Quantitative structure activity relationship study of anticonvulsant

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  • Abdulfatai et al., Cogent Chemistry (2016), 2: 1166538http://dx.doi.org/10.1080/23312009.2016.1166538


    Quantitative structure activity relationship study of anticonvulsant activity of _substituted acetamido-N-benzylacetamide derivativesUsman Abdulfatai1*, Adamu Uzairu1 and Sani Uba1

    Abstract:To develop the quantitative structureactivity relationship (QSAR) for pre-dicting the anticonvulsant activity of _substituted acetamido-N-benzylacetamide derivatives. Density Functional Theory (B3LYP/6-31G*) quantum chemical calculation method was used to find the optimized geometry of the studied molecules. Nine types of molecular descriptors were used to derive a quantitative relation between anticonvulsant activity and structural properties. The relevant molecular descriptors were selected by genetic algorithm approximation. The high value of the correla-tion coefficient, (R2) of 0.98, indicates that the model was satisfactory. The proposed model has good stability, robustness, and predictability on verifying with internal and external validation.

    Subjects: Atomic, Molecular, Physical Chemistry; Chemistry; Physical Chemistry

    Keywords: epilepsy; QSAR; GFA; DFT (B3LYP/6-31G*)

    1. IntroductionEpilepsy is defined as a brain disorder characterized by an enduring predisposition to generate epi-leptic seizures (Fisher, Boas, & Blume, 2005). John Hughlings Jackson recommended that seizures were caused by occasional, sudden, severe, extreme, rapid and local discharge of gray matter, and that a generalized convulsion resulted when normal brain tissue invaded by the seizure activity initi-ated in the abnormal focus (Brunton, Lazo, & Parker, 2006). Ant-epilepsy campaign conducted by World Health Organization (WHO) in conjunction with International Bureau for Epilepsy (IBE) and International League Against Epilepsy (ILAE) suggests that 1% of world population at any time is afflicted with this neurological disorder. Every year about 2.4 million new cases are added to these

    *Corresponding author: Usman Abdulfatai, Department of Chemistry, Ahmadu Bello University, Zaria, Nigeria E-mail: faithyikare4me@gmail.com

    Reviewing editor:Juan Ignacio Melo, Universidad de Buenos Aires Facultad de Ciencias Exactas y Naturales, Argentina

    Additional information is available at the end of the article

    ABOUT THE AUTHORSUsman Abdulfatai is a research scholar in the Department of Chemistry, Ahmadu Bello University, Zaria-Nigeria. He is working in the field of Quantitative structural activity relationship study of anticonvulsant activity under supervision of Adamu Uzairu and Sani Uba.

    PUBLIC INTEREST STATEMENTThe principal investigator and other authors have been actively engaged in the research of the area of Quantitative Structural Activity Relationship (QSAR) of _substituted acetamido-N-benzylacetamide derivatives as an anticonvulsant activity. QSAR as a major factor in drug design, are mathematical equations relating chemical structure to their biological activity and it is also used to understand the structural features controlling the activities of neurotransmitters. The modeled _substituted acetamido-N-benzylacetamide derivatives as an anticonvulsant activity will be used to inhibit/ deactivate the activities of Gamma Amino Butyrate Acid Transferases (GABAAT). An enzyme that causes epilepsy.

    Received: 21 October 2015Accepted: 11 March 2016Published: 22 April 2016

    2016 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.

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    Abdulfatai et al., Cogent Chemistry (2016), 2: 1166538http://dx.doi.org/10.1080/23312009.2016.1166538

    figures (WHO/IBE/ILAEGlobal Campaign Against Epilepsy, 2009; Shadows & Hoofddorp, 2003). Several new compounds such as zonisamide, vigabatrin, gabapentin have emerged following the wide use of the classical antiepileptic drugs such as phenytoin, Phenobarbital, carbamazepine, valp-roic acid and various benzodiazepines. The need to synthesize newer compounds persists to treat those cases that are resistant to the available drugs and to reduce the side effects to the lowest possible level (Kathuria & Pathak, 2012). Ant-epileptic drugs exert their action by different mecha-nisms. They include an enhancement of the GABA-ergic neurotransmission effects on neuronal voltage-gated sodium and/or calcium channels (Anger, Madge, Mulla, & Riddall, 2001).

    Quantitative structureactivity relationships (QSAR) are mathematical equations relating chemi-cal structure to their biological activity (Krogsgaard-Larsen, Liljefors, & Ulf, 2002). The far reaching utilization of QSAR models was from the improvement of new basic descriptors and measurable mathematical statements relating different physical and organic properties of the substance struc-ture. The main hypothesis in the QSAR approach is that all properties of a chemical substance are statistically related to its molecular structure. The success of the QSAR approach can be explained by the insight offered into the structural determination of chemical properties and biological activi-ties, and the possibility to estimate the properties of new chemical compounds without the need to synthesize and test them. These molecular design techniques, which significantly reduce the cost and time involved in obtaining compounds with desired properties, were applied to a wide range of properties, such as melting and boiling temperature, molar heat capacity, standard Gibbs energy of formation, vaporization enthalpy refractive index, density, aqueous solubility, 1-octanol/water parti-tion coefficient, solvation free energy, receptor binding affinities, pharmacological activities, and enzyme inhibition constants (Tarkoa & Ivanciuc, 2001; Palluotto et al., 1996).

