CAVES: A Novel Tool for Comparative Analysis of Variant Epitope Sequences

• Published in: Viruses Vol. 14; no. 6; p. 1152
• Main Authors: Li, Katherine, Lowey, Connor, Sandstrom, Paul, Ji, Hezhao
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 26.05.2022; MDPI
• Subjects: Amino acids; Antigenic determinants; antigenic variation; bioinformatics; Cavernicolous species; Caves; Comparative analysis; comparative genomics; computational biology; Computer programs; computer simulation; computer software; Coronaviruses; COVID-19; data collection; Design; Epitopes; evolution; Genetic aspects; Lymphocytes; Open source software; Pathogens; Peptides; prediction; Proteins; Public software; Science; sequence analysis; Severe acute respiratory syndrome coronavirus 2; therapeutics; User interface; vaccines; Canada
• ISSN: 1999-4915; 1999-4915
• DOI: 10.3390/v14061152

In silico methods for immune epitope prediction have become essential for vaccine and therapeutic design, but manual intra-species comparison of putative epitopes remains challenging and subject to human error. Created initially for analyzing SARS-CoV-2 variants of concern, comparative analysis of variant epitope sequences (CAVES) is a novel tool designed to carry out rapid comparative analyses of epitopes amongst closely related pathogens, substantially reducing the required time and user workload. CAVES applies a two-level analysis approach. The Level-one (L1) analysis compares two epitope prediction files, and the Level-two (L2) analysis incorporates search results from the IEDB database of experimentally confirmed epitopes. Both L1 and L2 analyses sort epitopes into categories of exact matches, partial matches, or novel epitopes based on the degree to which they match with peptides from the compared file. Furthermore, CAVES uses positional sequence data to improve its accuracy and speed, taking only a fraction of the time required by manual analyses and minimizing human error. CAVES is widely applicable for evolutionary analyses and antigenic comparisons of any closely related pathogen species. CAVES is open-source software that runs through a graphical user interface on Windows operating systems, making it widely accessible regardless of coding expertise. The CAVES source code and test dataset presented here are publicly available on the CAVES GitHub page.