Additional file 2: Text S1. of CSmetaPred: a consensus method for prediction of catalytic residues
Creators: name: Choudhary, Preeti
name: Shailesh Kumar
name: Bachhawat, Anand
name: Pandit, Shashi
Publisher: name: figshare
Year: 2017
Subjects: subject: Biophysics
subject: Biochemistry
subject: Medicine
subject: Molecular Biology
subject: 69999 Biological Sciences not elsewhere classified
subject: FOS: Biological sciences
subject: FOS: Biological sciences
subject: 80699 Information Systems not elsewhere classified
subject: FOS: Computer and information sciences
subject: FOS: Computer and information sciences
subject: 19999 Mathematical Sciences not elsewhere classified
subject: FOS: Mathematics
subject: FOS: Mathematics
subject: 110309 Infectious Diseases
subject: FOS: Health sciences
subject: FOS: Health sciences

description: Extended Methods and Results sections. Table S2. Table summarizing quantitative measures for ROC and PR curves. Quantitative comparison of average ROC curves using AUCROC and MAS as single value measures of ROC and AUCPR and MAP are used to quantitatively compare average PR curves (see Methods section). Median and average ranks of catalytic residues are also summarized. Table S3. Summary of p-values obtained from Wilcoxon signed ranked statistical test. Summary of p-values from Wilcoxon signed-rank test computed on AveS (MAS) and AP (MAP) measures to estimate statistical significance of performance difference between CSmetaPred and its constituent methods (EXIA2, DISCERN, and WCN). Table S4. Quantitative comparison of average PR and ROC curves for various methods when either polar/charged or non-polar residues are ranked separately. Comparison of ROC/PR curves quantitative measures when only (A) polar/charged amino acids and (B) non-polar amino acids are ranked. Quantitative measure of ROC is AUCROC and MAS, whereas PR curves are compared using AUCPR and MAP. Median and average ranks of catalytic residues are also summarized. Table S5. Comparison of CSmetaPred_poc prediction performance on modelled and their respective native structures. Summary of quantitative analysis of ROC and PR curves using AUCROC/MAS and AUCPR/MAP respectively, for CSmetaPred_poc prediction on model and their respective native structures. Median and average ranks of catalytic residues are also summarized. Table S6. Comparison of catalytic residues rank obtained from various methods on set of pdb entries mostly from benchmark dataset. Summary of known catalytic residues ranks given by various predictors for pdb entries mostly from previous and present works. Table S7. Catalytic residue prediction for protein structures deposited in PDB after development of CSmetaPred. Meta-predictor prediction performance on pdb entries, with experimentally known catalytic residues, submitted in RCSB PDB database subsequent to development of meta-approach method. Catalytic residue ranks from CSmetaPred_poc is summarized in the table. Table S8. Predicted catalytic residues of γ-glutamylcysteine synthetase. List of top 20 predicted catalytic residues of γ-glutamylcysteine synthetase from E. coli (pdbid: 1v4gA) by CSmetaPred_poc. Table S9. Summary of relative enzymatic activity of GshA mutants. Table showing enzyme activity (in vitro) of GshA mutants calculated with respect to wild type activity of enzyme. Table S10. Primers used for cloning. List of primers sets used in site overlap extension PCR in cloning mutant GshA. Figure S1. Cumulative distribution of catalytic residues present in predicted pockets. Plot showing cumulative distribution of catalytic residues within a given pocket rank on macie-254 dataset for: a) Pockets output from LIGSITE/Fpocket, b) re-ranked pockets using poc_sc score and, c) merged top 5 re-ranked pockets. The vertical line shows that at pocket rank 5 both LIGSITE and Fpocket have achieved close to the maximum catalytic residues identified within predicted pockets. The drastic increase in catalytic residues fraction after re-ranking in LIGSITE could also be due to merging of pockets within LIGSITE. Figure S2. Average ROC plots for all datasets. Average