(Internal) Using SDAs to Detect and Characterize Intrinsically Disordered Protein Sequences

Advisor: Steffen Graether, Molecular and Cellular Biology

Proposed computational advisor: Sheridan Houghton (Brock)

Dehydrins are plant proteins that can protect from damage caused by abiotic stress (drought, cold, and high salinity). Dehydrins have no structure, and therefore belong to the intrinsically disordered protein family (IDPs). Most interestingly, dehydrins have a variable number of conserved motifs and a lack of conservation between these motifs, making it nearly impossible to align sequences using traditional approaches (e.g. multiple sequence alignments). This project will use self-driving automata (SDAs) to generate sequences that can be used to match dehydrin sequences. We have already established a pipeline to generate sequences that are able to match known dehydrin sequences. This proposal will extend this approach by developing matches to multiple dehydrin sequences, and potentially use SDA-generated sequences to search plant genomes for previously unidentified dehydrins. To generate SDAs, knowledge of evolutionary computation is an assent but not a requirement. Likewise, familiarity with proteins is helpful but also not required.

This project is suitable for one or two semesters. The student is required to occasionally be on-site.

Knowledge/Skills

Protein sequences, protein structure, familiarity with evolutionary algorithms is helpful but not required