HRAS Human

What is the HRAS gene and what is its primary function in human cells?

HRAS (Harvey rat sarcoma viral oncogene homolog) is a member of the RAS family of oncogenes located on chromosome 11p15.5. It spans approximately 3,308 base pairs from position 532,242 to 535,550 on the plus strand . At the molecular level, HRAS functions as a GTPase that plays a crucial role in cell growth and differentiation by acting as a molecular switch in signal transduction pathways.

The HRAS protein participates in multiple cellular processes including:

• MAPK cascade signaling

• Cell surface receptor signaling pathways

• Epidermal growth factor receptor signaling

• Cell cycle arrest and mitotic cell cycle checkpoint functions

• Endocytosis and chemotaxis

Research methodologies for studying HRAS function typically involve knockdown/knockout approaches using siRNA or CRISPR-Cas9, coupled with signaling pathway analyses using phospho-specific antibodies to detect activation of downstream effectors.

How does HRAS differ from other RAS family proteins, and why is this significant?

HRAS shares significant homology with other RAS family members (KRAS and NRAS), particularly in the G-domain, but contains distinct regions that influence its specific functions. While the three isoforms have similar biochemical properties, they exhibit different binding interactions that significantly impact their oncogenic potential.

Methodologically, understanding these differences requires:

• Structural analysis through X-ray crystallography or molecular dynamics simulations

• Protein-protein interaction studies using co-immunoprecipitation, proximity ligation assays, or FRET

• Isoform-specific knockdown/knockout experiments to determine non-redundant functions

Recent molecular dynamics simulations have revealed that wildtype KRAS binds to HRAS with an average binding energy of -46.68 kcal/mol, demonstrating thermodynamically favorable interaction . This binding pattern is significant as it may serve as an intrinsic regulatory mechanism among RAS isoforms.

What experimental models are most appropriate for studying HRAS in human aging and cancer?

When selecting experimental models for HRAS research, consider both the research question and the translational relevance:

For aging research, C. elegans has provided valuable insights despite evolutionary distance, as the RAS pathway influences both development and aging in conjunction with the insulin/IGF1 signaling pathway . For cancer studies, patient-derived xenografts and genetically engineered mouse models expressing mutant HRAS provide the most translational relevance.

How do specific HRAS mutations alter protein structure and function in human cancers?

HRAS mutations in cancer predominantly occur at specific hotspots (particularly G12, G13, and Q61), creating constitutively active forms that promote uncontrolled cellular proliferation. These mutations impair intrinsic GTPase activity or prevent interaction with GTPase-activating proteins (GAPs).

Research approaches to characterize mutational effects include:

• Structural analysis using molecular dynamics simulations to visualize conformational changes

• Binding assays to measure altered interactions with effector proteins

• Functional assays measuring downstream pathway activation (e.g., MAPK, PI3K)

• Cellular transformation assays to quantify oncogenic potential

Molecular dynamics simulations have revealed significant differences in binding energies between wildtype HRAS and various KRAS mutants. For example, a G12D mutation in KRAS results in weaker binding to wildtype HRAS (with a standardized mean of 1.20 kcal/mol compared to wildtype), while a G13D mutation significantly strengthens this interaction (standardized mean of -22.04 kcal/mol) . These binding differences may explain variations in oncogenic potency among different RAS mutations.

What methodological approaches best capture the dynamic interactions between HRAS and other signaling proteins?

Studying dynamic HRAS interactions requires methodologies that can capture transient and regulated protein-protein interactions in living cells:

• Live-cell imaging techniques:

  • FRET/BRET to measure real-time protein interactions

  • Optogenetic approaches to control RAS activation with spatial and temporal precision

  • Fluorescence correlation spectroscopy to measure diffusion dynamics

• Biochemical approaches with temporal resolution:

  • Time-course immunoprecipitation following stimulation

  • Proximity labeling techniques (BioID, APEX) with controlled labeling windows

  • Hydrogen-deuterium exchange mass spectrometry to identify binding interfaces

• Computational approaches:

  • Molecular dynamics simulations examining conformational changes over time

  • Root mean square fluctuation (RMSF) analysis to identify mobile regions involved in interactions

  • Binding energy calculations to quantify interaction strength

Studies have used these approaches to identify that HRAS interacts with multiple proteins relevant to aging and cancer, including TP53, PLAU, INSR, MAPK8, PIK3R1, and PIK3CA . These interaction partners provide insights into how HRAS integrates various signaling inputs to influence cellular outcomes.

How can molecular dynamics simulations advance our understanding of HRAS-isoform interactions?

