From d72119a3f676432f1023e2420008e59a179bf7c7 Mon Sep 17 00:00:00 2001 From: Zeming Lin Date: Fri, 29 May 2026 20:06:20 +0000 Subject: [PATCH] sync from internal --- README.md | 14 ++--- _assets/ESM3_README.md | 4 +- cookbook/local/open_generate.ipynb | 2 +- cookbook/tutorials/embed.ipynb | 58 +++++++++---------- cookbook/tutorials/esm3_generate.ipynb | 2 +- .../tutorials/esm3_guided_generation.ipynb | 2 +- cookbook/tutorials/esmc_layer_sweep.ipynb | 2 +- .../tutorials/esmc_mutation_scoring.ipynb | 2 +- .../esmc_sae_feature_interpretation.ipynb | 20 +++---- cookbook/tutorials/esmfold2.ipynb | 2 +- cookbook/tutorials/esmprotein.ipynb | 2 +- cookbook/tutorials/gfp_design.ipynb | 2 +- esm/models/esmfold2/prepare_input.py | 35 ++++++++--- esm/models/esmfold2/prepare_input_test.py | 31 ++++++++++ pixi.lock | 12 ++-- pyproject.toml | 2 +- 16 files changed, 120 insertions(+), 72 deletions(-) create mode 100644 esm/models/esmfold2/prepare_input_test.py diff --git a/README.md b/README.md index 92894872..7c9d3a64 100644 --- a/README.md +++ b/README.md @@ -9,7 +9,7 @@ We are releasing a world model for protein biology: a scientific engine for prediction, design, and discovery. Built on the latest generation of Evolutionary Scale Modeling (ESM), this system learns from the protein sequences produced by evolution and uses that knowledge to represent, map, predict, and design proteins across scales — from atomic interactions to evolutionary relationships spanning billions of years. The system includes three artifacts: ESMC, ESMFold2, and ESM Atlas. -**[ESMC](https://biohub.ai/esm/protein)** is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC defines a new scaling frontier relative to ESM2, achieving stronger performance in emergent long-range structural understanding as model scale increases +**[ESMC](https://biohub.ai/esm/protein)** is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC defines a new scaling frontier relative to ESM2, achieving stronger performance in emergent long-range structural understanding as model scale increases.
@@ -21,7 +21,7 @@ We are releasing a world model for protein biology: a scientific engine for pred **[ESMFold2](https://huggingface.co/Biohub/ESMFold2)**, built on the ESMC 6B model, is a state-of-the-art structure prediction model that has been validated for the design of protein-protein interactions. ESMFold2 surpasses other models in DockQ pass-rate on Foldbench protein-protein and antibody-antigen complexes, and can be used in single-sequence mode for an order of magnitude speedup in folding.
- +
@@ -50,7 +50,7 @@ For information on using ESM3, see the [ESM3 README](https://github.com/Biohub/e [ESMC](https://biohub.ai/esm/protein) is a state-of-the-art protein language model that has learned representations of protein biology from training on billions of protein sequences. -Codebase, model weights, and model variants for ESMC are available through [Hugging Face](https://huggingface.co/collections/Biohub/esmc-model-family). +Codebase, model weights, and model variants for ESMC are available through [Hugging Face](https://huggingface.co/collections/biohub/esmc-model-family). There are two primary ways of running the ESM models: through the [**Biohub Platform**](https://biohub.ai/) or locally with Hugging Face. The Biohub Platform enables users to easily run inference with ESM models with minimal setup. Users interested in customizing or fine-tuning ESM models can use the models from