Search results for "Simulation."

showing 10 items of 4779 documents

A topological substructural approach for the prediction of P-glycoprotein substrates

2006

A topological substructural molecular design approach (TOPS-MODE) has been used to predict whether a given compound is a P-glycoprotein (P-gp) substrate or not. A linear discriminant model was developed to classify a data set of 163 compounds as substrates or nonsubstrates (91 substrates and 72 nonsubstrates). The final model fit the data with sensitivity of 82.42% and specificity of 79.17%, for a final accuracy of 80.98%. The model was validated through the use of an external validation set (40 compounds, 22 substrates and 18 nonsubstrates) with a 77.50% of prediction accuracy; fivefold full cross-validation (removing 40 compounds in each cycle, 80.50% of good prediction) and the predictio…

Quantitative structure–activity relationshipMolecular modelLinear modelQuantitative Structure-Activity RelationshipPharmaceutical ScienceLinear discriminant analysisTopologyModels BiologicalData setSet (abstract data type)Pharmaceutical PreparationsPredictive Value of TestsTest setLinear ModelsComputer SimulationATP Binding Cassette Transporter Subfamily B Member 1Sensitivity (control systems)FluoroquinolonesMathematicsJournal of Pharmaceutical Sciences
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New tyrosinase inhibitors selected by atomic linear indices-based classification models.

2005

In the present report, the use of the atom-based linear indices for finding functions that discriminate between the tyrosinase inhibitor compounds and inactive ones is presented. In this sense, discriminant models were applied and globally good classifications of 93.51% and 92.46% were observed for non-stochastic and stochastic linear indices best models, respectively, in the training set. The external prediction sets had accuracies of 91.67% and 89.44%. In addition, these fitted models were used in the screening of new cycloartane compounds isolated from herbal plants. A good behavior is shown between the theoretical and experimental results. These results provide a tool that can be used i…

Quantitative structure–activity relationshipMolecular modelStereochemistryTyrosinaseClinical BiochemistryMolecular ConformationPharmaceutical ScienceQuantitative Structure-Activity RelationshipBiochemistrySensitivity and SpecificityChemometricsDrug DiscoveryComputer SimulationEnzyme InhibitorsMolecular BiologyTraining setChemistryMonophenol MonooxygenaseOrganic ChemistryLinear discriminant analysisTriterpenesDiscriminantModels ChemicalTopological indexMolecular MedicineBiological systemBioorganicmedicinal chemistry letters
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Prospective computational design and in vitro bio-analytical tests of new chemical entities as potential selective CYP17A1 lyase inhibitors

2019

[EN] The development and advancement of prostate cancer (PCa) into stage 4, where it metastasize, is a major problem mostly in elder males. The growth of PCa cells is stirred up by androgens and androgen receptor (AR). Therefore, therapeutic strategies such as blocking androgens synthesis and inhibiting AR binding have been explored in recent years. However, recently approved drugs (or in clinical phase) failed in improving the expected survival rates for this metastatic-castration resistant prostate cancer (mCRPC) patients. The selective CYP17A1 inhibition of 17,20-lyase route has emerged as a novel strategy. Such inhibition blocks the production of androgens everywhere they are found in t…

Quantitative structure–activity relationshipStereochemistry01 natural sciencesBiochemistryStructure-Activity Relationship3D-QSAR pharmacophore modelDrug DiscoveryCytochrome P-450 Enzyme InhibitorsHumansStructure–activity relationshipCYP17A1 InhibitorMolecular BiologyDensity Functional TheoryVirtual screeningDose-Response Relationship DrugMolecular Structure010405 organic chemistryChemistryOrganic ChemistryProspective computational designSteroid 17-alpha-Hydroxylasecomputer.file_format1720-lyase selective inhibitionProtein Data BankLyase0104 chemical sciencesMolecular Docking Simulation010404 medicinal & biomolecular chemistryDocking (molecular)CYP17A1 inhibitorsMetastatic-castration resistant prostate cancerPharmacophorecomputer
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Vanilloid Derivatives as Tyrosinase Inhibitors Driven by Virtual Screening-Based QSAR Models

