Please use this identifier to cite or link to this item: https://doi.org/10.1093/jmcb/mjz009
Title: Roles of computational modelling in understanding p53 structure, biology, and its therapeutic targeting
Authors: Tan, Y.S.
Mhoumadi, Y.
Verma, C.S. 
Keywords: Computational modelling
P53
Structure
Therapeutic targeting
Issue Date: 2019
Publisher: Oxford University Press
Citation: Tan, Y.S., Mhoumadi, Y., Verma, C.S. (2019). Roles of computational modelling in understanding p53 structure, biology, and its therapeutic targeting. Journal of Molecular Cell Biology 11 (4) : 306-316. ScholarBank@NUS Repository. https://doi.org/10.1093/jmcb/mjz009
Rights: Attribution-NonCommercial 4.0 International
Abstract: The transcription factor p53 plays pivotal roles in numerous biological processes, including the suppression of tumours. The rich availability of biophysical data aimed at understanding its structure-function relationships since the 1990s has enabled the application of a variety of computational modelling techniques towards the establishment of mechanistic models. Together they have provided deep insights into the structure, mechanics, energetics, and dynamics of p53. In parallel, the observation that mutations in p53 or changes in its associated pathways characterize several human cancers has resulted in a race to develop therapeutic modulators of p53, some of which have entered clinical trials. This review describes how computational modelling has played key roles in understanding structural-dynamic aspects of p53, formulating hypotheses about domains that are beyond current experimental investigations, and the development of therapeutic molecules that target the p53 pathway. © 2019 Oxford University Press. All rights reserved.
Source Title: Journal of Molecular Cell Biology
URI: https://scholarbank.nus.edu.sg/handle/10635/212315
ISSN: 16742788
DOI: 10.1093/jmcb/mjz009
Rights: Attribution-NonCommercial 4.0 International
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