Hugging Face. @@ -60,7 +60,7 @@ There are two primary ways of running the ESM models: through the [**Biohub Plat Install `esm` from GitHub (a PyPI release is coming soon): ``` -pip install esm@git+https://github.com/Biohub/esm.git@c94ed8d +pip install esm@git+https://github.com/Biohub/esm.git@main ``` The following code demonstrates how to run ESMC locally @@ -103,7 +103,7 @@ Note that our API migrated from forge.evolutionaryscale.ai to [biohub.ai](https: To get started with ESM, install the python library using `pip`: ``` -pip install esm@git+https://github.com/Biohub/esm.git@c94ed8d +pip install esm@git+https://github.com/Biohub/esm.git@main ``` Then import the necessary libraries and instantiate your desired model. @@ -180,7 +180,7 @@ For tutorials on how to use ESMC SAEs, see our [tutorials](https://github.com/Bi The model predicts high-resolution, all-atom 3D protein structures directly from amino acid sequences, with optional multiple sequence alignment (MSA) input for enhanced accuracy on challenging targets. ESMFold2 achieves state-of-the-art performance matching or exceeding AlphaFold3 across diverse evaluation datasets, while offering improved computational efficiency through optimized diffusion sampling and architectural innovations. -Codebase, model weights, and model variants for ESMFold2 are available through [Hugging Face](https://huggingface.co/collections/biohub/esmfold2-model-family) +Codebase, model weights, and model variants for ESMFold2 are available through [Hugging Face](https://huggingface.co/Biohub/ESMFold2) ### Running ESMFold2 Locally @@ -237,7 +237,7 @@ with open("1mht_pred.cif", "w") as f: Install the `esm` Python package ``` -pip install esm@git+https://github.com/Biohub/esm.git@c94ed8d +pip install esm@git+https://github.com/Biohub/esm.git@main ``` Import the necessary libraries. diff --git a/_assets/ESM3_README.md b/_assets/ESM3_README.md index 66796e9b..d7531994 100644 --- a/_assets/ESM3_README.md +++ b/_assets/ESM3_README.md @@ -34,7 +34,7 @@ The code for ESM3 is available from Github and weights for esm3-sm-open-v1 is av First install the python library using `pip`: ``` -pip install esm@git+https://github.com/Biohub/esm.git@c94ed8d +pip install esm@git+https://github.com/Biohub/esm.git@main ``` Then import the necessary libraries and instantiate your model. Use your token from the [Biohub platform](https://biohub.ai") @@ -54,7 +54,7 @@ The following code demonstrates how to run ESM3 locally and generate a simple se First install the python library using `pip`: ``` -pip install esm@git+https://github.com/Biohub/esm.git@c94ed8d +pip install esm@git+https://github.com/Biohub/esm.git@main ``` Then import the necessary libraries for your model. diff --git a/cookbook/local/open_generate.ipynb b/cookbook/local/open_generate.ipynb index 189a2f3a..6f075106 100644 --- a/cookbook/local/open_generate.ipynb +++ b/cookbook/local/open_generate.ipynb @@ -32,7 +32,7 @@ "outputs": [], "source": [ "%set_env TOKENIZERS_PARALLELISM=false\n", - "!pip install esm@git+https://github.com/Biohub/esm.git@c94ed8d\n", + "!pip install esm@git+https://github.com/Biohub/esm.git@main\n", "import numpy as np\n", "import torch\n", "\n", diff --git a/cookbook/tutorials/embed.ipynb b/cookbook/tutorials/embed.ipynb index 523461a6..4b1596da 100644 --- a/cookbook/tutorials/embed.ipynb +++ b/cookbook/tutorials/embed.ipynb @@ -23,9 +23,9 @@ "outputs": [], "source": [ "# If you are working in colab, uncomment these