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Dimerization

Dimerization is the process by which two identical molecules or subunits associate to form a dimer.
This process is common in biological systems and plays a crucial role in the regulation of many cellular processes.
Dimerization can affect the structure, function, and stability of proteins, enzymes, and other macromolecules.
Understanding the mechanisms and factors influencing dimerization is important for studying protein-protein interactions, drug development, and the design of novel biomaterical.
Researchers can leverage AI-driven platforms like PubComapre.ai to optimize dimerization protocols, enhace reproducibility, and identify the best products and approaches for their work.

Most cited protocols related to «Dimerization»

1
Fluorescent Protein-tagged Biosensors for RhoA Signaling
Mammalian expression vectors are all based on pEGFP-C1 plasmids (Clontech), in which EGFP was replaced by the YFP variant mVenus. The red fluorescent protein monomeric Cherry (mCherry) was used as RFP variant in this paper.
PCR products were ligated into mVenus-C1 plasmids by cutting the vector and PCR product with restriction enzymes BsrGI and KpnI. Restriction sites are marked in bold in primer sequences. In all cases, full length p63RhoGEF16 (link) was used as a template for PCR. To construct YFP-cDH (amino acid 155–347 of p63RhoGEF), p63RhoGEF was amplified using forward primer 5′- GCTGTACAAGTCCAAGAAGGCTCTGGAAAGG-3′ and reverse primer 5′ - ACGGTACCTTAGCCCTCAAATCCCCGCAA-3′. To construct YFP-pmDH (amino acid 1-347 of p63RhoGEF), p63RhoGEF was amplified using forward primer 5′ - GCTGTACAAGTCCCGGGGGGGGCACAAAGGG-3′ and reverse primer 5′-ACGGTACCTTAGCCCTCAAATCCCCGCAA-3′.
RFP variants of these constructs were made by color swapping the mVenus with mCherry with restriction enzymes AgeI and BsrGI.
The RFP-p63RhoGEF and RFP-p63RhoGEF1 (link)2 (link)3 (link)4 (link)5 (link)6 (link)7 (link)8 (link)9 (link)10 11 (link)12 (link)13 (link)14 (link)15 (link)16 (link)17 (link)18 (link)19 (link)20 (link)21 (link)22 (link)23 (link)24 (link)25 (link)26 (link)27 (link)28 (link)29 (link) (amino acid 1–29 of p63RhoGEF) were obtained by cutting the mVenus variants described earlier20 (link) with AgeI and BsrGI and exchanging mVenus for mCherry.
RFP-FKBP12-C1 was obtained as previously described20 (link).
The RFP-FKBP12-cDH was obtained by cutting RFP-FKBP12-C1 with MfeI and Acc651 and inserting the DH domain cut from the RFP-cDH vector with MfeI and BsrGI. A schematic overview of the constructs is depicted in Supplemental Fig. S1.
A Dimerization Optimized Reporter for Activation (DORA) single-chain RhoA biosensor was constructed such that GTP-loading of RhoA is translated into fluorescent protein heterodimerization, thereby increasing FRET.
The DORA-RhoA coding sequence within a pTriEx backbone is MAHHHHHHGSGS-cpPKN-GTGS-cpV-L9H-L9H-L9H-GS-Cer3(1–229)-AS-RhoA. The lay-out is analogous to a previously published RhoA probe21 (link), retaining regulation by Rho GDIs. Introducing the Q63L mutation in RhoA, locking RhoA in the GTP-bound state and mutating PKN1 (L59Q), preventing binding of RhoA, respectively, resulted in constitutive active (RhoAsensor-ca) and non-binding (RhoAsensor-nb) sensors. The detailed development of the sensor will be described elsewhere.
pTriExRhoA1G and pTriExRhoA2G (Addgene plasmid # 40176) were a gift from Olivier Pertz.
EGFP-MKL2 was a kindly provided by J.S. Hinson33 (link). We swapped the EGFP for mVenus with restriction enzymes AgeI and BsrGI.
