Protein kinases are a diverse group of enzymes that play a crucial role in cellular signaling pathways by catalyzing the phosphorylation of target proteins.
These enzymes are involved in a wide range of biological processes, including cell growth, differentiation, metabolism, and apoptosis.
Protein kinases are classified into several families based on their structure and substrate specificity, and they are widely studied in the context of disease states, such as cancer, neurological disorders, and autoimmune diseases.
Researchers can leverage the power of PubCompare.ai, an innovative AI-driven platform, to easily locate the most reliable protocols from literature, pre-prints, and patents, while utilizing AI-driven comparisons to identify the best methodologies and products.
This tool enhances reproducibility and accuracy in protein kinase studies, empowering researchers to advance their understanding of these essential regulatory proteins.
PANTHER version 3.0 (1 (link),2 (link)) used seed-based clustering to define protein families. The advantage of this approach was its modularity: new families could be easily added in areas that were inadequately covered in previous versions. However, the seed-based clustering resulted in significant redundancy for a number of large protein families, such as protein kinases and G-protein-coupled receptors, which were covered by a number of families that overlapped to varying degrees. The current version, PANTHER version 5.0, addresses this issue by implementing a global clustering of proteins. Proteins from PANTHER version 4.0 were clustered using a similarity metric derived from the pairwise BLASTP scores: where S(a, b) is the BLASTP raw score for the alignment of sequences a and b using the BLOSUM62 matrix and masked for low-complexity segments. The denominator is the largest self-alignment score, and therefore, the similarity is the fraction of the maximum score possible for an alignment of sequences a and b. In cases where there were multiple high-scoring pairs (HSPs; i.e. partial alignments), S(a, b) was set equal to the sum of the scores for the maximal set of non-overlapping HSPs. This pairwise similarity was used to define single-linkage clusters (maximal clusters in which each protein is connected to at least one other protein in the cluster by a non-zero similarity score). A dendrogram was built for each single-linkage cluster using the UPGMA algorithm (17 ). The family labels from the PANTHER version 4.0 library were then used to define the optimal cut of each UPGMA dendrogram into family clusters, to maximize the correspondence to previous versions of PANTHER. In the great majority of cases, the PANTHER version 5.0 family was almost identical to the corresponding family in the previous version of the library. Only about 40 subtrees in the UPGMA dendrograms, primarily those that were represented by overlapping clusters in the previous version, had to be broken further into functionally homogeneous clusters using manual curation. Overall, the family clusters identified from the UPGMA dendrograms covered over 96% of the version 4.0 training sequences. The rest of the sequences were either singletons according to Equation 1 (often due to low-complexity masking), or lay outside the family boundaries defined by PANTHER version 4.0 family labels on the UPGMA dendrograms. Each of these ‘leftover’ sequences (unmasked) was scored against SAM HMMs built for the family clusters, and was brought into the family of the best scoring HMM if the NLL-NULL score was less than −50. Those leftovers not meeting this criterion were added as singleton families if they were from a primate or rodent species; otherwise they were removed from the library.
Mi H., Lazareva-Ulitsky B., Loo R., Kejariwal A., Vandergriff J., Rabkin S., Guo N., Muruganujan A., Doremieux O., Campbell M.J., Kitano H, & Thomas P.D. (2004). The PANTHER database of protein families, subfamilies, functions and pathways. Nucleic Acids Research, 33(Database Issue), D284-D288.