lines to install dependencies\n", - "# ! pip install esm@git+https://github.com/Biohub/esm.git@c94ed8d\n", - "# ! pip install matplotlib\n", - "# ! pip install seaborn\n" + "#! pip install esm@git+https://github.com/Biohub/esm.git@main\n", + "#! pip install matplotlib\n", + "#! pip install seaborn" ] }, { @@ -46,7 +46,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -57,7 +57,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -84,8 +84,9 @@ "from esm.sdk import batch_executor\n", "from esm.sdk.api import ESMCInferenceClient, ESMProtein, LogitsConfig, LogitsOutput\n", "\n", + "# request mean-pooled hidden states to save memory\n", "EMBEDDING_CONFIG = LogitsConfig(\n", - " sequence=True, return_embeddings=True, return_hidden_states=True\n", + " sequence=True, return_hidden_states=False, return_mean_hidden_states=True\n", ")\n", "\n", "\n", @@ -136,28 +137,28 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "--2025-10-15 01:22:42-- https://docs.google.com/uc?export=download&id=1SpOkL11MJxIgy99dqufvUNJuCiuhxuyg\n", - "Resolving docs.google.com (docs.google.com)... 142.250.189.174, 2607:f8b0:4005:813::200e\n", - "Connecting to docs.google.com (docs.google.com)|142.250.189.174|:443... connected.\n", + "--2026-05-28 16:44:15-- https://docs.google.com/uc?export=download&id=1SpOkL11MJxIgy99dqufvUNJuCiuhxuyg\n", + "Resolving docs.google.com (docs.google.com)... 142.251.210.78\n", + "Connecting to docs.google.com (docs.google.com)|142.251.210.78|:443... connected.\n", "HTTP request sent, awaiting response... 303 See Other\n", "Location: https://drive.usercontent.google.com/download?id=1SpOkL11MJxIgy99dqufvUNJuCiuhxuyg&export=download [following]\n", - "--2025-10-15 01:22:42-- https://drive.usercontent.google.com/download?id=1SpOkL11MJxIgy99dqufvUNJuCiuhxuyg&export=download\n", - "Resolving drive.usercontent.google.com (drive.usercontent.google.com)... 142.250.191.65, 2607:f8b0:4005:810::2001\n", - "Connecting to drive.usercontent.google.com (drive.usercontent.google.com)|142.250.191.65|:443... connected.\n", + "--2026-05-28 16:44:15-- https://drive.usercontent.google.com/download?id=1SpOkL11MJxIgy99dqufvUNJuCiuhxuyg&export=download\n", + "Resolving drive.usercontent.google.com (drive.usercontent.google.com)... 192.178.50.65\n", + "Connecting to drive.usercontent.google.com (drive.usercontent.google.com)|192.178.50.65|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 43132 (42K) [application/octet-stream]\n", - "Saving to: ‘adk.csv’\n", + "Saving to: 'adk.csv'\n", "\n", "adk.csv 100%[===================>] 42.12K --.-KB/s in 0.02s \n", "\n", - "2025-10-15 01:22:43 (2.49 MB/s) - ‘adk.csv’ saved [43132/43132]\n", + "2026-05-28 16:44:16 (2.17 MB/s) - 'adk.csv' saved [43132/43132]\n", "\n" ] } @@ -168,7 +169,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 28, "metadata": {}, "outputs": [], "source": [ @@ -198,7 +199,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -212,11 +213,8 @@ "source": [ "import torch\n", "\n", - "# we'll summarize the embeddings using their mean across the sequence dimension\n", - "# which allows us to compare embeddings for sequences of different lengths\n", - "all_mean_embeddings = [\n", - " torch.mean(output.hidden_states.float(), dim=-2).squeeze() for output in outputs\n", - "]\n", + "# pull the mean-pooled embedding tensor out of each result object\n", + "all_mean_embeddings = [output.mean_hidden_state.float().squeeze() for output in outputs]\n", "\n", "# now we have a list