A computational study of protein dynamics,structure ensembles,and functional mechanisms.
详细信息
- 作者：Lin ; Tu-Liang.
- 学历：Doctor
- 年：2011
- 导师：Song, Guang,eadvisorFernandez-Baca, Davidecommittee memberHargrove, Mark S.ecommittee memberHonavar, Vasantecommittee memberJernigan, Robert L.ecommittee member
- 毕业院校：Iowa State University
- Department：Computer Science
- ISBN：9781124871523
- CBH：3473051
- Country：USA
- 语种：English
- FileSize：6664936
- Pages：150
文摘
Proteins are vital parts of living organisms and involved in almost every single biological process. When participating in in-vivo reactions, proteins are constantly in motion and their dynamics is critical to the realization of their functions. Although the advancement of structure determination methods and computational approaches has opened up great opportunities for studying protein dynamics and functional mechanisms, much remains to be understood. In this thesis, I aim to establish some new computational methods for studying protein dynamics and functional mechanisms. In the first half of this thesis, I will describe the new computational methods for protein dynamics that I have developed. One of the most common methods for obtaining the protein dynamics computationally is molecular dynamics MD) simulations. Although MD simulations can provide atomic details of the protein dynamics, it is computationally expensive and is thus limited to short time scales, especially for large systems. In this thesis I focus on methods for studying protein dynamics that can circumvent such limitations. Two strategies are employed: 1) represent protein dynamics using weighted structure ensembles； 2) improve existing coarse-grained models with multi-body potentials using generalized spring tensors. In the second half of the thesis, I investigate the functional mechanisms of ligand migration and allosteric communication using novel, dynamics-based methods. Specifically, two subgoals are defined and accomplished: 1)chart the ligand migration channels in heme proteins using different structure ensembles； 2) determine the allosteric communication pathways using dynamic motion correlations.