TY - JOUR
T1 - MASS
T2 - Multiple structural alignment by secondary structures
AU - Dror, O.
AU - Benyamini, H.
AU - Nussinov, R.
AU - Wolfson, H.
N1 - Funding Information:
This research has been supported in part by the ‘Center of Excellence in Geometric Computing and its Applications’ funded by the Israel Science Foundation (administered by the Israel Academy of Sciences) and by grants of Tel-Aviv University Basic Research Foundation. The research of H.J. Wolfson and O. Dror has been partially supported by the Hermann Minkowski-Minerva Center for Geometry at Tel Aviv University. The research of H. Benyamini has been supported by the Eshkol Fellowship funded by the Israeli Ministry of Science. The research of R. Nussinov has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under contract number NO1-CO-12400. The content of this publication does not necessarily reflect the view or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organization imply endorsement by the U.S. Government.
PY - 2003
Y1 - 2003
N2 - We present a novel method for multiple alignment of protein structures and detection of structural motifs. To date, only a few methods are available for addressing this task. Most of them are based on a series of pairwise comparisons. In contrast, MASS (Multiple Alignment by Secondary Structures) considers all the given structures at the same time. Exploiting the secondary structure representation aids in filtering out noisy results and in making the method highly efficient and robust. MASS disregards the sequence order of the secondary structure elements. Thus, it can find non-sequential and even non-topological structural motifs. An important novel feature of MASS is subset alignment detection: It does not require that all the input molecules be aligned. Rather, MASS is capable of detecting structural motifs shared only by a subset of the molecules. Given its high efficiency and capability of detecting subset alignments, MASS is suitable for a broad range of challenging applications: It can handle large-scale protein ensembles (on the order of tens) that may be heterogeneous, noisy, topologically unrelated and contain structures of low resolution.
AB - We present a novel method for multiple alignment of protein structures and detection of structural motifs. To date, only a few methods are available for addressing this task. Most of them are based on a series of pairwise comparisons. In contrast, MASS (Multiple Alignment by Secondary Structures) considers all the given structures at the same time. Exploiting the secondary structure representation aids in filtering out noisy results and in making the method highly efficient and robust. MASS disregards the sequence order of the secondary structure elements. Thus, it can find non-sequential and even non-topological structural motifs. An important novel feature of MASS is subset alignment detection: It does not require that all the input molecules be aligned. Rather, MASS is capable of detecting structural motifs shared only by a subset of the molecules. Given its high efficiency and capability of detecting subset alignments, MASS is suitable for a broad range of challenging applications: It can handle large-scale protein ensembles (on the order of tens) that may be heterogeneous, noisy, topologically unrelated and contain structures of low resolution.
KW - Non-sequential alignment
KW - Non-topological motif
KW - Structural bioinformatics
KW - Subset alignment
KW - Supersecondary structural motif
UR - http://www.scopus.com/inward/record.url?scp=0142143332&partnerID=8YFLogxK
U2 - 10.1093/bioinformatics/btg1012
DO - 10.1093/bioinformatics/btg1012
M3 - מאמר
AN - SCOPUS:0142143332
VL - 19
SP - i95-i104
JO - Bioinformatics
JF - Bioinformatics
SN - 1367-4803
IS - SUPPL. 1
ER -