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- W2801622187 abstract "A quantitative structure-activity relationship (QSAR) study was performed to develop a model that relates the structures of 50 compounds to their activities against M. tuberculosis . The compounds were optimized by employing density functional theory (DFT) with B3LYP/6-<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M1><mml:mn mathvariant=normal>31</mml:mn><mml:msup><mml:mrow><mml:mi mathvariant=normal>G</mml:mi></mml:mrow><mml:mrow><mml:mo>⁎</mml:mo></mml:mrow></mml:msup></mml:math>. The Genetic Function Algorithm (GFA) was used to select the descriptors and to generate the correlation model that relates the structural features of the compounds to their biological activities. The optimum model has squared correlation coefficient (<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M2><mml:mrow><mml:msup><mml:mrow><mml:mi>R</mml:mi></mml:mrow><mml:mrow><mml:mn fontstyle=italic>2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math>) of 0.9202, adjusted squared correlation coefficient (<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M3><mml:mrow><mml:msub><mml:mrow><mml:mi>R</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=normal>a</mml:mi><mml:mi mathvariant=normal>d</mml:mi><mml:mi mathvariant=normal>j</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math>) of 0.91012, and leave-one-out (LOO) cross-validation coefficient (<mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M4><mml:mrow><mml:msubsup><mml:mrow><mml:mi>Q</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant=normal>c</mml:mi><mml:mi mathvariant=normal>v</mml:mi></mml:mrow><mml:mrow><mml:mn fontstyle=italic>2</mml:mn></mml:mrow></mml:msubsup></mml:mrow></mml:math>) value of 0.8954. The external validation test used for confirming the predictive power of the built model has <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML id=M5><mml:mrow><mml:msup><mml:mrow><mml:mi>R</mml:mi></mml:mrow><mml:mrow><mml:mn mathvariant=normal>2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math>pred value of 0.8842. These parameters confirm the stability and robustness of the model. Docking analysis showed the best compound with high docking affinity of −14.6 kcal/mol which formed hydrophobic interaction and hydrogen bond with amino acid residues of M. tuberculosis cytochromes (Mtb CYP121). QSAR and molecular docking studies provide valuable approach for pharmaceutical and medicinal chemists to design and synthesize new anti- Mycobacterium tuberculosis compounds." @default.
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- W2801622187 date "2018-01-01" @default.
- W2801622187 modified "2023-10-11" @default.
- W2801622187 title "QSAR Modeling and Molecular Docking Analysis of Some Active Compounds against<i> Mycobacterium tuberculosis</i> Receptor (Mtb CYP121)" @default.
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- W2801622187 doi "https://doi.org/10.1155/2018/1018694" @default.
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