PRMT3 Human

What is PRMT3 and what is its primary function in human cells?

PRMT3 belongs to the family of type I protein arginine N-methyltransferases that catalyze the asymmetric dimethylation of arginine residues on target proteins. It primarily functions as a methyltransferase that uses S-adenosyl-L-methionine (SAM) as a methyl-donor cofactor for protein arginine labeling . PRMT3 is predominantly localized in the cytoplasm, though its substrates have been found in various cellular compartments, suggesting broad regulatory roles .
The enzyme contains a conserved catalytic core with two characteristic motifs: a substrate-interacting motif (featuring a double-Glu loop and THW loop for substrate recognition) and a SAM binding motif . PRMT3's methyltransferase activity plays crucial roles in multiple cellular processes, including cytoskeleton dynamics, protein synthesis regulation, and metabolic reprogramming in cancer cells .

How does PRMT3 differ from other members of the PRMT family?

While PRMT3 shares catalytic domain similarities with other type I PRMTs (PRMT1, 2, 4, 6, and 8), it possesses distinct structural features and substrate preferences. Unlike other family members, PRMT3 contains a zinc finger domain at its N-terminus, which contributes to its substrate recognition specificity, particularly for ribosomal proteins .
Regarding cofactor recognition, PRMT3 exhibits different patterns of SAM analogue processing compared to PRMT1. For instance, while both PRMT1's M48G and PRMT3's M233G mutations enable recognition of bulky SAM analogues, the Y39FM48G double mutant of PRMT1 shows higher activity with Pob-SAM than its single mutant, a pattern not observed in the corresponding PRMT3 mutations . This indicates that despite structural similarities in their SAM-binding pockets, these enzymes recognize transalkylation cofactors differently.

What are the primary cellular substrates of PRMT3?

Through Bioorthogonal Profiling of Protein Methylation (BPPM) approaches, more than 80 novel protein substrates of PRMT3 have been identified in cellular contexts . The ribosomal protein rpS2 (40S ribosomal protein S2) was the first validated PRMT3 substrate, but recent studies have expanded this substrate repertoire significantly .
Validated PRMT3 substrates include:

What techniques are most effective for studying PRMT3 substrate specificity?

When investigating PRMT3 substrate specificity, researchers can employ several complementary approaches:

• Bioorthogonal Profiling of Protein Methylation (BPPM): This innovative approach uses engineered methyltransferases and SAM analogues for target identification. For PRMT3, the M233G mutant variant combined with 4-propargyloxy-but-2-enyl (Pob)-SAM analogue has proven highly effective in identifying novel substrates . The methodology typically involves:

  • Transfecting cells with engineered PRMT3 (M233G variant)

  • Treating cells with adenosine-2',3'-dialdehyde (AdOx) to induce hypomethylation

  • Processing cell lysates with RNase

  • Incubating lysates with Pob-SAM followed by chemically-cleavable azido-azo-biotin probes

  • Affinity enrichment with streptavidin and selective cleavage

  • Mass spectrometry analysis of released proteins

• In vitro methylation assays: Using recombinant PRMT3 and radiolabeled SAM ([3H]SAM) or antibodies detecting methylated arginine residues (anti-MMA or anti-aDMA) to validate direct methylation of candidate substrates .

• MS-based approaches: Utilizing high-resolution mass spectrometry to identify specific methylation sites on substrates, often combining immunoprecipitation with targeted MS analysis.
  For validation of methylation events, western blotting with antibodies specific for monomethylarginine (MMA) and asymmetric dimethylarginine (aDMA) provides confirmation of PRMT3-mediated modifications .

How can researchers effectively manipulate PRMT3 activity in experimental settings?

