(A) method to detect important residues using protein binding site comparison = 단백질의 결합자리 비교를 통한 중요 잔기 탐색 방법

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 402
  • Download : 0
DC FieldValueLanguage
dc.contributor.advisorKim, Dong-Sup-
dc.contributor.advisor김동섭-
dc.contributor.authorPark, Keun-Wan-
dc.contributor.author박근완-
dc.date.accessioned2011-12-12T07:28:41Z-
dc.date.available2011-12-12T07:28:41Z-
dc.date.issued2007-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=264223&flag=dissertation-
dc.identifier.urihttp://hdl.handle.net/10203/27135-
dc.description학위논문(석사) - 한국과학기술원 : 바이오시스템학과, 2007.2, [ vii, 68 p. ]-
dc.description.abstract(1) As the number of protein sequences with unknown function increases, assigning accurate function to unknown protein becomes increasingly an important issue. Protein function is often encoded in a small number of residues located in binding pocket, and there have been many attempts to predict the function using the binding site. Here, I developed a binding site comparison method which can easily identify spatially matched residues between binding sites. Using clique detection algorithm, the new method finds the matched residues of maximum size, and then these matched residues are scored in a way similar to sequence alignment scoring. In addition, the significance of matched score is estimated from the empirical random score distribution. Results of benchmark test suggest that the method successfully detects functionally related binding sites. Furthermore, conserved residues and subfamily-specific residues in the functional family can be identified. In addition, we investigated systematic relationship between binding sites and functions using the binding site comparison method. Result showed that proteins with similar binding site largely perform similar function. (2) The multi-target strategy in drug discovery process is discussed as a turning point to overcome the problem of single-target strategy. As an earliest approach of multi-target drug design and virtual screening, I try to make rules which can discriminate between multi-binding and specific-binding ligands by machine learning technique. Using the information of protein-ligand complex in Protein Data Bank (PDB), the ‘multi-binding’ and ‘specific-binding’ chemical compound datasets are defined, and the structures of chemical compounds are mapped onto the chemical space defined by molecular descriptors. Under the assumption that multi-binding property is fundamentally related with multi-target ability, classifier is generated to discriminate between multi-binding and specific binding ligands. A result ...eng
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectfunction prediction-
dc.subjectclique detection algorithm-
dc.subject단백질 결합 자리-
dc.subject리간드-
dc.subject기능 예측-
dc.subject클릭 탐색 알고리즘-
dc.subjectprotein binding site-
dc.subjectligand-
dc.title(A) method to detect important residues using protein binding site comparison = 단백질의 결합자리 비교를 통한 중요 잔기 탐색 방법-
dc.typeThesis(Master)-
dc.identifier.CNRN264223/325007 -
dc.description.department한국과학기술원 : 바이오시스템학과, -
dc.identifier.uid020053203-
dc.contributor.localauthorKim, Dong-Sup-
dc.contributor.localauthor김동섭-
Appears in Collection
BiS-Theses_Master(석사논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0