Log In Sign up
The largest database of trusted experimental protocols
> Chemicals & Drugs > Amino Acid > Cell Membrane Proteins

Cell Membrane Proteins

Cell Membrane Proteins: Integral and peripheral proteins that are embedded in or associate with the cell membrane.
They play crucial roles in diverse cellular processes, including signaling, transport, adhesion, and cell-cell interaction.
These proteins are of great interest for drug discovery and biomedical research, as they are often key targets for therapeutic intervention.
Unlock the power of cell membrane protein research with PubCompare.ai's AI-driven protocol optimization.
Discover the best protocols and products from literature, pre-prints, and patents through our intelligent comparison tools.
Simplify your reseach and accelerate your discoveries with PubCompare.ai's cutting-edge technology.
Experence the future of research today!

Most cited protocols related to «Cell Membrane Proteins»

1
Multimodal Single-Cell Data Integration
The WNN procedure begins by first applying standard analytical workflows to each modality independently and constructing KNN graphs for each one. In this manuscript we analyze data falling into three categories: measurements of single-cell gene expression, single-cell surface protein expression, and single-cell chromatin accessibility (ATAC-seq). For most analyses in this manuscript, we use a default value of k = 20, which is also the default value of k in the standard Seurat clustering workflow. For the analysis of the multimodal PBMC atlas, due to the substantial size of the dataset, we used a value of k = 30. In Figure S2, we show that we obtain very similar results from the WNN procedure when varying k across a series of values ranging from 10 to 50.
For clarity, we overview the analytical workflows for each data type below:

Single-cell gene expression: We analyze scRNA-seq data using standard pipelines in Seurat which include normalization, feature selection, and dimensional reduction with PCA. We then construct a KNN graph after dimensional reduction.

We emphasize that WNN analysis can leverage any scRNA-seq preprocessing workflow that generates a KNN graph. For example, users can preprocess their scRNA-seq data with a variety of normalization tools including log-normalization, scran (Lun et al., 2016 (link)) or SCTransform (Hafemeister and Satija, 2019 (link)), and can utilize alternative dimensional reduction procedures such as factor analysis or variational autoencoders. In this manuscript, we use workflows that are available in the Seurat package, and detail exact settings for each analysis later in this document.

Single-cell cell surface protein level expression: We analyze single-cell protein data (representing the quantification of antibody-derived tags (ADTs) in CITE-seq or ASAP-seq data) using a similar workflow to scRNA-seq. We normalize protein expression levels within a cell using the centered-log ratio (CLR) transform, followed by dimensional reduction with PCA, and subsequently construct a KNN graph. Unless otherwise specified, we do not perform feature selection on protein data, and use all measured proteins during dimensional reduction.

Single-cell chromatin accessibility: We analyze single-cell ATAC-seq data using our previously described workflow (Stuart et al., 2019 (link)), as implemented in the Signac package. We reduced the dimensionality of the scATAC-seq data by performing latent semantic indexing (LSI) on the scATAC-seq peak matrix, as suggested by Cusanovich et al. (2018) (link). We first computed the term frequency-inverse document frequency (TF-IDF) of the peak matrix by dividing the accessibility of each peak in each cell by the total accessibility in the cell (the “term frequency”), and multiplied this by the inverse accessibility of the peak in the cell population. This step ‘upweights’ the contribution of highly variable peaks and down-weights peaks that are accessible in all cells. We then multiplied these values by 10,000 and log-transformed this TF-IDF matrix, adding a pseudocount of 1 to avoid computing the log of 0. We decomposed the TF-IDF matrix via SVD to return LSI components, and scaled LSI loadings for each LSI component to mean 0 and standard deviation 1.