Several approaches are available for modulating PRMT3 activity in experimental systems:

• Genetic manipulation:

  • siRNA or shRNA-mediated knockdown has been successfully employed in various cell types, showing significant effects on cell proliferation and migration, particularly in glioblastoma cell lines and glioblastoma stem cells (GSCs)

  • CRISPR/Cas9-mediated knockout for complete elimination of PRMT3 expression

  • Overexpression systems using wild-type PRMT3 or catalytically dead mutants (e.g., deletion of 37 amino acids in the C-terminal region)

• Pharmacological inhibition:

  • The PRMT3-specific inhibitor SGC707 has demonstrated efficacy in impairing GBM cell growth

  • Adenosine-2',3'-dialdehyde (AdOx), a global methyltransferase inhibitor, can be used to generate hypomethylated proteomes for studying methylation-dependent processes

• Engineering cofactor specificity:

  • Point mutations in the SAM binding pocket, particularly M233G, can create PRMT3 variants with altered cofactor specificity, useful for studying selective methylation events

  • These engineered variants can be expressed in cells to study substrate methylation with minimal disruption of endogenous PRMT3 function
    When designing PRMT3 manipulation experiments, researchers should carefully consider cell type-specific effects and potential compensatory mechanisms by other PRMTs, as these enzymes often have overlapping substrate specificities .

What are the recommended protocols for purifying active PRMT3 protein for in vitro studies?

For obtaining active PRMT3 protein for in vitro studies, the following protocol is recommended:

• Expression system selection:

  • E. coli BL21(DE3) strain typically yields good expression of recombinant human PRMT3

  • Mammalian expression systems (HEK293T cells) may provide better post-translational modifications but lower yield

• Construct design:

  • Full-length human PRMT3 cDNA (amino acids 1-531) cloned into a bacterial expression vector with an N-terminal His-tag or GST-tag

  • For studying specific domains, constructs containing the catalytic domain (amino acids 211-531) can be generated

• Purification procedure:

  • Affinity chromatography using Ni-NTA or glutathione sepharose for His- or GST-tagged proteins, respectively

  • Ion exchange chromatography (typically Q-Sepharose) as a secondary purification step

  • Size exclusion chromatography for final polishing and buffer exchange

• Quality control:

  • Enzymatic activity verification using a standard methylation assay with [3H]SAM and a known substrate (e.g., rpS2)

  • Western blot analysis to confirm automethylation, which indicates proper folding and activity
    Note that PRMT3 purified from bacterial systems may contain endogenous SAM, which can result in background methylation. Researchers should account for this by including negative controls without additional SAM in activity assays .

How does PRMT3 contribute to cancer progression, particularly in glioblastoma?

PRMT3 plays significant roles in glioblastoma (GBM) progression through several mechanisms:

What role does PRMT3 play in bone homeostasis and related disorders?

PRMT3 serves as an essential regulator of mesenchymal stem cell (MSC)-mediated osteogenesis and bone homeostasis:

• Osteogenic differentiation: PRMT3 expression is strongly induced during osteoinductive culture of human MSCs, along with upregulation of the osteogenic marker RUNX2 .

• Histone methylation patterns: PRMT3 promotes osteogenic differentiation of MSCs by increasing H4R3me2a (histone H4 asymmetric dimethylarginine 3) levels in specific genomic regions:

  • Particularly in regions 343 bp upstream and 505 bp downstream of the transcription starting site (TSS) of miR-3648

  • These regions likely function as promoters regulating osteogenic pathways

• Bone loss correlation: PRMT3 deficiency contributes to bone loss in mice, suggesting its potential involvement in osteoporotic conditions .

• Methyltransferase activity requirement: The catalytic activity of PRMT3 is essential for its role in osteoblastic commitment, as demonstrated by:

  • Reduced H4R3me2a expression levels in PRMT3 knockdown cells

  • Failure of catalytically dead PRMT3 mutants (with deletion of 37 amino acids in C-terminal) to rescue osteogenic defects

• Disease models: In ovariectomized (OVX) mouse models that exhibit reduced trabecular area in femurs (mimicking postmenopausal osteoporosis), PRMT3 expression patterns are altered in bone marrow-derived MSCs, suggesting potential therapeutic relevance .
  These findings collectively suggest that targeting PRMT3 might represent an effective therapeutic strategy for bone metabolic diseases and in bone regenerative medicine .

How can the BPPM technique be optimized for identifying novel PRMT3 substrates?

