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Markovian chemicals “in silico” design (MARCH-INSIDE), a promising approach for computer-aided molecular design III: 2.5D indices for the discovery of antibacterials

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Abstract

The present work continues our series on the use of MARCH-INSIDE molecular descriptors (parts I and II: J Mol Mod 8:237–245, [2002] and 9:395–407, [2003]). These descriptors encode information pertaining to the distribution of electrons in the molecule based on a simple stochastic approach to the idea of electronegativity equalization (Sanderson’s principle). Here, 3D-MARCH-INSIDE molecular descriptors for 667 organic compounds are used as input for a linear discriminant analysis. This 2.5D-QSAR model discriminates between antibacterial compounds and non-antibacterial ones with 92.9% accuracy in training sets. On the other hand, the model classifies 94.0% of the compounds in test set correctly. Additionally, the present QSAR performs similar-to-better than other methods reported elsewhere. Finally, the discovery of a novel compound illustrates the use of the method. This compound, 2-bromo-3-(furan-2-yl)-3-oxo-propionamide has MIC50 of 6.25 and 12.50 μg/mL against Pseudomonas aeruginosa ATCC 27853 and Escherichia coli ATCC 27853, respectively while ampicillim, amoxicillim, clindamycin, and metronidazole have, for instance, MIC50 values higher than 250 μg/mL against E. coli. Consequently, the present method may becomes a useful tool for the in silico discovery of antibacterials.

Figure Colour scaled backprojection analysis of some compounds in training and predicting sets: Nitrofurantoin (left top), Cefuroxime (right top), Nifuroxime (left bottom) and 2-bromo-3-(fur-2-yl)-3-oxo-propionamide (right bottom). Colour code is as follows: Blue: structural framework with high (more than 50 %) contribution to the property, Light blue: group with significant contribution (20-50 %), Grey: group with low (< 10 %) or not contribution to the property.

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Acknowledgements

We thank the Spanish Ministry of Science and Technology (SAF2003-02222), for partial financial support. Molina RR, Castañedo C, and Almeida SM, acknowledge support from the Universität Rostock, Germany. Both unknown referees are acknowledged by their useful comments.

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Authors and Affiliations

  1. Department of Organic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela, 15782, Spain

    Humberto González-Díaz, Lourdes Santana & Eugenio Uriarte

  2. Chemical Bioactives Center, Central University of Las Villas, 54830, Cuba

    Humberto González-Díaz, Luis A. Torres-Gómez, Yaima Guevara, Reinaldo Molina & Nilo Castañedo

  3. Department of Chemistry, University of Granma, Cuba

    Manuel S. Almeida

  4. Universität Rostock, FB Chemie, Albert-Einstein-Str 3a, 18059, Rostock, Germany

    Manuel S. Almeida & Reinaldo Molina

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  1. Humberto González-Díaz
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Correspondence to Humberto González-Díaz.

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González-Díaz, H., Torres-Gómez, L.A., Guevara, Y. et al. Markovian chemicals “in silico” design (MARCH-INSIDE), a promising approach for computer-aided molecular design III: 2.5D indices for the discovery of antibacterials. J Mol Model 11, 116–123 (2005). https://doi.org/10.1007/s00894-004-0228-3

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