cDNA Library G-Protein-Coupled Receptors Hypertelorism, Severe, With Midface Prominence, Myopia, Mental Retardation, And Bone Fragility Primates Protein Kinases Proteins Rodent Staphylococcal Protein A
PIC server accepts atomic coordinate set of a protein structure in the standard Protein Data Bank (PDB) format. The user is prompted with selecting one or more of the following interaction types: Interaction between apolar residues, disulphide bridges, hydrogen bond between main chain atoms, hydrogen bond between main chain and sidechain atoms, hydrogen bond between two sidechain atoms, interaction between oppositely charged amino acids (ionic interactions), aromatic–aromatic interactions, aromatic–sulphur interactions and cation–π interactions. The input coordinate set is accepted, under each section of the page, for recognition of interactions within a polypeptide chain. If an ensemble of NMR-derived structures is input then the first model in the file is taken as a representative and is used by the PIC server. The output corresponds to the list of residues involved in interaction type of interest. An option is provided, using RasMol (25 (link)) interface and Jmol interface, for enabling visualization of structure in the graphics with interactions highlighted. It is possible to get the results by e-mail. It is also possible to download the output files of the original programs. A separate panel is available for identification of various types of interactions between polypeptide chains when a multi-chain PDB file is subjected to the analysis. All the said interactions could be explored for their occurrence across the inter-polypeptide chain interface. Thus this panel facilitates recognition of interactions between different subunits in a multimeric protein structures or between proteins in a protein–protein complex structure. Figure 1 show ionic interactions between oppositely charged sidechains across the interface, formed between cyclin-dependent protein kinase and bound cyclin (26 (link)), recognized using PIC server.
Interactions between oppositely charged amino acid sidechains in the interaction interface of cyclic dependent protein kinase 2 (CDKs) and cyclin identified using PIC server. The folds of CDK2 and cyclin and the charged residues in the interface formed by the two proteins are represented in different colours. The ion pairs are highlighted by black dotted lines. This figure is produced using SETOR (35 ).
Solvent accessibility calculations could be used to identify different kinds of interactions between buried or between solvent exposed residues. Solvent accessibility calculations are performed using NACCESS program (Hubbard, S.J. and Thornton, J.M., 1993, NACCESS Computer Program, Department of Biochemistry and Molecular Biology, University College London.). The exposed and buried residues are identified by >7% and ⩽7% residue accessibility, respectively. Under this facility list of all the interaction types are displayed prompting the user to select list of interaction types of interest. For example, a user may prefer to identify interactions between apolar residues that are exposed. Figure 2 shows interactions between solvent exposed apolar residues, in crambin (27 (link)), recognized using PIC server.
Structure of crambin with solvent exposed and interacting apolar sidechains, recognized using PIC. Interactions between apolar sidechains is shown by green dots. Disulphide bonds are shown in yellow. This figure is produced using SETOR (35 ).
Depth of an atom in a protein is defined as the distance from the nearest atom in the surface of the protein structure. Mean depths of atoms of a residue defines the residue depth (28 (link),29 (link)). Analogous to the panel on solvent accessibility, panel on residue depth enables the users to identify specific types of interactions near the protein surface or deep inside the core of the structure. Based on the analysis of residue depth parameter by Chakravarty and Varadarajan (28 (link)) we consider those residues with depths ⩽5 Å as close to the protein surface and others as deep inside. Using this part of the PIC server it is possible to identify interactions between, say, aromatic residues near the protein structural surface. As calculation of residue depths takes a few minutes for most protein structures, results involving depth calculation are sent by e-mail to the user if a valid e-mail address is provided.
Tina K.G., Bhadra R, & Srinivasan N. (2007). PIC: Protein Interactions Calculator. Nucleic Acids Research, 35(Web Server issue), W473-W476.
Amino Acids Amino Acids, Cyclic CDK2 protein, human crambin protein, Crambe abyssinica Cyclin-Dependent Kinases Cyclins Disulfides Hydrogen Bonds Membrane Proteins Polypeptides Protein Kinases Proteins Protein Subunits SET protein, human Solvents Staphylococcal Protein A Sulfur
The multiple sequence alignments are the only source of information used in the predictions. Predictions are best for accurate, nonredundant alignments of diverse sequences without significant gap regions. In the interface prediction tests, we used alignments from the 'Superfamily' [33 (link)] and PFAM [34 (link)] collections, as well as the Homology-Derived Secondary Structure of Proteins database [35 (link)] and curated alignments of human protein kinases [36 (link)] from the Protein Kinase Resource [37 (link)]. As needed, the original alignments were prepared for specificity analysis by trimming deletions and insertions across the whole alignment so as to preserve the continuity of the main sequence (the sequence of a given protein); removing redundant sequences (typically at the level of about 95% identical residues for large alignments) using the MView program [38 (link),39 ]; and removing sequences with many gaps (for example, with more than about 10% to 20% gaps compared with the main sequence). Finally, the total number of sequences in the alignment must be large (>100).