of tensors of [num_layers, hidden_size]\n", "print(\"embedding shape [num_layers, hidden_size]:\", all_mean_embeddings[0].shape)" @@ -233,7 +231,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 32, "metadata": {}, "outputs": [], "source": [ @@ -246,7 +244,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 33, "metadata": {}, "outputs": [], "source": [ @@ -285,12 +283,12 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 34, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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", + "image/png": 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", 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" ] @@ -324,9 +322,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Pixi (ESM)", "language": "python", - "name": "python3" + "name": "pixi-esm" }, "language_info": { "codemirror_mode": { @@ -338,7 +336,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.9" + "version": "3.12.12" } }, "nbformat": 4, diff --git a/cookbook/tutorials/esm3_generate.ipynb b/cookbook/tutorials/esm3_generate.ipynb index c391f3a8..52b68f31 100644 --- a/cookbook/tutorials/esm3_generate.ipynb +++ b/cookbook/tutorials/esm3_generate.ipynb @@ -31,7 +31,7 @@ "source": [ "%set_env TOKENIZERS_PARALLELISM=false\n", "# If you are working in colab, uncomment these lines to install dependencies\n", - "# !pip install esm@git+https://github.com/Biohub/esm.git@c94ed8d\n", + "# !pip install esm@git+https://github.com/Biohub/esm.git@main\n", "# !pip install py3Dmol\n", "\n", "import numpy as np\n", diff --git a/cookbook/tutorials/esm3_guided_generation.ipynb b/cookbook/tutorials/esm3_guided_generation.ipynb index 59364b29..1e4b0b49 100644 --- a/cookbook/tutorials/esm3_guided_generation.ipynb +++ b/cookbook/tutorials/esm3_guided_generation.ipynb @@ -38,7 +38,7 @@ "outputs": [], "source": [ "# # If you are working in colab, uncomment these lines to install dependencies\n", - "# !pip install esm@git+https://github.com/Biohub/esm.git@c94ed8d\n", + "# !pip install esm@git+https://github.com/Biohub/esm.git@main\n", "# !pip install py3dmol" ] }, diff --git a/cookbook/tutorials/esmc_layer_sweep.ipynb b/cookbook/tutorials/esmc_layer_sweep.ipynb index e495e823..c37bec3a 100644 --- a/cookbook/tutorials/esmc_layer_sweep.ipynb +++ b/cookbook/tutorials/esmc_layer_sweep.ipynb @@ -73,7 +73,7 @@ "outputs": [], "source": [ "# If you are working in colab, uncomment these lines to install dependencies\n", - "# !pip install esm@git+https://github.com/Biohub/esm.git@c94ed8d" + "# !pip install esm@git+https://github.com/Biohub/esm.git@main" ] }, { diff --git a/cookbook/tutorials/esmc_mutation_scoring.ipynb b/cookbook/tutorials/esmc_mutation_scoring.ipynb index 4b912058..49a529c4 100644 --- a/cookbook/tutorials/esmc_mutation_scoring.ipynb +++ b/cookbook/tutorials/esmc_mutation_scoring.ipynb @@ -77,7 +77,7 @@ "outputs": [], "source": [ "# If you are working in colab, uncomment these lines to install dependencies\n", - "# !pip install esm@git+https://github.com/Biohub/esm.git@c94ed8d\n", + "# !pip install esm@git+https://github.com/Biohub/esm.git@main\n", "# !pip install py3dmol" ] }, diff --git a/cookbook/tutorials/esmc_sae_feature_interpretation.ipynb b/cookbook/tutorials/esmc_sae_feature_interpretation.ipynb index 76469326..7e0f8e35 100644 --- a/cookbook/tutorials/esmc_sae_feature_interpretation.ipynb +++ b/cookbook/tutorials/esmc_sae_feature_interpretation.ipynb @@ -45,26 +45,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "cell-3", "metadata": { "id": "cell-3" }, "outputs": [], "source": [ - "# Install dependencies\n", - "# If you are working in colab, uncomment this line to install dependencies\n", + "# If you are working in colab, uncomment these lines to install dependencies\n", "\n", - "#!pip install -q py3Dmol matplotlib requests numpy" + "!pip install -q \"esm @ git+https://github.com/Biohub/esm.git@main\"\n", + "!pip install -q py3Dmol matplotlib requests numpy " ] }, { "cell_type": "code", - "execution_count": null, - "id": "cell-4", - "metadata": { - "id": "cell-4" - }, + "execution_count": 3, + "id": "4eb60dfb", + "metadata": {}, "outputs": [], "source": [ "from functools import lru_cache\n", @@ -237,7 +235,7 @@ "source": [ "Now we'll extract SAE features using the Biohub API. We use:\n", "- **Model**: `esmc-6b-2024-12` (6 billion parameter ESMC model)\n", - "- **SAE**: `esmc-6b-2024-12-sae-sweep-layer60-k64-codebook16384` (k=64 means top 64 features per position)\n", + "- **SAE**: `esmc-6b-2024-12-sae-layer60-k64-codebook16384` (k=64 means top 64 features per position)\n", "- **Normalization**: `normalize_features=True` applies TF-IDF normalization to down-weight common features" ] }, @@ -255,7 +253,7 @@ "protein_tensor = model.encode(protein)\n", "\n", "# Get SAE features\n", - "sae_model_name = \"esmc-6b-2024-12-sae-sweep-layer60-k64-codebook16384\"\n", + "sae_model_name = \"esmc-6b-2024-12-sae-layer60-k64-codebook16384\"\n", "output = model.logits(\n", " protein_tensor,\n", " config=LogitsConfig(\n", diff --git a/cookbook/tutorials/esmfold2.ipynb b/cookbook/tutorials/esmfold2.ipynb index f564d872..7b14ce59 100644 --- a/cookbook/tutorials/esmfold2.ipynb +++ b/cookbook/tutorials/esmfold2.ipynb @@ -57,7 +57,7 @@ "outputs": [], "source": [ "# If you are working in colab, uncomment these lines to install dependencies\n", - "# !pip install esm@git+https://github.com/Biohub/esm.git@c94ed8d\n", + "# !pip install esm@git+https://github.com/Biohub/esm.git@main\n", "# !pip install py3dmol" ] }, diff --git a/cookbook/tutorials/esmprotein.ipynb b/cookbook/tutorials/esmprotein.ipynb index d68a1c82..d972403e 100644 --- a/cookbook/tutorials/esmprotein.ipynb +++ b/cookbook/tutorials/esmprotein.ipynb @@ -52,7 +52,7 @@ "outputs": [], "source": [ "# If you are working in colab, uncomment these lines to install dependencies\n", - "# ! pip install esm@git+https://github.com/Biohub/esm.git@c94ed8d\n", + "# ! pip install esm@git+https://github.com/Biohub/esm.git@main\n", "# ! pip install py3Dmol\n", "# ! pip install matplotlib\n", "# ! pip install dna-features-viewer" diff --git a/cookbook/tutorials/gfp_design.ipynb b/cookbook/tutorials/gfp_design.ipynb index 9dc7a7d4..f5e4140b 100644 --- a/cookbook/tutorials/gfp_design.ipynb +++ b/cookbook/tutorials/gfp_design.ipynb @@ -41,7 +41,7 @@ "outputs": [], "source": [ "# If you are working in colab, uncomment these lines to install dependencies\n", - "# !pip install esm@git+https://github.com/Biohub/esm.git@c94ed8d\n", + "# !pip install esm@git+https://github.com/Biohub/esm.git@main\n", "# !pip install py3Dmol\n", "\n", "from IPython.display import clear_output\n", diff --git a/esm/models/esmfold2/prepare_input.py b/esm/models/esmfold2/prepare_input.py index 5355fee6..fbbbe4e8 100644 --- a/esm/models/esmfold2/prepare_input.py +++ b/esm/models/esmfold2/prepare_input.py @@ -100,6 +100,8 @@ class ChainInfo: sym_id: int mol_type: int tokens: list[TokenInfo] = field(default_factory=list) + # (atom_name1, atom_name2) bonds