From: DeepQA: improving the estimation of single protein model quality with deep belief networks
Feature Name | Feature descriptions |
---|---|
(1). Surface score (SU) | The total area of exposed nonpolar residues divided byc the total area of all residues |
(2). Exposed mass score (EM) | The percentage of mass for exposed area, equal to the total mass of exposed area divided by the total mass of all area |
(3). Exposed surface score (ES) | The total exposed area divided by the total area |
(4). Solvent accessibility score (SA) | The difference of solvent accessibility predicted by SSpro4 [1] from the protein sequence and those of a model parsed by DSSP [2] |
(5). RF_CB_SRS_OD score [3] | A novel distance dependent residue-level potential energy score. |
(6). DFIRE2 score [4] | A distance-scaled all atom energy score. |
(7). Dope score [5] | A new statistical potential discrete optimized protein energy score. |
(8). GOAP score [6] | A generalized orientation-dependent, all-atom statistical potential score. |
(9). OPUS score [7] | A knowledge-based potential score. |
(10). ProQ2 score [8] | A single-model quality assessment method by machine learning techniques. |
(11). RWplus score [9] | A new energy score using pairwise distance-dependent atomic statistical potential function and side-chain orientation-dependent energy term |
(12). ModelEvaluator score [10] | A single-model quality assessment score based on structural features using support vector machine. |
(13). Secondary structure similarity score (SS) | The difference of secondary structure information predicted by Spine X [11] from a protein sequence and those of a model parsed by DSSP [2] |
(14). Secondary structure penalty score (SP) | Calculated from the predicted secondary structure alpha-helix and beta-sheet matching with the one parsed by DSSP. |
(15). Euclidean compact score (EC) | The pairwise Euclidean distance of all residues divided by the maximum Euclidean distance (3.8) of all residues. |
(16). Qprob [12] | A single-model quality assessment score that utilizes 11 structural and physicochemical features by feature-based probability density functions. |