The pyrosequencing reactions were performed at LGC Genomics GmbH, Berlin, Germany. All sequencing reactions were based upon FLX—Titanium chemistry (Roche/454 Life Sciences, Branford, CT 06405, USA; www.454.com ) and all methods were performed using the manufacturers’ protocol. Briefly, genomic DNA from metagenome studies (22 (link)) as well as PCR-amplified DNA fragments were checked for quality on a 2% agarose gel. 500 ng of each sample was then used for the sequencing library. In a minor modification to the protocol, no size selection of the fragments was performed. The fragments were subjected to end repair and polishing. An extra A was added to the ends of the fragments and the Roche Rapid Library adaptors were ligated on to the fragments as described in the Roche Rapid Library Preparation Manual for GS FLX Titanium Series, October 2009, Rev. January 2010 (Roche/454 Life Sciences, Branford, CT 06405, USA; www.454.com ). After subsequent emulsion PCR the fragment libraries were processed and sequenced according to the Roche protocols. The resulting sequences were processed using the standard Roche software for base calling, trimming of adaptors and quality trimming (Genome Sequencer FLX System Software Manual version 2.3, Roche/454 Life Sciences, Branford, CT 06405, USA; www.454.com ). For PCR-amplified DNA fragments, per sample two distinct PCR reactions were sequenced on 1/8 of picotiter plate (PTP). Raw data were stored as FNA file. Sequences were submitted to INSDC (EMBL-EBI/ENA, Genbank, DDBJ) with accession number ERP001031. For metagenomics two full PTPs per sample were sequenced. Metagenome sequences were published by the MIMAS project (22 (link)) and can be obtained from INSDC with accession number ERP001227.
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Protein Tyrosine Phosphatase
Protein Tyrosine Phosphatase
Protein Tyrosine Phosphatase (PTPs) are a family of enzymes that play a crucial role in cellular signaling by catalyzing the dephosphorylation of phosphotyrosine residues in proteins.
These enzymes are involved in the regulation of a wide range of cellular processes, including cell growth, differentiation, metabolism, and immune response.
PTPs are classifed into several subfamilies based on their structural and functional characteristics, and they have been implicated in the pathogenesis of various diseases, such as cancer, diabetes, and autoimmune disorders.
Understading the role of PTPs in these processes is an important area of biomedical research, and the development of selective PTP inhibitors is an active area of drug discovery.
These enzymes are involved in the regulation of a wide range of cellular processes, including cell growth, differentiation, metabolism, and immune response.
PTPs are classifed into several subfamilies based on their structural and functional characteristics, and they have been implicated in the pathogenesis of various diseases, such as cancer, diabetes, and autoimmune disorders.
Understading the role of PTPs in these processes is an important area of biomedical research, and the development of selective PTP inhibitors is an active area of drug discovery.
Most cited protocols related to «Protein Tyrosine Phosphatase»
DNA Library
Emulsions
Genome
Metagenome
Protein Tyrosine Phosphatase
Sepharose
Titanium
Amino Acids
Homo sapiens
NR4A2 protein, human
Peptides
Protein Isoforms
Proteins
Protein Tyrosine Phosphatase
Proteome
Single Nucleotide Polymorphism
Trypsin
Classic speciation models such as the birth–death process (BDP) assume that new species will emerge and current species will become extinct at certain rates that are measured in unit time (Barraclough and Nee, 2001 (link)). Usually, a time-calibrated tree is required as an input. Thus, for molecular sequence data, a molecular clock model must be applied to calibrate the tree. Coalescent theory also relies on unit time to describe the relationships among ancestors and descendants in a population.
Instead, we may consider the number of substitutions between branching and/or speciation events, by modeling speciations using the number of substitutions instead of the time. The underlying assumption is that each substitution has a small probability of generating a speciation. Note that the substitutions are independent of each other. If we consider one substitution at a time in discrete steps, the probability of observing η speciations for κ substitutions is given by a binomial distribution. Because we assume that each substitution has a small probability ρ of generating a speciation, and the number of substitutions in a population of size η is large, the process follows a Poisson distribution in continuous time with rate . Therefore, the number of substitutions until the next speciation event follows an exponential distribution.
