A B-cell epitope is the three-dimensional structure within an antigen that can be bound to the variable region of an antibody. The prediction of B-cell epitopes is highly desirable for various immunological applications, but has presented a set of unique challenges to the bioinformatics and immunology communities. Improving the accuracy of B-cell epitope prediction methods depends on a community consensus on the data and metrics utilized to develop and evaluate such tools. A workshop, sponsored by the National Institute of Allergy and Infectious Disease (NIAID), was recently held in Washington, DC to discuss the current state of the B-cell epitope prediction field. Many of the currently available tools were surveyed and a set of recommendations was devised to facilitate improvements in the currently existing tools and to expedite future tool development. An underlying theme of the recommendations put forth by the panel is increased collaboration among research groups. By developing common datasets, standardized data formats, and the means with which to consolidate information, we hope to greatly enhance the development of B-cell epitope prediction tools.

The structures of protein antigen–antibody (Ag–Ab) interfaces contain information about how Ab recognize Ag as well as how Ag are folded to present surfaces for Ag recognition. As such, the Ab surface holds information about Ag folding that resides with the Ab–Ag interface residues and how they interact. In order to gain insight into the nature of such interactions, a data set comprised of 53 non-redundant 3D structures of Ag–Ab complexes was analyzed. We assessed the physical and biochemical features of the Ag–Ab interfaces and the degree to which favored interactions exist between amino acid residues on the corresponding interface surfaces. Amino acid compositional analysis of the interfaces confirmed the dominance of TYR in the Ab paratope-containing surface (PCS), with almost two fold greater abundance than any other residue. Additionally TYR had a much higher than expected presence in the PCS compared to the surface of the whole antibody (defined as the occurrence propensity), along with aromatics PHE, TRP, and to a lesser degree HIS and ILE. In the Ag epitope-containing surface (ECS), there were slightly increased occurrence propensities of TRP and TYR relative to the whole Ag surface, implying an increased significance over the compositionally most abundant LYS>ASN>GLU>ASP>ARG. This examination encompasses a large, diverse set of unique Ag–Ab crystal structures that help explain the biological range and specificity of Ag–Ab interactions. This analysis may also provide a measure of the significance of individual amino acid residues in phage display analysis of Ag binding.

The N-formyl peptide receptor (FPR), a G protein-coupled receptor that binds proinflammatory chemoattractant peptides, serves as a model receptor for leukocyte chemotaxis. Recombinant histidine-tagged FPR (rHis-FPR) was purified in lysophosphatidyl glycerol (LPG) by Ni2+-NTA agarose chromatography to >95% purity with high yield. MALDI-TOF mass analysis (>36% sequence coverage) and immunoblotting confirmed the identity as FPR. The rHis-FPR served as an immunogen for the production of 2 mAbs, NFPR1 and NFPR2, that epitope map to the FPR C-terminal tail sequences, 305-GQDFRERLI-313 and 337-NSTLPSAEVE-346, respectively. Both mAbs specifically immunoblotted rHis-FPR and recombinant FPR (rFPR) expressed in Chinese hamster ovary cells. NFPR1 also recognized recombinant FPRL1, specifically expressed in mouse L fibroblasts. In human neutrophil membranes, both Abs labeled a 45–75 kDa species (peak Mr ∼60 kDa) localized primarily in the plasma membrane with a minor component in the lactoferrin-enriched intracellular fractions, consistent with FPR size and localization. NFPR1 also recognized a band of Mr ∼40 kDa localized, in equal proportions to the plasma membrane and lactoferrin-enriched fractions, consistent with FPRL1 size and localization. Only NFPR2 was capable of immunoprecipitation of rFPR in detergent extracts. The recognition of rFPR by NFPR2 is lost after exposure of cellular rFPR to f-Met-Leu-Phe (fMLF) and regained after alkaline phosphatase treatment of rFPR-bearing membranes. In neutrophils, NFPR2 immunofluorescence was lost upon fMLF stimulation. Immunoblotting ∼60 kDa species, after phosphatase treatment of fMLF-stimulated neutrophil membranes, was also enhanced. We conclude that the region 337–346 of FPR becomes phosphorylated after fMLF activation of rFPR-expressing Chinese hamster ovary cells and neutrophils.

Antibodies that bind to protein surfaces of interest can be used to report the three-dimensional structure of the protein as follows: Proteins are composed of linear polypeptide chains that fold together in complex spatial patterns to create the native protein structure. These folded structures form binding sites for antibodies. Antibody binding sites are typically "assembled" on the protein surface from segments that are far apart in the primary amino acid sequence of the target proteins. Short amino acid probe sequences that bind to the active region of each antibody can be used as witnesses to the antibody epitope surface and these probes can be efficiently selected from random sequence peptide libraries. This paper presents a new method to align these antibody epitopes to discontinuous regions of the one-dimensional amino acid sequence of a target protein. Such alignments of the epitopes indicate how segments of the protein sequence must be folded together in space and thus provide long-range constraints for solving the 3-D protein structure. This new antibody-based approach is applicable to the large fraction of proteins that are refractory to current approaches for structure determination and has the additional advantage of requiring very small amounts of the target protein. The binding site of an antibody is a surface, not just a continuous linear sequence, so the epitope mapping alignment problem is outside the scope of classical string alignment algorithms, such as Smith-Waterman. We formalize the alignment problem that is at the heart of this new approach, prove that the epitope mapping alignment problem is NP-complete, and give some initial results using a branch-and-bound algorithm to map two real-life cases. Initial results for two validation cases are presented for a graph-based protein surface neighbor mapping procedure that promises to provide additional spatial proximity information for the amino acid residues on the protein surface.

A multi-assembly problem asks to reconstruct multiple genomic sequences from mixed reads sequenced from all of them. Standard formulations of such problems model a solution as a path cover in a directed acyclic graph, namely a set of paths that together cover all vertices of the graph. Since multi-assembly problems admit multiple solutions in practice, we consider an approach commonly used in standard genome assembly: output only partial solutions (contigs, or safe paths), that appear in all path cover solutions. We study constrained path covers, a restriction on the path cover solution that incorporate practical constraints arising in multi-assembly problems. We give efficient algorithms finding all maximal safe paths for constrained path covers. We compute the safe paths of splicing graphs constructed from transcript annotations of different species. Our algorithms run in less than 15 seconds per species and report RNA contigs that are over 99% precise and are up to 8 times longer than unitigs. Moreover, RNA contigs cover over 70% of the transcripts and their coding sequences in most cases. With their increased length to unitigs, high precision, and fast construction time, maximal safe paths can provide a better base set of sequences for transcript assembly programs.