Project properties
Title Screen for Auxin binding pockets in AlphaFold2 structures of the Arabidopsis proteome
Group Biochemistry, Laboratory of
Project type thesis
Credits 24-36
Supervisor(s) Sumanth Mutte
Examiner(s) Prof. Dr. Dolf Weijers
Contact info sumanth.mutte@wur.nl
Begin date 2023/02/01
End date 2023/12/31
Description Phytohormone Auxin (Indole-3-acetic acid, IAA) is known to regulate multiple process in plant growth and development. This is possible only after the receptor proteins sense and binds auxin after which the signal is transduced to regulate the downstream process. So far, only a few proteins are known that can bind the auxin. Very well studied are the TIR1/AFB receptors and to a certain extent ABP1. Some recent studies show that the transcription factors of the nuclear auxin pathway, ARFs, might bind auxin directly. Moreover, recent phosphoproteome studies indicate the need for a rapid signal transduction that is very fast compare to a transcriptional process. All these developments lead to the hypothesis that there could be many more proteins present in the Arabidopsis proteome that may bind auxin but not identified yet. Aim of this project is to find such proteins that may bind auxin using the rich structural information produced by the predictions of AlphaFold2 and find the ligand binding pockets those structures. This project also aims to develop a (scoring) method to compare the binding capacities of IAA compared to other auxin analogs such as 1-NAA, 2-NAA and 2,4-D. Methods used here include docking, but also to scout for new methods based on machine learning because of the scalability of docking for thousands of proteins, where some inspiration could be drawn from the field of drug discovery. At the end of the project, the candidate will have a good hold of AlphaFold2 predictions, structural analysis, docking, interaction scoring methods and of course auxin binding proteins.

Used skills Phylogenetic analysis, molecular docking, computational and bioinformatic analysis
Requirements Basic knowledge of biology, protein structure and bioinformatics.