ISSN

0974-4150 (Online)
0974-4169 (Print)


Author(s): Sameer Dixit, Arun K. Sikarwar

Email(s): dixitsameer1@rediffmail.com

DOI: 10.5958/0974-4150.2020.00046.2   

Address: Sameer Dixit1, Arun K. Sikarwar2
1Department of Chemistry, M. J. P. Govt. Polytechnic College Khandwa, Madhya Paradesh (India).
2Department of Chemistry, Govt. Home Science P. G. College Hoshangabad, Madhya Paradesh (India).
*Corresponding Author

Published In:   Volume - 13,      Issue - 3,     Year - 2020


ABSTRACT:
A Quantitative Structure-Property relationship (QSPR) model was developed for prediction of Activity of Phenol’s and its congeners against L1210 Leukaemia cells. Murine cell lines such as P388 leukemia, L1210 leukemia, and B16 melanoma, dominated the early years of cancer cell testing both in culture and in mice. In this study we have attempted to develop a multiple linear regression (MLR) model with high accuracy and precision. For this first we prepare several models and then validate them by statistical parameters like Q Factor, PE, PSE, SPRESS etc. and proposed a model which has better prediction power to prediction of Activity against L1210 Leukaemia cells.


Cite this article:
Sameer Dixit, Arun K. Sikarwar. Statistical Approach to Modelling of Activity of Phenol’s and its Derivatives against L1210 Leukaemia cells. Asian J. Research Chem. 2020; 13(3):237-240. doi: 10.5958/0974-4150.2020.00046.2


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3.    Haghi, A.K. Methodologies and Applications for Chemoinformatics and Chemical Engineering, IGI Global, 2, (2013)
4.    Richon A. B., An Introduction to QSAR Methodology, Network Science Corporation, 5, (2018)
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6.    Rishikesh V. Antre, Rajesh J. Oswal, et al., QSAR Studies of Substituted Pyrazolone Derivatives as AntiInflammatory Agents, Med chem, 2(6): 126-130 (2012)
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