Development of protein modeling methods for structure refinement in the context of unreliable environments
신뢰도가 낮은 구조 환경에서의 단백질 모델 정밀화 방법 개발
- 자연과학대학 화학부
- Issue Date
- 서울대학교 대학원
- Protein model refinement; protein structure prediction; loop modeling; flexible protein-ligand docking; hybrid energy function; G-protein-coupled receptor
- 학위논문 (박사)-- 서울대학교 대학원 : 화학부 물리화학 전공, 2017. 2. 석차옥.
- The number of experimentally determined protein structures is increasing exponentially. Based on this abundant structural information, homology modeling is now the most popular method for protein structure prediction. Still however, knowledge of high resolution structures is critical for applications using the protein structure such as drug discovery and protein design. By realizing this, protein structure refinement methods have been developed to improve the structure quality of low resolution experimental structures or model structures. Another realm of protein structure refinement is to predict the protein structure in the environment of interest, such as binding to a specific partner, when only structures resolved in different conformational states or model structures are provided.
In this thesis, four modeling methods (GalaxyLoop-PS2, GalaxyRefine2, GalaxyVoyage, and Galaxy7TM) developed in the scope of refining predicted protein structures are introduced. The methods were evolved by either extending the range of structure targeted for refinement or considering the interaction with a particular binding partner. The shared problem of these methods was that the environment of modeling was unreliable due to errors embedded in model structures. Commonly, two approaches were taken to tackle this problem. These were initially searching the conformational space in low resolution and developing a hybrid energy function less sensitive to environmental error. The development and application results of the approaches taken for each modeling method will be addressed in detail.