Protein Sequence-Based Design and Analysis Software for the Development of Diagnosis Tools
Abstract
Biomarkers unique to injury and illness are crucial components of diagnostic devices, and are often endogenous proteins released from the injury. Their identification, using specific probes, guides treatment courses. Some sites on these biomarkers may be similar to active sites on other proteins that are ubiquitous in a patient. Therefore, any probe used to detect an injury or illness must be able to bind to a unique site on the biomarker protein. In order to identify specific binders to these unique biomarker active sites, small peptides can be synthesized to serve as an epitope-mimicking target for library screening methods such as phage display. When a protein must be identified preferentially over another protein, the synthesized peptide should represent the most unique region of the desired biomarkers amino acid sequence where binding can occur. Selecting and analyzing these unique sequences manually with database queries and local software tools are time-consuming, labor intensive, and error-prone. We offer the Peptide Uniqueness Quantification Tool (PUnQT), a Python program that automates the generation of unique peptide targets for high-throughput protein target selection rapidly, easily, and minimizing possible user error.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 16, 2021
- Accession Number
- AD1136730
Entities
People
- April S. Ford
- David J. Lemon
- Eun Y. Huh
- Holly C. May
- Steven X. Moffett
- Yoon Y. Hwang
Organizations
- Naval Medical Research Unit—San Antonio