scholarly journals FAST: A novel protein structure alignment algorithm

2004 ◽  
Vol 58 (3) ◽  
pp. 618-627 ◽  
Author(s):  
Jianhua Zhu ◽  
Zhiping Weng
Keyword(s):  
Protein Structure ◽  
Structure Alignment ◽  
Protein Structure Alignment ◽  
Alignment Algorithm ◽  
Novel Protein

PROTEIN STRUCTURE ALIGNMENT AND FAST SIMILARITY SEARCH USING LOCAL SHAPE SIGNATURES

2004 ◽  
Vol 02 (01) ◽  
pp. 215-239 ◽  
Author(s):  
TOLGA CAN ◽  
YUAN-FANG WANG
Keyword(s):  
Protein Structure ◽  
Protein Structures ◽  
Structure Alignment ◽  
Protein Structure Alignment ◽  
Specific Information ◽  
Alignment Algorithm ◽  
Screening Process ◽  
Domain Specific ◽  
Local Sequence ◽  
Shape Signatures

We present a new method for conducting protein structure similarity searches, which improves on the efficiency of some existing techniques. Our method is grounded in the theory of differential geometry on 3D space curve matching. We generate shape signatures for proteins that are invariant, localized, robust, compact, and biologically meaningful. The invariancy of the shape signatures allows us to improve similarity searching efficiency by adopting a hierarchical coarse-to-fine strategy. We index the shape signatures using an efficient hashing-based technique. With the help of this technique we screen out unlikely candidates and perform detailed pairwise alignments only for a small number of candidates that survive the screening process. Contrary to other hashing based techniques, our technique employs domain specific information (not just geometric information) in constructing the hash key, and hence, is more tuned to the domain of biology. Furthermore, the invariancy, localization, and compactness of the shape signatures allow us to utilize a well-known local sequence alignment algorithm for aligning two protein structures. One measure of the efficacy of the proposed technique is that we were able to perform structure alignment queries 36 times faster (on the average) than a well-known method while keeping the quality of the query results at an approximately similar level.

scholarly journals Implementation of a Parallel Protein Structure Alignment Service on Cloud

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Che-Lun Hung ◽  
Yaw-Ling Lin
Keyword(s):  
Protein Structure ◽  
Programming Model ◽  
Protein Structures ◽  
Structure Alignment ◽  
Evolutionary Relationships ◽  
Protein Structure Alignment ◽  
Alignment Algorithm ◽  
Cloud Platform ◽  
Computational Performance ◽  
Refinement Algorithm

Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment and refinement algorithms are implemented using MapReduce. We analyzed and compared the structure alignments produced by different methods using a dataset randomly selected from the PDB database. The experimental results verify that the proposed algorithm refines the resulting alignments more accurately than existing algorithms. Meanwhile, the computational performance of the proposed service is proportional to the number of processors used in our cloud platform.

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