As described for scRNA-seq analysis, while we use Seurat and Signac functions in this manuscript, any analytical workflow that computes a KNN graph for surface protein or chromatin accessibility data can also be used in the first step of WNN analysis.
Hao Y., Hao S., Andersen-Nissen E., Mauck WM I.I.I., Zheng S., Butler A., Lee M.J., Wilk A.J., Darby C., Zager M., Hoffman P., Stoeckius M., Papalexi E., Mimitou E.P., Jain J., Srivastava A., Stuart T., Fleming L.M., Yeung B., Rogers A.J., McElrath J.M., Blish C.A., Gottardo R., Smibert P, & Satija R. (2021). Integrated analysis of multimodal single-cell data. Cell, 184(13), 3573-3587.e29.
Full text: Click here
Publication 2021
ATAC-Seq Cell Membrane Proteins Cells Chromatin Gene Expression Immunoglobulins Membrane Proteins Multimodal Imaging Protein Domain Proteins Single-Cell RNA-Seq Staphylococcal Protein A
2
Identifying Membrane Protein Localization
The positive training set was composed of human ɑ-helical TM domain-containing proteins appearing in at least two of the following three datasets: (i) the “high confidence” subset of the CSPA containing 735 proteins, (ii) the UniProtKB/Swiss-Prot (Version 2015_01) containing 2,043 proteins attributed with the “cell membrane” keyword, and (iii) the subcellular localization database COMPARTMENTS (69 (link)) containing 826 high-confidence plasma membrane proteins (five stars), which belong to the COMPARTMENTS inherent “plasma membrane” positive benchmark set and also belong to the COMPARTMENTS inherent negative benchmark sets for each of the remaining subcellular locations (all but “extracellular space”). Additional details can be found in SI Appendix, SI Methods.
Bausch-Fluck D., Goldmann U., Müller S., van Oostrum M., Müller M., Schubert O.T, & Wollscheid B. (2018). The in silico human surfaceome. Proceedings of the National Academy of Sciences of the United States of America, 115(46), E10988-E10997.
Publication 2018
Cell Membrane Proteins Extracellular Space Helix (Snails) Homo sapiens Plasma Membrane Protein Domain Proteins Stars, Celestial
3
TRPV Channel FRET Detection
All TRPV constructs used in the present study were based on murine TRPV clones. For FRET recordings, the fluorescence donor was Cerulean, which is a brighter version of the enhanced cyan fluorescent protein (eCFP) due to improved quantum yield (Rizzo et al., 2004 (link)); Cerulean also carries a mutation that eliminated the tendency of eCFP to form dimers. The fluorescence acceptor was the enhanced yellow fluorescent protein (eYFP) (Heim and Tsien, 1996 (link)). In this report Cerulean and eYFP are referred to as CFP and YFP, respectively. The fluorophore was attached to the C terminus of each channel subunit. All constructs were confirmed by sequencing. Consistent with previous reports on similar constructs (Hellwig et al., 2005 (link)), functional recordings of cells transfected with these cDNA constructs did not show noticeable alteration in channel properties from untagged channels. Cell surface expression of each fusion protein was further supported by fluorescence microscopy and patch-clamp recordings.
As negative controls, we coexpressed TRPV constructs with unrelated membrane proteins, including TRPM4_Cerulean, TRPM5_Cerulean, TRPM5_eYFP (gifts from E. Liman, University of Southern California, Los Angeles, CA), and CLC-0_Cerulean (a gift from T.Y. Chen, University of California, Davis, CA). As in TRPV fusion constructs, Cerulean was attached to the C terminus of CLC-0 subunits in CLC-0_Cerulean. For TRPM4 and TRPM5 fusion constructs, the fluorophore was attached to the N terminus. Normal channel functions have been confirmed by the providers of each construct. Surface expression of each protein was confirmed by fluorescence microscopy and electrophysiology.
