Detecting local residue environment similarity for recognizing near‐native structure models |
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Authors: | Hyungrae Kim Daisuke Kihara |
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Institution: | 1. Department of Biological Sciences, Purdue University, , West Lafayette, Indiana, 47906;2. Department of Computer Science, Purdue University, , West Lafayette, Indiana, 47907 |
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Abstract: | We developed a new representation of local amino acid environments in protein structures called the Side‐chain Depth Environment (SDE). An SDE defines a local structural environment of a residue considering the coordinates and the depth of amino acids that locate in the vicinity of the side‐chain centroid of the residue. SDEs are general enough that similar SDEs are found in protein structures with globally different folds. Using SDEs, we developed a procedure called PRESCO (Protein Residue Environment SCOre) for selecting native or near‐native models from a pool of computational models. The procedure searches similar residue environments observed in a query model against a set of representative native protein structures to quantify how native‐like SDEs in the model are. When benchmarked on commonly used computational model datasets, our PRESCO compared favorably with the other existing scoring functions in selecting native and near‐native models. Proteins 2014; 82:3255–3272. © 2014 Wiley Periodicals, Inc. |
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Keywords: | protein local structures residue environment residue depth protein structure models quality assessment decoy selection |
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