Discovery of Novel Trichomonacidals Using LDA-Driven QSAR Models and Bond-Based Bilinear Indices as Molecular Descriptors

Few Years ago, the World Health Organization estimated the number of adults with trichomoniasis at 170 million worldwide, more than the combined numbers for gonorrhea, syphilis, and chlamydia. To combat this sexually transmitted disease, Metronidazole (MTZ) has emerged, since 1959, as a powerful dru...

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Autores: Rivera-Borroto, OM, Marrero-Ponce, Y, Meneses-Marcel, A, Escario, JA, Barrio, AG, Aran, VJ, Alho, MAM, Pereira, DM, Nogal, JJ, Torrens, F, Ibarra-Velarde, F, Montenegro, YV, Huesca-Guillen, A, Rivera, N, Vogel, C
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2009
País:México
Recursos:Universidad Nacional Autónoma de México
Repositorio:Sistema de Información de la Facultad de Ciencias, UNAM
OAI Identifier:oai:repositorio.fciencias.unam.mx:11154/2212
Acesso em linha:http://hdl.handle.net/11154/2212
Access Level:acceso abierto
Palavra-chave:Chemistry, Medicinal
Chemistry, Multidisciplinary
Computer Science, Interdisciplinary Applications
Pharmacology & Pharmacy
Bond-based bilinear indices
LDA-based QSAR model
Lead generation
TOMOCOMD-CARDD software
Trichomonacidal
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oai_identifier_str oai:repositorio.fciencias.unam.mx:11154/2212
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repository_id_str
spelling Discovery of Novel Trichomonacidals Using LDA-Driven QSAR Models and Bond-Based Bilinear Indices as Molecular DescriptorsRivera-Borroto, OMMarrero-Ponce, YMeneses-Marcel, AEscario, JABarrio, AGAran, VJAlho, MAMPereira, DMNogal, JJTorrens, FIbarra-Velarde, FMontenegro, YVHuesca-Guillen, ARivera, NVogel, CChemistry, MedicinalChemistry, MultidisciplinaryComputer Science, Interdisciplinary ApplicationsPharmacology & PharmacyBond-based bilinear indicesLDA-based QSAR modelLead generationTOMOCOMD-CARDD softwareTrichomonacidalFew Years ago, the World Health Organization estimated the number of adults with trichomoniasis at 170 million worldwide, more than the combined numbers for gonorrhea, syphilis, and chlamydia. To combat this sexually transmitted disease, Metronidazole (MTZ) has emerged, since 1959, as a powerful drug for the systematic treatment of infected patients. However, increasing resistance to MTZ, adverse effects associated to high-dose MTZ therapies and very expensive conventional technologies related to the development of new trichomonacidals necessitate novel computational methods that shorten the drug discover), pipeline. Therefore, bond-based bilinear indices, new 2-D bond-based TOMOCOMD-CARDD Molecular Descriptors (MDs), and Linear Discriminant Analysis (LDA) are combined to discover novel antitrichomonal agents. Generated models, using non-stochastic and stochastic indices, are able to classify correctly the 90.11% (93.75%) and the 87.92% (87.50%) of chemicals in the training (test) sets, respectively. In addition, they show large Matthews' correlation coefficients (C) of 0.80 (0.86) and 0.76 (0.71) for the training (test) sets, respectively. The result of predictions on the 10% full-out cross-validation test also evidences the quality of both models. In order to test the models' predictive power, 12 compounds, already proved against Trichomonas vaginalis (Tv), are screened in a simulated virtual screening experiment. As a result, they correctly classified 9 out of 12 (75.00%) and 10 out of 12 (83.33%) of the chemicals, respectively, which were the most important criteria to validate the models. Finally, in order to prove the reach of TOMOCOMD-CARDD approach and to discover new trichomonacidals, these classification