Cheng W., Yang F., Takanishi C.L, & Zheng J. (2007). Thermosensitive TRPV Channel Subunits Coassemble into Heteromeric Channels with Intermediate Conductance and Gating Properties. The Journal of General Physiology, 129(3), 191-207.
Publication 2007
Cell Membrane Proteins Cells Clone Cells DNA, Complementary enhanced cyan fluorescent protein Fluorescence Fluorescence Resonance Energy Transfer Gifts Membrane Proteins Microscopy, Fluorescence Mus Mutation Proteins Protein Subunits Tissue Donors TRPM5 protein, human
4
Membrane Protein Dynamics in a Realistic Plasma Membrane
The detailed methods are described in the Supporting Information. In summary, we embedded 10 membrane proteins in
a previously characterized model of the plasma membrane.20 (link) The starting structures of the 10 membrane proteins
simulated in this study were taken from the Protein Data Bank or obtained
from the corresponding publication: aquaporin-1 (AQP1, PDB ID 1J4N);98 (link) prostaglandin H2 synthase (COX1, PDB ID 1Q4G);99 (link) the dopamine transporter (DAT, PDB ID 4M48);44 (link) the epidermal growth factor receptor (EGFR);77 (link) AMPA-sensitive glutamate receptor 2 (GluA2,
PDB ID 3KG2);100 (link) glucose transporter 1 (GluT1, PDB ID 4PYP);101 (link) voltage-dependent Shaker potassium channel 1.2 (Kv1.2,
PDB ID 3LUT,102 (link) residues 32 to 4421 for each monomer); sodium,
potassium pump (Na,K-ATPase, PDB ID 4HYT);103 (link) δ-opioid
receptor (δ-OPR, PDB ID 4N6H);104 (link) and P-glycoprotein
(P-gp, PDB ID 4M1M).105 (link) In each system, four copies of each
protein were included and positioned at a distance of ca. 20 nm from
each other. Proteins were simulated using standard Martini protocols
with minor variations between systems to accommodate system-specific
issues (Supporting Information). The following
lipid classes were included: cholesterol (CHOL), in both leaflets;
charged lipids phosphatidylserine (PS), phosphatidic acid (PA), phosphatidylinositol
(PI), and the PI-phosphate, PI-bisphosphate, and PI-trisphosphate
(PIPs) placed in the inner leaflet; and ganglioside (GM) in the outer
leaflet. The zwitterionic phosphatidylcholine (PC), phosphatidylethanolamine
(PE), and sphingomyelin (SM) lipids were placed in both leaflets,
with PC and SM primarily in the outer leaflet and PE in the inner
leaflet. Ceramide (CER), diacylglycerol (DAG), and lysophosphatidylcholine
(LPC) lipids were also included, with all the LPC in the inner leaflet,
and CER and DAG primarily in the outer leaflet. The details of the
Martini lipids used in this study can be found on the Martini Lipidome
webpage (http://www.cgmartini.nl/index.php/force-field-parameters/lipids) and are described by Ingolfsson et al., and Wassenaar et al.20 (link),106 (link) The exact lipid composition of each system is given in the Supporting Information. The systems are ca. 42
× 42 nm in the membrane plane (x and y), including 4 proteins and ca. 6000 lipids.
Production
runs were performed in the presence of weak position
restraints applied to the protein backbone beads, with a force constant
of 1 kJ mol–1 nm–2, preventing
proteins from associating with each other. Each of the systems has
been simulated for 30 μs, which turned out to be adequate to
obtain convergence of major lipid components in the lipid shells around
the individual copies of the proteins (Supporting Information). Additional control simulations were performed
in the AQP1 system, in order to test the effects of simulation length,
position restraints on the proteins, lipid composition, and water
model on the results of lipid composition near the proteins (Supporting Information).
Simulations were
performed using the GROMACS simulation package
version 4.6.3,107 (link) with the Martini v2.2
force field parameters,62 (link),63 (link) and standard simulation
settings.108 (link) Additional details are provided
in Supporting Information. All the analyses
were performed on the last 5 μs of each simulation system.
