NDLI: A tool for structure alignment of molecules

Content Provider	IEEE Xplore Digital Library
Author	Pei-Ken Chang Chien-Cheng Chen Ming Ouhyoung
Copyright Year	2004
Description	Author affiliation: Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan (Pei-Ken Chang; Chien-Cheng Chen; Ming Ouhyoung)
Abstract	In this paper, a novel tool is proposed to align two molecules (not just proteins) based on their 3D structural data, and the user can observe the result of alignment visually via the tool. Most existing tools are designed only for alignment of proteins. Here, a new tool is developed to address shared structural features between protein structures and tRNA structures, that is, molecular mimicry, although they are two very different types of molecules. In order to align two molecules A and B, geometric hashing is applied to globally find initial matching of approximately overlapped atoms, thus parts of molecule A can be matched to parts of molecule B. Next, a fine tuning process is introduced, which is based on local optimization of overlapped parts, and the iterative closest point (ICP) is used until the number of overlapped atoms within a given distance threshold can not be increased any more. The results show that our method is useful to structurally align two molecules, not restricted to align two proteins only. Besides, our tool outperforms in terms of RMSD and number of matched atom pairs in comparison to other tools.
Starting Page	354
Ending Page	361
File Size	846212
Page Count	8
File Format	PDF
ISBN	0769522173
DOI	10.1109/MMSE.2004.19
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-12-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Protein engineering Iterative closest point algorithm Computer science Data engineering Search engines Throughput Databases Amino acids Genomics Bioinformatics
Content Type	Text
Resource Type	Article

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