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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