Corradi V., Mendez-Villuendas E., Ingólfsson H.I., Gu R.X., Siuda I., Melo M.N., Moussatova A., DeGagné L.J., Sejdiu B.I., Singh G., Wassenaar T.A., Delgado Magnero K., Marrink S.J, & Tieleman D.P. (2018). Lipid–Protein Interactions Are Unique Fingerprints for Membrane Proteins. ACS Central Science, 4(6), 709-717.
Publication 2018
Adenosinetriphosphatase alpha-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid AMPA Receptors AQP1 protein, human Aquaporin 1 Cell Membrane Proteins Ceramides Cholesterol Debility Diacylglycerol Dopamine Transporter Epidermal Growth Factor Receptor Gangliosides Glucose Transporter Glutamate Glutamate Receptor Lipids Lysophosphatidylcholines Na(+)-K(+)-Exchanging ATPase P-Glycoproteins Phosphates Phosphatidic Acid Phosphatidylcholines phosphatidylethanolamine Phosphatidylinositols Phosphatidylserines Potassium Channel Proteins PTGS1 protein, human SLC2A1 protein, human Sphingomyelins Tissue, Membrane Vertebral Column
5
Dissecting Substance P-Mediated Signaling
The study was designed to examine the contribution of SP-induced endocytosis of the NK1R to signal transduction in subcellular compartments, excitation of spinal neurons, and nociception. Endocytosis of the NK1R was examined in HEK293 cells by using BRET to assess the proximity between the NK1R and proteins resident in the plasma membrane and early endosomes and by localizing fluorescent SP by confocal microscopy. BRET was also used to examine the assembly of signaling complexes, which were localized in endosomes by immunofluorescence and super-resolution microscopy. Signaling in subcellular compartments of HEK293 cells was studied by expressing genetically encoded FRET biosensors, which allowed analysis of signaling with high spatial and temporal fidelity. NK1R endocytosis was studied in spinal neurons in slice preparations and in vivo by immunofluorescence and confocal microscopy. To examine the excitation of pain-transmitting neurons, cell-attached patch clamp recordings were made from second-order neurons in slices of rat spinal cord. Nociceptive behavior was evaluated in conscious mice after intraplantar administration of capsaicin, formalin, or CFA. To examine the contribution of NK1R endocytosis to signaling, neuronal excitation, and nociception, HEK293 cells, rat spinal cord slices, or mice were treated with pharmacological or genetic inhibitors of clathrin, dynamin, or βARRs, or with peptide inhibitors of NK1R/βARR interactions. Peptidic and small-molecule antagonists of the NK1R were conjugated to the lipid cholestanol, which facilitated endosomal targeting and retention of antagonists. Cholestanol-conjugated antagonists were used to directly evaluate the contribution of NK1R signaling in endosomes to SP-induced compartmentalized signaling in HEK293 cells, excitation of spinal neurons, and nociception. Institutional Animal Care and Use Committees approved all studies.
Jensen D.D., Lieu T., Halls M.L., Veldhuis N.A., Imlach W.L., Mai Q.N., Poole D.P., Quach T., Aurelio L., Conner J., Herenbrink C.K., Barlow N., Simpson J.S., Scanlon M.J., Graham B., McCluskey A., Robinson P.J., Escriou V., Nassini R., Materazzi S., Geppetti P., Hicks G.A., Christie M.J., Porter C.J., Canals M, & Bunnett N.W. (2017). Neurokinin 1 receptor signaling in endosomes mediates sustained nociception and is a viable therapeutic target for prolonged pain relief. Science translational medicine, 9(392), eaal3447.
Publication 2017
Aftercare antagonists Biosensors Capsaicin Cell Membrane Proteins Cells Cholestanol Clathrin Consciousness Dynamins Endocytic Vesicles Endocytosis Endosomes Fluorescence Resonance Energy Transfer Formalin HEK293 Cells Immunofluorescence inhibitors Institutional Animal Care and Use Committees Lipids Microscopy Microscopy, Confocal Mus Neurons Nociception Pain Peptides Reproduction Retention (Psychology) Spinal Cord

