Protein Pathfinder
Reference
Free · Designed for iPad. Not verified for macOS.
A research-grade tool for protein interaction pathways: STRING v12.5 evidence scoring, force-field electrostatic surfaces, and cell-type expression validation via HPA.
Protein Interaction Pathfinder turns two gene names into a fully evidenced, visually explorable interaction pathway — combining STRING v12.5 network data, structural biology, and expression validation in one research tool.
WHETHER YOU'RE MAPPING A SIGNALING CASCADE, checking whether two proteins can plausibly interact in a specific cell line, or just want to see a protein's real electrostatic surface, this app builds the evidence trail for you instead of leaving you to stitch together five different databases by hand.
KEY FEATURES
Pathway Discovery
• Enter any two human gene symbols and find the shortest interaction path between them
• Choose your evidence type: Functional, Physical, or directional Regulatory (v12.5 with activation/inhibition signs)
• See the full STRING evidence breakdown for every edge — experimental, curated database, text mining, co-expression, neighborhood, gene fusion, and co-occurrence scores
• Jump straight to the live STRING network graph for any pair
Independent Dual-Panel 3D Structures
• View both proteins' real PDB or Alphafold DB structures side by side, each with its own camera
• Rotate and zoom each protein independently with a single touch — no more fighting over a shared view
• Overlay PTM(phosphorylation, etc) sites directly on the 3D surface
Electrostatic Surface Visualization
• Color each protein's surface by charge — red for negative, blue for positive — computed from real CHARMM27 force-field partial charges across nearly every atom, not just a handful of charged residues
• Fine-tune the approximation yourself: histidine protonation state, contrast, Debye screening length, and visual intensity are all adjustable sliders
• A fast, on-device approximation built for exploration — not a substitute for a full Poisson-Boltzmann calculation, and the app is upfront about that distinction
Cell-Type Expression Validation
• Check whether both proteins in an interaction are actually expressed together in a specific cancer cell line (HeLa, MCF-7, MDA-MB-468, A549, and more) or a primary tissue cell type
• Pulls real single-cell and cell-line RNA expression data from the Human Protein Atlas
• Flags subcellular co-localization so you can see whether two co-expressed proteins are even in the same compartment
PhosphoSite Validation
• Cross-reference kinase-substrate relationships against OmniPath and SIGNOR
• See which phosphorylation sites on a substrate are actually documented for a given kinase
Chemical Interaction Context
• Surface known small-molecule / chemical interaction data from STITCH for either protein in your pathway
Built-In Guide
• A full in-app user guide explains every screen, every data source, and every scoring system — no external documentation hunting required
WHY IT'S DIFFERENT
Most interaction-mapping tools stop at "these two proteins are connected." Protein Interaction Pathfinder asks the next three questions automatically: What kind of evidence supports that connection? Would these two proteins ever actually meet inside a real cell? And what does their physical interface actually look like? Answering all three normally means juggling STRING, the PDB, Alphafold DB, and the Human Protein Atlas in separate browser tabs — this app does it in one pass, on your phone.
DATA SOURCES
All data is pulled live from established, citable public resources: STRING (protein interaction evidence), RCSB PDB and Alphafold DB (3D structures), the Human Protein Atlas (expression data), OmniPath and SIGNOR (phosphorylation evidence), and STITCH (chemical interactions). Nothing is scraped or pre-baked — every query reflects the current state of these databases.
WHO IT'S FOR
Built for structural and cancer biologists, phosphoproteomics researchers, bioinformatics students, and anyone who needs a fast, evidence-backed answer to "how — and where — do these two proteins actually interact?"
Authors: Heebok Lee, Ph.D. and Gihoon Lee, Ph.D. — offered to the research community as a courtesy.
Ratings & Reviews
- This app hasn’t received enough ratings or reviews to display an overview.
What's New
- Common protein names next to gene symbols
Pathway cards now show the everyday name beside the official gene symbol, such as MAPK1 → ERK2, MAP2K1 → MEK1 and TP53 → p53, so pathways read the way they do in papers and diagrams.
- Synonyms and protein family in the details view
Each protein now lists its UniProt synonyms under "Also known as" and its family hierarchy (for example: Protein kinase superfamily › CMGC Ser/Thr protein kinase family › MAP kinase subfamily). A family tag also appears on each pathway card.
- More accurate kinase labelling
Kinases are now identified from EC numbers and protein names instead of free-text descriptions. Transcription factors such as p53 are no longer flagged as kinases, and the EC number is shown in the details view.
- Aliases in the 3D structure view
Protein headers in the structure comparison show the gene symbol with its common name.
- Search improvements
Gene names are matched regardless of upper or lower case, and repeated lookups are faster.
The developer, Heebok Lee, indicated that the app’s privacy practices may include handling of data as described below. For more information, see the developer’s privacy policy .
Data Not Collected
The developer does not collect any data from this app.
Accessibility
The developer has not yet indicated which accessibility features this app supports. Learn More
Information
- Seller
- Heebok Lee
- Size
- 22.4 MB
- Category
- Reference
- Compatibility
Requires iOS 15.6 or later.
- iPhone
Requires iOS 15.6 or later. - iPad
Requires iPadOS 15.6 or later. - iPod touch
Requires iOS 15.6 or later. - Mac
Requires macOS 12.5 or later and a Mac with Apple M1 chip or later. - Apple Vision
Requires visionOS 1.0 or later.
- iPhone
- Languages
- English
- Age Rating
4+
- 4+
- Copyright
- © heebok&Gihoon@2026