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The decoy sets we used include the multiple decoy sets from the Decoys ‘R’ Us collection (http://compbio.buffalo.edu/dd/download.shtml), which include the 4state_reduced, fisa, fisa_casp3, hg_structal, ig_structal, ig_structal_hires, lattice_ssfit, lmds, and lmds_v2 decoy sets. The MOULDER decoy set1 was downloaded from https://salilab.org/decoys/
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README.md

README.md

protein_folding-decoy-set

The decoy sets we used include the multiple decoy sets from the Decoys ‘R’ Us collection (http://compbio.buffalo.edu/dd/download.shtml), which include the 4state_reduced, fisa, fisa_casp3, hg_structal, ig_structal, ig_structal_hires, lattice_ssfit, lmds, and lmds_v2 decoy sets. The MOULDER decoy set1 was downloaded from https://salilab.org/decoys/; the I-TASSER decoy set-II was obtained from https://zhanglab.ccmb.med.umich.edu/decoys/decoy2.html; and the ROSETTA all-atom decoy set from https://zenodo.org/record/48780#.WvtCA63MzLF.

All protein structures (including both native and decoys) were converted into their biological oligomerization state and prepared with the Protein Preparation Wizard, which adds missing atoms, optimizes the H-bond network, and performs energy minimization to clean up the structures for subsequent calculations.

Please cite: Random Forest Refinement of the KECSA2 Knowledge-Based Scoring Function for Protein Decoy Detection Jun Pei, Zheng Zheng, and Kenneth M. Merz, Jr. Journal of Chemical Information and Modeling Article ASAP DOI: 10.1021/acs.jcim.8b00734

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