Update README.md

README.md

@@ -77,26 +77,54 @@ Of particular note, the train, valid, and test splits are deduplicated and heavi
 For more information on the original dataset compilation, please read their [paper](https://github.com/pinder-org/pinder), [GitHub](https://github.com/pinder-org/pinder), or [docs](https://pinder-org.github.io/pinder/readme.html).
 
 ## Differences between this version and the official version
-We further processed the dataset into a sequence only version via the script below.
-Importantly, any entry with a sequence involved in a [NEGATOME](https://huggingface.co/datasets/Synthyra/NEGATOME) pair was removed.
-This removed a few thousand from the training and one entry from the valid split.
+We further processed the dataset into via the script below.
 `invalid` split entries were removed and info based on holo (bound), apo (unbound), as well as if an entry is computationally predicted was included.
 We also limited the pair length to 2044 (2048 with special tokens), removed entries with sequences less than 20 amino acids, and removed entries with `X` amino acid characters.
 
 ```python
 import pandas as pd
-from datasets import Dataset, DatasetDict, load_dataset
-from pinder.core import get_index
+from datasets import Dataset, DatasetDict
+from pinder.core import get_index, get_metadata
 from pinder.core.index.utils import get_sequence_database
 
-# --- Load the index and sequence database ---
+
+# --- Load the data ---
 index = get_index()
+metadata = get_metadata()
 seq_db = get_sequence_database()
 
-# --- Merge the index and sequence database ---
+annotations = [
+    "id",
+    "probability",
+    "link_density",
+    "planarity",
+    "n_residue_pairs",
+    "n_residues",
+    "buried_sasa",
+    "intermolecular_contacts",
+    "charged_charged_contacts",
+    "charged_polar_contacts",
+    "charged_apolar_contacts",
+    "polar_polar_contacts",
+    "apolar_polar_contacts",
+    "apolar_apolar_contacts",
+]
+
+# --- Merge the data ---
 df = (
     pd.merge(
-        index[["id", "split", "holo_R_pdb", "holo_L_pdb", "predicted_R", "predicted_L", "apo_R", "apo_L", "holo_R", "holo_L"]], 
+        index[[
+            "id",
+            "split",
+            "holo_R_pdb",
+            "holo_L_pdb",
+            "predicted_R",
+            "predicted_L",
+            "apo_R",
+            "apo_L",
+            "holo_R",
+            "holo_L",
+            ]], 
         seq_db[["pdb", "sequence"]].rename(
             columns={"pdb": "holo_R_pdb", "sequence": "receptor_sequence"}
         ), 
@@ -108,16 +136,16 @@ df = (
         ), 
         how="left"
     )
+    .merge(
+        metadata[annotations],
+        on="id",
+        how="left"
+    )
     .drop(columns=["holo_R_pdb", "holo_L_pdb"])
 )
 
-# --- Load and process the negatome sequences ---
-negatome = load_dataset('Synthyra/NEGATOME')
-negatome_seqs = set()
-for name, split in negatome.items():
-    for sample in split:
-        negatome_seqs.add(sample['SeqA'])
-        negatome_seqs.add(sample['SeqB'])
+print(df.head())
+
 
 # --- Filter for valid split entries (only 'test', 'val', and 'train') ---
 allowed_splits = ['test', 'val', 'train']
@@ -126,9 +154,6 @@ df = df[df['split'].isin(allowed_splits)].copy()
 # --- Rename the splits: 'val' -> 'valid' ---
 df['split'] = df['split'].replace({'val': 'valid'})
 
-# --- Remove entries with sequences found in the negatome ---
-df = df[~(df['receptor_sequence'].isin(negatome_seqs) | df['ligand_sequence'].isin(negatome_seqs))].copy()
-
 # --- Create the Huggingface DatasetDict with the desired splits ---
 split_datasets = {}
 for split in ['train', 'valid', 'test']:
@@ -147,6 +172,7 @@ hf_dataset = hf_dataset.filter(lambda x: (len(x['receptor_sequence']) + len(x['l
 
 # --- Push the dataset to the hub ---
 hf_dataset.push_to_hub('Synthyra/PINDER')
+
 ```
 
 ## Please cite