2010

A number of vanilloids have been tested as tyrosinase inhibitors using Ligand-Based Virtual Screening (LBVS) driven by QSAR (Quantitative Structure-Activity Relationship) models as the multi-agent classification system. A total of 81 models were used to screen this family. Then, a preliminary cluster analysis of the selected chemicals was carried out based on their bioactivity to detect possible similar substructural features among these compounds and the active database used in the QSAR model construction. The compounds identified were tested in vitro to corroborate the results obtained in silico. Among them, two chemicals, isovanillin (K(M) (app) = 1.08 mM) near to kojic acid (reference d…

Quantitative structure–activity relationshipStereochemistryTyrosinaseIn silicoQuantitative Structure-Activity RelationshipPharmaceutical ScienceIsovanillinModels BiologicalSkin DiseasesVanilloidsAnalytical Chemistrychemistry.chemical_compoundCluster AnalysisHumansEnvironmental ChemistryComputer SimulationEnzyme InhibitorsSpectroscopyVirtual screeningMonophenol MonooxygenaseReference drugCombinatorial chemistrychemistryBenzaldehydesDrug DesignKojic acidAlgorithmsDrug Testing and Analysis
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Atom, atom-type, and total nonstochastic and stochastic quadratic fingerprints: a promising approach for modeling of antibacterial activity.

2005

The TOpological MOlecular COMputer Design (TOMOCOMD-CARDD) approach has been introduced for the classification and design of antimicrobial agents using computer-aided molecular design. For this propose, atom, atom-type, and total quadratic indices have been generalized to codify chemical structure information. In this sense, stochastic quadratic indices have been introduced for the description of the molecular structure. These stochastic fingerprints are based on a simple model for the intramolecular movement of all valence-bond electrons. In this work, a complete data set containing 1006 antimicrobial agents is collected and presented. Two structure-based antibacterial activity classificat…

Quantitative structure–activity relationshipStochastic ProcessesMolecular modelDatabases FactualChemistryOrganic ChemistryClinical BiochemistryMolecular ConformationPharmaceutical ScienceAtom (order theory)Quantitative Structure-Activity RelationshipModels TheoreticalLinear discriminant analysisBiochemistryAnti-Bacterial AgentsSet (abstract data type)Quadratic equationSimple (abstract algebra)Drug DiscoveryMolecular MedicineComputer SimulationBiological systemMolecular BiologyAntibacterial agentBioorganicmedicinal chemistry
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Harmonization of QSAR Best Practices and Molecular Docking Provides an Efficient Virtual Screening Tool for Discovering New G-Quadruplex Ligands

2015

Telomeres and telomerase are key players in tumorogenesis. Among the various strategies proposed for telomerase inhibition or telomere uncapping, the stabilization of telomeric G-quadruplex (G4) structures is a very promising one. Additionally, G4 stabilizing ligands also act over tumors mediated by the alternative elongation of telomeres. Accordingly, the discovery of novel compounds able to act on telomeres and/or inhibit the telomerase enzyme by stabilizing DNA telomeric G4 structures as well as the development of approaches efficiently prioritizing such compounds constitute active areas of research in computational medicinal chemistry and anticancer drug discovery. In this direction, we…

Quantitative structure–activity relationshipTelomeraseGeneral Chemical EngineeringDrug Evaluation PreclinicalQuantitative Structure-Activity RelationshipComputational biologyLibrary and Information SciencesBiologyG-quadruplexCrystallography X-RayLigandsMolecular Docking Simulationchemistry.chemical_compoundDrug DiscoveryHumansCell ProliferationGeneticsVirtual screeningMolecular StructureDrug discoveryQSARGeneral ChemistryFibroblastsTelomereComputer Science ApplicationsTelomereG-QuadruplexesMolecular Docking SimulationchemistryAcridinesDNAHeLa Cells
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Virtual darwinian drug design: QSAR inverse problem, virtual combinatorial chemistry, and computational screening.

