0000000000215088

AUTHOR

Froylán Ibarra-velarde

showing 6 related works from this author

Predicting antitrichomonal activity: A computational screening using atom-based bilinear indices and experimental proofs

2006

Existing Trichomonas vaginalis therapies are out of reach for most trichomoniasis people in developing countries and, where available, they are limited by their toxicity (mainly in pregnant women) and their cost. New antitrichomonal agents are needed to combat emerging metronidazole-resistant trichomoniasis and reduce the side effects associated with currently available drugs. Toward this end, atom-based bilinear indices, a new TOMOCOMD-CARDD molecular descriptor, and linear discriminant analysis (LDA) were used to discover novel, potent, and non-toxic lead trichomonacidal chemicals. Two discriminant functions were obtained with the use of non-stochastic and stochastic atom-type bilinear in…

Quantitative structure–activity relationshipDatabases FactualMolecular modelStereochemistryClinical BiochemistryDrug Evaluation PreclinicalPharmaceutical ScienceAntitrichomonal AgentsLigandsBiochemistryCross-validationChemometricsStructure-Activity Relationshipchemistry.chemical_compoundArtificial IntelligencePredictive Value of TestsMolecular descriptorDrug DiscoveryTrichomonas vaginalisAnimalsCluster AnalysisComputer SimulationMolecular BiologyStochastic ProcessesOrganic ChemistryComputational BiologyReproducibility of ResultsLinear discriminant analysisAntitrichomonal agentchemistryData Interpretation StatisticalTopological indexLinear ModelsMolecular MedicineBiological systemAlgorithmsBioorganic & Medicinal Chemistry
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Antiprotozoan lead discovery by aligning dry and wet screening: Prediction, synthesis, and biological assay of novel quinoxalinones

2014

Protozoan parasites have been one of the most significant public health problems for centuries and several human infections caused by them have massive global impact. Most of the current drugs used to treat these illnesses have been used for decades and have many limitations such as the emergence of drug resistance, severe side-effects, low-to-medium drug efficacy, administration routes, cost, etc. These drugs have been largely neglected as models for drug development because they are majorly used in countries with limited resources and as a consequence with scarce marketing possibilities. Nowadays, there is a pressing need to identify and develop new drug-based antiprotozoan therapies. In …

Quantitative structure–activity relationshipClinical BiochemistryAntiprotozoal AgentsQuantitative Structure-Activity RelationshipPharmaceutical ScienceLinear classifierBioinformaticsMachine learningcomputer.software_genreBiochemistryQuinoxalinesMolecular descriptorDrug DiscoveryBioassayMolecular BiologyVirtual screeningMolecular Structurebusiness.industryChemistryOrganic ChemistryBenchmark databaseDrug developmentCyclizationMolecular MedicineIn silico StudyArtificial intelligenceTOMOCOMD-CARDD SoftwarebusinessClassifier (UML)computer
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New antitrichomonal drug-like chemicals selected by bond (edge)-based TOMOCOMD-CARDD descriptors.

2008

Bond-based quadratic indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis (LDA) were used to discover novel lead trichomonacidals. The obtained LDA-based quantitative structure-activity relationships (QSAR) models, using nonstochastic and stochastic indices, were able to classify correctly 87.91% (87.50%) and 89.01% (84.38%) of the chemicals in training (test) sets, respectively. They showed large Matthews correlation coefficients of 0.75 (0.71) and 0.78 (0.65) for the training (test) sets, correspondingly. Later, both models were applied to the virtual screening of 21 chemicals to find new lead antitrichomonal agents. Predictions agreed with experimental resu…

DrugAdultQuantitative structure–activity relationshipStereochemistrymedia_common.quotation_subjectOvariectomyDrug Evaluation PreclinicalTrichomonas InfectionsAntitrichomonal AgentsBiochemistryAnalytical Chemistrychemistry.chemical_compoundIn vivoMolecular descriptorDrug Resistance BacterialTrichomonas vaginalisAnimalsHumansRats Wistarmedia_commonChromatographyMolecular StructureChemistryDiscriminant AnalysisLinear discriminant analysisRatsAntitrichomonal agentEdge basedMolecular MedicineComputer-Aided DesignFemaleSoftwareBiotechnologyJournal of biomolecular screening
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Dry selection and wet evaluation for the rational discovery of new anthelmintics

2017

Helminths infections remain a major problem in medical and public health. In this report, atom-based 2D bilinear indices, a TOMOCOMD-CARDD (QuBiLs-MAS module) molecular descriptor family and linear discriminant analysis (LDA) were used to find models that differentiate among anthelmintic and non-anthelmintic compounds. Two classification models obtained by using non-stochastic and stochastic 2D bilinear indices, classified correctly 86.64% and 84.66%, respectively, in the training set. Equation 1(2) correctly classified 141(135) out of 165 [85.45%(81.82%)] compounds in external validation set. Another LDA models were performed in order to get the most likely mechanism of action of anthelmin…

0301 basic medicineBiophysicsNon-stochastic and stochastic atom-based bilinear indicesBilinear interpolationLDA-based QSAR modelQuBiLs-MAS module01 natural sciencesSet (abstract data type)03 medical and health sciencesMolecular descriptorStatisticsPhysical and Theoretical ChemistryMolecular BiologySelection (genetic algorithm)MathematicsFree and open source softwareTraining setTOMOCOMD-CARDD softwareExternal validationAnthelmintic activityAtom (order theory)Computational creeningCondensed Matter PhysicsLinear discriminant analysis0104 chemical sciencesIndazole010404 medicinal & biomolecular chemistry030104 developmental biologyLead generationMolecular Physics
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Discovery of novel trichomonacidals using LDA-driven QSAR models and bond-based bilinear indices as molecular descriptors

2008

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 discovery pipeline. Therefore, bond-based bilinear indices, new 2-D bond-based TOMOCOMD-CARDD M…

Sexually transmitted diseaseVirtual screeningQuantitative structure–activity relationshipbusiness.industryDrug discoveryOrganic ChemistryBilinear interpolationComputational biologyMachine learningcomputer.software_genreLinear discriminant analysisWorld healthComputer Science ApplicationsMolecular descriptorDrug DiscoveryArtificial intelligencebusinesscomputerMathematics
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Atom, atom-type and total molecular linear indices as a promising approach for bioorganic and medicinal chemistry: theoretical and experimental asses…

2004

Abstract Helminth infections are a medical problem in the world nowadays. In this paper a novel atom-level chemical descriptor has been applied to estimate the anthelmintic activity. Total and local linear indices and linear discriminant analysis were used to obtain a quantitative model that discriminates between anthelmintic and non-anthelmintic drug-like compounds. The discriminant model has an accuracy of 90.11% in the training set, with a high Matthews’ correlation coefficient (MCC = 0.80). To assess the robustness and predictive power of the obtained model, internal (leave-n-out) and external validation process was performed. The QSAR model correctly classified 88.55% of compounds in t…

AnthelminticsQuantitative structure–activity relationshipVirtual screeningCorrelation coefficientStereochemistryChemistryOrganic ChemistryClinical BiochemistryPharmaceutical ScienceDerivativeLinear discriminant analysisBiochemistrySet (abstract data type)Models ChemicalRobustness (computer science)Atom (measure theory)Drug DesignDrug DiscoveryMolecular MedicineBiological systemMolecular BiologyBioorganicmedicinal chemistry
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