Search results for "In silico"

showing 10 items of 209 documents

On Cancer Cell Cycle and Universal Apoptosis Parameters Signaling Unravelled In Silico

2010

Here, cell cycle in higher eukaryotes and their molecular networks signals both in G1/S and G2/M transitions are in silico replicated. Systems control theory is employed to design multi-nestled digital layers to simulate protein-to- protein activation and inhibition in the cancer cell cycle dynamics in presence of damaged genome. Sequencing and controlling the digital process of four micro-scale species networks (p53/Mdm2/DNA damage; p21mRNA/cyclin-CDK complex; CDK/CDC25/wee1/SKP2/APC/CKI and apoptosis target genes system) paved the way for unravelling the participants and their by-products having the task to execute (or not) cell death. The results of the proposed cell digital multi-layers…

Programmed cell deathWee1Cell signalingCell cycle checkpointbiologyCdc25Cyclin-dependent kinaseIn silicobiology.proteinCell cycleCell biologyThe Open Conference Proceedings Journal
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Methodological approaches for the analysis of transmembrane domain interactions: A systematic review

2021

The study of protein-protein interactions (PPI) has proven fundamental for the understanding of the most relevant cell processes. Any protein domain can participate in PPI, including transmembrane (TM) segments that can establish interactions with other TM domains (TMDs). However, the hydrophobic nature of TMDs and the environment they occupy complicates the study of intramembrane PPI, which demands the use of specific approaches and techniques. In this review, we will explore some of the strategies available to study intramembrane PPI in vitro, in vivo, and, in silico, focusing on those techniques that could be carried out in a standard molecular biology laboratory regarding its previous e…

Protein FoldingBacteriaChemistryIn silicoProtein domainBiophysicsMembrane ProteinsCell CommunicationCell BiologyComputational biologyBiochemistryTransmembrane proteinIn vitroProtein–protein interactionTransmembrane domainProtein DomainsMembrane proteinProtein foldingProtein Interaction MapsHydrophobic and Hydrophilic InteractionsBiochimica et Biophysica Acta (BBA) - Biomembranes
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Identification of new claudin family members by a novel PSI-BLAST based approach with enhanced specificity.

2006

In an attempt to develop a novel strategy for the identification of new members of protein families by in silico approaches, we have developed a semi-automated procedure of consecutive PSI-BLAST (Position-Specific-Iterated Basic Local Alignment Search Tool) searches incorporating identificiation as well as subsequent validation of putative candidates. For a proof of concept study we chose the search for novel members of the claudin family. The initial step was an iterated PSI-BLAST search starting with the PMP22_Claudin domain of each known member of the claudin family against the human part of the RefSeq Database. Putative new claudin domains derived from the converged list were evaluated …

Protein familyIn silicoMolecular Sequence DataSequence alignmentBiologycomputer.software_genreBiochemistrySet (abstract data type)Protein structureStructural BiologySequence Analysis ProteinRefSeqFalse positive paradoxHumansAmino Acid SequenceClaudinDatabases ProteinMolecular BiologyPhylogenyReverse Transcriptase Polymerase Chain ReactionComputational BiologyMembrane ProteinsProtein Structure TertiaryData miningcomputerSequence AlignmentProteins
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LASS6, an additional member of the longevity assurance gene family

2005

Longevity assurance genes (LAGs) represent a subgroup of the homeobox gene family. Five mammalian homologs have been reported, and the corresponding proteins have previously been investigated with respect to their key role in ceramide synthesis. However, members of the LAG family have been shown to be involved in cell growth regulation and cancer differentiation. In an effort to characterize additional members of the LAG family, we have screened the latest releases of genomic databases and report on the bioinformatic characterization of yet another member, LAG1 longevity assurance homolog 6 (LASS6). Like other LAG family members, the LASS6 protein contained a homeodomain and LAG1 domain. In…

Protein familyProtein ConformationIn silicoLongevityMolecular Sequence DataBiologyHomology (biology)MiceDatabases GeneticSphingosine N-AcyltransferaseGeneticsAnimalsHumansGene familyAmino Acid SequenceGeneZebrafishPhylogenyZebrafishHomeodomain ProteinsGeneticsBase SequenceGenome HumanMicroarray analysis techniquesGenes HomeoboxMembrane ProteinsGeneral Medicinebiology.organism_classificationRatsChromosomes Human Pair 2HomeoboxInternational Journal of Molecular Medicine
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Protein S-nitrosylation: What's going on in plants?