Molecular dynamics (MD) simulations provide powerful insights into HRAS interactions that are difficult to capture experimentally:

Methodological workflow for effective MD simulations of HRAS:

Recent MD simulations revealed that wildtype KRAS binds to wildtype HRAS with remarkable stability (standard deviation of 3.85 kcal/mol), while mutant forms show variable binding patterns. The G13D KRAS mutant demonstrated the strongest binding to wildtype HRAS among all tested variants, suggesting potential therapeutic relevance for modulating these interactions .

What experimental challenges arise when studying HRAS post-translational modifications, and how can they be overcome?

Post-translational modifications (PTMs) of HRAS, including farnesylation, palmitoylation, and phosphorylation, critically regulate its localization and activity. Studying these modifications presents several challenges:

Challenge 1: Detecting specific modifications

• Solution: Combine enrichment strategies (e.g., click chemistry for lipid modifications, phospho-specific antibodies) with high-resolution mass spectrometry

• Method improvement: Use targeted multiple reaction monitoring (MRM) mass spectrometry for improved sensitivity

Challenge 2: Temporal dynamics of modifications

• Solution: Use pulse-chase approaches with metabolic labeling

• Method improvement: Develop biosensors that report specific PTM states in real-time

Challenge 3: Functional relevance of PTM patterns

• Solution: Generate modification-specific mutants and assess activity

• Method improvement: Combine with proximity labeling to identify PTM-specific interactors

Challenge 4: Spatial organization of modified HRAS

• Solution: Use super-resolution microscopy to visualize nanoscale distribution

• Method improvement: Correlative light and electron microscopy to link localization to membrane ultrastructure

When designing experiments, researchers should consider how PTMs may affect the results of interaction studies. For example, membrane-associated HRAS (with intact lipid modifications) may have different binding properties compared to recombinant proteins used in computational models or in vitro assays.

How do the kinetic properties of HRAS differ between normal and pathological states?

The kinetic properties of HRAS—including nucleotide binding, hydrolysis rates, and exchange kinetics—are fundamentally altered in pathological states such as cancer and certain developmental disorders:

Methodological approaches to measure HRAS kinetics:

• Real-time nucleotide binding/hydrolysis assays:

  • Fluorescent nucleotide analogs (mant-GTP, BODIPY-GTP)

  • Stopped-flow spectroscopy for rapid kinetic measurements

  • Single-molecule approaches for heterogeneity analysis

• Cellular activation dynamics:

  • FRET-based biosensors to measure activation in living cells

  • Optogenetic approaches to trigger activation with precise timing

  • Mathematical modeling to extract rate constants from cellular data

• Comprehensive kinetic parameter determination:

  • Determine association (kon) and dissociation (koff) rate constants

  • Measure GTP hydrolysis rates (kcat)

  • Quantify nucleotide exchange rates with and without GEFs

Recent kinetic studies of RAS proteins, including HRAS, demonstrate that oncogenic mutations primarily affect the GTP-bound state stability and interaction with regulatory proteins rather than the intrinsic nucleotide binding properties. These alterations create a prolonged active state that drives downstream signaling .

What are the most reliable antibody-based methods for detecting HRAS in human samples?

Antibody-based detection of HRAS requires careful consideration of specificity, given the high homology between RAS family members:

Best practices for HRAS immunodetection:

• Antibody selection considerations:

  • Verify isoform specificity using knockout/knockdown controls

  • Validate in multiple sample types (cell lines, tissues, etc.)

  • Test for cross-reactivity with KRAS and NRAS using recombinant proteins

• Recommended detection methods:

  • Western blotting with isoform-specific antibodies

  • Immunoprecipitation followed by mass spectrometry for confirmation

  • Immunohistochemistry with validated antibodies and appropriate controls

• Quantification approaches:

  • Use multiple antibodies targeting different epitopes

  • Include loading controls and standardization samples

  • Consider digital pathology tools for quantitative immunohistochemistry

How can researchers effectively design CRISPR-Cas9 experiments to study HRAS function?

CRISPR-Cas9 technology offers powerful approaches for manipulating HRAS in research models, but requires careful design:

CRISPR experimental design workflow for HRAS studies:

• Guide RNA design:

  • Target unique regions that differ from KRAS/NRAS to ensure specificity

  • Design multiple guides with minimal off-target effects

  • Consider the functional domains being disrupted (e.g., GTP-binding regions)

• Editing strategy selection:

  • Complete knockout via frameshift indels

  • Base editing for specific point mutations (e.g., G12V)

  • Knock-in of fluorescent tags for localization studies

  • Inducible CRISPR systems for temporal control

• Validation requirements:

  • Sequence verification of edits

  • Western blotting to confirm protein changes

  • RNA-seq to rule out compensatory expression of other RAS isoforms

  • Functional testing of downstream pathways

• Analytical considerations:

  • Develop clear phenotypic readouts relevant to HRAS function

  • Use clonal populations or single-cell analysis to address heterogeneity

  • Include rescue experiments with wildtype HRAS to confirm specificity

When introducing specific mutations, prime editing or base editing systems may offer advantages over traditional homology-directed repair, particularly for the common G→T transversions found in HRAS mutant cancers.