Most recents protocols related to «Cell Membrane Proteins»

1
Lentivirus Vector Production and Titration for CD19 CAR
Not available on PMC !

Example 10

CD19 was chosen as a B-CAR target, and an antigen binding domain comprising the sequence as shown in SEQ ID NO.:1 was used to construct the B-CAR. A fourth generation lentivirus vector system was used. CA19 CAR vector, packaging vector pMDL-gag, Rev, and envelop vector pMD2.G were co-transduced into HEK293T cells with calcium phosphate or liposome-PEI. The supernatant was collected after 48 hrs, and ultra-centrifuged to concentrate the lentivirus.

CD19 lentivirus titration was conducted on a three-fold serial dilution. 293T cells were collected after transduced with 50 ul lentivirus for 48 to 72 hrs, and then stained for CAR expression. The percentage of CAR+ (CAR+%) was analyzed via flow cytometry, and titration calculated as:
Titration (TU/ml)=(Number of starting 293T cells)*CAR+%*Fold of dilution*20 (first CAR+%<20%)

Lentivirus titration was calculated. Titration over 3*107 was considered ready for further use.

US11866731B2. Modified immune cells and uses thereof (2024-01-09). CHINEO MEDICAL TECHNOLOGY CO., LTD. [CN]. Inventors: Weiyue Gu [CN].
Full text: Click here
Patent 2024
Antigens B-Lymphocytes Calcium Phosphates Cell Membrane Proteins Cells Cloning Vectors Flow Cytometry HEK293 Cells Lentivirus Liposomes Technique, Dilution Titrimetry
2
Modeling Diffusion-Biased Protein Tracking
Tracks can terminate due to different reasons: photobleaching, diffusive molecules leaving the field of view, or molecules transiently not being detected. The process of leaving the field of view requires diffusive motion. Observation of long-lived molecules within a finite field of view can thus show a bias toward non-moving or slowly moving molecules. An extension of ExTrack can take this bias into account by explicitly modeling the probability of track termination. We consider two contributions to track termination: first, a constant termination probability pK, which is independently of the motion state. This probability summarizes photobleaching and the probability to not detect a molecule, for example because of low signal-to-noise ratio; second, a probability of leaving the field of view (or observation volume) pL that depends on the diffusion length and the dimensions of the field of view. In the case of a cytoplasmic particle tracked through epi-fluorescence or confocal microscopy, the monitored length is the depth of field (or focal depth). In case of a membrane protein moving around a cylindrical cell imaged in TIRF microscopy, the monitored length is a fraction of the cell diameter (Fig. 2, c and d).
In principle, pL can be calculated depending on the position of the molecule with respect to the boundaries of the field of view. However, we decided to implement an approximate form of pL(δi) that does not require this information and instead considers the position of the observed molecule as random inside the field of view. Within this approximation, the probability of leaving the field of view is given by: pL(δi)=1−∫x∈[0,l]F(l−xδi)−F(−xδi) dx, where F(x) is the cumulative density function of the standard normal law.
We thus modify fC,B,R(C,B,R | θ) in Eq. 2 by multiplication of the left-hand terms with the probability of observing a track of n positions, which is given by: (1−pL(δi))n−1(1−pK)n−1[pK+(1−pK)pL(δn)].
Simon F., Tinevez J.Y, & van Teeffelen S. (2023). ExTrack characterizes transition kinetics and diffusion in noisy single-particle tracks. The Journal of Cell Biology, 222(5), e202208059.
Full text: Click here
Publication 2023
Cell Membrane Proteins Cells Cytoplasm Diffusion Fluorescence Microscopy Microscopy, Confocal
3
Isolation of Rat Medullary Thick Ascending Limb Cells