The Lck-FRB-ECFP (W66A) and Lck-FRB-ECFP were a kind gift from M. Putyrski51 (link), FRB-YFP-Giantin and CFP-FRB-MoA were a kind gift from T. Inoue52 (link). We swapped the YFP in FRB-YFP-Giantin for ECFP (W66A) with restriction enzymes AgeI and BsrGI. We swapped the CFP in CFP-FRB-MoA for ECFP (W66A) with restriction enzymes NheI and BsrGI. A bacterial expression plasmid RSET-YCam 3.6 was a kind gift of A.Miyawaki36 (link). To enable expression in eukaryotic cells we cut the YCam 3.6 coding sequence from the plasmid with NheI and EcoRI and inserted the fragment in a Clontech-style pEGFP-C1 plasmid, cut with the same enzymes.
van Unen J., Reinhard N.R., Yin T., Wu Y.I., Postma M., Gadella T.W, & Goedhart J. (2015). Plasma membrane restricted RhoGEF activity is sufficient for RhoA-mediated actin polymerization. Scientific Reports, 5, 14693.
Publication 2015
Amino Acids Bacteria Biosensors Cloning Vectors Deoxyribonuclease EcoRI Dimerization DNA Restriction Enzymes Enzymes Eukaryotic Cells Fluorescence Resonance Energy Transfer macrogolgin Mammals MKL2 protein, human Mutation Oligonucleotide Primers Open Reading Frames Plasmids Proteins Prunus cerasus red fluorescent protein rho-Specific Guanine Nucleotide Dissociation Inhibitors RHOA protein, human Tacrolimus Binding Protein 1A Vertebral Column
2
Constructing CKAR FRET Biosensor
CKAR was generated in the mammalian expression vector pcDNA3.1(+) (Invitrogen). CFP was amplified by PCR from a plasmid template to encode a HindIII restriction site followed by a consensus initiation site for translation (CGCCACC) (Kozak, 1987 (link)) before the initiating ATG of CFP, and a KpnI restriction site at the 3′ end instead of a terminating codon. FHA2, a gift from Michael Yaffe (Massachusetts Institute of Technology, Cambridge, MA) was amplified by PCR to include KpnI and BamHI restriction sites at the 5′ and 3′ ends, respectively. Citrine, our preferred version of YFP (Griesbeck et al., 2001 (link)), was amplified by PCR to include a 5′ BamHI followed by the PKC substrate sequence and a 3′ XbaI following the terminating codon. These pieces were cloned into pcDNA3.1 and confirmed by sequencing.
A parallel construct was made including the mutation A206K in both CFP (mCFP) and citrine (mYFP) to reduce the intrinsic homoaffinity of all GFPs (Zacharias et al., 2002 (link)) and preclude intermolecular FRET by CFP-mYFP dimerization. This construct was shown to function as well as the original CKAR and so was used for all experiments. For in vitro experiments, CKAR was amplified to include a 5′ BglII site and a 3′ SalI site and cloned into pRSETB (Invitrogen) cut from BamHI to XhoI. MyrPalm-CKAR was generated by the addition of a HindIII restriction site, a consensus translational initiation site, and the 5′ 30 bp of Lyn kinase to the 5′ end of CKAR. This sequence encodes for myristoylation and palmitoylation, shown previously to be sufficient to target a protein to the plasma membrane (Zacharias et al., 2002 (link)).
Violin J.D., Zhang J., Tsien R.Y, & Newton A.C. (2003). A genetically encoded fluorescent reporter reveals oscillatory phosphorylation by protein kinase C. The Journal of Cell Biology, 161(5), 899-909.
Publication 2003
Cloning Vectors Codon Dimerization Fluorescence Resonance Energy Transfer Green Fluorescent Proteins Mammals Mutation Palmitoylation Phosphotransferases Plasma Membrane Plasmids Protein Biosynthesis Staphylococcal Protein A Transcription Initiation Site
3
Comprehensive Profiling of BRD4 Regulation

