similar motifs. The proteins with the highest PCPMer score in the database were primarily metal‐binding enzymes that were related in function to those in the alignment used to generate the PCPMer motif lists. The proteins that contained motifs similar to the dioxygenases differed from those found with PCP‐motifs for phosphatases and nucleases. Relatively few metal‐binding enzymes were detected when the search was done with PCP‐motifs defined for interleukin‐1 related proteins, which have a β‐strand core but do not bind metal ions. While the box architecture was constant in each superfamily, the specificity for the metal ion preferred for enzymatic activity is determined by the pattern of carbonyl, hydroxyl or imadazole groups in key positions in the molegos. These results have implications for the design of metal‐binding enzymes, and illustrate the ability of the PCPMer approach to distinguish, at the sequence level, structural and functional elements. Proteins 2005.

Types of inter-atomic interactions at the MHC-peptide interface: Identifying commonality from accumulated data

BackgroundQuantitative information on the types of inter-atomic interactions at the MHC-peptide interface will provide insights to backbone/sidechain atom preference during binding. Qualitative descriptions of such interactions in each complex have been documented by protein crystallographers. However, no comprehensive report is available to account for the common types of inter-atomic interactions in a set of MHC-peptide complexes characterized by variation in MHC allele and peptide sequence. The available x-ray crystallography data for these complexes in the Protein Databank (PDB) provides an opportunity to identify the prevalent types of such interactions at the binding interface.ResultsWe calculated the percentage distributions of four types of interactions at varying inter-atomic distances. The mean percentage distribution for these interactions and their standard deviation about the mean distribution is presented. The prevalence of SS and SB interactions at the MHC-peptide interface is shown in this study. SB is clearly dominant at an inter-atomic distance of 3Å.ConclusionThe prevalently dominant SB interactions at the interface suggest the importance of peptide backbone conformation during MHC-peptide binding. Currently, available algorithms are developed for protein sidechain prediction upon fixed backbone template. This study shows the preference of backbone atoms in MHC-peptide binding and hence emphasizes the need for accurate peptide backbone prediction in quantitative MHC-peptide binding calculations.

Bioinformatics: A Concept-Based Introduction

Bioinformatics is an evolving field that is gaining popularity due to genomics, proteomics and other high-throughput biological methods. The function of bioinformatic scientists includes biological data storage, retrieval and in silico analysis of the results from large-scale experiments. This requires a grasp of knowledge mining algorithms, a thorough understanding of biological knowledge base, and the logical relationship of entities that describe a process or the system. Bioinformatics researchers are required to be trained in multidisciplinary fields of biology, mathematics and computer science. Currently the requirements are satisfied by ad hoc researchers who have specific skills in biology or mathematics/computer science. But the learning curve is steep and the time required to communicate using domain specific terms is becoming a major bottle neck in scientific productivity. This workbook provides hands-on experience which has been lacking for qualified bioinformatics researchers.