HELFIT: Helix fitting by a total least squares method |
| |
Authors: | Enkhbayar Purevjav Damdinsuren Sodov Osaki Mitsuru Matsushima Norio |
| |
Institution: | aDepartment of Biophysics, Faculty of Biology, National University of Mongolia, Ulaanbaatar 210646/377, Mongolia;bDivision of Agricultural Science, Hokkaido University Graduate School of Agriculture, Sapporo, Hokkaido 060-0810, Japan;cDivision of Biophysics, Sapporo Medical University School of Health Sciences, Sapporo, Hokkaido 060-8556, Japan |
| |
Abstract: | The problem of fitting a helix to data arises in analysis of protein structure, in nuclear physics, and in engineering. A continuous helix is described by five parameters: helix axis, helix radius, and helix pitch. One of these helix parameters is frequently predefined in the helix fitting. Other algorithms find only the helix axis or determine separately the helix axis, the helix radius, or the helix pitch. Here we describe a total least squares method, HELFIT, for helix fitting. HELFIT enables one to calculate simultaneously all five of the helix parameters with high accuracy. The minimum number of data points required for the analysis is only four. HELFIT is very insensitive to noise even in short helices. HELFIT also calculates a parameter, p = rmsd/(N − 1)1/2, which estimates the regularity of helical structures independent of the number of data points, where rmsd is the root mean square distance from the best-fit helix to data points and N is the number of data points. It should become a basic tool of structural bioinformatics. |
| |
Keywords: | HELFIT Helix fitting Total least squares Helix parameters |
本文献已被 ScienceDirect PubMed 等数据库收录! |
|