2012

International audience; Nitric oxide (NO) is now recognized as a key regulator of plant physiological processes. Understanding the mechanisms by which NO exerts its biological functions has been the subject of extensive research. Several components of the signaling pathways relaying NO effects in plants, including second messengers, protein kinases, phytohormones, and target genes, have been characterized. In addition, there is now compelling experimental evidence that NO partly operates through posttranslational modification of proteins, notably via S-nitrosylation and tyrosine nitration. Recently, proteome-wide scale analyses led to the identification of numerous protein candidates for S-…

ProteomeKinaseIn silicoRegulatorPlant ImmunityNitric oxideComputational biologyS-NitrosylationPlantBiologyPlantsPosttranslational protein modificationBiochemistryS-NitrosylationPlant immunityBiochemistry[ SDV.SA.AGRO ] Life Sciences [q-bio]/Agricultural sciences/AgronomyPhysiology (medical)Second messenger system[SDV.BV]Life Sciences [q-bio]/Vegetal BiologySignal transductionGeneProtein Processing Post-TranslationalPlant Proteins
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Bioassays to monitor taspase1 function for the identification of pharmacogenetic inhibitors

2011

Background Threonine Aspartase 1 (Taspase1) mediates cleavage of the mixed lineage leukemia (MLL) protein and leukemia provoking MLL-fusions. In contrast to other proteases, the understanding of Taspase1's (patho)biological relevance and function is limited, since neither small molecule inhibitors nor cell based functional assays for Taspase1 are currently available. Methodology/Findings Efficient cell-based assays to probe Taspase1 function in vivo are presented here. These are composed of glutathione S-transferase, autofluorescent protein variants, Taspase1 cleavage sites and rational combinations of nuclear import and export signals. The biosensors localize predominantly to the cytoplasm…

ProteomicsCytoplasmHydrolasesmedicine.medical_treatmentThreonine Aspartase 1Drug Evaluation Preclinicallcsh:MedicineBiosensing TechniquesBiochemistryMiceMolecular Cell BiologyBasic Cancer Researchlcsh:ScienceMultidisciplinaryEnzyme ClassesProteomic Databases3T3 CellsSmall moleculeCellular StructuresEnzymesBiochemistryOncologyMedicineBiological AssayBiologieResearch ArticleProteasesCell SurvivalIn silicoBiologyCleavage (embryo)In vivoGenetic Mutationddc:570EndopeptidasesChemical BiologyConsensus sequencemedicineGeneticsAnimalsHumansProtease InhibitorsBiologyCell NucleusProteaselcsh:RProteinsPharmacogeneticsSmall MoleculesMutagenesislcsh:Q
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Using Deep Learning to Extrapolate Protein Expression Measurements

2020

Mass spectrometry (MS)-based quantitative proteomics experiments typically assay a subset of up to 60% of the ≈20 000 human protein coding genes. Computational methods for imputing the missing values using RNA expression data usually allow only for imputations of proteins measured in at least some of the samples. In silico methods for comprehensively estimating abundances across all proteins are still missing. Here, a novel method is proposed using deep learning to extrapolate the observed protein expression values in label-free MS experiments to all proteins, leveraging gene functional annotations and RNA measurements as key predictive attributes. This method is tested on four datasets, in…

ProteomicsIn silicoQuantitative proteomicsComputational biologyBiologyBiochemistryprotein abundance predictionMass SpectrometryProtein expressionMice03 medical and health sciencesDeep LearningAbundance (ecology)AnimalsMolecular BiologyGeneResearch Articles030304 developmental biologydeep learning networks0303 health sciencesUniProt keywordsbusiness.industryDeep learning030302 biochemistry & molecular biologyProteinsRNAMolecular Sequence AnnotationMissing dataGene OntologyArtificial intelligencebusinessResearch ArticlePROTEOMICS
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Polarity study of ionic liquids with the solvatochromic dye Nile Red: a QSPR approach using in silico VolSurf+ descriptors

