Search results for "QSAR"

showing 10 items of 48 documents

Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics

2021

To date, computational approaches have been recognized as a key component in drug design and discovery workflows. Developed to help researchers save time and reduce costs, several computational tools have been developed and implemented in the last twenty years. At present, they are routinely used to identify a therapeutic target, understand ligand–protein and protein–protein interactions, and identify orthosteric and allosteric binding sites, but their primary use remains the identification of hits through ligand-based and structure-based virtual screening and the optimization of lead compounds, followed by the estimation of the binding free energy. The repurposing of an old drug for the tr…

Computational approacheModels Molecularhealth care facilities manpower and servicesChemistry Pharmaceuticaldrug discovery drug design bioinformatics Docking Molecular Dynamics pharmacophore modeling QSAR drug-repurposing SARS-CoV2educationOrganic ChemistryPharmaceutical ScienceComputational BiologyAnalytical Chemistryn/aQD241-441EditorialChemistry (miscellaneous)health services administrationDrug DiscoveryMolecular MedicineHumansThermodynamicsPhysical and Theoretical Chemistryhealth care economics and organizationsMolecules
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A QSAR study investigating the potential anti-HIV-1 effect of some acyclovir and ganciclovir analogs

2009

A QSAR study, involving the use of calculated physical-chemical properties (TSAR TM ), and the use of a neural network approach (TSAR TM ), has been performed on the potential anti-HIV-1 activity of a series of Acyclovir and Ganciclovir analogs. Model obtained allows reliable predictions for the anti-HIV-1 activity of these derivatives, and showed that the presence of the Ganciclovir chain in triazolopyrrolopyrimidine and pyrimidopyrrolopyrimidine series seems to increase the antiviral effect.

GanciclovirAnti hiv 1Quantitative structure–activity relationshipStereochemistryChemistryOrganic ChemistrymedicineQSAR neural network BMLR anti-HIV-1 activityvirus diseasesPharmacologySettore CHIM/08 - Chimica Farmaceuticamedicine.drug
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Flavor Release from i-Carrageenan Matrix: A Quantitative Structure-Property Relationships Approach

2006

International audience; We carried out a QSPR (quantitative structure-property relationships) approach to evaluate the influence of the chemical structure of aqueous matrixes over the partition coefficient between the gas phase and the matrix. The determination of the partition coefficient of flavor ingredients was performed by headspace analysis at equilibrium for both saline solution and -carrageenan gel. Starting from an initial list of 90 descriptors, we selected 10 descriptors to perform equation generation by the GFA (genetic function approximation) method available in the Cerius2 package. The best obtained equations involve only five descriptors, which encode electronic properties of…

HEADSPACE ANALYSISQSARQSPRi-CARRAGEENANAROMA RELEASE[SDV.IDA]Life Sciences [q-bio]/Food engineering[SDV.IDA] Life Sciences [q-bio]/Food engineeringPARTITION COEFFICIENTGENETIC FUNCTION APPROXIMATIONINTERACTION
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Ligand binding study revealing a human olfactory receptor involved in waxy-floral odor perception

2006

International audience

HUMAN OLFACTORY PERCEPTION[CHIM.OTHE] Chemical Sciences/OtherOLFACTORY CODINGODORANT RECEPTION[CHIM.OTHE]Chemical Sciences/OtherCALCIUM IMAGINGComputingMilieux_MISCELLANEOUS3D-QSAR
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Exemples de QSAR sur des coefficients de partage

2005

National audience

IOTA-CARAGEENAN[SPI.GPROC] Engineering Sciences [physics]/Chemical and Process EngineeringQSARQSPRAROMA RELEASE[SDV.IDA]Life Sciences [q-bio]/Food engineering[SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering[SDV.IDA] Life Sciences [q-bio]/Food engineeringPARTITION COEFFICIENTINTERACTIONHEADSCAPE ANALYSISGELSComputingMilieux_MISCELLANEOUS
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Internal Test Sets Studies in a Group of Antimalarials

2006

Topological indices have been applied to build QSAR models for a set of 20 an- timalarial cyclic peroxy cetals. In order to evalua te the reliability of the proposed linear models leave-n-out and Internal Test Sets (ITS) approaches have b een considered. The pro- posed procedure resulted in a robust and consensued prediction equation and here it is shown why it is superior to the employed standard c ross-validation algorithms involving multilinear regression models.

Internal test sets method; topological indices; linear models; QSAR; statistical validation.Quantitative structure–activity relationshipMultilinear mapInternal test sets methodLinear models (Statistics)CatalysisInorganic ChemistrySet (abstract data type)lcsh:ChemistryQSAR (Bioquímica)Order (group theory)Applied mathematicsPhysical and Theoretical ChemistryMolecular Biologylcsh:QH301-705.5SpectroscopyReliability (statistics)Mathematicsstatistical validation.Group (mathematics)QSAROrganic ChemistryLinear modelRegression analysisGeneral MedicineComputer Science Applicationslcsh:Biology (General)lcsh:QD1-999Models lineals (Estadística)topological indiceslinear modelsInternational Journal of Molecular Sciences
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Chemometric and chemoinformatic analyses of anabolic and androgenic activities of testosterone and dihydrotestosterone analogues

