CiteULike is a free online bibliography manager. Register and you can start organising your references online.
Tags

How Accurately Can We Model Protein Structures with Dihedral Angles? Algorithms in Bioinformatics

by: Xuefeng Cui, Shuai C. Li, Dongbo Bu, Babak Alipanahi Ramandi, Ming Li

edited by: Ben Raphael, Jijun Tang

Vol. 7534 (2012), pp. 274-287, doi:10.1007/978-3-642-33122-0_22  Key: citeulike:11233611

Formatted Citation


Show HTML

Likes (beta)

This copy of the article hasn't been liked by anyone yet.

View FullText article


Abstract

Previous study shows that the same type of bond lengths and angles fit Gaussian distributions well with small standard deviations on high resolution protein structure data. The mean values of these Gaussian distributions have been widely used as ideal bond lengths and angles in bioinformatics. However, we are not aware of any research work done to evaluate how accurately we can model protein structures with dihedral angles and ideal bond lengths and angles. In this paper, we first introduce the protein structure idealization problem. Then, we develop a fast O ( nm / ε ) dynamic programming algorithm to find an approximately optimal idealized protein backbone structure according to our scoring function. Consequently, we demonstrate that idealized backbone structures always exist with small changes and significantly better free energy. We also apply our algorithm to refine protein pseudo-structures determined in NMR experiments.


babakap's tags for this article

Citations (CiTO)

No CiTO relationships defined

X There are no reviews yet

X Find related articles with these CiteULike tags

X Posting History


X Export records

Privacy Statement | Terms & Conditions
CiteULike organises scholarly (or academic) papers or literature and provides bibliographic (which means it makes bibliographies) for universities and higher education establishments. It helps undergraduates and postgraduates. People studying for PhDs or in postdoctoral (postdoc) positions. The service is similar in scope to EndNote or RefWorks or any other reference manager like BibTeX, but it is a social bookmarking service for scientists and humanities researchers.