The Bioorthogonal Profiling of Protein Methylation (BPPM) technique can be optimized for PRMT3 substrate identification through several strategic modifications:

• Engineered enzyme optimization:

  • While the M233G single mutation has been identified as the most promiscuous PRMT3 variant for processing sp²-β-sulfonium-containing SAM analogues, further engineering of adjacent residues in combination with M233G may yield variants with enhanced activity for specific substrate classes

  • Systematic exploration of the SAM-binding pocket through mutations of Tyr224, Ile229, His230, Met233, Tyr243, and Met340 into smaller hydrophobic residues (Gly, Ala, Val), larger hydrophobic residues (Trp), or polar residues (Ser, Thr, Asn, Gln) can yield variants with distinct specificities

• SAM analogue selection:

  • Pob-SAM (4-propargyloxy-but-2-enyl-SAM) has proven effective for PRMT3 substrate labeling

  • Testing additional SAM analogues with varying bulkiness and chemical properties may reveal substrate subsets missed by Pob-SAM

• Cell preparation enhancements:

  • Treating cells with adenosine-2',3'-dialdehyde (AdOx) to induce a hypomethylated proteome increases the detection sensitivity

  • Processing cell lysates with RNase has been shown to be beneficial for uncovering cellular substrates of PRMT3, particularly for RNA-associated substrates

  • Subcellular fractionation before BPPM can help identify compartment-specific substrates

• Click chemistry optimization:

  • Using chemically-cleavable azido-azo-biotin probes enables selective enrichment and gentle elution of labeled proteins

  • Comparing multiple cleavable linker chemistries can improve recovery efficiency

• Control strategies:

  • Empty-vector-transfected cells processed similarly to experimental samples help reveal background labeling, which may arise from nonspecific reactions between Pob-SAM and reactive cysteines

  • Including catalytically dead PRMT3 mutants as additional controls helps distinguish enzyme-dependent methylation events
    By implementing these optimizations, researchers can enhance the sensitivity and specificity of BPPM for comprehensive profiling of the PRMT3 substrate landscape across diverse cellular contexts.

What are the current strategies for developing selective PRMT3 inhibitors?

The development of selective PRMT3 inhibitors represents an important frontier in both basic research and potential therapeutic applications. Current strategies include:

• Structure-based design approaches:

  • Leveraging the crystal structure of human PRMT3 (e.g., PDB: 2FYT) complexed with S-adenosyl-L-homocysteine (SAH) to identify unique features of the PRMT3 cofactor binding pocket

  • Targeting the distinctive zinc finger domain at the N-terminus, which is unique to PRMT3 among PRMTs

  • Exploiting differences in the SAM-binding pocket between PRMT3 and other PRMTs, particularly around the Met233 residue and its surrounding amino acids

• Allosteric inhibitor development:

  • Identifying allosteric sites unique to PRMT3 that can be targeted without affecting other PRMTs

  • SGC707 represents a PRMT3-specific inhibitor that has demonstrated efficacy in impairing GBM cell growth

• Substrate-competitive inhibitors:

  • Designing peptide-mimetic compounds that compete with natural substrates in the PRMT3 active site

  • Focusing on the unique substrate recognition features of PRMT3, including the double-Glu loop and THW loop

• Fragment-based screening approaches:

  • Using fragment libraries to identify small molecules with binding affinity for PRMT3

  • Growing or linking fragments to develop high-affinity, selective inhibitors

• Validation strategies:

  • Cellular thermal shift assays (CETSA) to confirm target engagement

  • Monitoring H4R3me2a levels and other PRMT3-specific methylation events

  • Testing effects on validated PRMT3 substrates like rpS2, TUBA1C, and TPI1

  • Evaluating inhibitor specificity against a panel of other PRMTs to ensure selectivity
    Current challenges include achieving selectivity over other PRMTs (particularly type I PRMTs with similar catalytic mechanisms) and developing inhibitors with appropriate pharmacokinetic properties for in vivo studies and potential clinical applications in glioblastoma and other PRMT3-implicated disorders .