2001

The generation of diversity and its further selection by an external system is a common mechanism for the evolution of the living species and for the current drug design methods. This assumption allows us to label the methods based on generation and selection of molecular diversity as "Darwinian" ones, and to distinguish them from the structure-based, structure-modulation approaches. An example of a Darwinian method is the inverse QSAR. It consists of the computational generation of candidate chemical structures and their selection according to a previously established QSAR model. New trends in the field of combinatorial chemical syntheses comprise the concepts of virtual combinatorial synt…

Quantitative structure–activity relationshipVirtual screeningCombinatorial Chemistry TechniquesChemistryOrganic ChemistryQuantitative Structure-Activity RelationshipGeneral MedicineInverse problemCombinatorial chemistryBiological EvolutionField (computer science)Computer Science ApplicationsDrug DesignDrug DiscoveryGraph (abstract data type)Combinatorial Chemistry TechniquesComputer SimulationDesign methodsSelection (genetic algorithm)Combinatorial chemistryhigh throughput screening
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The Tensor Networks Anthology: Simulation techniques for many-body quantum lattice systems

2019

We present a compendium of numerical simulation techniques, based on tensor network methods, aiming to address problems of many-body quantum mechanics on a classical computer. The core setting of this anthology are lattice problems in low spatial dimension at finite size, a physical scenario where tensor network methods, both Density Matrix Renormalization Group and beyond, have long proven to be winning strategies. Here we explore in detail the numerical frameworks and methods employed to deal with low-dimension physical setups, from a computational physics perspective. We focus on symmetries and closed-system simulations in arbitrary boundary conditions, while discussing the numerical dat…

Quantum PhysicsComputer simulationComputer scienceLattice problemDensity matrix renormalization groupPhysicsQC1-999FOS: Physical sciencesData structure01 natural sciences010305 fluids & plasmasAlgebra0103 physical sciencesLinear algebraBoundary value problemQuantum Physics (quant-ph)010306 general physicsProgrammerQuantum
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Searching for exceptional points and inspecting non-contractivity of trace distance in (anti-) PT -symmetric systems

2022

Non-Hermitian systems with parity-time ($\mathcal{PT}$) symmetry and anti-$\mathcal{PT}$ symmetry give rise to exceptional points (EPs) with intriguing properties related to, e.g., chiral transport and enhanced sensitivity, due to the coalescence of eigenvectors. In this paper, we propose a powerful and easily computable tool, based on the Hilbert-Schmidt speed (HSS), which does not require the diagonalization of the evolved density matrix, to detect exactly the EPs and hence the critical behavior of the (anti-)$\mathcal{PT}\!-$symmetric systems, especially high-dimensional ones. Our theoretical predictions, made without the need for modification of the Hilbert space, which is performed by …

Quantum PhysicsHilbert–Schmidt speedModeling and SimulationNon-Hermitian systemsSignal ProcessingFOS: Physical sciencesStatistical and Nonlinear PhysicsElectrical and Electronic EngineeringQuantum Fisher informationQuantum Physics (quant-ph)Settore FIS/03 - Fisica Della MateriaTheoretical Computer ScienceElectronic Optical and Magnetic Materials
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Diagrammatic approach to quantum search

2014

We introduce a simple diagrammatic approach for estimating how a randomly walking quantum particle searches on a graph in continuous-time, which involves sketching small weighted graphs with self-loops and considering degenerate perturbation theory's effects on them. Using this method, we give the first example of degenerate perturbation theory solving search on a graph whose evolution occurs in a subspace whose dimension grows with $N$.

Quantum PhysicsQuantum particleDegenerate energy levelsFOS: Physical sciencesStatistical and Nonlinear PhysicsQuantum searchGraphTheoretical Computer ScienceElectronic Optical and Magnetic MaterialsDiagrammatic reasoningModeling and SimulationSignal ProcessingStatistical physicsElectrical and Electronic EngineeringQuantum Physics (quant-ph)Subspace topologyMathematicsQuantum Information Processing
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