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GPCR Binning: Structural binning and organisation utilities for GPCR datasets

GPCR Binning

Structural binning and organisation utilities for GPCR datasets.

domain field status licence author


GPCR Binning is a working repository for organising and grouping G-protein-coupled receptor (GPCR) structural data. GPCRs are the single largest class of drug targets, and the structural data describing them is large, heterogeneous, and growing fast across receptor families, conformational states, and bound ligands. This project collects utilities for binning that data into coherent, analysable groups.

Why it matters: GPCRs account for a substantial fraction of all approved drugs, and structure-based work on them depends on being able to slice a sprawling structural landscape into meaningful categories (by class, by state, by binding mode, by resolution and method). Sensible binning is the foundation for everything downstream: selectivity analysis, template selection for modelling, and triage for structure-based drug design. This repository is useful as a place to develop and keep those binning and grouping utilities in one structural-biology-aware codebase.

⚠️ Status: This project is in active development. The sections below describe its intended scope; specifics will be filled in as the codebase matures.


🎯 Scope

AreaIntent
🗃️ BinningGroup GPCR structures into coherent categories for analysis
🧬 Domain-awareBuilt around GPCR structural biology rather than generic clustering
🔬 Analysis-readyProduce groupings suitable for downstream SBDD and comparison

🚀 Getting started

git clone https://github.com/bellcheddar/gpcr-binning.git
cd gpcr-binning

Usage instructions will be documented here as the tooling stabilises.


🧭 Context

This repository sits alongside related structure-focused tools in the portfolio, including PocketTide (a GLP-1R structure dashboard) and the Boltz-2 co-folding utilities. Together they support a structure-based approach to drug discovery across GPCR and other target classes.


📄 Licence

See repository for licence terms.


👤 Author

Marc C. Deller, D.Phil.
Structural biologist & drug discovery scientist