Comparing this with the assumptions of a BDP, we observe that each generation (e.g. with a generation time of 20 years) on a time-calibrated ultrametric tree has a small probability of speciation. The BDP does not model substitutions, thus, substitutions are superimposed onto the BDP, whereas PTP explicitly models substitutions. Substitution information can easily be obtained by using the branch lengths of the phylogenetic input tree. Thus, in our model, the underlying assumptions for observing a branching event are consistent with the assumptions made for phylogenetic tree inference.
We can now consider two independent classes of Poisson processes. One process class describes speciation such that the average number of substitutions until the next speciation event follows an exponential distribution. Given the species tree, we can estimate the rate of speciations per substitution in a straightforward way. The second Poisson process class describes within-species branching events that are analogous to coalescent events. We assume that the number of substitutions until the next within-species branching event also follows an exponential distribution. Thus, our model assumes that the branch lengths of the input tree have been generated by two independent Poisson process classes.
In the following step, we assign/fit the Poisson processes to the tree. Let T be a rooted tree, and Pi be a path from the root to leaf i, where and l is the number of leaves. Let be the edge lengths of Pi, representing the number of substitutions. We further assume that are independent exponentially distributed random variables with parameter λ. Let be the sum over the edge lengths for . We further define . Bik is the number of substitutions of the kth branching event, and is the number of branching events below Bik. Note that constitutes a Poisson process. Thereby, T and together form a tree of Poisson processes, which we denote as Poisson Tree Processes (PTP). To a rooted phylogeny with m species, we apply/fit one among-species PTP and at most m within-species PTPs. An example is shown inFigure 1 .
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where x1 to xk are the branch lengths generated by among-species PTPs, to xn are the branch lengths of within-species PTPs, is the speciation rate per substitution and is the rate of within-species branching events per substitution. The rates and can be obtained via the inverse of the average branch lengths that belong to the respective processes. Based onEquation (1) , we search for the species delimitation that maximizes L. A standard likelihood-ratio test with one degree of freedom can be used to test if there are indeed two classes of branch lengths. Large P-value indicates that either all sequences are one species or that every sequence represents a single species.
We developed and assessed three heuristic search strategies for finding species delimitations with ‘good’ likelihood scores, which are described in the online supplement. For the experimental results presented here, we used the heuristic that performed best, based on our preliminary experiments.
Instead, we may consider the number of substitutions between branching and/or speciation events, by modeling speciations using the number of substitutions instead of the time. The underlying assumption is that each substitution has a small probability of generating a speciation. Note that the substitutions are independent of each other. If we consider one substitution at a time in discrete steps, the probability of observing η speciations for κ substitutions is given by a binomial distribution. Because we assume that each substitution has a small probability ρ of generating a speciation, and the number of substitutions in a population of size η is large, the process follows a Poisson distribution in continuous time with rate . Therefore, the number of substitutions until the next speciation event follows an exponential distribution.
Comparing this with the assumptions of a BDP, we observe that each generation (e.g. with a generation time of 20 years) on a time-calibrated ultrametric tree has a small probability of speciation. The BDP does not model substitutions, thus, substitutions are superimposed onto the BDP, whereas PTP explicitly models substitutions. Substitution information can easily be obtained by using the branch lengths of the phylogenetic input tree. Thus, in our model, the underlying assumptions for observing a branching event are consistent with the assumptions made for phylogenetic tree inference.
We can now consider two independent classes of Poisson processes. One process class describes speciation such that the average number of substitutions until the next speciation event follows an exponential distribution. Given the species tree, we can estimate the rate of speciations per substitution in a straightforward way. The second Poisson process class describes within-species branching events that are analogous to coalescent events. We assume that the number of substitutions until the next within-species branching event also follows an exponential distribution. Thus, our model assumes that the branch lengths of the input tree have been generated by two independent Poisson process classes.
