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Intrinsically disordered proteins are frequent targets for functional regulation through post-translational modification due to their high accessibility to modifying enzymes and the strong influence of changes in primary structure on their chemical properties. While lysine N ε -acetylation was first observed as a common modification of histone tails, proteomic data suggest that lysine acetylation is ubiquitous among both nuclear and cytosolic proteins. However, compared with our biophysical understanding of the other common post-translational modifications, mechanistic studies to document how lysine N ε -acetyl marks are placed, utilized to transduce signals, and eliminated when signals need to be turned off, have not kept pace with proteomic discoveries. Herein we report a nuclear magnetic resonance method to monitor N ε -lysine acetylation through enzymatic installation of a 13 C-acetyl probe on a protein substrate, followed by detection through 13 C direct-detect spectroscopy. We demonstrate the ease and utility of this method using histone H3 tail acetylation as a model. The clearest advantage to this method is that it requires no exogenous tags that would otherwise add steric bulk, change the chemical properties of the modified lysine, or generally interfere with downstream biochemical processes. The non-perturbing nature of this tagging method is beneficial for application in any system where changes to local structure and chemical properties beyond those imparted by lysine modification are unacceptable, including intrinsically disordered proteins, bromodomain containing protein complexes, and lysine deacetylase enzyme assays.
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DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction.
Protein succinylation has recently emerged as an important and common post-translation modification (PTM) that occurs on lysine residues. Succinylation is notable both in its size (e.g., at 100 Da, it is one of the larger chemical PTMs) and in its ability to modify the net charge of the modified lysine residue from + 1 to − 1 at physiological pH. The gross local changes that occur in proteins upon succinylation have been shown to correspond with changes in gene activity and to be perturbed by defects in the citric acid cycle. These observations, together with the fact that succinate is generated as a metabolic intermediate during cellular respiration, have led to suggestions that protein succinylation may play a role in the interaction between cellular metabolism and important cellular functions. For instance, succinylation likely represents an important aspect of genomic regulation and repair and may have important consequences in the etiology of a number of disease states. In this study, we developed DeepSuccinylSite, a novel prediction tool that uses deep learning methodology along with embedding to identify succinylation sites in proteins based on their primary structure.
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- Award ID(s):
- 1901191
- PAR ID:
- 10480256
- Publisher / Repository:
- Springer Nature
- Date Published:
- Journal Name:
- BMC bioinformatics
- ISSN:
- 1471-2105
- Subject(s) / Keyword(s):
- Succinylation Deep learning Convolutional neural network Recurrent neural network Long short-term memory Embedding
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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