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MS3ALIGN: an efficient molecular surface aligner using the topology of surface curvature

Overview of attention for article published in BMC Bioinformatics, January 2016
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Title
MS3ALIGN: an efficient molecular surface aligner using the topology of surface curvature
Published in
BMC Bioinformatics, January 2016
DOI 10.1186/s12859-015-0874-8
Pubmed ID
Authors

Nithin Shivashankar, Sonali Patil, Amrisha Bhosle, Nagasuma Chandra, Vijay Natarajan

Abstract

Aligning similar molecular structures is an important step in the process of bio-molecular structure and function analysis. Molecular surfaces are simple representations of molecular structure that are easily constructed from various forms of molecular data such as 3D atomic coordinates (PDB) and Electron Microscopy (EM) data. We present a Multi-Scale Morse-Smale Molecular-Surface Alignment tool, MS3ALIGN, which aligns molecular surfaces based on significant protrusions on the molecular surface. The input is a pair of molecular surfaces represented as triangle meshes. A key advantage of MS3ALIGN is computational efficiency that is achieved because it processes only a few carefully chosen protrusions on the molecular surface. Furthermore, the alignments are partial in nature and therefore allows for inexact surfaces to be aligned. The method is evaluated in four settings. First, we establish performance using known alignments with varying overlap and noise values. Second, we compare the method with SurfComp, an existing surface alignment method. We show that we are able to determine alignments reported by SurfComp, as well as report relevant alignments not found by SurfComp. Third, we validate the ability of MS3ALIGN to determine alignments in the case of structurally dissimilar binding sites. Fourth, we demonstrate the ability of MS3ALIGN to align iso-surfaces derived from cryo-electron microscopy scans. We have presented an algorithm that aligns Molecular Surfaces based on the topology of surface curvature. A webserver and standalone software implementation of the algorithm available at http://vgl.serc.iisc.ernet.in/ms3align .

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 7%
Unknown 13 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 36%
Other 2 14%
Student > Doctoral Student 2 14%
Professor 1 7%
Student > Master 1 7%
Other 2 14%
Unknown 1 7%
Readers by discipline Count As %
Computer Science 4 29%
Biochemistry, Genetics and Molecular Biology 3 21%
Agricultural and Biological Sciences 3 21%
Chemistry 1 7%
Unknown 3 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 12 January 2016.
All research outputs
#18,434,182
of 22,837,982 outputs
Outputs from BMC Bioinformatics
#6,320
of 7,288 outputs
Outputs of similar age
#285,487
of 395,128 outputs
Outputs of similar age from BMC Bioinformatics
#122
of 143 outputs
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