Author(s):
Lokendra Kumar Ojha, Harsh Pandey, Ajay M. Chaturvedi, Arpan Bhardwaj, Ashutosh Pandey
Email(s):
ojha.lokendra@gmail.com
DOI:
10.5958/0974-360X.2018.00025.2 
Address:
Lokendra Kumar Ojha1*, Harsh Pandey2, Ajay M. Chaturvedi3, Arpan Bhardwaj3, Ashutosh Pandey1
1Lovely Professional University, Jalandhar, Punjab, India
2School of Medical Science and Technology, IIT Kharagpur, India
3Govt. Madhav Science Post Graduate College, Ujjain, (MP), India
*Corresponding Author
Published In:
Volume - 11,
Issue - 1,
Year - 2018
ABSTRACT:
Aim: To study the statistical technique in order to find out the mathematical modeling of anti-HIV drug. Material and Methods: 14 TIBO derivatives are taken in account for statistical approach MLR (multiple linear regression) to predict the best drug model.Results:pIC50= 1.2722 (±.1571) I Cl -15.5513 (±3.5856) ? +29.0977. The role of indicator parameter (I Cl i.e. Presence of -C l atom at carbon of seven member ring) is important to increase the binding affinity of the drug and so as index of refraction (?) also plays vital role. Conclusion:Statistical results shows that the proposed model is best as far as synthesis of new drug molecule is concern.
Cite this article:
Lokendra Kumar Ojha, Harsh Pandey, Ajay M. Chaturvedi, Arpan Bhardwaj, Ashutosh Pandey. Statistical Analysis of TIBO Derivatives as Non- Nucleoside Reverse Transcriptase Inhibitors. Research J. Pharm. and Tech. 2018; 11(1): 131-134 doi: 10.5958/0974-360X.2018.00025.2
Cite(Electronic):
Lokendra Kumar Ojha, Harsh Pandey, Ajay M. Chaturvedi, Arpan Bhardwaj, Ashutosh Pandey. Statistical Analysis of TIBO Derivatives as Non- Nucleoside Reverse Transcriptase Inhibitors. Research J. Pharm. and Tech. 2018; 11(1): 131-134 doi: 10.5958/0974-360X.2018.00025.2 Available on: https://www.rjptonline.org/AbstractView.aspx?PID=2018-11-1-25