Rational Design of Complex Protein Functions by Modulation of Backbone Dynamics
通过主链动力学调节复杂蛋白质功能的合理设计
基本信息
- 批准号:RGPIN-2016-04831
- 负责人:
- 金额:$ 3.35万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2020
- 资助国家:加拿大
- 起止时间:2020-01-01 至 2021-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Proteins have found widespread application in research, industry, and medicine because of their ability to mediate complex molecular processes with extreme precision and efficiency. While it is generally assumed that the function of a protein is dictated by its three-dimensional structure, increasing evidence demonstrates that time-dependent structural fluctuations in solution (i.e. dynamics) are essential to complex functions of proteins. Currently, it is extremely challenging to rationally design these complex functions to meet ever-growing needs in industry and medicine because we lack methods to predict protein sequences that will display the necessary dynamics. Computational protein design (CPD) techniques have been developed to identify sequences that can adopt a specific three-dimensional structure and possess a desired property such as increased stability, improved binding affinity, or altered specificity. However, standard CPD methods evaluate sequences on a single fixed protein structure, which does not allow for the explicit consideration of dynamics, thereby preventing the rational design of complex protein functions on demand. In this proposed research program, we will pioneer the development of multistate design (MSD) methods for the modulation of protein dynamics, enhancing the complexity of functions that can be accessed by rational design.
MSD is an emerging methodology in CPD that considers any number of protein structures as inputs to calculation instead of a single protein backbone template. For example, backbone ensembles approximating protein flexibility can be used as input structures in MSD, opening the door to the design of complex protein functions that require the consideration of dynamics. With funding from NSERC, we will develop a MSD framework to modulate dynamics of any protein at will, and will use it to design mutants of the G1 test protein displaying increased or decreased dynamics and brighter red fluorescent proteins by rigidifying their barrel structure. These research projects will be carried out by a team composed of a postdoctoral fellow, three graduate students, and ten undergraduates. Our success will constitute a ground-breaking development in protein engineering, opening the door to the integration of structural plasticity into a wide range of designed functions such as conformational switching and enzymatic catalysis. Our work will also advance our understanding of the link between protein structure, dynamics, and function, leading to fundamental insights that will have far-reaching impact in the protein science community at large. In the longer term, our work will take us one step closer to an age of designer proteins on-demand', yielding new technologies required to tackle important challenges of 21st century Canada in industry, environment, agriculture, and medicine.
