Recombinant Human Putative uncharacterized protein FP248 (FP248)

Basic Research Questions

• What are uncharacterized proteins like FP248 and why are they significant in human proteome research?

Uncharacterized proteins like FP248 are proteins predicted to be expressed from open reading frames (ORFs) but lack experimental validation of their biological functions. According to UniProt data from early 2023, the human proteome contains 20,422 canonical and 21,998 non-canonical protein isoforms, with hundreds to thousands remaining uncharacterized . These proteins represent significant knowledge gaps in our understanding of cellular function.

The significance of studying uncharacterized proteins stems from:

• Their potential roles in unknown cellular pathways

• Possible involvement in disease mechanisms

• Contribution to evolutionary understanding of protein families

• Opportunities for discovering novel therapeutic targets

Research approaches should begin with computational prediction methods followed by experimental validation, as these proteins may reveal new biological functions critical to human health and disease .

• What bioinformatic methods should be used for initial characterization of FP248?

For initial characterization of uncharacterized proteins like FP248, researchers should implement a systematic bioinformatic approach:

It's important to use multiple databases and prediction methods, as studies on uncharacterized proteins have shown significantly improved accuracy when at least two or more databases predict the same domain or function . This approach can help generate initial hypotheses about FP248's function before experimental validation.

• What experimental methods are recommended for validating putative functions of FP248?

To validate the putative functions of uncharacterized proteins like FP248, researchers should consider this stepwise experimental approach:

• Protein Expression and Purification:

  • Recombinant expression in appropriate systems (bacterial, yeast, or mammalian cells)

  • Optimization of expression conditions to ensure proper folding

  • Purification using affinity tags with controls to verify protein integrity

• Structural Characterization:

  • Circular dichroism (CD) spectroscopy to assess secondary structure

  • Mass spectrometry for accurate molecular weight determination and post-translational modifications

  • X-ray crystallography or NMR for detailed structural information when possible

• Functional Assays:

  • Enzyme activity assays if domains suggest enzymatic function

  • Protein-protein interaction studies (pull-down, co-immunoprecipitation, Y2H)

  • Cell-based assays to observe phenotypic changes upon overexpression or knockdown

• Validation in Relevant Models:

  • Cell line studies with overexpression or CRISPR/Cas9 knockout

  • Analysis of expression patterns in different tissues or conditions

  • Phenotypic analysis in model organisms if applicable

This comprehensive approach ensures robust validation and minimizes false positives in functional assignment .

• How should researchers approach protein-protein interaction studies for uncharacterized proteins like FP248?

When studying protein-protein interactions (PPIs) involving uncharacterized proteins like FP248, researchers should implement a multi-technique strategy:

• In Silico Prediction:

  • Begin with computational PPI prediction tools based on sequence and structural features

  • Use string analysis to identify potential interacting partners based on co-expression and genomic context

• Affinity-Based Methods:

  • Co-immunoprecipitation (Co-IP) with tagged versions of the protein

  • Pull-down assays using the recombinant protein as bait

  • Proximity labeling approaches (BioID, APEX) in living cells to capture transient interactions

• Direct Binding Measurements:

  • Surface plasmon resonance (SPR) to determine binding kinetics

  • Isothermal titration calorimetry (ITC) for thermodynamic parameters

  • Microscale thermophoresis for interactions in solution

• High-Throughput Screening:

  • Yeast two-hybrid (Y2H) screening

  • Protein microarrays to test multiple potential partners

  • Mass spectrometry-based interactome analysis

• Validation and Characterization:

  • Confirm interactions using at least two independent methods

  • Map interaction domains through truncation or mutation analysis

  • Assess the functional relevance of interactions through cellular assays

For example, the study of PieF (Lpg1972) from Legionella pneumophila demonstrated how a bacterial effector protein directly interacts with the CNOT7/8 nuclease module, illustrating the importance of determining interaction specificity and affinity (reported dissociation constant in the low nanomolar range) .

• What approaches should be used to study the expression patterns of uncharacterized proteins?