2016

The in silico VolSurfþ descriptors, accounting for both cationic and anionic structural features of ionic liquids (ILs) were used to develop a Partial Least Squares (PLS) model able to establish a Quantitative Structure Property Relationship (QSPR) correlation with their solvatochromic dye Nile Red polarity. The PLS model allowed prediction of ENR values for 116 ILs providing an in silico ILs polarity database.

Quantitative structure–activity relationship010405 organic chemistryPolarity (physics)In silicoOrganic ChemistrySolvatochromismNile redIonic Liquids Polarity Nile Red QSPRSettore CHIM/06 - Chimica Organica010402 general chemistry01 natural sciencesBiochemistry0104 chemical sciencesQuantitative Structure Property Relationshipchemistry.chemical_compoundchemistryComputational chemistryDrug DiscoveryIonic liquidPartial least squares regressionOrganic chemistryTetrahedron
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In silico molecular investigations of pyridine N-Oxide compounds as potential inhibitors of SARS-CoV-2: 3D QSAR, molecular docking modeling, and ADME…

2020

The new coronavirus SARS-CoV-2 virus is causing a severe pneumonia in human, provoking the serious outbreak epidemic CoV-2. Since its appearance in Wuhan, China on December 2019, CoV-2 becomes the biggest challenge the world is facing today, including the discovery of antiviral drug for SARS-CoV-2. In this study, the potential inhibitory of a class of human SARS inhibitors, namely pyridine N-oxide derivatives, against CoV-2 was addressed by quantitative structure-activity relationship 3 D-QSAR. The reliable CoMSIA developed model of 110 pyridine N-oxide based-antiviral compounds, showed Q

Quantitative structure–activity relationship2019-20 coronavirus outbreakCoronavirus disease 2019 (COVID-19)PyridinesvirusesIn silicoSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)030303 biophysicsQuantitative Structure-Activity Relationshipmedicine.disease_causeAntiviral Agents03 medical and health sciencesStructural BiologymedicineHumansProtease InhibitorsMolecular BiologyCoronavirus0303 health sciencesSARS-CoV-2ChemistryDrug discoveryCOVID-19virus diseasesGeneral Medicinerespiratory systembiochemical phenomena metabolism and nutritionVirologyrespiratory tract diseasesMolecular Docking SimulationJournal of Biomolecular Structure and Dynamics
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Comparing in vivo data and in silico predictions for acute effects assessment of biocidal active substances and metabolites for aquatic organisms.

2020

Abstract The purpose of this study was to determine the acute toxicity in aquatic organisms of one biocidal active substance and six metabolites derived from biocidal active substances and to assess the suitability of available QSAR models to predict the obtained values. We have reported the acute toxicity in sewage treatment plant (STP) microorganisms, in the freshwater microalgae Pseudokirchneriella subcapitata and in Daphnia magna following OECD test methods. We have also identified in silico models for acute toxicity of these trophic levels currently available in widely recognized platforms such as VEGA and the OECD QSAR ToolBox. A total of six, four and two models have been selected fo…

Quantitative structure–activity relationshipBiocideAquatic OrganismsHealth Toxicology and MutagenesisIn silicoMicroorganismDaphnia magna0211 other engineering and technologiesQuantitative Structure-Activity RelationshipFresh Water02 engineering and technology010501 environmental sciences01 natural sciencesDaphniaModels BiologicalChlorophyceaeMicroalgaeAnimalsComputer Simulation0105 earth and related environmental sciencesEC50021110 strategic defence & security studiesbiologyChemistryPublic Health Environmental and Occupational HealthGeneral Medicinebiology.organism_classificationPollutionAcute toxicityDaphniaEnvironmental chemistryWater Pollutants ChemicalDisinfectantsEcotoxicology and environmental safety
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