What bioinformatic tools and databases are most valuable for HRAS human research?

A comprehensive bioinformatic analysis of HRAS requires multiple specialized tools and databases:

When conducting computational analyses, researchers should be aware that the confidence intervals for HRAS interactions with other proteins vary. For example, the interaction between KRAS and HRAS has an experimental and biochemical data confidence interval of 0.893, while the interaction between HRAS and NRAS has a confidence interval of 0.877 . These confidence scores should inform interpretation of predicted interaction networks.

How can understanding HRAS-isoform interactions inform therapeutic strategies for RAS-driven cancers?

The complex interactions between HRAS and other RAS isoforms present novel therapeutic opportunities:

Recent research has revealed that wildtype HRAS can interact with mutant KRAS proteins, potentially modulating their oncogenic activity. Molecular dynamics simulations have identified specific binding interfaces and energetics that could be exploited therapeutically . This approach represents a paradigm shift from direct RAS inhibition to modulating inter-isoform interactions.

Therapeutic strategies based on HRAS interactions:

• Peptide mimetics approach:

  • Design peptides mimicking the hypervariable region of HRAS that interact with KRAS

  • Optimize binding to mutant KRAS over wildtype forms

  • Engineer cell-penetrating capabilities and stability enhancements

• Small molecule development:

  • Target specific residues identified in binding interfaces

  • Focus on compounds that stabilize HRAS-KRAS interactions

  • Leverage the different binding energies observed between wildtype and mutant KRAS

• Biological approaches:

  • Modulate relative expression levels of RAS isoforms

  • Use gene therapy to increase wildtype HRAS expression in KRAS-mutant tumors

  • Develop transcriptional regulators of HRAS expression

Experimental data shows that wildtype KRAS binds to wildtype HRAS with a mean binding energy of -46.68 kcal/mol, while the G13D KRAS mutant shows significantly stronger binding (-22.04 kcal/mol standardized mean compared to wildtype) . These energy differences provide critical information for designing therapeutics that could mimic or enhance these interactions.

What methodological considerations are important when investigating HRAS in aging-related research?

HRAS has been implicated in aging processes across multiple model organisms, requiring specialized methodological approaches:

Key considerations for aging research involving HRAS:

• Model selection for aging studies:

  • Short-lived organisms (C. elegans, Drosophila) for rapid aging assessment

  • Cell senescence models (replicative, stress-induced) for cellular aging

  • Progeria models to study accelerated aging

  • Longitudinal studies in longer-lived models for physiological relevance

• Aging-specific endpoints:

  • Healthspan measures beyond simple lifespan

  • Molecular aging markers (telomere length, epigenetic clocks)

  • Senescence markers (SASP, SA-β-gal, p16INK4a levels)

  • Tissue-specific functional decline metrics

• Crossover with cancer pathways:

  • Address the paradoxical roles of HRAS in senescence vs. oncogenesis

  • Consider the cell-type specificity of responses

  • Investigate context-dependent outcomes of HRAS activation

• Integration with other aging pathways:

  • Connect HRAS signaling with established aging mechanisms

  • Study interactions with INS/IGF1 signaling

  • Explore interactions with mTOR and autophagy regulation

Research in C. elegans has demonstrated that the RAS pathway influences both development and aging in conjunction with the insulin/IGF1 signaling pathway . These findings illustrate the evolutionarily conserved role of HRAS in aging processes, suggesting similar mechanisms may be relevant in humans.

How should researchers interpret contradictory data regarding HRAS function across different experimental systems?