To comprehensively analyze the expression patterns of uncharacterized proteins like FP248, researchers should employ:

• Transcriptomic Analysis:

  • RNA-Seq to determine mRNA expression levels across different tissues and conditions

  • Single-cell RNA-Seq to identify cell type-specific expression

  • Translatome sequencing to specifically study protein isoforms and alternative splicing events

• Protein Detection Methods:

  • Western blotting with specific antibodies (if available) or tag-based detection

  • Immunohistochemistry or immunofluorescence for spatial localization in tissues

  • Proteomics approaches (MS/MS) to detect the protein in different cellular fractions

• Reporter Systems:

  • Creation of fluorescent protein fusions to monitor localization and expression

  • Promoter-reporter constructs to study transcriptional regulation

  • CRISPR-based endogenous tagging for physiological expression analysis

• Condition-Dependent Expression:

  • Analysis under different physiological stresses (e.g., hypoxia, nutrient deprivation)

  • Examination during developmental stages or cell cycle phases

  • Study of expression changes in disease states or after specific treatments

Research by Tan et al. demonstrated that uncharacterized human proteins C9orf85 and CXorf38 showed selective induction by specific micronutrients (manganese and selenium), highlighting the importance of examining expression under varied physiological conditions .

Advanced Research Questions

• What high-throughput techniques can be applied to determine the function of uncharacterized proteins like FP248?

For high-throughput functional characterization of uncharacterized proteins like FP248, researchers should consider these advanced methodologies:

• Multi-omics Integration Approaches:

  • Combined proteomics and transcriptomics data analysis

  • Correlation of expression with metabolomic profiles

  • Network-based analysis incorporating multiple data types

• Large-Scale Phenotypic Screens:

  • CRISPR-Cas9 knockout or CRISPRi screens with phenotypic readouts

  • Overexpression libraries with automated imaging for morphological changes

  • Pooled genetic screens with selection for specific phenotypes

• High-Content Imaging:

  • Automated subcellular localization screening

  • Protein-fragment complementation assays for interaction mapping

  • Live-cell tracking of protein dynamics under various perturbations

• Mass Spectrometry-Based Methods:

  • Thermal proteome profiling to identify substrates and interactors

  • Crosslinking mass spectrometry for structural interaction mapping

  • CETSA (Cellular Thermal Shift Assay) for target engagement studies

• Microfluidics Technologies:

  • Lab-on-a-chip methods for rapid and inexpensive assays

  • Microfluidics large scale integration (mLSI) technology for parallel assays

  • Single-cell analysis of protein function and interactions

Chen et al. demonstrated the power of untargeted proteomic approaches with LC-MS/MS to screen and functionally analyze peptides from placental tissues, identifying differentially expressed peptides that impact signaling pathways . Similar approaches could be valuable for FP248 characterization.

• How can researchers resolve contradictory functional predictions for uncharacterized proteins?

When faced with contradictory functional predictions for uncharacterized proteins like FP248, researchers should implement this systematic resolution framework:

• Critical Evaluation of Prediction Methods:

  • Assess the reliability of each prediction tool using receiver operating characteristics (ROC) analysis

  • Prioritize predictions from tools with established accuracy in your protein class

  • Consider the confidence scores provided by each prediction tool

• Consensus-Based Approach:

  • Focus on functions predicted by multiple independent methods

  • Implement weighted consensus scoring based on tool performance

  • Consider evolutionary conservation of predicted functions across homologs

• Domain-Based Disambiguation:

  • Analyze individual domains separately to resolve conflicting whole-protein predictions

  • Consider the possibility of multifunctional proteins with distinct domain roles

  • Examine domain arrangement and potential for context-dependent functions

• Experimental Validation Hierarchy:

  • Design experiments that can specifically distinguish between competing predictions

  • Begin with the most discriminating assays based on predicted functions

  • Implement orthogonal experimental approaches to avoid technique-specific biases

• Structural Information Integration:

  • Use structural modeling to evaluate the physical plausibility of predicted functions

  • Compare with known structures of functionally characterized proteins

  • Consider active site geometry for enzyme function predictions

Studies on bacterial uncharacterized proteins demonstrated that approximately 83% prediction accuracy could be achieved when multiple databases and methods were integrated in a consensus approach .

