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Table 5 Comparison of HIVprotI algorithm with existing QSAR based methods for predicting HIV proteins inhibitors

From: HIVprotI: an integrated web based platform for prediction and design of HIV proteins inhibitors

Serial number Target Predictive method and compounds type Number of compounds Correlation Web server/software Year References
1 Protease Non-peptide inhibitors 46 0.93–0.98 No 2010 [57]
2 Cycloalkylpyranone based compounds 170 0.6–0.83 No 2010 [58]
3 Ritonavir analogs 177 0.85 No 2012 [59]
4 Protease inhibitors 37 0.85–0.86 No 2015 [55]
5 Hydroxyethylamine derivatives 180 0.86 No 2015 [60]
6 Chemically diverse 1895 0.78 Yes 2017 HIVprotI
7 Reverse transcriptase Amino-arylsulfonylbenzonitriles 68 0.86 No 2009 [61]
8 TIBO derivatives 70 0.83–0.88 No 2009 [62]
9 PETT derivatives 61 0.77–0.83 No 2009 [63]
10 HEPT derivatives 36 0.92 No 2011 [64]
11 Substituted benzoxazinones 33 0.8 No 2012 [65]
12 Non-nucleoside inhibitors 80 0.7–0.8 No 2014 [66]
13 Chemically diverse 2126 0.76 Yes 2017 HIVprotI
14 Integrase Carboxylic acid derivatives 62 0.72–0.87 No 2010 [67]
15 N-methyl pyrimidones 51 0.84 No 2011 [43]
16 Quinoline ring derivatives 77 0.98 No 2012 [42]
17 Curcumine derivatives 39 0.91 No 2013 [68]
18 Chemically diverse 1240 0.74 Yes 2017 HIVprotI