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Publication 2017
Animals Apoptosis Biological Assay Cell Cycle cereblon protein, human Chromatin Immunoprecipitation Sequencing DDB1 protein, human Dimerization DNA Chips DNA Library Genome Immunoprecipitation Immunoprecipitation, Chromatin Luciferases Psychological Inhibition Xenografting
4
Housekeeping Gene Selection and Primer Design
Ten housekeeping genes were selected from commonly used reference genes (ABL1, ACTB, B2M, GAPD, GNB2L1, HRPT1, PBGD, RPL32, TBP, and TUBB). Gene symbols and their full names, gene accession numbers as well as functions are listed in Table 1. These genes were chosen because they have different functions in order to avoid genes belonging to the same biological pathways that may be co-regulated. In selecting the genes to be analyzed, preference was given to pseudogene-free genes in the NCBI linked database (Table 1). All the primers were designed by the software, Primer 3, . Hairpin structure and primer dimerization were analyzed by NetPrimer. Primers spanning at least one intron were chosen to minimize inaccuracies due to genomic DNA contamination. The length of the primers was from 18-mer to 22-mer, GC content was from 45% to 60%, and the expected PCR products range from 114 bp to 318 bp. If the genes have pseudogenes, primers were chosen according to the alignment results between the genes and the pseudogenes, so that the primers were unique to the genes and different from the pseudogenes (Table 2).
Zhang X., Ding L, & Sandford A.J. (2005). Selection of reference genes for gene expression studies in human neutrophils by real-time PCR. BMC Molecular Biology, 6, 4.
Publication 2005
Biopharmaceuticals Dimerization DNA Contamination Genes Genes, Housekeeping Genome Glyceraldehyde-3-Phosphate Dehydrogenases Hyperparathyroidism 1 Introns Oligonucleotide Primers Pseudogenes
5
Hippocampal ERK-Dependent Memory Modulation
Cyclodextrin-encapsulated 17β-estradiol (E2; Sigma, St. Louis, MO) at a dose of 0.2 mg/kg was dissolved in physiological saline in a volume of 4 ml/kg, and injected intraperitoneally (i.p.). This dose in mice facilitates object memory consolidation in the task used here (Gresack and Frick, 2004 (link), 2006 (link)). The vehicle, hydroxypropyl-β-cyclodextrin (HBC), was dissolved in an equal volume of saline and contained the same amount of cyclodextrin as E2. The MEK inhibitor SL327 (α-[Amino[(4-aminophenyl)thio]methylene]-2-(trifluoromethyl) benzeneacetonitrile; Sigma), at a dose of 30 mg/kg, was dissolved in 100% dimethyl sulfoxide (DMSO) and injected i.p. in a volume of 2.0 ml/kg. Vehicle controls received HBC or both HBC and DMSO. For intrahippocampal (IH) infusions, physiological saline or cyclodextrin-encapsulated E2 dissolved in physiological saline (5.0 μg/0.5μl) was infused at 0.5 μl/min for 1 minute.
To demonstrate that E2-induced increases in object recognition were dependent on dorsal hippocampal ERK activation, other mice received IH infusions of vehicle or the MEK inhibitor U0126 (1,4-Diamino-2,3-dicyano-1,4-bis (o-aminophenylmercapto) butadiene; 2.0 μg/μl; Sigma) concurrently with i.p. E2 injection or intracerebroventricular (ICV) infusion of bovine serum albumin-conjugated 17β-estradiol (see below) into the dorsal third ventricle. U0126 was dissolved in 100% DMSO to 4 μg/μl as a stock solution and then serially diluted in physiological saline for infusion of various doses. U0126 or vehicle (50% DMSO) were infused at a rate of 0.50 μl/min and a volume of 0.50 μl/side. Other mice received ICV infusions of vehicle or bovine serum albumin-conjugated 17β-estradiol (β-Estradiol 6-(O-carboxy-methyl)oxime; BSA-E2; Sigma). The covalent conjugation of E2 to the large BSA molecule prevents E2 from passing through the cell membrane and binding to intracellular ERs (Taguchi et al., 2004 (link)). Thus, effects of BSA-E2 should be mediated by membrane-bound ERs. BSA-E2 was dissolved in Tris-HCl to a concentration of 5.0 μM. Either 5.0 μM BSA-E2 or vehicle (Tris-HCl) was infused at a rate of 0.5 μl/min at a volume of 1.0 μl.