Reva B., Antipin Y, & Sander C. (2007). Determinants of protein function revealed by combinatorial entropy optimization. Genome Biology, 8(11), R232.
The PH domains of PLCδ1 (1–170), Bruton's tyrosine kinase (1–177), Akt protein kinase (1–167), and dynamin (508–652) were amplified with the Advantage Klentaq polymerase mix (CLONTECH Labs, Inc., Palo Alto, CA) from human cDNAs (marathon cDNA from brain and K562 leukemia cells; CLONTECH Labs, Inc.) with the following primer pairs: PLCδ: 5′-GGCATGGACTCGGGCCGGGACTTCCTG-3′, 5′-AAGATCTTCCGGGCATAGCTGTCG-3′; Btk: 5′-CCAAGTCCTGGCATCTCAATGCATCTG-3′, 5′-TGGAGACTGGTGCTGCTGCTGGCTC-3′; Akt: 5′-GTCAGCTGGTGCATCAGAGGCTGTG-3′, 5′-CACCAGGATCACCTTGCCGAAAGTGCC-3′; Dyn: 5′-ATGCTCAGCAGAGGAGCAACCAGATG-3′, 5′-GAGTCCACAAGATTCCGGATGGTCTC-3′. The amplified products were subcloned into the PGEM-Easy T/A cloning vector (Promega Corp., Madison, WI) and sequenced with dideoxy sequencing (thermosequenase; Amersham Corp.). A second amplification reaction was performed from these plasmids with nested primers that contained restriction sites for appropriate cloning into the pEGFP-N1 (PLCδ, Btk, and Akt) or pEGFP-C1 (dynamin) plasmids (CLONTECH Labs, Inc.) to preserve the reading frame. Plasmids were transfected into COS-7 cells or NIH-3T3 cells and cell lysates were resolved by SDS-PAGE followed by Western blot analysis for the presence of the GFP fusion proteins using a polyclonal antibody against GFP (CLONTECH Labs, Inc.). Mutations were created in the PHPLCδ–GFP fusion plasmid by the QuickChange™ mutagenesis kit (Stratagene, La Jolla, CA). For practical purposes, a SalI site was introduced into the PH domain sequence which changed S34 to a T but this substitution did not change any characteristic compared with the wild-type protein. All mutations were confirmed by dideoxy sequencing and the expression of the fusion protein by Western blot analysis.
Várnai P, & Balla T. (1998). Visualization of Phosphoinositides That Bind Pleckstrin Homology Domains: Calcium- and Agonist-induced Dynamic Changes and Relationship to Myo-[3H]inositol-labeled Phosphoinositide Pools. The Journal of Cell Biology, 143(2), 501-510.
Three tobacco lines, FC401 wild type (Wt); FC40-M207 mutant line fourth generation (M4) and FC401-M544 mutant line fourth generation (M4) were used for candidate gene screening. Low anatabine traits were confirmed for the two tobacco mutant lines (M207 and M544) in root and leaf before screening (see FIG. 3).
RNA was extracted from root tissues of wild type (Wt) FC401, M207 and M544 with RNeasy Plus Mini kit from Quiagen Inc. following the manufacturer's protocol. cDNA libraries were prepared from the RNAs using In-Fusion® SMARTer® Directional cDNA Library Construction Kit from Clontech Inc. cDNA libraries were diluted to 100 ng/μl and used as the template for candidate gene PCR screening.