functions were applied to a set of eight chemicals which, in turn, were synthesized and tested toward in vitro activity against Tv. As a result, experimental observations confirm theoretical predictions to a great extent, since it is gained a correct classification of 87.50% (7/8) of chemicals. Biological tests also show several candidates as antitrichomonals, since almost all the compounds [VAM2-(3-8)] exhibit pronounced cytocidal activities of 100% at the concentration of 100 mu g/mL and at 24 h (48 h) but VAM2-2: 99.37% (100%), and it is remarkable that these compounds do not show toxic activity in macrophage assays at this concentration. The Quantitative Structure-Activity Relationship (QSAR) models presented here could significantly reduce the number of synthesized and tested compounds as well as could act as virtual shortcuts to new chemical entities with trichomonacidal activity.2011-01-22T10:25:55Z2011-01-22T10:25:55Z2009info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1611-020Xhttp://hdl.handle.net/11154/221265510.1002/qsar.20061016528(1):9-26reponame:Sistema de Información de la Facultad de Ciencias, UNAMinstname:Universidad Nacional Autónoma de Méxicoinstacron:UNAMenQsar & Combinatorial Scienceinfo:eu-repo/semantics/openAccessoai:repositorio.fciencias.unam.mx:11154/22122025-09-17T19:20:52Z
dc.title.none.fl_str_mv Discovery of Novel Trichomonacidals Using LDA-Driven QSAR Models and Bond-Based Bilinear Indices as Molecular Descriptors
title Discovery of Novel Trichomonacidals Using LDA-Driven QSAR Models and Bond-Based Bilinear Indices as Molecular Descriptors
spellingShingle Discovery of Novel Trichomonacidals Using LDA-Driven QSAR Models and Bond-Based Bilinear Indices as Molecular Descriptors
Rivera-Borroto, OM
Chemistry, Medicinal
Chemistry, Multidisciplinary
Computer Science, Interdisciplinary Applications
Pharmacology & Pharmacy
Bond-based bilinear indices
LDA-based QSAR model
Lead generation
TOMOCOMD-CARDD software
Trichomonacidal
title_short Discovery of Novel Trichomonacidals Using LDA-Driven QSAR Models and Bond-Based Bilinear Indices as Molecular Descriptors
title_full Discovery of Novel Trichomonacidals Using LDA-Driven QSAR Models and Bond-Based Bilinear Indices as Molecular Descriptors
title_fullStr Discovery of Novel Trichomonacidals Using LDA-Driven QSAR Models and Bond-Based Bilinear Indices as Molecular Descriptors
title_full_unstemmed Discovery of Novel Trichomonacidals Using LDA-Driven QSAR Models and Bond-Based Bilinear Indices as Molecular Descriptors
title_sort Discovery of Novel Trichomonacidals Using LDA-Driven QSAR Models and Bond-Based Bilinear Indices as Molecular Descriptors
dc.creator.none.fl_str_mv Rivera-Borroto, OM
Marrero-Ponce, Y
Meneses-Marcel, A
Escario, JA
Barrio, AG
Aran, VJ
Alho, MAM
Pereira, DM
Nogal, JJ
Torrens, F
Ibarra-Velarde, F
Montenegro, YV
Huesca-Guillen, A
Rivera, N
Vogel, C
author Rivera-Borroto, OM
author_facet Rivera-Borroto, OM
Marrero-Ponce, Y
Meneses-Marcel, A
Escario, JA
Barrio, AG
Aran, VJ
Alho, MAM
Pereira, DM
Nogal, JJ
Torrens, F
Ibarra-Velarde, F
Montenegro, YV
Huesca-Guillen, A
Rivera, N
Vogel, C
author_role author
author2 Marrero-Ponce, Y
Meneses-Marcel, A
Escario, JA
Barrio, AG
Aran, VJ
Alho, MAM
Pereira, DM
Nogal, JJ
Torrens, F
Ibarra-Velarde, F
Montenegro, YV
Huesca-Guillen, A
Rivera, N
Vogel, C
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Chemistry, Medicinal
Chemistry, Multidisciplinary
Computer Science, Interdisciplinary Applications
Pharmacology & Pharmacy
Bond-based bilinear indices
LDA-based QSAR model
Lead generation
TOMOCOMD-CARDD software
Trichomonacidal
topic Chemistry, Medicinal
Chemistry, Multidisciplinary
Computer Science, Interdisciplinary Applications