2008

Predictive quantitative structure-activity relationship (QSAR) models of anabolic and androgenic activities for the testosterone and dihydrotestosterone steroid analogues were obtained by means of multiple linear regression using quantum and physicochemical molecular descriptors (MD) as well as a genetic algorithm for the selection of the best subset of variables. Quantitative models found for describing the anabolic (androgenic) activity are significant from a statistical point of view: R2 of 0.84 (0.72 and 0.70). A leave-one-out cross-validation procedure revealed that the regression models had a fairly good predictability [q2 of 0.80 (0.60 and 0.59)]. In addition, other QSAR models were …

MaleQuantitative structure–activity relationshipAnabolismStereochemistrymedicine.medical_treatmentClinical BiochemistryAnabolic and androgenic activitiesQSAR modelQuantitative Structure-Activity RelationshipPharmaceutical ScienceBiochemistrySteroidAnabolic AgentsMolecular descriptorDrug DiscoveryLinear regressionmedicineCluster AnalysisHumansComputer SimulationTestosteroneMolecular BiologyChemistryOrganic ChemistryDihydrotestosteroneModels ChemicalGenetic algorithmDihydrotestosteroneAndrogensQuantum and physicochemical molecular descriptorMolecular MedicineTestosterone and dihydrotestosterone steroid analoguesAlgorithmsAnabolic steroidApplicability domainmedicine.drugBioorganic and Medicinal Chemistry 16: 6448-6459 (2008)
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Alzheimer: A Decade of Drug Design. Why Molecular Topology can be an Extra Edge?

2017

Background The last decade was characterized by a growing awareness about the severity of dementia in the field of age-related and no age-related diseases and about the importance to invest resources in the research of new, effective treatments. Among the dementias, Alzheimer's plays a substantial role because of its extremely high incidence and fatality. Several pharmacological strategies have been tried but still now, Alzheimer keeps being an untreatable disease. In literature, the number of QSAR related drug design attempts about new treatments for Alzheimer is huge, but only few results can be considered noteworthy. Providing a detailed analysis of the actual situation and reporting the…

Models Molecular0301 basic medicineDrugQuantitative structure–activity relationshiptopologyComputer sciencemedia_common.quotation_subjectdesignQuantitative Structure-Activity RelationshipHistory 21st CenturyArticle03 medical and health sciencesAlzheimer DiseasemedicineHumansDementiaPharmacology (medical)molecularTopology (chemistry)media_commonPharmacologyQSARdrugGeneral Medicinemedicine.diseaseDatabases BibliographicPsychiatry and Mental healthIdentification (information)030104 developmental biologyNeurologyRisk analysis (engineering)Drug DesignAlzheimerNeurology (clinical)Enhanced Data Rates for GSM EvolutionHigh incidenceMolecular topologyAntipsychotic AgentsCurrent Neuropharmacology
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DNA minor groove binders: an overview on molecular modeling and QSAR approaches

2007

Molecular recognition of DNA by small molecules and proteins is a fundamental problem in structural biology and drug design. Understanding of recognition in both sequence-selective and sequence neutral ways at the level of successful prediction of binding modes and site selectivity will be instrumental for improvements in the design and synthesis of new molecules as potent and selective gene-regulatory drugs. Minor groove is the target of a large number of non-covalent binding agents. DNA binding with specific sequences, mostly AT, takes place by means of a combination of directed hydrogen bonding to base pair edges, van der Waals interactions with the minor groove walls and generalized ele…

Models MolecularPharmacologyDNA minor groove binders (mGBs) in silico techniques molecular modeling ab initio methods docking molecular dynamics simulations (MDS) QSAR QSPR.Molecular modelBase pairStereochemistryChemistryIn silicoOrganic ChemistryQuantitative Structure-Activity RelationshipDNAComputational biologyBiochemistrySmall moleculechemistry.chemical_compoundMolecular recognitionPharmaceutical PreparationsStructural biologyDocking (molecular)Drug DesignDrug DiscoveryNucleic Acid ConformationMolecular MedicineDNA
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Receptor-guided 3D-QSAR approach for the discovery of c-kit tyrosine kinase inhibitors

2012

Studies of the the three-dimensional quantitative structure–activity relationships for ninety-five c-kit tyrosine kinase inhibitors were performed. Based on a co-crystallized compound (1 T46), known inhibitors were aligned with c-kit by induced-fit docking, and multiple training/test set splitting was performed to validate the selected pharmacophore model. The best pharmacophore model consisted of five features: one hydrogen-bond donor and four aromatic rings. Reliable statistics were obtained (R 2 = 0.95, R pred 2  = 0.75), and the model was validated by using it to select c-kit inhibitors from a database; 82.1% of the hits it retrieved were active. Accordingly, our model can be reliably u…

Models MolecularQuantitative structure–activity relationshipChemistryStereochemistryOrganic ChemistryQuantitative Structure-Activity RelationshipC-kit . 3D-QSAR . Kohonen maps . Induced-fit dockingSettore CHIM/08 - Chimica FarmaceuticaCatalysisComputer Science ApplicationsInorganic ChemistryProto-Oncogene Proteins c-kitComputational Theory and MathematicsDocking (molecular)Drug DiscoveryPhysical and Theoretical ChemistryPharmacophoreReceptorTyrosine kinaseProtein Kinase Inhibitors
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