In the following step, we assign/fit the Poisson processes to the tree. Let T be a rooted tree, and Pi be a path from the root to leaf i, where and l is the number of leaves. Let be the edge lengths of Pi, representing the number of substitutions. We further assume that are independent exponentially distributed random variables with parameter λ. Let be the sum over the edge lengths for . We further define . Bik is the number of substitutions of the kth branching event, and is the number of branching events below Bik. Note that constitutes a Poisson process. Thereby, T and together form a tree of Poisson processes, which we denote as Poisson Tree Processes (PTP). To a rooted phylogeny with m species, we apply/fit one among-species PTP and at most m within-species PTPs. An example is shown in
Illustration of the PTP. The example tree contains 6 speciation events: R, A, B, D, E, F, and 4 species: C, D, E, F. Species C consists of one individual; species D, E, F have two individuals each. The thick lines represent among-species PTP, and the thin lines represent within-species PTPs. The Newick representation of this tree is ((C:0.14, (d1:0.01, d2:0.02)D:0.1)A:0.15, ((e1:0.015, e2:0.014)E:0.1, (f1:0.03, f2:0.02)F:0.12)B:0.11)R. The tree has a total of 16 different possible species delimitations. The maximum likelihood search returned the depicted species delimitation with a log-likelihood score of 24.77, and
where x1 to xk are the branch lengths generated by among-species PTPs, to xn are the branch lengths of within-species PTPs, is the speciation rate per substitution and is the rate of within-species branching events per substitution. The rates and can be obtained via the inverse of the average branch lengths that belong to the respective processes. Based on
We developed and assessed three heuristic search strategies for finding species delimitations with ‘good’ likelihood scores, which are described in the online supplement. For the experimental results presented here, we used the heuristic that performed best, based on our preliminary experiments.
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Dietary Supplements
Extinction, Psychological
Genetic Processes
Pons
Protein Tyrosine Phosphatase
Root Tip
Trees
Wild-type, male C57BL/6 mice (3–6 mo) were used for all studies. An initial dose–response curve was carried out using S8 (0.5, 1, and 3 mg/kg, i.p.) or TC-2153 (1, 3, 6, and 10 mg/kg, i.p.). Pilot studies were conducted to optimize the time after i.p. injection when STEP substrates showed maximum Tyr phosphorylation (1–3 h). Cortical tissues were dissected out 3 h postinjection and processed for subcellular fractionation. We homogenized brain tissue in buffer containing (in mM): 10 Tris-HCl, pH 7.6, 320 sucrose, 150 NaCl, 5 EDTA, 5 EGTA, 20 NaF, 1 Na3VO4, and protease inhibitors (TEVP). Homogenates were centrifuged at 800 × g to remove nuclei and large debris (P1). Synaptosomal fractions (P2) were prepared from S1 by centrifugation at 9,200 × g for 15 min. The P2 pellet was washed twice and was resuspended in TEVP buffer. In some experiments, mice were injected with S8 (1 mg/kg, i.p.) or TC-2153 (3 mg/kg, i.p.), and cortex, cerebellum, and spleen were removed to test for the in vivo inhibition of the highly related PTPs, HePTP, and PTP-SL [57] (link)–[60] (link).
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Brain
Buffers
Cell Nucleus
Centrifugation
Cerebellum
Cortex, Cerebral
Edetic Acid
Egtazic Acid
G-800
Kidney Cortex
Males
Mice, House
Mice, Inbred C57BL
Phosphorylation
Protease Inhibitors
Protein Tyrosine Phosphatase
Psychological Inhibition
PTPN7 protein, human
PTPRR protein, human
Radiotherapy Dose Fractionations
Sodium Chloride
Spleen
Sucrose
Synaptosomes
TC-2153
Tissues
Tromethamine
Nups were quantified in nuclear or NE extracts using targeted proteomics in combination with the spike-in of isotopically labeled peptides used as internal standard. For absolute quantification, the abundance of each Nup was calculated from the median ratio between the intensities of its endogenous proteotypic peptides (PTPs, light) and the corresponding spiked-in AQUA peptides (heavy). A panel of 90 MRM assays for 76 PTPs was used for absolute quantification. For relative quantification of Nup abundances across cell lines, crude synthetic peptides were used as internal standard instead of AQUA peptides. Therefore, a larger panel of 142 MRM assays for 119 PTPs was used. A detailed description of MRM assays development, data acquisition and processing is available in Supplementary Materials and Methods and Supplementary Figures S1E–G . A list of the MRM assays employed is available in Supplementary Table S1 . Raw MRM data and method files are available at http://www.peptideatlas.org/PASS/PASS00189 for absolute quantification, and http://www.peptideatlas.org/PASS/PASS00188 for relative quantification across cell lines.