To demonstrate that the effects of BSA-E2 on memory and ERK activation were independent of nuclear estrogen receptors, other mice received ICV infusions of BSA-E2 conducted as described above concurrently with IH infusions of the nuclear estrogen receptor antagonist ICI 182,780 ((7a,17b)-7-[9[(4,4,5,5,5pentafluoropentyl) Sulfinyl]nonyl]estra-1,3,5(10)-triene-3,17-diol; 10 μg/μl; Sigma). ICI 182,780 is an antagonist of ERα and ERβ that impairs E2-induced ER dimerization (Weatherman et al., 2002 (link)) and translocation of ERs into the cell nucleus (Dauvois et al., 1993 (link)). If ICI 182,780 does not block the effects of BSA-E2 on memory and ERK activation, then this would indicate that these effects are mediated by membrane-associated estrogen receptors rather than nuclear receptors. Intrahippocampal infusions of ICI 182,780 were conducted at a rate of 0.5 μl/min and a volume of 0.5 μl/side, resulting in a dose of 5.0 μg/side. In other mice, ICI 182,780 was infused intrahippocampally without concurrent ICV infusion as a control due to a report that this compound in female rats can act as an estrogen receptor agonist to enhance place learning when administered in the absence of E2 (Zurkovsky et al., 2006 (link)). To compare effects of ICI 182,780 with those of traditional E2, 0.2 mg/kg E2 was administered i.p. either alone or with ICI 182,780 infused intrahippocampally. The E2 + IH ICI 182,780 group also served as a control for the effectiveness of the ICI compound in blocking the effects of traditional, non-BSA conjugated E2 on object memory consolidation and ERK activation. Vehicle controls for the aforementioned groups received ICV and IH infusions of saline or BSA dissolved in saline.
Finally, to demonstrate that the effects of BSA-E2 on memory and ERK activation involved the dorsal hippocampus, BSA-E2 was infused bilaterally into the dorsal hippocampus of another set of mice. Intrahippocampal infusions were conducted at a rate of 0.5 μl/min and at a volume of 0.5 μl/side, resulting in doses of 5.0 μM/side. As a control, these mice also received ICV infusions of vehicle (BSA dissolved in saline). Additional mice received ICV BSA-E2 + IH vehicle as a control to replicate the effects of ICV BSA-E2 observed above. As an additional method of demonstrating hippocampal involvement in the BSA-E2 effect, other mice received ICV infusions of BSA-E2 conducted as described above concurrently with IH infusions of the GABAA receptor agonist muscimol (3-Hydroxy-5-aminomethyl-isoxazole; 0.50 μg/μl dissolved in saline; Sigma). Muscimol temporarily inactivates a brain region of interest by increasing GABAergic inhibition without permanently damaging the tissue (Martin, 1991 (link)). Therefore, if muscimol interferes with the beneficial effects of ICV BSA-E2 on memory, then this would suggest critical involvement of the dorsal hippocampus in this effect. Intrahippocampal infusions of muscimol were conducted at the same rate and volume as above. Vehicle controls for all of the aforementioned groups received ICV and IH infusions of saline or BSA dissolved in saline.
Injection cannulae for IH and ICV infusions remained in place for 1 minute after infusion to prevent drug diffusion up the injection track. For behaviorally tested mice, all solutions were administered immediately after the sample phase of object recognition training.
Fernandez S.M., Lewis M.C., Pechenino A.S., Harburger L.L., Orr P.T., Gresack J.E., Schafe G.E, & Frick K.M. (2008). Estradiol-Induced Enhancement of Object Memory Consolidation Involves Hippocampal Extracellular Signal-Regulated Kinase Activation and Membrane-Bound Estrogen Receptors. The Journal of Neuroscience, 28(35), 8660-8667.
Publication 2008
1,3-butadiene Brain Cannula carbene Cell Nucleus Cyclodextrins Diffusion Dimerization Estradiol estradiol-bovine serum albumin Estrogen Nuclear Receptor estrogen receptor alpha, human Estrogen Receptor Antagonists Females GABA-A Receptor Agonists GPER protein, human Hypromellose ICI 182780 Infusions, Intracerebroventricular Isoxazoles Memory Memory Consolidation Mus Muscimol Oximes Pharmaceutical Preparations physiology Plasma Membrane Protoplasm Psychological Inhibition Rattus Receptors, Nuclear Saline Solution Seahorses Serum Albumin, Bovine Sulfoxide, Dimethyl Tissue, Membrane Tissues Translocation, Chromosomal Tromethamine U 0126 Ventricles, Third