How do post-translational modifications of PRMT3 regulate its catalytic activity?

PRMT3 undergoes several post-translational modifications that modulate its catalytic activity, substrate specificity, and cellular functions:

• Automethylation:

  • PRMT3 has been demonstrated to undergo automethylation, joining PRMT1, PRMT4, PRMT6, and PRMT8 as type I PRMTs with self-methylation activity

  • This automethylation likely regulates PRMT3's catalytic activity and interactions with other proteins

  • Background methylation has been observed even in bacterially expressed PRMT3, suggesting this is a fundamental regulatory mechanism

• Phosphorylation:

  • While not explicitly detailed in the provided search results, phosphorylation represents a common regulatory mechanism for methyltransferases

  • Phosphorylation may influence PRMT3's subcellular localization, protein-protein interactions, and catalytic efficiency

• Regulation by protein-protein interactions:

  • PRMT3 activity can be modulated through interactions with regulatory proteins

  • These interactions may be dependent on post-translational modifications of either PRMT3 or its binding partners

• Subcellular localization effects:

  • Although primarily cytoplasmic, PRMT3 substrates are found in various cellular compartments (70% cytoplasmic, 23% nuclear/plasma membrane/extracellular)

  • Post-translational modifications likely regulate PRMT3's access to different subcellular compartments and substrate pools

• Cross-talk with other enzymes:

  • Potential interplay between PRMT3 and other arginine methyltransferases or demethylases may create complex regulatory networks

  • In contexts like glioblastoma progression, PRMT3's interaction with metabolic enzymes and HIF1α suggests regulatory connections between methylation and metabolic pathways
    Understanding these regulatory mechanisms is crucial for developing targeted approaches to modulate PRMT3 activity in research and therapeutic applications. Further studies employing phospho-proteomics, proximity labeling, and structural biology approaches would help elucidate the complete landscape of PRMT3 regulation by post-translational modifications.

What therapeutic opportunities exist for targeting PRMT3 in cancer treatment?

PRMT3 presents several promising therapeutic opportunities for cancer treatment, particularly for glioblastoma:

How might PRMT3 modulators be developed for bone disorders based on its role in osteogenesis?

Based on PRMT3's essential role in MSC-mediated osteogenesis and bone homeostasis, several approaches could be pursued to develop modulators for bone disorders:

• PRMT3 activators for osteoporosis:

  • Since PRMT3 deficiency contributes to bone loss in mice , small molecule activators could enhance PRMT3 methyltransferase activity

  • Structure-based drug design targeting allosteric sites that enhance catalytic efficiency

  • Developing stabilizers that increase PRMT3 protein levels or prevent its degradation

• Gene therapy approaches:

  • Localized delivery of PRMT3-expressing vectors to stimulate bone formation in areas of bone loss

  • CRISPR-based epigenetic activation of PRMT3 expression in MSCs

• MSC-based therapeutic strategies:

  • Ex vivo engineering of MSCs with optimized PRMT3 expression for bone regeneration applications

  • Combination of PRMT3-enhanced MSCs with biomaterial scaffolds for improved bone repair

• Targeting downstream pathways:

  • Developing compounds that mimic PRMT3's effects on H4R3me2a levels in the promoter regions of osteogenic genes

  • Modulating miR-3648 expression, as PRMT3 increases H4R3me2a levels in regions near its transcription start site

• Diagnostic applications:

  • Developing assays for PRMT3 activity or H4R3me2a levels as biomarkers for bone metabolism

  • Personalized medicine approaches based on PRMT3 expression patterns in patient-derived MSCs

• Combination therapies:

  • Integrating PRMT3 modulators with established osteoporosis treatments

  • For ovariectomy-induced bone loss (mimicking postmenopausal osteoporosis), combining PRMT3 activators with hormone replacement therapy might provide synergistic benefits
    These therapeutic strategies could address both degenerative bone disorders like osteoporosis and bone regeneration needs in trauma or surgical settings, offering new approaches in the field of bone metabolic disease treatment and regenerative medicine .