PCR amplifications were performed in 50 μl final volumes that contained 50-100 ng of template DNA (i.e., the cDNA library) and 0.2 μM of primers (Fisher Scientific) using the Platinum® Taq DNA Polymerase High Fidelity kit (Life Technology Inc.). Thermocycling conditions included a 5 min incubation at 94° C.; followed by 34 cycles of 30 seconds at 94° C., 30 seconds at 58° C., 1 min 30 seconds at 68° C.; with a final reaction step of 68° C. for 7 mins. The PCR products were evaluated by agarose gel electrophoresis, and desired bands were gel purified and sequenced using an ABI 3730 DNA Analyzer (ABI).
51 candidate genes (listed in Table 4) were cloned from F401, Wt, M207 and M544 lines, and sequenced for single nucleotide polymorphism (SNP) detection.
TABLE 4
Listing of Candidate Genes for Screening
Quinolinate Synthase A-1Pathogenesis related protein 1
Allene oxide synthaseAllene oxide cyclase
ET861088.1 Methyl esteraseFH733463.1 TGACG-sequence specific transcription factor
FH129193.1 Aquaporin-TransportFH297656.1 Universal stress protein
Universal stress protein Tabacum sequenceFH077657.1 Scarecrow-like protein
US11873500B2. Genetic locus imparting a low anatabine trait in tobacco and methods of using (2024-01-16). ALTRIA CLIENT SERVICES LLC [US]. Inventors: Chengalrayan Kudithipudi [US], Alec J. Hayes [US], Robert Frank Hart [US], Yanxin Shen [US], Jesse Frederick [US], Dongmei Xu [US].
In order to get specific markers for the alien chromosome, we screened 197 wheat group-7-specific microsatellite markers reported by Somers et al. (2004) (link) and 88 pairs of sequence-tagged sites-polymerase chain reaction (STS-PCR) primers on wheat group-7 chromosomes (Supplementary Table S1). At the two-leaf stage, 27 plants of T14-44 and 25 plants of T14-42 were collected and separately pooled for RNA isolation using a TRIzol reagent (InvitrogenTM, Shanghai, China), followed by the treatment with DNase I (InvitrogenTM, Shanghai, China). The samples were sequenced using the Illumina Hiseq2500 platform (Berry Genomics, Beijing, China) to generate 125 bp pair-end reads. The de novo assembly of clean reads was performed by using the software Trinity 2.1.1 (Haas et al., 2013 (link)). The expression level was calculated by mapping reads to the assembled transcripts employing Trinity scripts, RSEM, and edgeR (Haas et al., 2013 (link)). The TransDecoder software package (https://sourceforge.net/projects/transdecoder/) was used to predict the coding region for these transcripts. The transcripts were annotated in the Swiss-Prot database using Blastx. The transcripts expressed in T14-44 but not in T14-42 were extracted. Then, the transcripts annotated as Nucleotide Binding Site–Leucine Rich Repeat (NBS-LRR) protein and protein kinases were used to design primers using the software Primer 5.0 (PREMIER Biosoft, San Francisco, CA, USA). The conditions of the polymerase chain reaction (PCR) were as follows: initial denaturation at 94°C for 4 min, followed by 35 cycles of 30 s at 94°C, 30 s for annealing at 55°C–60°C, 1 min for extension at 72°C, and a final extension at 72°C for 10 min. Amplified PCR products were separated on 8% non-denaturing polyacrylamide gels stained with silver at 200 V for 1 h and 1.5% agarose gels stained with ethidium bromide at 150 V for approximately 25 min. The D2000 Plus DNA Ladder (GenStar, Beijing, China) and the 100 bp DNA Ladder (TianGen Biotech Co, Beijing, China) were used for the DNA marker in non-denaturing polyacrylamide gel and agarose gel electrophoresis, respectively.
Guo X., Huang Y., Wang J., Fu S., Wang C., Wang M., Zhou C., Hu X., Wang T., Yang W, & Han F. (2023). Development and cytological characterization of wheat–Thinopyrum intermedium translocation lines with novel stripe rust resistance gene. Frontiers in Plant Science, 14, 1135321.