Conflicting results regarding HRAS function are common in the literature and require systematic approaches to reconciliation:

Framework for resolving contradictory HRAS data:

• Identify sources of variation:

  • Cell/tissue type differences (context-dependency)

  • Experimental conditions (growth factors, stress levels)

  • Expression levels (physiological vs. overexpression)

  • Temporal aspects (acute vs. chronic activation)

  • Species differences (human vs. model organisms)

• Technical validation strategies:

  • Replicate using multiple methodological approaches

  • Validate key findings in diverse cellular contexts

  • Use recombinant expression with controlled levels

  • Apply dose-response relationships rather than single conditions

• Integrative analysis approaches:

  • Develop computational models that incorporate contextual variables

  • Use systems biology approaches to define network-level effects

  • Consider feedback mechanisms and pathway cross-talk

  • Analyze dynamic rather than steady-state responses

• Reporting recommendations:

  • Clearly define experimental conditions and cellular context

  • Report cell densities, passage numbers, and culture conditions

  • Include all relevant controls (positive, negative, isotype)

  • Share raw data to enable re-analysis and meta-analysis

For example, in brain degeneration studies, RAS signaling appears detrimental in Drosophila models , while in certain cellular contexts HRAS activation promotes survival. These apparent contradictions likely reflect context-dependent effects and highlight the importance of specifying the precise experimental conditions when interpreting results.

What emerging technologies will advance our understanding of HRAS function in human biology?

Several cutting-edge technologies are poised to transform HRAS research:

• Spatial multi-omics:

  • Spatial transcriptomics to map HRAS expression within tissues

  • Spatial proteomics to visualize HRAS protein localization and interactors

  • Integration with histopathology for clinicopathological correlations

• Advanced protein engineering approaches:

  • Optogenetic HRAS variants for spatiotemporal control

  • Split protein complementation for visualization of specific interactions

  • Degron-based systems for rapid protein depletion

• Single-cell technologies:

  • Single-cell RNA-seq to capture heterogeneity in HRAS expression

  • Single-cell proteomics to measure HRAS activity states

  • Live-cell tracking of HRAS signaling in individual cells over time

• AI and machine learning applications:

  • Deep learning for structure prediction and dynamics

  • ML algorithms to predict mutation effects

  • Network inference to identify novel interactions

• Refined computational simulation approaches:

  • Enhanced molecular dynamics simulations with longer timescales

  • Integration of experimental constraints into simulations

  • Quantum mechanics/molecular mechanics (QM/MM) for detailed reaction mechanisms

These technologies will be particularly valuable for understanding the context-dependent nature of HRAS function across different cell types and physiological states.

How can researchers design experiments to distinguish isoform-specific functions of HRAS vs KRAS and NRAS?

Despite high sequence homology, RAS isoforms have distinct functions that require specialized experimental approaches to differentiate:

Experimental design strategies for isoform specificity:

• Genetic approaches:

  • Isoform-specific knockout/knockdown with rescue experiments

  • Chimeric proteins swapping domains between isoforms

  • Point mutations of isoform-specific residues

  • Domain swapping between isoforms

• Interaction profiling:

  • BioID or APEX proximity labeling with each isoform as bait

  • Comparative interactomics across all three isoforms

  • Analysis of interaction dynamics following stimulation

  • Identification of isoform-specific adaptor proteins

• Localization studies:

  • Super-resolution imaging of endogenous isoforms

  • Membrane microdomain analysis

  • Trafficking kinetics following synthesis

  • Response to membrane-targeting drugs

• Computational approaches:

  • Comparative molecular dynamics simulations

  • Analysis of binding energy differences between isoforms

  • Identification of isoform-specific conformational states

Recent work has revealed that the orientation of wildtype KRAS when bound to wildtype HRAS versus wildtype NRAS differs by 180°, with binding sites that overlap with both the GDP/GTP active site and dimerization interface . These structural differences likely contribute to isoform-specific functions and provide targets for selective intervention.

What standardized reporting guidelines should researchers follow when publishing HRAS-related findings?

To enhance reproducibility and facilitate integration of findings, HRAS researchers should adhere to comprehensive reporting standards:

Recommended reporting elements for HRAS research:

• Detailed methods documentation:

  • Complete sequence information for constructs used

  • Expression levels relative to endogenous proteins

  • Cell line authentication and mycoplasma testing results

  • Passage numbers and culture conditions

  • Antibody validation methods and catalog numbers

• Results presentation:

  • Include all controls (positive, negative, loading)

  • Show representative images alongside quantification

  • Report biological and technical replicate numbers

  • Include statistical analysis methods and power calculations

  • Provide raw data in supplementary materials or repositories

• Contextual information:

  • Cell density and confluency at experiment time

  • Growth factor conditions and serum percentages

  • Time points for all measurements

  • Drug concentrations with exposure durations

  • Consideration of cell cycle effects

• Computational methods:

  • Software versions and parameters

  • Force fields used in simulations

  • Runtime parameters and convergence criteria

  • Validation metrics for structural predictions

  • Statistical approaches for energy calculations

These standardized reporting practices will not only improve reproducibility but also enable meta-analyses that can resolve apparent contradictions in the literature and accelerate progress in understanding HRAS function in human biology.