Journal :   Research Journal of Pharmacy and Technology

Volume No. :   11

Issue No. :  9

Year :  2018

Pages :   3802-3810

ISSN Print :  0974-3618

ISSN Online :  0974-360X


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QSAR Analysis of some N, N-diphenyl urea derivatives as CCR5 Receptor Antagonist



Address:   Yogesh Vaishnav1*, Aloksingh Thakur1, Chanchal Deep Kaur1, Shekhar Verma2, Achal Mishra3, Sanmati Kumar Jain4 , Piyush Ghode5
1Shri Rawatpurasarkar Institute of Pharmacy, Kumhari, Durg.490042
2University College of Pharmacy, Pt Deendayal Upadhyay Memorial Health Sciences and Ayush University, Raipur Chhattisgarh.493661
3SSTC-SSGI-Faculty of Pharmaceutical Sciences, Bhilai (C.G.) 490020 India
4Smt. Sulochna Lakhanlal Trivedi Institute of Pharmaceutical Sciences, Guru Ghasidas Vishwavidyalaya, Koni, Bilaspur, Chhattisgarh 495009 India.
5School of Pharmacy and Technology Management, NMIMS, Shirpur Dist :Dhule (Maharashtra), 425405
*Corresponding Author
DOI No: 10.5958/0974-360X.2018.00697.2

ABSTRACT:
Quantitative structure–activity relationship (QSAR) has been established for 29 molecules of N, N- diphenylureas, reported to inhibit the binding of RANTES to membranes prepared from Chinese hamster ovary (CHO) cells stably expressing recombinant human CCR5. Partial Least Square Regressions (PLSR) was used to generate the relationship between biological activity and calculated descriptors. Model with good statistical qualities was developed using the software VLIFE MDS 3.0. Validation of the model was done bycross validation, randomization, and external test set prediction. On the basis of the QSAR model, we calculated the activity and found that theexisting compounds were potent.
KEYWORDS:
N, N- diphenylureas,CCR5, AIDS, HIV, Quantitative structure–activity relationship (QSAR), PLS (Partial least square) regression analysis
Cite:
Yogesh Vaishnav, Aloksingh Thakur, Chanchal Deep Kaur, Shekhar Verma, Achal Mishra, Sanmati Kumar Jain , Piyush Ghode. QSAR Analysis of some N, N-diphenyl urea derivatives as CCR5 Receptor Antagonist. Research J. Pharm. and Tech 2018; 11(9): 3802-3810.
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