ROC plots to show comparison among various predictors (CSmetaPred, EXIA2, DISCERN and WCN) on POOL-148, PW-79, EF-Fold-164, csalit-688, macie-254 and EF_POOL_PW datasets. CRpred SVM performance is shown as filled triangle. Figure S3. Average ROC plots for modified CSmetaPred, wherein one score is excluded from meta-score computation. Average ROC curves showing effect of individual method on the performance of CSmetaPred using CSAMAC (A) and EF_POOL_PW (B) datasets. All four methods contribute to different extent towards improving meta-score based ranking in CSmetaPred. It is apparent from ROC curves that excluding CRpred or CATSID residue score has maximum effect on prediction performance. This suggests that these 2 methods have major contribution in meta-score. Figure S4. Average PR curves for benchmarking datasets. The figure showing average PR curves for CSmetaPred and other predictors (EXIA2, DISCERN and WCN) on EF_POOL_PW and five individual datasets. CRpred SVM performance is shown as filled triangle. Figure S5. Average ROC and PR curves for predictors considering ranked list of only polar/charged residues. Average ROC (A-F) and average PR (G-L) curves on EF_POOL_PW and 5 datasets, when only polar/charged amino acids are ranked. CRpred SVM performance is shown as filled triangle. Figure S6. Average ROC and PR curves for predictors considering ranked list of only non-polar residues. Figure showing average ROC (A, B) and average PR (C, D) curves for various predictors (CSmetaPred, EXIA2, DISCERN and WCN) when only non-polar amino acids are ranked from CSAMAC and EF_POOL_PW datasets. CRpred SVM performance is shown as filled triangle. Figure S7. CSmetaPred_poc comparison with CSmetaPred using average ROC plots. Average ROC plots showing comparison of prediction performance between CSmetaPred and CSmetaPred_poc on all datasets. Figure S8. CSmetaPred_poc comparison with CSmetaPred using average PR curves. Average PR curves showing comparison of prediction performance between CSmetaPred_poc and CSmetaPred on all datasets. Figure S9. Average ROC and PR curves for various predictors on UB-137 datasets. Average ROC (A) and average PR (B) curves for meta-predictors and other predictors (EXIA2, DISCERN and WCN) on UB-137 dataset. CRpred SVM performance is shown as filled triangle. Figure S10. Filtration ratio plotted as a function of average recall. Average recall plotted as a function of filtration ratio for proteins in EF_POOL_PW dataset. Figure S11. Fraction of proteins with catalytic residue coverage plotted as a function of ranks. Cumulative fraction of proteins (in percent) having at least 0.5, 0.8 and 1.0 catalytic residue coverage at various ranks ≤100. Figure S12. Comparison of CSmetaPred_poc prediction performance on models and their respective native structures. Figure showing prediction performances of CSmetaPred_poc on models and their respective native structures assessed using average ROC (A) and PR (B) curves. CRpred SVM performance is shown with filled triangle. Figure S13. In vivo complementation assay of GshA wild type and mutant enzymes. Figure showing in vivo complementation assay of predicted catalytic residues mutants of GshA enzyme. Saccharomyces cerevisiae strain ABC1195 plasmids bearing WT gshA or the different cysteine binding residues gshA mutant gene cloned under TEF promoter. The transformants were grown overnight in SD + GSH medium and used to re-inoculate secondary culture. Cells were harvested at OD600 = 0.6 and serially diluted (0.2 to 0.0002 OD600). 10 μl was spotted on SD medium with or without GSH as sole source of organic sulphur. The vector pTEF416 and EcGshA were used as negative and positive control respectively. Figure S14. Residues rank comparison between EXIA2 server and in-house recoded EXIA2. Plot showing residues rank comparison from EXIA2 server output and in-house recoded EXIA2 for (A) all residues, and (B) catalytic residues. The Pearson correlation coefficient between ranks for all residues obtained from EXIA2 and in-house program is 0.86, and the same for catalytic residues is 0.55. (PDF 5965 kb)