What are the considerations for balancing PRMT3 inhibition in cancer versus its normal physiological functions?

Developing PRMT3-targeted therapies requires careful consideration of the balance between inhibiting pathological processes and maintaining normal physiological functions:

• Tissue-specific targeting strategies:

  • Delivery systems that preferentially target cancer tissues, such as glioblastoma, while minimizing exposure to bone and other PRMT3-dependent tissues

  • Nanoparticle-based or antibody-drug conjugate approaches for tumor-specific delivery of PRMT3 inhibitors

• Dosing and scheduling optimization:

  • Intermittent dosing schedules that allow recovery of normal PRMT3 functions between treatment cycles

  • Determining the minimal effective dose that impacts cancer progression while preserving essential physiological roles

• Selective inhibition approaches:

  • Developing inhibitors that preferentially block PRMT3's interaction with cancer-specific substrates

  • Targeting PRMT3 in specific protein complexes relevant to cancer progression

  • Exploiting differences in PRMT3's function in cancer versus normal cells (e.g., targeting its role in HIF1α-mediated glycolysis)

• Combinatorial strategies:

  • Using lower doses of PRMT3 inhibitors in combination with other anti-cancer agents

  • Targeting compensatory pathways that become activated upon PRMT3 inhibition in normal tissues

• Risk assessment considerations:

  • Bone health monitoring during PRMT3 inhibitor treatment, given PRMT3's role in osteogenesis

  • Monitoring ribosomal function and protein synthesis, considering PRMT3's interaction with ribosomal proteins

  • Assessment of potential immune system effects, as PRMT3 may regulate cytoskeletal dynamics in immune cells

• Patient stratification:

  • Identifying patients with PRMT3-driven cancers who would benefit most from inhibitor therapy

  • Using biomarkers to predict patients at lower risk for adverse effects on bone metabolism
    By addressing these considerations through careful preclinical and clinical development, PRMT3-targeted therapies could provide meaningful benefits in cancer treatment while managing risks to normal physiological functions, particularly in contexts like glioblastoma where therapeutic options remain limited and the need for novel approaches is urgent .

What emerging technologies could advance our understanding of PRMT3 function?

Several cutting-edge technologies hold promise for deepening our understanding of PRMT3 function:

• Cryo-electron microscopy (Cryo-EM):

  • Visualizing PRMT3-substrate complexes at near-atomic resolution

  • Capturing dynamic conformational changes during the methylation process

  • Elucidating the structural basis of PRMT3's substrate specificity compared to other PRMTs

• Proximity-dependent biotinylation (BioID/TurboID):

  • Mapping the PRMT3 interactome in various cellular contexts

  • Identifying transient interactions with substrates and regulatory proteins

  • Comparing interactomes across normal and disease states (e.g., glioblastoma)

• Single-cell methylome analysis:

  • Characterizing cell-to-cell variation in PRMT3-mediated methylation patterns

  • Identifying cell subpopulations with distinct PRMT3 activity in heterogeneous tissues

  • Tracking changes in methylation during developmental processes or disease progression

• CRISPR-based epigenome editing:

  • Precisely modulating PRMT3 expression or activity in specific cellular contexts

  • Creating spatiotemporal patterns of PRMT3 activity to understand developmental roles

  • Determining the consequences of acute versus chronic PRMT3 modulation

• Advanced proteomics approaches:

  • Developing methyl-arginine-specific enrichment strategies for comprehensive substrate identification

  • Quantitative proteomics to measure dynamic changes in the PRMT3 substrate landscape

  • Integrating proteomics with phospho-proteomics to understand cross-talk between methylation and phosphorylation pathways

• Organoid and patient-derived xenograft models:

  • Testing PRMT3 modulators in complex 3D tissue environments

  • Evaluating the effects of PRMT3 manipulation in patient-derived cancer models

  • Developing bone organoid systems to study PRMT3's role in osteogenesis
    These technologies, particularly when used in combination, could provide unprecedented insights into PRMT3's structural properties, dynamic interactions, tissue-specific functions, and potential as a therapeutic target in various disease contexts.