For protein alignment of AthRLCK XI and representative RLKs in Figure 1, we aligned members of RLCK XI from A. thaliana together with well-studied RLK AthCLV1 from LRR-RLK XI-1 subfamily, AthBIK1 from RLCK VIIa-2 subfamily, and the distant RLK homolog HsaIRAK1 from humans. For Supplementary Figure 1, we used the RLK dataset from Dievart et al. (2020) (link), which included grouped subfamilies of RLKs from the iTAK database of protein kinases (http://itak.feilab.net/cgi-bin/itak/index.cgi). To identify suitable RLK representatives, each RLK subfamily was aligned with AthRLCK XI-2. The sequence with the highest pairwise comparison score with AthRLCK XI-2 was chosen to represent their subfamily. AthRLCK XI-2 was selected because it has the highest average pairwise similarity score among all AthRLCK XI members. Each RLK representative selected for alignment contained all eleven conserved protein kinase subdomains. RLK subfamilies whose members lacked one or more conserved protein kinase subdomains were excluded from the alignment. To determine the evolutionary conservation of the RLCK XI subfamily in plants, full RLCK XI protein sequences were aligned using the L-INS-i strategy from MAFFT version 7 (Katoh and Standley, 2013 (link)). The resulting alignment was used to construct a phylogenetic tree using the maximum likelihood method from IQ-TREE (Nguyen et al., 2015 (link)). The Phylogenetic tree was illustrated using iTOL (https://itol.embl.de) (Letunic and Bork, 2021 (link)).
Yayen J., Chan C., Sun C.M., Chiang S.F, & Chiou T.J. (2023). Conservation of land plant-specific receptor-like cytoplasmic kinase subfamily XI possessing a unique kinase insert domain. Frontiers in Plant Science, 14, 1117059.
The transfected cells or xenograft tumor tissue samples were rinsed with phosphate-buffered saline (PBS) and lysed in Pierce™ RIPA buffer (cat. no. 89900; Thermo Fisher Scientific, Inc.) with Halt™ phosphatase and protease inhibitor cocktail (cat. no. 1862495 and 1862209; Thermo Fisher Scientific, Inc.). The quantification of proteins in the cell lysate was performed using a BCA protein assay (cat. no. 23228; Thermo Fisher Scientific, Inc.). Equal amounts (20 µg/lane) of protein lysate were separated by electrophoresis on 8-12% polyacrylamide gels and transferred onto Immobilon®-P transfer membranes (cat. no. IPVH00010; MilliporeSigma). The blot membranes were incubated with 5% BSA solution at room temperature for 1 h and immunoblotted with specific antibodies (1:1,000 dilution) overnight at 4°C. Antibodies against ADAM12 (cat. no. ab28747), matrix metalloproteinase (MMP)2 (cat. no. ab37150) and MMP9 (cat. no. ab58803) were purchased from Abcam. Antibodies against E-cadherin (cat. no. #14472), Snail (cat. no. #3879), vimentin (cat. no. #5741), claudin-1 (cat. no. #4933), integrin α5 (cat. no. #4705), integrin β1 (cat. no. #9699), integrin β3 (cat. no. #13166), phosphorylated (p)-AKT (S473) (cat. no. #4060), p-phosphoinositide-dependent protein kinase 1 (PDK1) (S241) (cat. no. #3438), p-glycogen synthase kinase-3β (GSK-3β) (S9) (cat. no. #9323), total AKT (cat. no. #4691), total PDK1 (cat. no. #3062), total GSK-3β (cat. no. #9832) and Myc-tag (cat. no. #2278) were obtained from Cell Signaling Technology, Inc. Antibodies against β-tubulin (cat. no. sc-9104) and GAPDH (cat. no. sc-25778) were purchased from Santa Cruz Biotechnology, Inc. The blot membranes were washed four times with Tris-buffered saline-0.1% Tween-20 (TBS-T) and were then incubated with a horseradish peroxidase-conjugated secondary antibody (anti-rabbit, cat. no. #7074, anti-mouse, cat. no. #7076; Cell Signaling, Technology, Inc.) at 1:2,000 dilution for 1 h at room temperature. Amersham ECL Prime Western Blotting Detection Reagent (cat no. RPN2232SK; Cytiva) was used for blot development. Visualization of specific bands was obtained using the LAS-400 luminescent image analyzer (FUJIFILM Wako Pure Chemical Corporation). Semi-quantification of specific bands was performed using Multi-Gauge gel analysis software (version 3.0; FUJIFILM Wako Pure Chemical Corporation).