• What strategies should be employed for structural determination of challenging uncharacterized proteins?

For structural determination of challenging uncharacterized proteins like FP248, researchers should consider this progressive approach:

• Initial Biophysical Characterization:

  • Circular dichroism to assess secondary structure content

  • Size exclusion chromatography with multi-angle light scattering for oligomeric state

  • Differential scanning fluorimetry to optimize buffer conditions for stability

• Protein Engineering for Structural Studies:

  • Construct design with flexible terminus truncations based on domain predictions

  • Surface entropy reduction mutations to enhance crystallizability

  • Fusion protein strategies to aid crystallization or improve solubility

• Hybrid Structural Approaches:

  • Combine lower-resolution techniques (SAXS, Cryo-EM) with computational modeling

  • Use NMR for flexible regions combined with X-ray crystallography for ordered domains

  • Implement integrative structural biology approaches incorporating multiple data types

• Advanced Computational Prediction:

  • AlphaFold2 or RoseTTAFold for deep learning-based structure prediction

  • Molecular dynamics simulations to assess structural stability and dynamics

  • Homology modeling with remote templates identified through sensitive profile searches

• Co-structure Determination:

  • Crystallization with binding partners or ligands to stabilize the structure

  • Use of antibody fragments to facilitate crystallization

  • Crosslinking strategies to capture transient states

Research on uncharacterized proteins from Fusobacterium nucleatum successfully employed homology-based structural modeling using Swiss PDB and Phyre2 servers, achieving structure predictions for 25 annotated proteins with identity ranging from 14% to 97% .

• How can researchers investigate the potential role of uncharacterized proteins in disease mechanisms?

To investigate the potential roles of uncharacterized proteins like FP248 in disease mechanisms, implement this comprehensive research strategy:

• Genetic Association Analysis:

  • Examine GWAS data for associations between gene variants and disease phenotypes

  • Analyze whole exome/genome sequencing data from patient cohorts for rare variants

  • Study copy number variations affecting the gene encoding the uncharacterized protein

• Expression Correlation Studies:

  • Compare expression levels between healthy and disease tissues

  • Perform single-cell transcriptomics to identify cell type-specific alterations

  • Analyze protein levels in patient samples using targeted proteomics

• Functional Genomics Approaches:

  • CRISPR-based screens to identify phenotypes relevant to disease mechanisms

  • Overexpression studies to examine gain-of-function effects

  • Rescue experiments in disease models to validate causality

• Pathway Integration Analysis:

  • Map potential interactions with known disease-associated pathways

  • Identify post-translational modifications in disease contexts

  • Study effects on signaling pathway outputs using reporter assays

• Model Systems:

  • Generate animal models with gene knockouts or disease-associated variants

  • Develop patient-derived cellular models (iPSCs, organoids)

  • Study effects in tissue-specific contexts relevant to the disease

Research by Zhang et al. on arrestin domain containing 2 (ARRDC2), previously an uncharacterized protein in the α-arrestin family, revealed its association with ovarian cancer progression and poor survival outcomes, demonstrating how uncharacterized proteins can be implicated in disease mechanisms through systematic investigation .

• What considerations are important when designing experiments to study post-translational modifications of uncharacterized proteins?

When investigating post-translational modifications (PTMs) of uncharacterized proteins like FP248, researchers should implement this strategic experimental design:

• Prediction-Guided PTM Site Identification:

  • Use computational tools to predict potential PTM sites based on sequence motifs

  • Consider evolutionary conservation of potential modification sites

  • Examine structural models to assess surface accessibility of predicted sites

• Comprehensive PTM Detection Strategies:

  • Employ enrichment techniques specific to PTM types (phosphopeptide enrichment, etc.)

