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README.md

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+---
+license: cc-by-nc-4.0
+task_categories:
+- tabular-regression
+tags:
+- protein-protein-interaction
+- binding-affinity
+- interactome
+---
+
+# OccupancyFlow data
+
+Data for the OccupancyFlow pipeline: sequence-based binding-affinity prediction and the
+competition-adjusted weighting of the human interactome.
+Code: https://github.com/GainGod-Xu/OccupancyFlow
+
+## Contents
+
+| path | rows | what it is |
+|---|---|---|
+| `affinity/train_6655_no_overlap_s79_s90.csv` | 6,655 | chain pairs with a measured Kd, converted to ΔG (kcal/mol). Curated from PPB-Affinity: chain-pair decomposition, interface filtering, deduplication, then removal of every PDB entry shared with S79/S90 |
+| `affinity/test_s79.csv` | 111 | S79 benchmark (110 labelled), sequences re-extracted per chain from RCSB |
+| `affinity/test_s90.csv` | 89 | S90 benchmark |
+| `interactome/edges_RSW_20231018_filtered.csv` | 328,433 | human interaction network (Entrez gene IDs + symbols) after removing proteins without a reference sequence |
+| `interactome/proteins_RSW_20231018_clean.csv` | 17,219 | protein table: sequence, PaxDb abundance (ppm), identifiers |
+| `interactome/predictions_esm2_650M_nM.csv` | 328,389 | predicted ΔG and Kd per interaction, plus abundances converted to nM |
+| `weights/interactome_weights_0708.csv` | 328,378 | competition-adjusted weights `w_ij` with complex and free concentrations |
+| `weights/interactome_weights_0630.xlsx` | 328,378 | the weight file used by the disease-module analyses |
+| `negatome_check/predictions_negatome_random.csv` | 6,352 | predictions for Negatome human non-interactions, Negatome pairs that are also reported interactions, and random pairs of the same proteins |
+| `negatome_check/per_protein_comparison.csv` | 283 | per-protein median ΔG for reported partners vs Negatome partners |
+
+## Things to know before using these files
+
+- **ΔG sign convention**: negative means binding. Kd in nM.
+- **Affinity values in the interactome files are predictions**, not measurements, and they are
+  compressed: SD 0.64 kcal/mol against 2.68 for the measured training labels. They order
+  interactions better than they calibrate them.
+- **The predictions do not distinguish interactions from non-interactions** (Negatome AUC 0.481);
+  the model was trained only on binders. See `negatome_check/`.
+- **Abundance conversion** uses k = 1.881 nM/ppm (hepatocyte GAPDH: 3.39e7 copies/cell, 3,000 fL,
+  divided by the PaxDb whole-organism abundance 9,978 ppm).
+- **44 titin (TTN) interactions are missing** from the weighted network: the 34,350-residue
+  sequence broke an intermediate spreadsheet export. They are present in the `interactome/edges`
+  file and absent downstream.
+- **Leakage control in the affinity split is at PDB-entry level**, not sequence identity: 2 of 111
+  S79 chain pairs have both sequences present in the training set (S90: none).
+
+## Sources
+
+PPB-Affinity (Liu et al., Sci Data 2024) · PPI-Affinity S79/S90 (Romero-Molina et al., JPR 2022) ·
+PaxDb (Wang et al. 2015) · Negatome 2.0 (Blohm et al., NAR 2014) via `Synthyra/NEGATOME`.