Biological Assay
Cell Lines
Light
Peptides
Protein Tyrosine Phosphatase
Most recents protocols related to «Protein Tyrosine Phosphatase»
Total RNA (15–35 ng) was reverse transcribed with a High-Capacity cDNA Reverse Transcription Kit, using random primers (Applied Biosystems, Waltham, MA, USA). To quantify the levels of sperm-specific marker (sex determining region Y: SRY), we used a pre-designed quantitative PCR (qPCR) gene expression assay (Integrated DNA Technologies, Coralville, IA, USA, Ref Seq # NM_003140, exon location: 1-1). A GAPDH pre-designed assay (Ref Seq # NM_002046, exons: 2-3) was included to normalize the data. In both cases, the dye/quencher modifications were 6-FAM/ZEN/3IABkFQ and the primer:probe ratio was 2:1. To detect potential leukocyte contamination in sperm samples, we quantified the protein tyrosine phosphatase, receptor type, C (PTPRC marker, also known as CD45) (Ref Seq # NM_001267798, exon location: 3a-4). Reactions were set up in duplicates in 96-well plates with 1× PrimeTime Gene Expression Master Mix (Integrated DNA Technologies, Coralville, IA, USA) and run on a QuantStudio 5 Flex System (0.2 ml 96-well block, Applied Biosystems, Waltham, MA, USA), with the following conditions: denaturation/enzyme activation for 3 min at 95°C, 40 cycles of 15 s denaturation at 95°C and 60 s annealing/extension at 60°C followed by a hold at 4°C.
Transglutaminase 4 (TGM4) and protamine 2 (PRM2) assays were run using SYBR™ Green chemistry. The primers used were: TGM4-sense, 5′-TCCCTCAAGCCCACAGATA-3′; TGM4, antisense: 5′-ACTGCCTGTCCACTTGTATG-3′; PRM2-sense, 5′-GAAAGTCACCTGCCCAAGAA-3′ and PRM2-antisense, 5′-CTCAGATCTTGTGGGCTTCTC-3′. The PCR reactions were run using 1× PowerUp™ SYBR™ Green Master Mix (Applied Biosystems, Waltham, MA, USA) and 500 nM of each primer. The cycling conditions were: UDP activation for 2 min 50°C, Dual-Lock™ DNA polymerase activation for 2 min at 95°C, 40 cycles of 15 s denaturation at 95°C and 60 s annealing/extension at 60°C followed by a dissociation step (melt curve analysis). PCR reactions were run in duplicates. No-template control PCR reactions were run with each experiment and we observed no amplification. For both Taqman and SYBR Green assays, results were analyzed using Quant Studio v 1.4.1 (Applied Biosystems, Waltham, MA, USA).
Transglutaminase 4 (TGM4) and protamine 2 (PRM2) assays were run using SYBR™ Green chemistry. The primers used were: TGM4-sense, 5′-TCCCTCAAGCCCACAGATA-3′; TGM4, antisense: 5′-ACTGCCTGTCCACTTGTATG-3′; PRM2-sense, 5′-GAAAGTCACCTGCCCAAGAA-3′ and PRM2-antisense, 5′-CTCAGATCTTGTGGGCTTCTC-3′. The PCR reactions were run using 1× PowerUp™ SYBR™ Green Master Mix (Applied Biosystems, Waltham, MA, USA) and 500 nM of each primer. The cycling conditions were: UDP activation for 2 min 50°C, Dual-Lock™ DNA polymerase activation for 2 min at 95°C, 40 cycles of 15 s denaturation at 95°C and 60 s annealing/extension at 60°C followed by a dissociation step (melt curve analysis). PCR reactions were run in duplicates. No-template control PCR reactions were run with each experiment and we observed no amplification. For both Taqman and SYBR Green assays, results were analyzed using Quant Studio v 1.4.1 (Applied Biosystems, Waltham, MA, USA).
