A quality metric for homology modeling: the H-factor |
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Authors: | Eric di Luccio Patrice Koehl |
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Affiliation: | (1) Computer Science Department, Room 4337, Genome Center, GBSF University of California, Davis 451 East Health Sciences Drive, Davis, CA 95616, USA;(2) School of Applied Biosciences, Kyungpook National University (KNU), 1370 Sangyeok-dong, Buk-gu, Daegu, 702-701, Republic of Korea |
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Abstract: | Background The analysis of protein structures provides fundamental insight into most biochemical functions and consequently into the cause and possible treatment of diseases. As the structures of most known proteins cannot be solved experimentally for technical or sometimes simply for time constraints, in silico protein structure prediction is expected to step in and generate a more complete picture of the protein structure universe. Molecular modeling of protein structures is a fast growing field and tremendous works have been done since the publication of the very first model. The growth of modeling techniques and more specifically of those that rely on the existing experimental knowledge of protein structures is intimately linked to the developments of high resolution, experimental techniques such as NMR, X-ray crystallography and electron microscopy. This strong connection between experimental and in silico methods is however not devoid of criticisms and concerns among modelers as well as among experimentalists. |
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