RELIC:

Suneeta Mandava, Lee Makowski, Satish Devarapalli, Joseph Uzubell and Diane J. Rodi. RELIC – A bioinformatics server for combinatorial peptide analysis and identification of protein-ligand interaction sites . Proteomics 2004, 4, 1439–1460. request reprint

Purpose:

The long term goal of our research is the genome-wide identification of small molecule binding sites on proteins using phage displayed peptides. In spite of the large number of functional genomics tools currently available, typically 40% of predicted ORFs remain unidentified in terms of function, even after the application of sequence similarity comparisons, genomic context analysis, profile comparisons across multiple genomes, and structural genomics methods. Characterization of the type(s) of small molecules to which an ORFan binds gives a vital clue as to its function within the cell. Preliminary results demonstrate that the similarity between the sequence of a protein and the sequences of phage-displayed peptides affinity-selected against small molecules can be predictive for protein binding to that small molecule ligand. Affinity-selected peptides provide information analogous to that of a consensus-binding sequence, and can be used in an analogous fashion to identify ligand binding sites. Libraries of phage-displayed peptides are screened for affinity to common metabolites and other small molecule ligands. The sequences of affinity-selected peptides are determined and used as the basis of genome-wide analyses to identify proteins that have a high probability of binding to the screened ligands. Each set of affinity-selected peptides are validated through comparison with well-characterized proteins, and can be used for genome-wide annotation of all available genomes. Affinity-selected peptide populations are evaluated by comparison with completely sequenced microbial genomes of interest to the DOE. The list of proteins identified as small molecule binders via this technique is validated by comparison with annotated proteins to assess the false positive and false negative rates. These comparisons have been used to optimize software and develop a method to calculate a confidence level for each prediction made.

Software:

RELIC is a publicly accessible bio-technology system that utlilizes web technology, traditional programming and a relational database to process and manipulate the experimental data of affinity selected peptides. RELIC receives user input via web interface (Active Server Pages) and pass the input to various programs. These programs interface with the ASP pages through COM+ wrappers written in Visual C++ utilizing the Active Template Library (ATL). The COM+ objects interface with FORTRAN programs that process the data. The processed information is then stored into an Oracle 9i database where the user can retrieve it immediately or at a later date.

RELIC is intended to provide to the community the access to our sequence analysis tools as well as the sequences of affinity-selected peptides of multiple ligands and the functional information generated from our research. Our programs can statistically analyze a population of peptides, search for motifs with peptides, predict what parts of the protein are involved in binding, and rank order the proteins against a set of peptides to predict which proteins are most likely to bind that ligand. The result will be a highly efficient means of genome annotation that will increase in utility as more ligands are screened and more genome sequences become available.

The programs will require any or all of the following input from the user:

Peptide sequence files : Programs will analyze a population of peptides
Fasta file of single proteins : Programs will yield both the probability that the protein will bind to a specific ligand, and the alignment of peptides to that protein
Fasta files of multiple proteins or whole genomes : Programs will rank the order of the proteins against a set of peptides to predict which proteins bind to that ligand

We can then use our software and the affinity selected peptides as a global approach to:
1. predict which proteins bind to the ligand
2. identify the position of the ligand binding sites within a protein

Example Application:

The user is interested in the probability that a protein of unknown function will bind to ATP. The fasta sequence of the hypothetical protein is entered and can be compared to the phage displayed peptides that have been affinity selected for binding to ATP. The degree of similarity calculated provides a measure of the probability of binding. 

This project is supported by the Office of Biological and Environmental Research of the Department of Energy