Biological Assay
Cardiac Arrest
DNA, Complementary
DNA-Directed DNA Polymerase
Enzyme Activation
Exons
GAPDH protein, human
Gene Expression
Leukocytes
Oligonucleotide Primers
protamine 2
Protein Tyrosine Phosphatase
PTPRC protein, human
Reverse Transcription
Sperm
SYBR Green I
transglutaminase 4
A PRL-1 (human protein tyrosine phosphatase type 4A, member 1 [PTP4A1]) plasmid was purchased (Origene, Rockville, MD, USA). The CMV6-AC vector containing the PTP4A1 gene was digested with the restriction enzymes Sgf1 and Mlu1 and included a GFP reporter gene and neomycin. A lentiviral vector including the PRL-1 gene was acquired from SeouLin Bioscience (Seongnam, Republic of Korea). A pLenti-RSV-EF1a vector containing PRL-1 was constructed as a tagged protein with C-terminal GFP and puromycin. To generate a control group, we used the AMAXA pCMV-GFP vector (Lonza, Basel, Switzerland) containing kanamycin, and maxGFP was digested with the restriction enzymes Kpn1 and Bgl2.
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Cloning Vectors
DNA Restriction Enzymes
Genes
Genes, Reporter
Homo sapiens
Kanamycin
Neomycin
Plasmids
Protein Tyrosine Phosphatase
PTP4A1 protein, human
Puromycin
Staphylococcal Protein A
T1D was diagnosed according to the presence of classical symptoms at the onset, blood glucose concentration above 11.1 mmol/l and the presence of at least one of the assessed autoantibodies: islet cells (ICA), glutamic acid decarboxylase (anti-GAD), insulinoma-associated tyrosine phosphatase (IA-2A) autoantibodies.
All patients underwent a complete physical examination with anthropometric measurements.
We assessed the metabolic control of diabetes and the presence of diabetic retinopathy and neuropathy. Diabetic retinopathy was diagnosed using direct ophthalmoscopy through dilated pupils. Neuropathy assessment was performed using pressure sensation (10-g monofilament perception), vibration perception (128-Hz tuning fork), and ankle reflex tests. Diabetic neuropathy was diagnosed in patients with two or more of the following four components: the presence of typical symptoms of neuropathy, the absence of ankle tendon reflexes, and/or abnormal scores for pressure and/or vibration perception.
Blood samples were obtained after an overnight fast. Serum lipids and creatinine were measured with standard techniques. Hemoglobin A1c (HbA1c) was measured using the high-performance liquid chromatography method aligned to the Diabetes Control and Complications Trial DCCT standard.
All patients underwent a complete physical examination with anthropometric measurements.
We assessed the metabolic control of diabetes and the presence of diabetic retinopathy and neuropathy. Diabetic retinopathy was diagnosed using direct ophthalmoscopy through dilated pupils. Neuropathy assessment was performed using pressure sensation (10-g monofilament perception), vibration perception (128-Hz tuning fork), and ankle reflex tests. Diabetic neuropathy was diagnosed in patients with two or more of the following four components: the presence of typical symptoms of neuropathy, the absence of ankle tendon reflexes, and/or abnormal scores for pressure and/or vibration perception.
Blood samples were obtained after an overnight fast. Serum lipids and creatinine were measured with standard techniques. Hemoglobin A1c (HbA1c) was measured using the high-performance liquid chromatography method aligned to the Diabetes Control and Complications Trial DCCT standard.
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Ankle
Autoantibodies
BLOOD
Blood Glucose
Complications of Diabetes Mellitus
Creatinine
Diabetes Mellitus
Diabetic Neuropathies
Diabetic Retinopathy
Glutamate Decarboxylase
Hemoglobin A, Glycosylated
High-Performance Liquid Chromatographies
Insulinoma
Islets of Langerhans
Lipids
Mydriasis
Ophthalmoscopy
Patients
Physical Examination
Pressure
Protein Tyrosine Phosphatase
Reflex
Serum
Tendons
Vibration
The PTP1B activity was measured by using the fluorometric Protein tyrosine phosphatase activity assay kit (BioVision). The recombinant PTP1B and immunoprecipitated PTP1B were applied to the working solution by following the instruction and acquiring the fluorescence from (Ex/Em = 368/460 nm) with the Synergy HT multi-detection microplate reader (Bio-TeK, Winooski, VT, USA). The data were collected with kinetic mode with a 20 s period for 10 min for calculate the change in fluorescence with time.
