The dynamic conformational landscape of the protein methyltransferase SETD8
- Memorial Sloan Kettering Cancer Center, United States
- McMaster University, Canada
- Icahn School of Medicine at Mount Sinai, United States
- University of Toronto, Canada
- The University of Georgia, United States
- Takeda, United States
- Shanghai Institute of Materia Medica, China
Abstract
Elucidating the conformational heterogeneity of proteins is essential for understanding protein function and developing exogenous ligands. With the rapid development of experimental and computational methods, it is of great interest to integrate these approaches to illuminate the conformational landscapes of target proteins. SETD8 is a protein lysine methyltransferase (PKMT), which functions in vivo via the methylation of histone and nonhistone targets. Utilizing covalent inhibitors and depleting native ligands to trap hidden conformational states, we obtained diverse X-ray structures of SETD8. These structures were used to seed distributed atomistic molecular dynamics simulations that generated a total of six milliseconds of trajectory data. Markov state models, built via an automated machine learning approach and corroborated experimentally, reveal how slow conformational motions and conformational states are relevant to catalysis. These findings provide molecular insight on enzymatic catalysis and allosteric mechanisms of a PKMT via its detailed conformational landscape.
Data availability
The molecular dynamics datasets generated and analyzed in this study are available via the Open Science Framework at https://osf.io/2h6p4.The code used for the generation and analysis of the molecular dynamics data is available via a Github repository at https://github.com/choderalab/SETD8-materials.PDB files: 6BOZ for BC-Inh1, 5W1Y for BC-Inh2, 4IJ8 for BC-SAM, and 5V2N for APO.
Article and author information
Author details
Funding
National Cancer Institute
- Jian Jin
- John D Chodera
- Minkui Luo
K. C. Wong Education Foundation
- Cheng Luo
Chinese Academy of Sciences
- Cheng Luo
National Natural Science Foundation of China
- Cheng Luo
the Tri-Institutional PhD Program in Chemical Biology
- Shi Chen
- Rafal P Wiewiora
Peer Reviewed Cancer Research Program of the Department of Defense
- Rafal P Wiewiora
AbbVie
- Peter J Brown
Bayer Pharma AG
- Peter J Brown
Boehringer Ingelheim
- Peter J Brown
Eshelman Institute for Innovation
- Peter J Brown
Genome Canada
- Peter J Brown
National Institute of General Medical Sciences
- Yujun George Zheng
- Jian Jin
- John D Chodera
- Minkui Luo
Innovative Medicines Initiative
- Peter J Brown
Canada Foundation for Innovation
- Peter J Brown
Janssen
- Peter J Brown
Merck & Co.
- Peter J Brown
Novartis Pharma AG
- Peter J Brown
Ontario Ministry of Economic Development and Innovation
- Peter J Brown
Pfizer
- Peter J Brown
São Paulo Research Foundation-FAPESP
- Peter J Brown
Takeda
- Hua Zou
- Robert J Skene
- Peter J Brown
the Wellcome Trust
- Peter J Brown
Eunice Kennedy Shriver National Institute of Child Health and Human Development
- Jian Jin
Starr Cancer Consortium
- John D Chodera
- Minkui Luo
MSKCC Functional Genomics Initiative
- John D Chodera
- Minkui Luo
The Sloan Kettering Institute
- Kyle A Beauchamp
- John D Chodera
- Minkui Luo
Mr. William H. Goodwin and Mrs. Alice Goodwin Commonwealth Foundation for Cancer Research, and the Experimental Therapeutics Center of Memorial Sloan Kettering Cancer Center
- Minkui Luo
Tri-Institutional Therapeutics Discovery Institute
- Minkui Luo
Louis V. Gerstner Young Investigator Award
- John D Chodera
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Sarel Jacob Fleishman, Weizmann Institute of Science, Israel
Version history
- Received: January 22, 2019
- Accepted: May 8, 2019
- Accepted Manuscript published: May 13, 2019 (version 1)
- Version of Record published: June 17, 2019 (version 2)
Copyright
© 2019, Chen et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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The dynamic conformational landscape of the protein methyltransferase SETD8
eLife 8:e45403.
https://doi.org/10.7554/eLife.45403
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