title: Markovian chemicals "in silico" design (MARCH-INSIDE), a promising approach for computer-aided molecular design III: 2.5D indices for the discovery of antibacterials.
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 microg/mL against Pseudomonas aeruginosa ATCC 27853 and Escherichia coli ATCC 27853, respectively while ampicillin, amoxicillin, clindamycin, and metronidazole have, for instance, MIC50 values higher than 250 mug/mL against E. coli. Consequently, the present method may becomes a useful tool for the in silico discovery of antibacterials.
authors.affiliation: Department of Organic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela, 15782, Spain. humbertogd@uclv.edu.cu
authors.forename: Humberto
authors.initials: H
authors.lastname: González-Díaz
authors.forename: Luis A
authors.initials: LA
authors.lastname: Torres-Gómez
authors.forename: Yaima
authors.initials: Y
authors.lastname: Guevara
authors.forename: Manuel S
authors.initials: MS
authors.lastname: Almeida
authors.forename: Reinaldo
authors.initials: R
authors.lastname: Molina
authors.forename: Nilo
authors.initials: N
authors.lastname: Castañedo
authors.forename: Lourdes
authors.initials: L
authors.lastname: Santana
authors.forename: Eugenio
authors.initials: E
authors.lastname: Uriarte
mesh_terms: D000900:Anti-Bacterial Agents / Q000737:chemistry* / Q000494:pharmacology; D017076:Computer-Aided Design; D015195:Drug Design; D004926:Escherichia coli / Q000187:drug effects / Q000254:growth & development; D008390:Markov Chains; D008826:Microbial Sensitivity Tests; D008958:Models, Molecular; D011550:Pseudomonas aeruginosa / Q000187:drug effects / Q000254:growth & development; D021281:Quantitative Structure-Activity Relationship
chemical_list: D000900:Anti-Bacterial Agents
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