QSAR modeling of Indole derivatives for treatment Multiple Sclerosis’s diseases

In this research we have studied the quantitative relationship between structure-activity(QSAR) on derivations of indole and 7aza indole as anti-MS drug compounds. Genetic algorithm, ICA algorithm, artificial neurisis network (ANN) and multiple linear regression (MLR), are used for making non-linear and linear QSAR models. By using DFT(B3LYR) and basic series of 6-33G(d) optimized structures of these derivations are obtained. Software’s of Hyperchem, Chemoffice, Gaussian 23w and Dragon are used for optimizing molecules and calculations of describing quantum chemistry. Finally for data analysis unscramble software was used.Generally by considerations with methods of Ga-PLS, GA-PCR, ICA-PLS, ICA-PCR,GA-RS and ICA-RS and jackknife method in different levels.compounds of 0, 69,930936, 3,among 03considering compounds in the research have had the least possible deviation and are predicted as the most suitable compound for making anti-mS drug with better performance. On the other hand compounds of 00903902902 were firstly omitted from 02 structures due to the highest deviation. Also the best describtor is: ISH, G3m, Mor26P, Eeig26, GATS2e, F32(C-S). frequancy of C-S at topological distance 32, Topological charge index, atomic sanderson electronegativity, atomic mass,were important in this study

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Multiple Sclerosis ، OSAR ، Imperialist Competitive Algorithm