Research Article Open Access

Determination of Optimum Values of Descriptors to Set Filters for Synthetic Tri-Pyrrole Derivatives (Prodiginines) Against Multi Drug Resistant Strain of Plasmodium Falciparum

Vijay H. Masand1, Devidas T. Mahajan1, Eslam Pourbasheer2, Taibi Ben Hadda3, Harsh Chauhan4, J.M. Gajbhiye5 and A. M. Alafeefy6
  • 1 Vidya Bharati College, India
  • 2 University of Qom, Iran
  • 3 Université Mohammed Premier, Morocco
  • 4 Creighton University, United States
  • 5 Division of Organic Chemistry, India
  • 6 Kind Saud University, Saudi Arabia

Abstract

In the present study, we have carried out extensive non-linear Quantitative-Structure Activity Relationship (QSAR) analysis to correlate in vitro anti-malarial activity against multi drug resistant strain of Plasmodium falciparum. Forty-three synthetic prodiginines with different structural features were used for their potential antimalarial activity. Linear, bilinear, biexponential and parabolic equations were developed. These equations were compared to determine the optimum values of descriptors for very useful and easily interpretable descriptors. The optimum values of these descriptors could be helpful in finding and optimizing a good lead compound. Obtained correlations reveal that various factors like lipophilicity, molecular weight and number of bonds have non-linear relation with the anti-malarial activity.

Current Research in Drug Discovery
Volume 1 No. 2, 2014, 51-59

DOI: https://doi.org/10.3844/crddsp.2014.51.59

Submitted On: 6 November 2014 Published On: 26 January 2015

How to Cite: Masand, V. H., Mahajan, D. T., Pourbasheer, E., Hadda, T. B., Chauhan, H., Gajbhiye, J. & Alafeefy, A. M. (2014). Determination of Optimum Values of Descriptors to Set Filters for Synthetic Tri-Pyrrole Derivatives (Prodiginines) Against Multi Drug Resistant Strain of Plasmodium Falciparum. Current Research in Drug Discovery, 1(2), 51-59. https://doi.org/10.3844/crddsp.2014.51.59

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Keywords

  • Prodiginines
  • Anti-Malarial Activity
  • Optimum/Desirability Values
  • Hybrid Inverse-QSAR