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Biological Assay
Fluorescence
Fluorometry
Kinetics
Proteins
Protein Tyrosine Phosphatase
PTPN1 protein, human
Immunoprecipitation and the measurement of SHP-2 activity were done as previously described [9 (link),23 (link)]. All the steps related to the SHP-2 activity were performed on ice and inside an anoxic chamber to prevent the spontaneous oxidation of the catalytic cysteine of SHP-2 (GB2202-P-V, MBraun, Garching Germany). The activity of SHP-2 was measured in the immunoprecipitates using the Malachite-Green based-Tyrosine Phosphatase Assay System (Promega, Walldorf, Germany).
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Anoxia
Biological Assay
Catalysis
Cysteine
Immunoprecipitation
malachite green
Promega
Protein Tyrosine Phosphatase
PTPN11 protein, human
Top products related to «Protein Tyrosine Phosphatase»
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The RediPlate 96 EnzChek Tyrosine Phosphatase Assay Kit is a fluorescence-based assay that measures the activity of tyrosine phosphatases. The kit provides a substrate and necessary reagents to quantify tyrosine phosphatase activity in a 96-well plate format.
Sourced in United States
The SHP-1 activity assay is a laboratory instrument designed to measure the enzymatic activity of the SHP-1 (Src Homology 2 domain-containing Protein Tyrosine Phosphatase-1) protein. SHP-1 is a phosphatase enzyme that plays a crucial role in regulating cellular signaling pathways. The assay provides a quantitative assessment of SHP-1 activity, which can be useful in various research applications involving cellular signaling and immune system regulation.
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The Tyrosine Phosphatase Assay System is a laboratory equipment designed to measure the activity of tyrosine phosphatase enzymes. The system provides the necessary reagents and protocols to quantify the phosphatase activity using a colorimetric or fluorometric detection method.
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Protein G Sepharose 4 Fast Flow is a pre-packed agarose-based chromatography medium designed for the purification of antibodies and other proteins that bind to Protein G. It offers high binding capacity and fast flow characteristics.
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The SpectraMax i3 is a multi-mode microplate reader that can perform absorbance, fluorescence, and luminescence measurements. It is designed to provide accurate and reliable results for a wide range of assays and applications in life science research and drug discovery.
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Sodium orthovanadate is a laboratory chemical compound commonly used as a protein tyrosine phosphatase inhibitor in various biochemical and cell-based assays. It is a white crystalline solid that is soluble in water and other polar solvents. Sodium orthovanadate is often utilized in research applications to investigate cellular signaling pathways and protein phosphorylation dynamics.
Sourced in United States
The RediPlate 96 EnzChekR Tyrosine Phosphatase Assay Kit is a fluorescence-based assay designed to measure the activity of tyrosine phosphatases. The kit includes a fluorogenic substrate that releases a fluorescent product upon dephosphorylation by tyrosine phosphatases.
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The Tyrosine Phosphatase Assay Kit is a laboratory tool used to measure the activity of tyrosine phosphatase enzymes. It provides a quantitative colorimetric method to determine the level of phosphatase activity in a sample.
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P-nitrophenyl phosphate is a colorless crystalline compound used as a substrate in various biochemical assays. It is commonly used in enzyme-linked immunosorbent assays (ELISA) and other colorimetric detection methods to measure the activity of phosphatase enzymes.
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The Protease Inhibitor Cocktail is a laboratory product designed to inhibit the activity of proteases, which are enzymes that can degrade proteins. It is a combination of various chemical compounds that work to prevent the breakdown of proteins in biological samples, allowing for more accurate analysis and preservation of protein integrity.
More about "Protein Tyrosine Phosphatase"
Protein Tyrosine Phosphatases (PTPs) are a family of enzymes that play a crucial role in cellular signaling by catalyzing the dephosphorylation of phosphotyrosine residues in proteins.
