Post translational modifications (PTMs) play critical roles in regulating protein functions and mediating protein-protein interaction. Deterioration of PTMs is known to cause many diseases. PTMs on histone tail peptides dictate chromatin structure remodeling and orchestrate gene expression, which is at the heart of epigenetics. These histone modifications are recognized by reader proteins that often contain particular modular domains binding to specific PTMs such as chromodomains recognizing methylated Lysine. Understanding the mechanisms of how these PTMs are recognized and developing tools to manipulate such recognition are critical for developing new therapeutics. In the proposed research, we will develop and test an integrated approach that combines computational simulation and experimental validation to design the binding specificity between the modified peptides and their recognition domains.
In Aim 1, we will engineer the binding interface residues of chromodomains to achieve the desired binding specificity.
In Aim 2, we aim to engineer chromodomains' recognition of multiply-modified peptides.
In Aim 3, we will test the generality of the proposed engineering strategy on another modular domain, PHD domain. Once the proposed research is completed, it will illustrate the recognition principles of modified peptides and demonstrates the possibility of manipulating such recognition, which opens a new avenue of rewiring signal transduction in epigenetics.
Post-translational modifications (PTMs) are critical in regulating protein-protein interactions and signal transduction. Aberrant PTMs can lead to cellular dysfunction and cause diseases. Understanding the mechanisms of how these modifications are recognized and developing tools to manipulate such recognition would lay the foundation of developing effective therapeutics.
| Hard, Ryan; Li, Nan; He, Wei et al. (2018) Deciphering and engineering chromodomain-methyllysine peptide recognition. Sci Adv 4:eaau1447 |
| Li, Nan; Ainsworth, Richard I; Wu, Meixin et al. (2016) MIEC-SVM: automated pipeline for protein peptide/ligand interaction prediction. Bioinformatics 32:940-2 |