Most recents protocols related to «Dimerization»

1
Targeting Myc Transcription Factor for Anti-Cancer Therapy
Not available on PMC !

Example 10

Myc encodes a helix-loop-helix transcription factor upregulated in 50-80% of human cancers and is associated with 100,000 US cancer deaths per year. Myc heterodimerizes with its partner Max to control target gene transcription and is deeply integrated into the regulatory and control mechanisms governing cell viability and proliferation. A recent estimate suggests that Myc binds to approximately 25,000 regions in the human genome. The loss of Myc proteins inhibits cell proliferation and growth, accelerates differentiation, increases cell adhesion, and accentuates the response to DNA damage.

We believe that Myc is an ideal target for anti-cancer therapeutics, particularly MM in which it is highly overexpressed by selective disruptive interference of Myc-Max dimerization while permiting Myc-Mad interactions.

FIG. 28 illustrates that an αvβ3 targeted particle comprising a myc prodrug reduces SMC proliferation. Human coronary smooth muscle cells were plated on cover slips (2500 cells) and incubated 2 hours. Each treatment was replicated 6 times. The intramural delivery of an αvβ3 targeted particle comprising a myc prodrug, alone or with stents, offers an attractive new approach to restenosis.

US11872313B2. Prodrug compositions, prodrug nanoparticles, and methods of use thereof (2024-01-16). Washington University [US]. Inventors: Gregory M. Lanza [US], Dipanjan Pan [US].
Patent 2024
Cardiac Arrest Cell Adhesion Cell Proliferation Cells Cell Survival Dimerization DNA Damage Genome, Human Heart Homo sapiens Malignant Neoplasms Myocytes, Smooth Muscle Obstetric Delivery Prodrugs Proteins Stents Transcription, Genetic Transcription Factor
2
Characterization of MATCH Chain Dimerization
Not available on PMC !

Example 3

Efficient MATCH chain dimerization was further demonstrated by the remarkable homogeneity of the protein content in protein L-purified samples. The protein was analyzed over the course of four weeks and storage at 4° C. and 37° C. with respect to oligomerization by SE-HPLC and degradation by SDS-PAGE (see FIGS. 7 to 9). Prior to the study the sample concentration was adjusted to 1 g/L and t0 time points were determined. The monomer content was quantified by separation of the samples on a Shodex KW-402.5-4F (Showa Denko) and evaluation of the resulting chromatograms. For the calculation of the relative percentage of protein monomer the area of the monomeric peak was divided by the total area of peaks that could not be attributed to the sample matrix. The protein degradation was assessed by SDS-PAGE analysis with Any kD Mini-Protean TGX gels (Bio-Rad Laboratories) and stained with Coomassie brilliant blue. The protein concentration was monitored at the different time points by UV-Vis spectroscopy with an Infinity reader M200 Pro equipped with Nanoquant plate (Tecan Group Ltd.).

