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Title: A Novel Approach to Structure Alignment

Abstract

Aligning protein structures is a highly relevant task. It enables the study of functional and ancestry relationships between proteins and is very important for homology and threading methods in structure prediction. Existing methods typically only partially explore the space of possible alignments and being able to efficiently handle permutations efficiently is rare. A novel approach for structure alignment is presented, where the key ingredients are: (1) An error function formulation of the problem simultaneously in terms of binary (Potts) assignment variables and real-valued atomic coordinates. (2) Minimization of the error function by an iterative method, where in each iteration a mean field method is employed for the assignment variables and exact rotation/translation of atomic coordinates is performed, weighted with the corresponding assignment variables. The approach allows for extensive search of all possible alignments, including those involving arbitrary permutations. The algorithm is implemented using a C{sub alpha}-representation of the backbone and explored on different protein structure categories using the Protein Data Bank (PDB) and is successfully compared with other algorithms. The approach performs very well with modest CPU consumption and is robust with respect to choice of parameters. It is extremely generic and exible and can handle additional user-prescribed constraints easily.more » Furthermore, it allows for a probabilistic interpretation of the results.« less

Publication Date:
Research Org.:
Stanford Linear Accelerator Center, Menlo Park, CA (US)
Sponsoring Org.:
USDOE Office of Energy Research (ER) (US)
OSTI Identifier:
763767
Report Number(s):
SLAC-PUB-8429
TRN: AH200033%%46
DOE Contract Number:  
AC03-76SF00515
Resource Type:
Technical Report
Resource Relation:
Other Information: PBD: 18 May 2000
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; PROTEIN STRUCTURE; DATA ANALYSIS; ITERATIVE METHODS; COMPUTER CALCULATIONS

Citation Formats

NONE. A Novel Approach to Structure Alignment. United States: N. p., 2000. Web. doi:10.2172/763767.
NONE. A Novel Approach to Structure Alignment. United States. doi:10.2172/763767.
NONE. Thu . "A Novel Approach to Structure Alignment". United States. doi:10.2172/763767. https://www.osti.gov/servlets/purl/763767.
@article{osti_763767,
title = {A Novel Approach to Structure Alignment},
author = {NONE},
abstractNote = {Aligning protein structures is a highly relevant task. It enables the study of functional and ancestry relationships between proteins and is very important for homology and threading methods in structure prediction. Existing methods typically only partially explore the space of possible alignments and being able to efficiently handle permutations efficiently is rare. A novel approach for structure alignment is presented, where the key ingredients are: (1) An error function formulation of the problem simultaneously in terms of binary (Potts) assignment variables and real-valued atomic coordinates. (2) Minimization of the error function by an iterative method, where in each iteration a mean field method is employed for the assignment variables and exact rotation/translation of atomic coordinates is performed, weighted with the corresponding assignment variables. The approach allows for extensive search of all possible alignments, including those involving arbitrary permutations. The algorithm is implemented using a C{sub alpha}-representation of the backbone and explored on different protein structure categories using the Protein Data Bank (PDB) and is successfully compared with other algorithms. The approach performs very well with modest CPU consumption and is robust with respect to choice of parameters. It is extremely generic and exible and can handle additional user-prescribed constraints easily. Furthermore, it allows for a probabilistic interpretation of the results.},
doi = {10.2172/763767},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2000},
month = {5}
}

Technical Report:

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