Pharmacology & Pharmacy
Bond-based bilinear indices
LDA-based QSAR model
Lead generation
TOMOCOMD-CARDD software
Trichomonacidal
description Few Years ago, the World Health Organization estimated the number of adults with trichomoniasis at 170 million worldwide, more than the combined numbers for gonorrhea, syphilis, and chlamydia. To combat this sexually transmitted disease, Metronidazole (MTZ) has emerged, since 1959, as a powerful drug for the systematic treatment of infected patients. However, increasing resistance to MTZ, adverse effects associated to high-dose MTZ therapies and very expensive conventional technologies related to the development of new trichomonacidals necessitate novel computational methods that shorten the drug discover), pipeline. Therefore, bond-based bilinear indices, new 2-D bond-based TOMOCOMD-CARDD Molecular Descriptors (MDs), and Linear Discriminant Analysis (LDA) are combined to discover novel antitrichomonal agents. Generated models, using non-stochastic and stochastic indices, are able to classify correctly the 90.11% (93.75%) and the 87.92% (87.50%) of chemicals in the training (test) sets, respectively. In addition, they show large Matthews' correlation coefficients (C) of 0.80 (0.86) and 0.76 (0.71) for the training (test) sets, respectively. The result of predictions on the 10% full-out cross-validation test also evidences the quality of both models. In order to test the models' predictive power, 12 compounds, already proved against Trichomonas vaginalis (Tv), are screened in a simulated virtual screening experiment. As a result, they correctly classified 9 out of 12 (75.00%) and 10 out of 12 (83.33%) of the chemicals, respectively, which were the most important criteria to validate the models. Finally, in order to prove the reach of TOMOCOMD-CARDD approach and to discover new trichomonacidals, these classification functions were applied to a set of eight chemicals which, in turn, were synthesized and tested toward in vitro activity against Tv. As a result, experimental observations confirm theoretical predictions to a great extent, since it is gained a correct classification of 87.50% (7/8) of chemicals. Biological tests also show several candidates as antitrichomonals, since almost all the compounds [VAM2-(3-8)] exhibit pronounced cytocidal activities of 100% at the concentration of 100 mu g/mL and at 24 h (48 h) but VAM2-2: 99.37% (100%), and it is remarkable that these compounds do not show toxic activity in macrophage assays at this concentration. The Quantitative Structure-Activity Relationship (QSAR) models presented here could significantly reduce the number of synthesized and tested compounds as well as could act as virtual shortcuts to new chemical entities with trichomonacidal activity.
publishDate 2009
dc.date.none.fl_str_mv 2009
2011-01-22T10:25:55Z
2011-01-22T10:25:55Z
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv 1611-020X
http://hdl.handle.net/11154/2212
655
10.1002/qsar.200610165
identifier_str_mv 1611-020X
655
10.1002/qsar.200610165
url http://hdl.handle.net/11154/2212
dc.language.none.fl_str_mv en
language_invalid_str_mv en
dc.relation.none.fl_str_mv Qsar & Combinatorial Science
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv 28(1):9-26
reponame:Sistema de Información de la Facultad de Ciencias, UNAM
instname:Universidad Nacional Autónoma de México
instacron:UNAM
instname_str Universidad Nacional Autónoma de México
instacron_str UNAM
institution UNAM
reponame_str Sistema de Información de la Facultad de Ciencias, UNAM
collection Sistema de Información de la Facultad de Ciencias, UNAM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812429

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