    The purpose of this research is to perform a quantum chemical QSAR study of a series of _substi-tuted acetamido-N-benzylacetamide derivatives to investigate the experimental activities of the molecules as anticonvulsant activity agents and obtain a linear model using the Genetic function Approximation (GFA) method.

    2. Material and methodology

    2.1. Data collectionThirty-five molecules belonging to _substituted acetamido-N-benzylacetamide derivatives were used as anticonvulsant activities were taken from the literature and used for the present study (Kohn, Conley, & Leander, 1998). The observed structures, the biological activities of the training, outliers and test sets of these compounds are presented in Figure 1 and Table 1, respectively.

    2.2. Biological activityThe logarithm of measured ED50 (M) against anticonvulsant activity as pED50 (pED50=log 1/ED50) was used as dependent variable, consequently correlating the data linearly to the independent vari-able/descriptors.

    2.3. Molecular optimizationThe process of finding the equilibrium or lowest energy geometry of molecules is called Molecular Optimization. All molecular modeling studies were carried out using Spartan14 version 1.1.2

    Figure 1. General structure of _substituted acetamido-N-benzylacetamide derivatives.

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    Abdulfatai et al., Cogent Chemistry (2016), 2: 1166538http://dx.doi.org/10.1080/23312009.2016.1166538

    (Wavefunction. Inc, 2013) and PaDEL-Descriptor version 2.18 (Yap, 2011) running on Toshiba Satellite, Dual-core processor window eight (8) operating system. The molecular structures of the compounds in the selected series were drawn in the graphic user interface of the software. Structures were built using 2D application tool and exported in 3D format. All 3D structures were geometrically

    Table 1. Biological activities of training and test set derivativesS. No R1 R2 ED501a CH3 CH2-Ph 1.88

    2t CH3 CH2-Ph-m-F 1.89

    3t 2-Furanyl CH2-Ph-o-F 1.60

    4t 2-Furanyl CH2-Ph-m-F 1.12

    5t 2-Furanyl CH2-Ph-p-F 1.10

    6a 2-Furanyl CH2-2,5-C6H6 1.38

    7t 2-Furanyl CH2-2,5-C6H6 1.80

    8t 3-Allyl CH2-Ph 1.53

    9b 2-tetrahydrofuranyl CH2-Ph 1.71

    10t Ph CH2-Ph 1.31

    11b 2-Furanyl CH2-Ph 1.01

    12t 2-Furanyl-5-CH3 CH2-Ph 1.28

    13t 2-Pyrrolyl CH2-Ph 1.21

    14t 2-Pyrrolyl-5-CH3 CH2-Ph 1.56

    15t 2-Thienyl CH2-Ph 1.65

    16t 3-Thienyl CH2-Ph 1.94

    17t 1-Pyrrole CH2-Ph 1.90

    18a 1-Pyrazole CH2-Ph 1.22

    19t 2-Pyridyl CH2-Ph 1.03

    20t C(S)NH2 CH2-Ph 1.94

    21b NHCH2CH3 CH2-Ph 1.63

    22t N(CH3)2 CH2-Ph 1.66

    23t N(CH3)OH CH2-Ph 1.48

    24t NPhNH2 CH2-Ph 1.63

    25a OH CH2-Ph 1.90

    26t OCH2CH3 CH2-Ph 1.79

    27t CH2OCH3 CH2-Ph 0.92

    28a CH2OCH2CH3 CH2-Ph 1.23

    29t 2-Pyrazinyl CH2-Ph 1.17

    30a 2-Pyrimidyl CH2-Ph 0.91

    31t 2-Oxazole CH2-Ph 1.02

    32b 2-Thiazole CH2-Ph 1.08

    33t N(H)Ph(3-NH2) CH2-Ph 1.99

    34t 1.26


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    Abdulfatai et al., Cogent Chemistry (2016), 2: 1166538http://dx.doi.org/10.1080/23312009.2016.1166538

    optimized by minimizing energy. Calculation of the structural electronic and other descriptors of _substituted acetamido-N-benzylacetamide derivatives was conducted by means of Density func-tional theory (DFT) using the B3LYP version and 6-31G* basis set. The lowest energy structure was used for each molecule to calculate their physicochemical properties (molecular descriptor).

    2.4. Descriptor calculationsMolecular descriptors are mathematical values that describe properties of molecules. The quantum chemical descriptors were calculated using the Spartan14 version 1.1.2 (Wavefunction. Inc, 2013) quantum chemistry package while the 1D,