Update README.md

README.md

@@ -30,12 +30,10 @@ configs:
         path: parts.csv
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-# OpenProteinSet Archive
-
-This is an upload-friendly mirror of OpenProteinSet/OpenFold training data components. The source tree is kept intact inside archive shards rather than expanded as hundreds of thousands of repository files.
-
-The main use case is simple: search `metadata.csv`, download the shard or part files you need with the Hugging Face Python API, then extract or reassemble the original file.
+# OpenProteinSet
 
+OpenProteinSet is an open-source corpus released by the OpenFold team (Ahdritz et al., NeurIPS 2023 Datasets and Benchmarks) that reproduces and extends the kind of training data used for AlphaFold2, which DeepMind never released. It contains more than 16 million precomputed multiple sequence alignments (MSAs), structural template hits from the Protein Data Bank, and AlphaFold2 structure predictions, and was used to train OpenFold from scratch to parity with AlphaFold2.
+The corpus has two main components. The first is a faithful, updated reconstruction of AlphaFold2's PDB-side training set: MSAs and HHSearch template hits for every unique PDB chain, generated with the same pipeline (JackHMMER against UniRef90 and MGnify, HHBlits against BFD+Uniclust30, HHSearch against PDB70). The second is a Uniclust30-side set: one MSA per Uniclust30 cluster representative, totaling roughly 16M MSAs, from which a maximally diverse and deep subset is identified and paired with AlphaFold2 self-distillation predictions suitable for AlphaFold2-style noisy student training.
 ## What Is Included
 
 | Component | Files | Size |