US11879005B2. Hetero-dimeric multi-specific antibody format (2024-01-23). Numab Therapeutics AG [CH]. Inventors: Sebastian Meyer [CH], David Urech [CH].
Patent 2024
brilliant blue G Dimerization Figs Gels High-Performance Liquid Chromatographies M-200 Proteins Proteolysis SDS-PAGE Spectrum Analysis
3
Ovine-specific SARS-CoV-2 Antigen Designs

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Publication 2023
Amino Acids Amino Acid Sequence Antigens Base Sequence Consensus Sequence Densitometry Dietary Supplements Dimerization DNA, Complementary Enzyme-Linked Immunosorbent Assay Granulocyte-Macrophage Colony-Stimulating Factor IgG2 IgG2A Immunization Mutation Ovalbumin Protein C Protein Dimerization Proteins Rabbits SARS-CoV-2 SDS-PAGE Sheep Signal Peptides
4
Receptor Dimerization Dynamics in Silico
Simulations were performed in NetLogo 6.2.2 (Supplementary Figure S1), using the algorithm illustrated in Fig. 2 (for details see Supplementary Figure S2). A list of simulation parameters per research question is provided in Table 2. The default start setting was 47 receptor monomers that were uniformly distributed in a box representing the plasma membrane. Of note, this default did not take into account the heterogeneities caused by membrane cytoskeletal connections and receptor complexes, although the model may reach a non-uniform equilibrium after the simulation. Based on the calculations above, the diameter of GPVI was approximated as 3.8% of the length of the simulation box (scaled as 30 × 30 pixels). The movement speed of monomers was set to D½. Each simulation was run for ≥ 200,000 steps to ensure equilibrium. An average of the last 50,000 steps was used for the analysis.

List of parameters used in each simulation. CD, confined domain. Please note in this context, kd and kb are implemented as a rate in unit time as described in the “Methodology” section.

Simulation typeBinding rate (kb) (per molecule per unit time)Dissociation rate (kd) (per unit time)Diffusivity outside CD (Do) (unit lenght2 per unit time)Diffusivity inside CD (Di) (unit lenght2 per unit time)CD occupied area (%)Number of added inert proteins (molecule)Number of inert protein packs (dimensionless)Fold number of CD merging (dimensionless)GPVI number per platelet (% of 9600)
1. Receptors in CD area vs Di0011,2−1…,2−9,2−1035001100
2. Dimerisation (with CD) vs Di0.050.0111,2−1…,2−9,2−1035001100
3. Dimerisation vs %CD & Di0.050.0111,2−1…,2−4,2−50,5…,75,80001100
4. Dimerisation vs CD merging0.050.0110.135000.5,1…,7.5,8100
5. Added inert proteins0.050.011100,25…,175,2000,25…,175,2001100
6. Disintegrated inert proteins0.050.011101001,21…,27,281100
7. Dimerisation (w/o CD) vs D0.050.012−5,2−4…,24,2510001100
8. Receptors in CD area vs %CD0, 0.01, 0.005, …, 0.000625kb/510.115,16,…,22001100
9. Dimerisation vs receptor number0.050.0110.13500125, 50, …, 150, 175, 200
10. Dimerisation vs kb & kd60, 70, …, 130, 140% of 0.0560, 70, …, 130, 140% of 0.0110.135001100
Except where indicated otherwise, binding and dissociating probabilities were arbitrarily defined as kb = 0.05 molecule–1 per unit time and kd = 0.01 per unit time (or per timestep, dt ~ 0.43 ms as calculated above). These numbers were chosen to ensure balancing of the time scale of dimerisation and dissociation, i.e., to prevent an equilibrium without dimers or monomers. This also ensured that the number of GPVI molecules in dimeric form in the simulations were broadly consistent with the dimeric levels measured experimentally26 (link). The impact of variation of these parameters is shown in the results (see “Simulation of ligand binding increases GPVI dimerisation”). All simulations were repeated three times. The code for this model, together with the setup for each simulation, is available in the Supplement.
Tantiwong C., Dunster J.L., Cavill R., Tomlinson M.G., Wierling C., Heemskerk J.W, & Gibbins J.M. (2023). An agent-based approach for modelling and simulation of glycoprotein VI receptor diffusion, localisation and dimerisation in platelet lipid rafts. Scientific Reports, 13, 3906.
Publication 2023
Cytoskeleton Dietary Supplements Diffusion Dimerization Genetic Heterogeneity Ligands Movement Plasma Membrane Platelet Counts, Blood Proteins Tissue, Membrane
5
Simulating Receptor Dynamics on Cell Membranes
An ABM approach was used to simulate agents (receptors and lipids) on the cell surface31 (link). This approach has been used in different fields of physical science, biological science, social science, and finances32 (link). For example, several recently published works used ABM to study the spreading of the COVID-19 pandemic33 (link)–35 (link). There are several ways to implement ABM, either by coding the model from scratch or using existing software. A commonly used ABM software package is NetLogo, which is multi-purpose, computationally efficient and easy to use, offering the advantage of being easily implemented and modified by non-theoretical experimentalists36 . Using NetLogo, we simulated the diffusion of receptors in a two-dimensional plasma membrane. The implementation of this is demonstrated in Fig. 2A-D, and a flowchart is provided in the Supplement. The generated models can be easily modified to model different kinds of receptors and transmembrane proteins, by adjusting properties such as size, mass and diffusivity. To ease this modification, the code to run simulations is made available, and details on how to install and implement it are given in the Supplement. In our ABM approach, receptors are able to move with an assigned behaviour, which is either deterministic or stochastic as modelled. Certain areas of the plasma membrane were considered as confined areas with reduced diffusivity. By default, components in the system were studied in a two-dimensional box with periodic boundary conditions to imitate an infinite membrane37 (link).