These enzymes, also known as tyrosine-specific protein phosphatases (TSPPs) or protein-tyrosine-phosphatases (PTPs), are involved in the regulation of a wide range of cellular processes, including cell growth, differentiation, metabolism, and immune response.
PTPs are classified into several subfamilies based on their structural and functional characteristics, such as classical PTPs, dual-specificity phosphatases (DUSPs), and low-molecular-weight PTPs (LMW-PTPs).
These enzymes have been implicated in the pathogenesis of various diseases, including cancer, diabetes, and autoimmune disorders, making them an important area of biomedical research.
The RediPlate 96 EnzChek Tyrosine Phosphatase Assay Kit and the Tyrosine Phosphatase Assay System are tools used to measure the activity of tyrosine phosphatases, such as PTP-1B and SHP-1.
The SHP-1 activity assay specifically measures the activity of the SHP-1 (Src Homology 2 domain-containing Phosphatase-1) enzyme, which is a PTP involved in the regulation of cell signaling pathways.
Protein G Sepharose 4 Fast Flow is a common affinity resin used for the purification of antibodies, which can be useful in the study of PTPs and their interacting partners.
The SpectraMax i3 is a multi-mode microplate reader that can be used to measure the activity of PTPs using colorimetric or fluorometric assays, such as the RediPlate 96 EnzChekR Tyrosine Phosphatase Assay Kit.
Sodium orthovanadate is a known inhibitor of PTPs and can be used to study the role of these enzymes in various cellular processes.
The Tyrosine Phosphatase Assay Kit and P-nitrophenyl phosphate are also commonly used tools for the assessment of PTP activity.
Protease inhibitor cocktails can be used to prevent the degradation of PTPs during sample preparation and analysis, ensuring the accurate measurement of their activity and expression levels.
By understanding the role of PTPs in cellular signaling and their involvement in disease pathogenesis, researchers can develop selective PTP inhibitors, which is an active area of drug discovery.
The insights gained from the study of PTPs can lead to the development of new therapeutic strategies for a wide range of diseases.
These enzymes, also known as tyrosine-specific protein phosphatases (TSPPs) or protein-tyrosine-phosphatases (PTPs), are involved in the regulation of a wide range of cellular processes, including cell growth, differentiation, metabolism, and immune response.
PTPs are classified into several subfamilies based on their structural and functional characteristics, such as classical PTPs, dual-specificity phosphatases (DUSPs), and low-molecular-weight PTPs (LMW-PTPs).
These enzymes have been implicated in the pathogenesis of various diseases, including cancer, diabetes, and autoimmune disorders, making them an important area of biomedical research.
The RediPlate 96 EnzChek Tyrosine Phosphatase Assay Kit and the Tyrosine Phosphatase Assay System are tools used to measure the activity of tyrosine phosphatases, such as PTP-1B and SHP-1.
The SHP-1 activity assay specifically measures the activity of the SHP-1 (Src Homology 2 domain-containing Phosphatase-1) enzyme, which is a PTP involved in the regulation of cell signaling pathways.
Protein G Sepharose 4 Fast Flow is a common affinity resin used for the purification of antibodies, which can be useful in the study of PTPs and their interacting partners.
The SpectraMax i3 is a multi-mode microplate reader that can be used to measure the activity of PTPs using colorimetric or fluorometric assays, such as the RediPlate 96 EnzChekR Tyrosine Phosphatase Assay Kit.
Sodium orthovanadate is a known inhibitor of PTPs and can be used to study the role of these enzymes in various cellular processes.
The Tyrosine Phosphatase Assay Kit and P-nitrophenyl phosphate are also commonly used tools for the assessment of PTP activity.
Protease inhibitor cocktails can be used to prevent the degradation of PTPs during sample preparation and analysis, ensuring the accurate measurement of their activity and expression levels.
By understanding the role of PTPs in cellular signaling and their involvement in disease pathogenesis, researchers can develop selective PTP inhibitors, which is an active area of drug discovery.
The insights gained from the study of PTPs can lead to the development of new therapeutic strategies for a wide range of diseases.