How might artificial intelligence approaches contribute to PRMT3 research?

Artificial intelligence (AI) and machine learning (ML) approaches offer transformative potential for advancing PRMT3 research:

• Predictive substrate identification:

  • Developing ML algorithms to predict novel PRMT3 substrates based on sequence patterns, structural features, and protein-protein interaction networks

  • Training models on the >80 known PRMT3 substrates to identify common motifs and structural contexts

  • Integrating these predictions with experimental approaches like BPPM for efficient substrate discovery

• Structure-based drug design:

  • Using AI to design selective PRMT3 inhibitors or activators targeting unique features of the enzyme

  • Predicting binding modes and affinities of candidate compounds

  • Optimizing pharmacokinetic properties while maintaining target selectivity

• Multi-omics data integration:

  • Analyzing relationships between PRMT3 expression, substrate methylation, and downstream functional consequences

  • Identifying key nodes in PRMT3-regulated networks across different disease contexts

  • Uncovering unexpected connections between PRMT3 and other cellular pathways

• Patient stratification models:

  • Developing algorithms to identify patients who might benefit from PRMT3-targeted therapies

  • Predicting potential adverse effects based on molecular profiles

  • Creating personalized dosing strategies that balance efficacy and side effects

• Pathway modeling and simulation:

  • Simulating the effects of PRMT3 modulation on complex systems like glycolysis in cancer or osteogenesis in bone disorders

  • Predicting compensatory mechanisms and resistance pathways

  • Identifying optimal combination therapies that target PRMT3 alongside synergistic pathways

• Literature mining and knowledge extraction:

  • Automating the extraction of PRMT3-related information from the scientific literature

  • Identifying under-explored aspects of PRMT3 biology

  • Generating testable hypotheses based on existing knowledge
    By leveraging these AI/ML approaches, researchers could accelerate discovery, optimize experimental design, and develop more effective therapeutic strategies targeting PRMT3 in various disease contexts.

What are the most critical unresolved questions in PRMT3 biology?

Despite significant advances in PRMT3 research, several critical questions remain unresolved:

• Enzyme regulation:

  • How is PRMT3 activity regulated in different cellular contexts?

  • What are the complete patterns of post-translational modifications on PRMT3, and how do they affect its function?

  • Are there endogenous inhibitors or activators of PRMT3 that modulate its activity in vivo?

• Substrate selection mechanisms:

  • What determines PRMT3's substrate specificity compared to other PRMTs?

  • How does PRMT3 recognize such diverse substrates spanning cytoskeletal proteins, metabolic enzymes, and ribosomal components?

  • What role does the zinc finger domain play in substrate recognition beyond ribosomal proteins?

• Functional redundancy:

  • To what extent do other PRMTs compensate for PRMT3 deficiency?

  • Are there truly PRMT3-specific functions that cannot be performed by other family members?

  • What determines whether a substrate is exclusively methylated by PRMT3 or can be modified by multiple PRMTs?

• Disease mechanisms:

  • How exactly does PRMT3 regulate HIF1α in glioblastoma, and is this mechanism active in other cancer types?

  • What is the molecular mechanism by which PRMT3 promotes osteogenic differentiation of MSCs?

  • Are there other disease contexts where PRMT3 plays a currently unrecognized role?

• Evolutionary considerations:

  • How has PRMT3 function evolved across species?

  • Are its roles in processes like osteogenesis and cancer metabolism conserved in model organisms?

  • What can comparative studies across species tell us about essential versus contextual functions of PRMT3?

• Therapeutic potential:

  • What is the therapeutic window for PRMT3 inhibition in cancer treatment?

  • Can PRMT3 activators be developed as effective treatments for bone disorders?

  • What are the long-term consequences of PRMT3 modulation in different tissues? Addressing these questions will require integrative approaches combining structural biology, biochemistry, cell biology, and in vivo models, as well as the emerging technologies discussed in previous sections. Resolving these questions would significantly advance our understanding of PRMT3 biology and its therapeutic potential in various disease contexts.