TY - JOUR
T1 - Molecular mechanisms of RNA polymerase II transcription elongation elucidated by kinetic network models
AU - Unarta, Ilona Christy
AU - Zhu, Lizhe
AU - Tse, Carmen Ka Man
AU - Cheung, Peter Pak-Hang
AU - Yu, Jin
AU - Huang, Xuhui
N1 - KAUST Repository Item: Exported on 2021-04-06
Acknowledged KAUST grant number(s): OSR-2016-CRG5-3007
Acknowledgements: This work was supported by the Hong Kong Research Grant Council (HKUST C6009-15G, 16305817, 16302214, 16304215, 16318816, AoE/P-705/16, M-HKUST601/13, and T13-607/12R), King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) (OSR-2016-CRG5-3007), Shenzhen Science and Technology Innovation Committee (JCYJ20170413173837121), Innovation and Technology Commission (ITCPD/17-9 and ITC-CNERC14SC01), and National Natural Science Foundation of China (11275022, 11635002). XH is the Padma Harilela Associate Professor of Science.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
PY - 2018/4
Y1 - 2018/4
N2 - Transcription elongation cycle (TEC) of RNA polymerase II (Pol II) is a process of adding a nucleoside triphosphate to the growing messenger RNA chain. Due to the long timescale events in Pol II TEC, an advanced computational technique, such as Markov State Model (MSM), is needed to provide atomistic mechanism and reaction rates. The combination of MSM and experimental results can be used to build a kinetic network model (KNM) of the whole TEC. This review provides a brief protocol to build MSM and KNM of the whole TEC, along with the latest findings of MSM and other computational studies of Pol II TEC. Lastly, we offer a perspective on potentially using a sequence dependent KNM to predict genome-wide transcription error.
AB - Transcription elongation cycle (TEC) of RNA polymerase II (Pol II) is a process of adding a nucleoside triphosphate to the growing messenger RNA chain. Due to the long timescale events in Pol II TEC, an advanced computational technique, such as Markov State Model (MSM), is needed to provide atomistic mechanism and reaction rates. The combination of MSM and experimental results can be used to build a kinetic network model (KNM) of the whole TEC. This review provides a brief protocol to build MSM and KNM of the whole TEC, along with the latest findings of MSM and other computational studies of Pol II TEC. Lastly, we offer a perspective on potentially using a sequence dependent KNM to predict genome-wide transcription error.
UR - http://hdl.handle.net/10754/668563
UR - https://linkinghub.elsevier.com/retrieve/pii/S0959440X17300921
UR - http://www.scopus.com/inward/record.url?scp=85041617670&partnerID=8YFLogxK
U2 - 10.1016/j.sbi.2018.01.002
DO - 10.1016/j.sbi.2018.01.002
M3 - Article
SN - 0959-440X
VL - 49
SP - 54
EP - 62
JO - Current Opinion in Structural Biology
JF - Current Opinion in Structural Biology
ER -