title: Bond-based linear indices in QSAR: computational discovery of novel anti-trichomonal compounds.
abstract: Trichomonas vaginalis (Tv) is the causative agent of the most common, non-viral, sexually transmitted disease in women and men worldwide. Since 1959, metronidazole (MTZ) has been the drug of choice in the systemic treatment of trichomoniasis. However, resistance to MTZ in some patients and the great cost associated with the development of new trichomonacidals make necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, bond-based linear indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis were used to discover novel trichomonacidal chemicals. The obtained models, using non-stochastic and stochastic indices, are able to classify correctly 89.01% (87.50%) and 82.42% (84.38%) of the chemicals in the training (test) sets, respectively. These results validate the models for their use in the ligand-based virtual screening. In addition, they show large Matthews' correlation coefficients (C) of 0.78 (0.71) and 0.65 (0.65) for the training (test) sets, correspondingly. The result of predictions on the 10% full-out cross-validation test also evidences the robustness of the obtained models. Later, both models are applied to the virtual screening of 12 compounds already proved against Tv. As a result, they correctly classify 10 out of 12 (83.33%) and 9 out of 12 (75.00%) of the chemicals, respectively; which is the most important criterion for validating the models. Besides, these classification functions are applied to a library of seven chemicals in order to find novel antitrichomonal agents. These compounds are synthesized and tested for in vitro activity against Tv. As a result, experimental observations approached to theoretical predictions, since it was obtained a correct classification of 85.71% (6 out of 7) of the chemicals. Moreover, out of the seven compounds that are screened, synthesized and biologically assayed, six compounds (VA7-34, VA7-35, VA7-37, VA7-38, VA7-68, VA7-70) show pronounced cytocidal activity at the concentration of 100 mug/ml at 24 h (48 h) within the range of 98.66%-100% (99.40%-100%), while only two molecules (chemicals VA7-37 and VA7-38) show high cytocidal activity at the concentration of 10 mug/ml at 24 h (48 h): 98.38% (94.23%) and 97.59% (98.10%), correspondingly. The LDA-assisted QSAR models presented here could significantly reduce the number of synthesized and tested compounds and could increase the chance of finding new chemical entities with anti-trichomonal activity.
authors.affiliation: Faculty of Chemistry-Pharmacy, Unit of Computer-Aided Molecular Biosilico Discovery and Bioinformatic Research (CAMD-BIR Unit), Central University of Las Villas, Santa Clara, 54830 Villa Clara, Cuba. ymarrero77@yahoo.es
authors.forename: Yovani
authors.initials: Y
authors.lastname: Marrero-Ponce
authors.forename: Alfredo
authors.initials: A
authors.lastname: Meneses-Marcel
authors.forename: Oscar M
authors.initials: OM
authors.lastname: Rivera-Borroto
authors.forename: Ramón
authors.initials: R
authors.lastname: García-Domenech
authors.forename: Jesus Vicente
authors.initials: JV
authors.lastname: De Julián-Ortiz
authors.forename: Alina
authors.initials: A
authors.lastname: Montero
authors.forename: José Antonio
authors.initials: JA
authors.lastname: Escario
authors.forename: Alicia Gómez
authors.initials: AG
authors.lastname: Barrio
authors.forename: David Montero
authors.initials: DM
authors.lastname: Pereira
authors.forename: Juan José
authors.initials: JJ
authors.lastname: Nogal
authors.forename: Ricardo
authors.initials: R
authors.lastname: Grau
authors.forename: Francisco
authors.initials: F
authors.lastname: Torrens
authors.forename: Christian
authors.initials: C
authors.lastname: Vogel
authors.forename: Vicente J
authors.initials: VJ
authors.lastname: Arán
mesh_terms: D000465:Algorithms; D000818:Animals; D000994:Antitrichomonal Agents / Q000737:chemistry* / Q000494:pharmacology; D049109:Cell Proliferation / Q000187:drug effects; D002470:Cell Survival / Q000187:drug effects; D055598:Chemical Phenomena; D002627:Chemistry, Physical; D019295:Computational Biology / Q000379:methods; D016002:Discriminant Analysis; D015195:Drug Design; D016014:Linear Models; D008795:Metronidazole / Q000494:pharmacology; D015394:Molecular Structure; D021281:Quantitative Structure-Activity Relationship; D011810:Quinoxalines / Q000737:chemistry / Q000494:pharmacology; D012984:Software; D012986:Software Validation; D013269:Stochastic Processes; D014246:Trichomonas vaginalis / Q000187:drug effects
chemical_list: D000994:Antitrichomonal Agents; D011810:Quinoxalines; D008795:Metronidazole