Rat medullary TAL suspensions were obtained as previously described (4 (link), 7 (link)). Male Sprague–Dawley rats weighing 200–250 g (Charles River Breeding Laboratories, Wilmington, MA) were fed a diet containing 0.22% sodium and 1.1% potassium (Purina, Richmond, IN) with water provided ad libitum for at least 7 days. On the day of the experiment, rats were anesthetized with ketamine and xylazine (100 mg/kg and 20 mg/kg body wt delivered intraperitoneally, respectively). The abdominal cavity was opened, and the kidneys were perfused retrogradely via the aorta with PS containing 0.1% collagenase (Sigma, St. Louis, MO) and 100 U/mL heparin. The inner strip of the outer medulla was cut into coronal slices, minced, and incubated at 37°C for 30 min with 0.1% collagenase in PS with gassing every 5 min with 100% oxygen. The tissue was pelleted by gentle centrifugation at 120 g for 2 min, suspended in chilled PS, and stirred on ice for 30 min to detach the tubules from each other. The suspension was filtered through 250-μm nylon mesh and centrifuged at 120 g for 2 min. The pellet was washed, centrifuged again, and finally suspended in 0.4 mL of chilled PS. In general, TAL suspensions were split into four aliquots for ubiquitin pulldown assays or experiments to study the biotinylation of plasma membrane proteins. All animal protocols were approved by the Institutional Animal Care and Use Committee of Henry Ford Hospital and Wayne State University.
, & Ares G.R. (2023). Ubiquitination of NKCC2 by the cullin-RING E3 ubiquitin ligase family in the thick ascending limb of the loop of Henle. American Journal of Physiology - Renal Physiology, 324(3), F315-F328.
Full text: Click here
Publication 2023
Abdominal Cavity Adrenal Medulla Animals Aorta Biological Assay Biotinylation Cell Membrane Proteins Centrifugation Collagenase collagenase 1 Diet Heparin Human Body Institutional Animal Care and Use Committees Ketamine Kidney Males Medulla Oblongata Nylons Oxygen Potassium Rats, Sprague-Dawley Rattus Rivers Sodium Tissues Ubiquitin Xylazine
4
Membrane Protein Extraction and Western Blot Analysis
We lysed the cells in RIPA buffer for 30 min, and we then centrifugated them at 13 000 r.p.m. for 15 min at 4 °C. We obtained the membrane/cytoplasmic protein fractions of the cultured cells with the Mem‐PER Plus Membrane Protein Extraction kit (Thermo, Waltham, MA, USA). We measured the protein concentration using BCA protein assay reagents (Thermo). We separated the total proteins (30 μg) by SDS–PAGE on 10% polyacrylamide gels, and we transferred them to a PVDF membrane. We hybridized the membranes with primary antibodies overnight after blocking for 30 min in 5% nonfat milk. We incubated the samples with the secondary antibodies for 1 h, and we then visualized the proteins using enhanced chemiluminescence (ECL) reagents (Perkin Elmer, Waltham, MA, USA). We obtained the quantitative data using imagej software. The detailed process and classification are introduced in our previous articles [22 (link)].
Chang Y., Li C., Chan M., Fang C., Zhang Z., Chen C, & Hsiao M. (2023). Overexpression of synaptic vesicle protein Rab GTPase 3C promotes vesicular exocytosis and drug resistance in colorectal cancer cells. Molecular Oncology, 17(3), 422-444.
Full text: Click here
Publication 2023
Antibodies Biological Assay Buffers Cell Membrane Proteins Chemiluminescence Cytoplasm Membrane Proteins Milk, Cow's polyacrylamide gels polyvinylidene fluoride Proteins Radioimmunoprecipitation Assay SDS-PAGE Tissue, Membrane
5
Comparative Evolutionary Analysis of Monkeypox Virus
The mPox viral protein sequence was retrieved as a FASTA file from the UniProt database (https://www.uniprot.org/) [21 (link)] by searching with the keyword “monkeypox cell surface binding protein.” Following that, we used our target sequence as the query sequence to analyze the BLASTp program [22 (link)] for evaluating phylogenetic information from the NCBI database (https://www.ncbi.nlm.nih.gov). Finally, in order to better understand the comparative evolution of the organisms, a phylogenetic tree was constructed and visualized using the Microreact database (https://microreact.org/) [23 (link)].
Mazumder L., Hasan M.R., Fatema K., Begum S., Azad A.K, & Islam M.A. (2023). Identification of B and T Cell Epitopes to Design an Epitope-Based Peptide Vaccine against the Cell Surface Binding Protein of Monkeypox Virus: An Immunoinformatics Study. Journal of Immunology Research, 2023, 2274415.
Full text: Click here
Publication 2023
3-(2-methoxyphenyl)-5-methoxy-1,3,4-oxadiazol-2(3H)-one Amino Acid Sequence Biological Evolution Cell Membrane Proteins Monkeypox Viral Proteins