  • Use multiple protease digestion strategies to maximize sequence coverage

  • Implement top-down proteomics approaches to maintain PTM-protein connections

• Mass Spectrometry Protocol Optimization:

  • Select appropriate fragmentation methods (HCD, ETD, EThcD) based on PTM type

  • Use neutral loss scanning for specific modifications

  • Implement targeted approaches (PRM, MRM) for quantitative analysis of specific sites

• Site-Specific Validation Methods:

  • Generate site-specific antibodies for key PTM sites

  • Create site-directed mutants (S/T/Y→A for phosphorylation, K→R for ubiquitination)

  • Use CRISPR knock-in strategies to create tagged versions for in vivo studies

• Functional Consequence Assessment:

  • Compare wild-type and PTM-deficient mutants in functional assays

  • Study dynamics of modifications under various cellular conditions

  • Investigate how PTMs affect protein-protein interactions or subcellular localization

The study by Chiang et al. on the lysine methyltransferase SETD7 demonstrated how this enzyme can methylate over 30 non-histone protein substrates, highlighting the importance of studying PTMs on previously uncharacterized proteins and their functional implications .

• How should researchers approach the study of uncharacterized protein aggregation properties?

To investigate aggregation properties of uncharacterized proteins like FP248, researchers should implement this methodological framework:

• Aggregation Propensity Prediction:

  • Use computational tools (TANGO, AGGRESCAN, ZipperDB) to identify aggregation-prone regions

  • Analyze protein sequence for characteristics associated with aggregation (hydrophobic patches, intrinsically disordered regions)

  • Consider charge distribution and its impact on solubility

• Controlled Aggregation Studies:

  • Monitor aggregation kinetics under various conditions (pH, temperature, ionic strength)

  • Use mild denaturants at sub-denaturing concentrations to induce controlled aggregation

  • Implement real-time monitoring techniques (light scattering, ThT fluorescence)

• Structural Characterization of Aggregates:

  • Employ transmission electron microscopy to visualize aggregate morphology

  • Use FTIR or CD spectroscopy to assess secondary structure changes during aggregation

  • Implement solid-state NMR for detailed structural analysis of stable aggregates

• Preventive Strategy Testing:

  • Evaluate osmolytes (like sucrose) for their ability to prevent aggregation

  • Test the effect of chaperones on aggregation kinetics

  • Explore structure-based design of stabilizing mutations

• Native State Analysis:

  • Characterize the native state ensemble through hydrogen-deuterium exchange

  • Monitor conformational dynamics using FRET or single-molecule techniques

  • Identify transient expanded states that may precede aggregation

A study on rhIFN-γ demonstrated that aggregation proceeds through a transient expansion of the native state, with sucrose shifting the equilibrium to favor more compact native species, thus stabilizing the protein against aggregation. This mechanism may be relevant for understanding aggregation properties of uncharacterized proteins like FP248 .

Collaborative Research Approaches

• What interdisciplinary approaches can accelerate functional characterization of uncharacterized proteins?

To accelerate functional characterization of uncharacterized proteins like FP248, researchers should implement these interdisciplinary approaches:

• Integrated Computational-Experimental Pipelines:

  • Begin with parallel computational predictions using multiple algorithms

  • Design targeted experiments to validate highest-confidence predictions

  • Implement machine learning to improve prediction accuracy based on experimental feedback

• Cross-Species Functional Analysis:

  • Study orthologous proteins in model organisms with faster experimental cycles

  • Perform complementation assays in knockout models across species

  • Leverage evolutionary insights to prioritize conserved functions

• Collaborative Technology Platforms:

  • Combine structural biology with chemoproteomics approaches

  • Integrate systems biology with targeted biochemical assays

  • Merge high-throughput phenotypic screening with detailed mechanistic studies

• Data Science Integration:

  • Apply network analysis to position uncharacterized proteins in functional networks

  • Implement text mining of scientific literature to capture emerging knowledge

  • Develop interactive databases to share results across research communities

• Collaborative Research Initiatives:

  • Form focused research consortia around families of uncharacterized proteins

  • Establish standardized protocols for consistent data generation

  • Create centralized repositories for raw data sharing

The "Characterizing the uncharacterized human proteins" Research Topic showcased 9 published manuscripts with 66 contributors, demonstrating the power of collaborative research in advancing knowledge of uncharacterized proteins through diverse methodological approaches .