Oh H.H., Park Y.L., Park S.Y, & Joo Y.E. (2023). A disintegrin and metalloprotease 12 contributes to colorectal cancer metastasis by regulating epithelial-mesenchymal transition. International Journal of Oncology, 62(4), 50.
After the section of DLBCL paraffin tissues, the samples were kept in an oven at 55 °C for 60 min. Dried tissue sections were dewaxed and rehydrated. The dewaxing process was as follows: dimethylbenzene for 10 min, dimethylbenzene for 10 min, absolute ethyl alcohol for 10 min, absolute ethyl alcohol for 10 min, 95% ethyl alcohol for 10 min, 95% ethyl alcohol for 10 min, 85% ethyl alcohol for 10 min, 70% ethyl alcohol for 10 min, and tap water. Antigens were recovered after heating with citrate buffer and 3% H2O2 at high pressure for 10 min, and then sealed with 5% normal goat serum (NGS, SAP-9100, ZSGB-BIO) for 1 min at room temperature, which was then incubated with NGS-diluted PIM kinase family antibodies (PIM1: ab54503, PIM2: ab107102, PIM3: ab198842, USA, Abcam) (dilution, 1:300; Proteintech Group Inc.) overnight at 4 °C 1 h later. NGS was taken as a negative control. The samples were incubated with biotin-labeled goat anti-mouse/rabbit immunoglobulin G (SAP-9100, ZSGB-BIO) for 15 min on the following day, which were, then, incubated and colored with diaminobidine solution, counterstained with hematoxylin for 2 min, and sealed with neutral glue. The expression levels of proteins of PIM kinase family were assessed by the product of the percentage of positive cells and staining intensity.
Wang C., Chen Q., Luo H, & Chen R. (2023). Role and mechanism of PIM family in the immune microenvironment of diffuse large B cell lymphoma. World Journal of Surgical Oncology, 21, 76.
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β-actin is a cytoskeletal protein that is ubiquitously expressed in eukaryotic cells. It is an important component of the microfilament system and is involved in various cellular processes such as cell motility, structure, and integrity.
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TRIzol reagent is a monophasic solution of phenol, guanidine isothiocyanate, and other proprietary components designed for the isolation of total RNA, DNA, and proteins from a variety of biological samples. The reagent maintains the integrity of the RNA while disrupting cells and dissolving cell components.
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β-actin is a cytoskeletal protein that is ubiquitously expressed in eukaryotic cells. It is a component of the microfilament system and plays a crucial role in various cellular processes, such as cell motility, maintenance of cell shape, and intracellular trafficking.
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Lipofectamine 2000 is a cationic lipid-based transfection reagent designed for efficient and reliable delivery of nucleic acids, such as plasmid DNA and small interfering RNA (siRNA), into a wide range of eukaryotic cell types. It facilitates the formation of complexes between the nucleic acid and the lipid components, which can then be introduced into cells to enable gene expression or gene silencing studies.
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Fetal Bovine Serum (FBS) is a cell culture supplement derived from the blood of bovine fetuses. FBS provides a source of proteins, growth factors, and other components that support the growth and maintenance of various cell types in in vitro cell culture applications.
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Compound C is a lab equipment product manufactured by Merck Group. It is a chemical compound with a specific molecular structure and properties. The core function of Compound C is to serve as a research tool for scientific investigations, but its precise intended use is not provided in this factual and unbiased description.