Overview of ABM simulation procedure. (A) The target system, i.e. the platelet membrane. The simplified version of a membrane consists of two areas, i.e. parts where molecules are confined in movements (confined domains), and the remaining part where they move freely (Brownian motion). In addition to inert proteins, the receptors of interest are indicated as transmembrane proteins. (B) Application of ABM to target receptor dimerisation. The membrane in the simulation box consists of agents (receptor molecules) in monomeric or dimeric forms and inert proteins. The confined domains are considered to represent lipid rafts. All agents are treated as independent, of which mathematical rules determine their properties and interactions. (C) Assignment of agent parameters. The simulation parameters included diffusivity, particle size and step size. (D) Rules for agent movements. Each simulation step consists of a randomly placed agent with random walk (rejected in case of overlapping), dimerisation and dissociation. Steps are repeated until all agents are selected, after which movements follow.

Tantiwong C., Dunster J.L., Cavill R., Tomlinson M.G., Wierling C., Heemskerk J.W, & Gibbins J.M. (2023). An agent-based approach for modelling and simulation of glycoprotein VI receptor diffusion, localisation and dimerisation in platelet lipid rafts. Scientific Reports, 13, 3906.
Publication 2023
Blood Platelets Cells COVID 19 Dietary Supplements Diffusion Dimerization Familial Mediterranean Fever Integral Membrane Proteins Lipids Movement Plasma Membrane Proteins Tissue, Membrane

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More about "Dimerization"

Dimerization is a crucial biological process where two identical molecules or subunits associate to form a dimer.
This phenomenon is prevalent in various cellular systems and plays a pivotal role in regulating numerous cellular functions.
The dimerization of proteins, enzymes, and other macromolecules can significantly impact their structure, function, and stability.
Understanding the mechanisms and factors influencing dimerization is essential for studying protein-protein interactions, drug development, and the design of novel biomaterials.
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In addition to dimerization research, researchers may also find value in other molecular biology tools and techniques.
For instance, the IScript cDNA Synthesis Kit and RNeasy Mini Kit from Qiagen can facilitate RNA extraction and cDNA synthesis, while AP20187 and Lipofectamine 2000 from Thermo Fisher Scientific can be used for cell signaling and transfection studies.
The ITaq Universal SYBR Green Supermix from Bio-Rad and the 7500 Fast Real-Time PCR System from Applied Biosystems can be utilized for qPCR analysis.
Furthermore, compounds like Rapamycin and growth factors such as FBS (Fetal Bovine Serum) may play a role in regulating cellular processes related to dimerization.
The X-tremeGENE 9 DNA Transfection Reagent from Roche can also be employed for efficient gene delivery and expression studies.
By leveraging the insights from PubCompare.ai and incorporating relevant molecular biology tools and techniques, researchers can optimize their dimerization studies, enhance reproducibility, and drive their research forward with increased efficiency and accuracy.