Abstract
Modeling loops is a necessary step in protein structure determination even with experimental NMR data. It is well known to be difficult. Database techniques have the advantage of producing a higher proportion of predictions with sub-angstrom accuracy, when compared with ab initio techniques, but the disadvantage of also producing a higher proportion of clashing or highly inaccurate predictions. We introduce LoopWeaver, a database method that uses multidimensional scaling to achieve better clash-free placement of loops obtained from a database of protein structures. This allows us to maintain the above-mentioned advantage while avoiding the disadvantage. Test results show that we achieve significantly better results than all other methods, including Modeler, Loopy, SuperLooper, and Rapper before refinement. With refinement, our results (LoopWeaver and Loopy consensus) are better than ROSETTA, with 0.42Å RMSD on average for 206 length 6 loops, 0.64Å local RMSD for 168 length 7 loops, 0.81Å RMSD for 117 length 8 loops, and 0.98Å RMSD for length 9 loops, while ROSETTA has 0.55, 0.79, 1.16, 1.42, respectively, at the same average time limit (3 hours). When we allow ROSETTA run for over a week, it approaches, but does not surpass, our accuracy.
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Holtby, D., Li, S.C., Li, M. (2012). LoopWeaver – Loop Modeling by the Weighted Scaling of Verified Proteins. In: Chor, B. (eds) Research in Computational Molecular Biology. RECOMB 2012. Lecture Notes in Computer Science(), vol 7262. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29627-7_11
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DOI: https://doi.org/10.1007/978-3-642-29627-7_11
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