蛋白质在研究,工业和医学中发现了广泛的应用,因为它们具有以极高的精度和效率介导复杂分子过程的能力。虽然通常认为蛋白质的功能是由其三维结构决定的,但越来越多的证据表明,溶液中时间依赖性的结构波动(即动力学)对于蛋白质的复杂功能至关重要。目前,理性地设计这些复杂功能以满足行业和医学的不断增长的需求是极其挑战的,因为我们缺乏预测将显示必要动态的蛋白质序列的方法。已经开发了计算蛋白设计(CPD)技术来识别可以采用特定三维结构并具有所需特性的序列,例如提高稳定性,改善的结合亲和力或改变特异性。但是,标准CPD方法评估了单个固定蛋白质结构上的序列,该蛋白质结构不允许明确考虑动力学,从而防止了根据需要进行复杂蛋白质功能的合理设计。在此拟议的研究计划中,我们将开发用于调节蛋白质动力学的多态设计(MSD)方法的开发,从而增强了可以通过理性设计访问的功能的复杂性。
MSD是CPD中的一种新兴方法,它将任何数量的蛋白质结构视为计算的输入,而不是单个蛋白质主链模板。例如,近似蛋白质柔韧性的骨干集合可以用作MSD中的输入结构,为需要考虑动力学的复杂蛋白质功能的设计打开了大门。借助NSERC的资金,我们将开发一个MSD框架,以随意调节任何蛋白质的动力学,并将其用于设计G1测试蛋白的突变体,从而通过缩放其枪管结构来显示增加或减少的动力学和更明亮的红色荧光蛋白。这些研究项目将由一个由博士后研究员,三名研究生和十个本科生组成的团队进行。我们的成功将构成蛋白质工程方面的突破性发展,这为结构可塑性整合到各种设计功能(例如构象开关和酶促催化)中打开了大门。我们的工作还将提高我们对蛋白质结构,动力学和功能之间联系的理解,从而导致基本见解,这些见解将对整个蛋白质科学界产生深远的影响。从长远来看,我们的工作将使我们更接近Designer蛋白质的按需时代,从而产生了应对加拿大21世纪加拿大在工业,环境,农业和医学方面的重要挑战所需的新技术。
项目成果
期刊论文数量(0)
专著数量(0)
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会议论文数量(0)
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{{ truncateString('Chica, Roberto', 18)}}的其他基金
Next-generation computational enzyme design for the creation of efficient artificial biocatalysts
用于创建高效人工生物催化剂的下一代计算酶设计
- 批准号:
RGPIN-2021-03484 - 财政年份:2022
- 资助金额:
$ 3.35万 - 项目类别:
Discovery Grants Program - Individual
Next-generation computational enzyme design for the creation of efficient artificial biocatalysts
用于创建高效人工生物催化剂的下一代计算酶设计
- 批准号:
RGPAS-2021-00017 - 财政年份:2022
- 资助金额:
$ 3.35万 - 项目类别:
Discovery Grants Program - Accelerator Supplements
Advanced Protein Engineering Training, Internships, Courses, and Exhibition (APPRENTICE)
高级蛋白质工程培训、实习、课程和展览(学徒)
- 批准号:
511956-2018 - 财政年份:2021
- 资助金额:
$ 3.35万 - 项目类别:
Collaborative Research and Training Experience
Next-generation computational enzyme design for the creation of efficient artificial biocatalysts
用于创建高效人工生物催化剂的下一代计算酶设计
- 批准号:
RGPIN-2021-03484 - 财政年份:2021
- 资助金额:
$ 3.35万 - 项目类别:
Discovery Grants Program - Individual
Next-generation computational enzyme design for the creation of efficient artificial biocatalysts
用于创建高效人工生物催化剂的下一代计算酶设计
- 批准号:
RGPAS-2021-00017 - 财政年份:2021
- 资助金额:
$ 3.35万 - 项目类别:
Discovery Grants Program - Accelerator Supplements
Advanced Protein Engineering Training, Internships, Courses, and Exhibition (APPRENTICE)
高级蛋白质工程培训、实习、课程和展览(学徒)
- 批准号:
511956-2018 - 财政年份:2020
- 资助金额:
$ 3.35万 - 项目类别:
Collaborative Research and Training Experience
Rational Design of Complex Protein Functions by Modulation of Backbone Dynamics
通过主链动力学调节复杂蛋白质功能的合理设计
- 批准号:
RGPIN-2016-04831 - 财政年份:2019
- 资助金额:
$ 3.35万 - 项目类别:
Discovery Grants Program - Individual
Advanced Protein Engineering Training, Internships, Courses, and Exhibition (APPRENTICE)
高级蛋白质工程培训、实习、课程和展览(学徒)
- 批准号:
511956-2018 - 财政年份:2019
- 资助金额:
$ 3.35万 - 项目类别:
Collaborative Research and Training Experience
Advanced Protein Engineering Training, Internships, Courses, and Exhibition (APPRENTICE)
高级蛋白质工程培训、实习、课程和展览(学徒)
- 批准号:
511956-2018 - 财政年份:2018
- 资助金额:
$ 3.35万 - 项目类别:
Collaborative Research and Training Experience
Rational Design of Complex Protein Functions by Modulation of Backbone Dynamics
通过主链动力学调节复杂蛋白质功能的合理设计
- 批准号:
RGPIN-2016-04831 - 财政年份:2018
- 资助金额:
$ 3.35万 - 项目类别:
Discovery Grants Program - Individual
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