Top products related to «Cell Membrane Proteins»

1
Pierce cell surface protein isolation kit by Thermo Fisher Scientific
Sourced in United States
The Pierce Cell Surface Protein Isolation Kit is a laboratory product designed to isolate and purify cell surface proteins from mammalian cells. It utilizes a biotinylation reagent and streptavidin-coated beads to selectively capture and extract cell surface proteins from cell lysates.
2
Cell surface protein isolation kit by Thermo Fisher Scientific
Sourced in United States
The Cell Surface Protein Isolation Kit is a laboratory tool designed to isolate cell surface proteins from biological samples. It provides a standardized method for the extraction and purification of cell surface proteins, which are important for various applications in cell biology, immunology, and proteomics research.
3
Plasma membrane protein extraction kit by Abcam
Sourced in United States, United Kingdom
The Plasma Membrane Protein Extraction Kit is designed for the isolation of plasma membrane proteins from various cell types. It utilizes a series of centrifugation steps to fractionate cellular components and enrich for plasma membrane proteins.
4
Mem per plus membrane protein extraction kit by Thermo Fisher Scientific
Sourced in United States, China, United Kingdom
The Mem-PER Plus Membrane Protein Extraction Kit is a laboratory product designed to isolate and purify membrane proteins from various cell and tissue samples. The kit utilizes a detergent-based approach to extract and separate membrane proteins from other cellular components.
5
Protease inhibitor cocktail by Roche
Sourced in United States, Switzerland, Germany, China, United Kingdom, France, Canada, Japan, Italy, Australia, Austria, Sweden, Spain, Cameroon, India, Macao, Belgium, Israel
Protease inhibitor cocktail is a laboratory reagent used to inhibit the activity of proteases, which are enzymes that break down proteins. It is commonly used in protein extraction and purification procedures to prevent protein degradation.
6
Facscanto 2 by BD
Sourced in United States, Germany, United Kingdom, Belgium, China, France, Australia, Japan, Italy, Spain, Switzerland, Canada, Uruguay, Netherlands, Czechia, Jersey, Brazil, Denmark, Singapore, Austria, India, Panama
The FACSCanto II is a flow cytometer instrument designed for multi-parameter analysis of single cells. It features a solid-state diode laser and up to four fluorescence detectors for simultaneous measurement of multiple cellular parameters.
7
Protease inhibitor cocktail by Merck Group
Sourced in United States, Germany, China, United Kingdom, Italy, Japan, Sao Tome and Principe, France, Canada, Macao, Switzerland, Spain, Australia, Israel, Hungary, Ireland, Denmark, Brazil, Poland, India, Mexico, Senegal, Netherlands, Singapore
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.
8
Facscalibur by BD
Sourced in United States, Germany, United Kingdom, China, Canada, Japan, Italy, France, Belgium, Singapore, Uruguay, Switzerland, Spain, Australia, Poland, India, Austria, Denmark, Netherlands, Jersey, Finland, Sweden
The FACSCalibur is a flow cytometry system designed for multi-parameter analysis of cells and other particles. It features a blue (488 nm) and a red (635 nm) laser for excitation of fluorescent dyes. The instrument is capable of detecting forward scatter, side scatter, and up to four fluorescent parameters simultaneously.
9
Facscalibur flow cytometer by BD
Sourced in United States, Germany, United Kingdom, China, Canada, Japan, Belgium, France, Spain, Italy, Australia, Finland, Poland, Switzerland, Cameroon, Uruguay, Denmark, Jersey, Moldova, Republic of, Singapore, India, Brazil
The FACSCalibur flow cytometer is a compact and versatile instrument designed for multiparameter analysis of cells and particles. It employs laser-based technology to rapidly measure and analyze the physical and fluorescent characteristics of cells or other particles as they flow in a fluid stream. The FACSCalibur can detect and quantify a wide range of cellular properties, making it a valuable tool for various applications in biology, immunology, and clinical research.
10
Membrane and cytosol protein extraction kit by Beyotime
Sourced in China
The Membrane and Cytosol Protein Extraction Kit is a laboratory tool designed to separate and extract membrane-bound and cytosolic proteins from cell samples. It provides a systematic approach to isolating these distinct protein fractions for further analysis.

More about "Cell Membrane Proteins"

Cell surface proteins, integral membrane proteins, peripheral membrane proteins, cell-cell adhesion, cell signaling, drug targets, biomedical research, flow cytometry, protein extraction kits, protease inhibitors.
Cell membrane proteins, also known as plasma membrane proteins or cell surface proteins, are a crucial class of biomolecules that play vital roles in diverse cellular processes.
These proteins are embedded in or associated with the cell membrane, enabling them to mediate essential functions such as signaling, transport, adhesion, and cell-cell interactions.
Due to their importance in cellular physiology and their frequent involvement as therapeutic targets, cell membrane proteins are of great interest in drug discovery and biomedical research.
Researchers often utilize specialized techniques and tools to study and manipulate these proteins, such as cell surface protein isolation kits, membrane protein extraction kits, and flow cytometry instruments like the FACSCanto II and FACSCalibur.
To optimize research on cell membrane proteins, scientists may employ AI-driven protocol optimization tools like PubCompare.ai, which can help discover the best protocols and products from literature, preprints, and patents.
By leveraging cutting-edge technology, researchers can simplify their work and accelerate their discoveries, unlocking the full potential of cell membrane protein research and experencing the future of research today.
It's important to note that effective research on cell membrane proteins often involves the use of protease inhibitor cocktails to preserve the integrity of these delicate biomolecules.
With the right tools and techniques, researchers can delve deeper into the complex world of cell membrane proteins and uncover new insights that may lead to groundbreaking advancements in biomedical science and therapeutic development.