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Research Article

Chemometric study of some α, β-unsaturated ketone as potential antifungal agents using density function theory and GFA (ATCC 10231 and NCIM 3446 cell line)

, & | (Reviewing Editor)
Article: 1175073 | Received 24 Oct 2015, Accepted 24 Mar 2016, Published online: 02 Jun 2016

References

  • Adamuuzairu, A., Idris, S., & Bello, A. (2015). Qsar of ketones derivatives using genetic function approximation. IOSR Journal of Applied Chemistry, 8, 57–64. doi:10.9790/5736-08815764
  • Ameji, J. P., Uzairu, A., & Idris, S. O. (2015). Quantum modeling of the toxicity of selected Anti-Candida albicans Schiff bases and their Nickel (II) complexes. Journal of Computational Methods in Molecular Design Scholars Research Library, 5, 91–103. Retrieved from http://scholarsresearchlibrary.com/archive.html
  • Bag, S., Ramar, S., & Degani, M. S. (2009). Synthesis and biological evaluation of α, β-unsaturated ketone as potential antifungal agents. Medicinal Chemistry Research, 18, 309–316.10.1007/s00044-008-9128-x
  • Beheshti, A., Pourbasheer, E., & Nekoei, M. (2012). QSAR modeling of antimalarial activity of urea derivatives using genetic algorithm – multiple linear regressions. Journal of Saudi Chemical Society, 1, 1–9. doi:10.1016/j.jscs.2012.07.019
  • Hango, K. J. D. C. R. (n.d.). Computational chemistry (Doctoral dissertation). Worcester Polytechnic Institute.
  • Hansen, K. (2012). Novel machine learning methods for computational chemistry. Berlin: Technische Universitat Berlin.
  • Kar, S., & Roy, K. (2011). Development and validation of a robust QSAR model for prediction of carcinogenicity of drugs. Indian Journal of Biochemistry & Biophysics, 48, 111–122.
  • Karki, R. G., & Kulkarni, V. M. (2001). Three-dimensional quantitative structure–activity relationship (3D-QSAR) of 3-aryloxazolidin-2-one antibacterials. Bioorganic and Medicinal Chemistry, 9, 3153–3160.
  • Khaled, K. F., & Abdel-Shafi, N. S. (2011). Quantitative structure and activity relationship modeling study of corrosion inhibitors: Genetic function approximation and molecular dynamics simulation methods. International Journal of Electrochemical Science, 6, 4077–4094. Retrieved from www.electrochemsci.org
  • Khaled, K. F., & El-Sherik, A. M. (2013). Using molecular dynamics simulations and genetic function approximation to model corrosion inhibition of iron in chloride solutions. International Journal of Electrochemical Science, 8, 10022–10043. Retrieved from www.electrochemsci.org
  • Motta, L. F., & Almeida, W. P. (2011). Ketone derivatives as Anti-Candida albicans. International Journal of Drug Discovery, 3, 6–9.
  • Pourbasheer, E., Aalizadeh, R., Ganjali, M. R., Norouzi, P., & Shadmanesh, J. (2014). QSAR study of ACK1 inhibitors by genetic algorithm-multiple linear regression (GA-MLR). Journal of Saudi Chemical Society, 18, 681–688. doi:10.1016/j.jscs.2014.01.010
  • Sahu, N. K., Sharma, M. K., Mourya, V., & Kohli, D. V. (2010). QSAR studies of some side chain modified 7-chloro-4-aminoquinolines as antimalarial agents. Arabian Journal of Chemistry, 7, 701–707. doi:10.1016/j.arabjc.2010.12.005
  • Todeschini, R., & Consonni, V. (2000). Handbook of molecular descriptors. Milano: Wiley VCH.