| 项目编号: | BB/P007562/1
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| 项目名称: | Mechanistic models of protein sequence evolution |
| 作者: | Richard Allen Goldstein
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| 承担单位: | University College London
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| 批准年: | 2016
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| 开始日期: | 2017-01-04
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| 结束日期: | 2020-31-03
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| 资助金额: | GBP407027
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| 资助来源: | UK-BBSRC
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| 项目类别: | Research Grant
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| 国家: | UK
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| 语种: | 英语
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| 特色学科分类: | Biomolecules & biochemistry
; Ecol, biodivers. & systematics
; Genetics & development
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| 英文摘要: | All life on earth is the result of molecular evolution, so it is not surprising that evolutionary viewpoints have yielded so much understanding of living systems. By modelling how proteins have evolved and co-evolved, by re-creating ancestral forms in the laboratory, by analysing patterns of conservation and change in individual proteins, by identifying related proteins about which more is known, phylogenetic analysis has become a powerful tool throughout the life sciences.
Analyses of protein evolution rely on appropriate models of sequence change. Currently, such analyses are dominated by empirical models created by comparing closely related proteins. In order to make model creation tractable and their use computationally feasible, a number of seemingly unjustifiable assumptions are made, such that all sites in the protein evolve independently in a similar manner. This simplicity has been the source of much of their power, success, and widespread use. Unfortunately, these simplifications have three major negative consequences. Firstly, the parameters in these models do not necessarily correspond to biologically relevant quantities, making interpretations of the results difficult. Secondly, some of the analyses are very sensitive to the assumptions made, with unrealistic assumptions yielding erroneous or misleading results. Thirdly, we are often interested in situations where the assumptions break down, providing important information about the proteins' properties and roles and how these change. These limitations have led to an interest in mechanistic models of the substitution process based on the underlying protein biophysics, molecular biology, and evolutionary dynamics. Progress in this area has been limited, however, due to the complexity and our lack of understanding of protein evolution, especially the extent, significance, and impact of epistatic interactions where the substitution patterns at one site depend on the amino acids found in other sites.
We propose a systematic integrated approach to the problem. This will involve:
- Performing computational simulations of protein evolution, where proteins evolve to maintain thermodynamic stability or ability to bind a constant or changing ligand. The purpose of these simulations is to allow us to investigate various phenomena that occur when selection acts on properties of the entire protein that cannot be reduced to the sum of contributions of single sites.
- Evaluating, validating, and characterising the hypotheses generated by the simulations through phylogenetic analyses of well-sampled proteins, including mitochondrial proteins.
- Connecting the results of these simulations with well-developed approaches in the physical sciences, such as the theory of chemical reaction rates.
- Using the insights drawn from the computational simulations and phylogenetic analysis of real proteins to construct more powerful and accurate models of the substitution process that are firmly rooted in the underlying biology.
- Using these substitution models to develop important applications, including the analysis of the degree, nature, and time dependence of the selection acting on proteins, and the identification of deleterious mutations.
- Applying these tools to study selection on G-protein coupled receptors and the detection of disease-related nsSNPs.
- Incorporating the new models and applications into the powerful publically available phylogenetics analysis program PLEX.
By increasing the accuracy, interpretability, and scope of phylogenetic analysis, we will impact a wide range of investigations throughout the life sciences, including how proteins and other biomolecules function and interact, how organisms adapt to new environments, how pathogens change in order to defeat host immune systems and infect new hosts, how humans and other organisms adjust to new and changing pathogens, and how we can modify proteins to our own specifications. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/100234
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| Appears in Collections: | 科学计划与规划
气候变化与战略
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作者单位: | University College London
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| Recommended Citation: | |
Richard Allen Goldstein. Mechanistic models of protein sequence evolution. 2016-01-01.
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