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GAPDH is a protein that functions as an enzyme involved in the glycolysis process, catalyzing the conversion of glyceraldehyde 3-phosphate to 1,3-bisphosphoglycerate. It is a common reference or housekeeping protein used in various assays and analyses.
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P-ERK is a phospho-specific antibody that recognizes the phosphorylated form of Extracellular Signal-Regulated Kinase (ERK). ERK is a key component of the MAPK signaling pathway, which plays a crucial role in cellular processes such as proliferation, differentiation, and survival. The P-ERK antibody can be used to detect the activated, phosphorylated state of ERK in various experimental applications.
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[γ-32P]ATP is a radiolabeled compound containing the radioactive isotope phosphorus-32 (32P) attached to the gamma phosphate group of adenosine triphosphate (ATP). This product is commonly used as a tracer in various biochemical and molecular biology applications, such as nucleic acid labeling and analysis.
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β-actin is a highly conserved, ubiquitously expressed cytoskeletal protein that is involved in various cellular processes, including cell motility, structure, and integrity. It is commonly used as a loading control in Western blotting, immunocytochemistry, and other biochemical assays.
Protein kinases can be classified into several major families based on their structural and functional characteristics. Some of the main types include serine/threonine kinases, tyrosine kinases, dual-specificity kinases, and lipid kinases. Each family has distinct substrate preferences and roles in cellular signaling pathways. Understanding the different kinase variations is crucial for targeted therapeutic development and elucidating their specific biological functions.
Dysregulation of protein kinase activity is implicated in a wide range of disease conditions, including cancer, neurological disorders, autoimmune diseases, and metabolic disorders. Aberrant kinase signaling can lead to uncontrolled cell growth, altered metabolism, and impaired cellular responses. Researchers studying Protein Kinases often focus on elucidating their roles in pathological processes and developing kinase-targeted therapies to restore proper cellular function.
Working with Protein Kinases can present several challenges, such as ensuring the specificity and sensitivity of assays, maintaining the stability and activity of kinase enzymes, and accurately quantifying kinase-substrate interactions. Researchers must also navigate the complexity of kinase signaling networks and identify the most relevant kinases to target for their specific research or therapeutic applications. Leveraigng the power of PubCompare.ai can help address these challenges by providing access to the most reliable and effective protocols from the literature.
PubCompare.ai is an innovative AI-driven platform that can greatly enhance Protein Kinase research. The tool allows researchers to efficiently screen protocol literature, leveraging AI to pinpoint critical insights that can inform their experimental design. By comparing the effectiveness of different protocols related to Protein Kinases, PubCompare.ai can help researchers identify the most reliable and reproducible methodologies for their specific research goals. This empowers scientists to choose the best options and improve the accuracy and quality of their Protein Kinase studies.
More about "Protein Kinases"
Protein kinases are a diverse family of enzymes that play a crucial role in cellular signaling pathways.
These essential regulatory proteins catalyze the phosphorylation of target proteins, thereby modulating their activity and function.
Protein kinases are involved in a wide range of biological processes, including cell growth, differentiation, metabolism, and apoptosis.
These enzymes are classified into several families based on their structural characteristics and substrate specificity.
They are widely studied in the context of various disease states, such as cancer, neurological disorders, and autoimmune diseases.
Researchers can leverage the power of PubCompare.ai, an innovative AI-driven platform, to easily locate the most reliable protocols from literature, pre-prints, and patents, while utilizing AI-driven comparisons to identify the best methodologies and products.
This tool enhances reproducibility and accuracy in protein kinase studies, empowering researchers to advance their understanding of these essential regulatory proteins.
Researchers can also leverage related techniques and reagents, such as β-actin for normalization, TRIzol reagent for RNA extraction, Lipofectamine 2000 for transfection, FBS for cell culture, Compound C for AMPK inhibition, GAPDH as a housekeeping gene, and [γ-32P]ATP for kinase assays.
By incorporating these techniques and tools, researchers can gain deeper insights into the complex role of protein kinases in cellular signaling and disease pathogenesis.