for SMILES ligands, which have no CCD entry. + ligand_bonds: list[tuple[str, str]] = field(default_factory=list) # ============================================================================= @@ -566,8 +568,11 @@ def tokenize_ligand_smiles( atom_offset: int, space_uid_offset: int, seed: int | None = None, -) -> tuple[list[TokenInfo], list[AtomInfo]]: - """Tokenize a ligand from SMILES (1 token per heavy atom).""" +) -> tuple[list[TokenInfo], list[AtomInfo], list[tuple[str, str]]]: + """Tokenize a ligand from SMILES (1 token per heavy atom). + + Returns tokens, atoms, and heavy-atom bonds as (name1, name2) pairs. + """ from rdkit import Chem from rdkit.Chem import AllChem @@ -651,7 +656,13 @@ def tokenize_ligand_smiles( token_idx += 1 atom_idx += 1 - return tokens, atoms_list + bonds: list[tuple[str, str]] = [] + for bond in mol_no_h.GetBonds(): + n1 = bond.GetBeginAtom().GetProp("name") + n2 = bond.GetEndAtom().GetProp("name") + bonds.append((n1, n2)) + + return tokens, atoms_list, bonds # ============================================================================= @@ -753,6 +764,7 @@ def build_chains_from_input( elif isinstance(item, LigandInput): has_cov = chain_id_str in covalent_chain_ids + ligand_bonds: list[tuple[str, str]] = [] if item.ccd is not None: if item.smiles is not None: warnings.warn("Both ccd and smiles provided, using ccd") @@ -767,7 +779,7 @@ def build_chains_from_input( has_covalent_bond=has_cov, ) elif item.smiles is not None: - new_tokens, new_atoms = tokenize_ligand_smiles( + new_tokens, new_atoms, ligand_bonds = tokenize_ligand_smiles( smiles=item.smiles, entity_id=entity_id, asym_id=asym_id, @@ -789,6 +801,7 @@ def build_chains_from_input( sym_id=sym_id, mol_type=new_tokens[0].mol_type if new_tokens else MOL_TYPE_PROTEIN, tokens=new_tokens, + ligand_bonds=ligand_bonds if isinstance(item, LigandInput) else [], ) chains.append(chain) all_tokens.extend(new_tokens) @@ -990,16 +1003,24 @@ def add_bond(i: int, j: int) -> None: (atom.name, atom.token_index) ) + # SMILES ligand bonds keyed by (asym_id, residue_index 0). + explicit_bonds: dict[tuple[int, int], list[tuple[str, str]]] = { + (c.asym_id, 0): c.ligand_bonds for c in chains if c.ligand_bonds + } + # Add intra-residue bonds from CCD for (asym_id_val, res_idx), atom_list in residue_tokens.items(): if not atom_list: continue res_name = tokens[atom_list[0][1]].residue_name - ccd_bonds = get_ligand_ccd_bonds(res_name) atom_to_tok = {name: ti for name, ti in atom_list} - if ccd_bonds: - for a1, a2 in ccd_bonds: + bonds = explicit_bonds.get((asym_id_val, res_idx)) + if bonds is None: + bonds = get_ligand_ccd_bonds(res_name) + + if bonds: + for a1, a2 in bonds: if a1 in atom_to_tok and a2 in atom_to_tok: add_bond(atom_to_tok[a1], atom_to_tok[a2]) else: diff --git a/esm/models/esmfold2/prepare_input_test.py b/esm/models/esmfold2/prepare_input_test.py new file mode 100644 index 00000000..338a0625 --- /dev/null +++ b/esm/models/esmfold2/prepare_input_test.py @@ -0,0 +1,31 @@ +"""Tests for ESMFold2 input preparation (prepare_input).""" + +import pytest +from rdkit import Chem + +from esm.models.esmfold2.prepare_input import ( + build_chains_from_input, + compute_token_bonds, +) +from esm.models.esmfold2.types import LigandInput, StructurePredictionInput + + +@pytest.mark.parametrize( + "smiles", + [ + "c1ccccc1", # benzene: 6 atoms, 6 bonds + # The drug-like ligand from the SMILES-vs-CCD issue. + "COC1=CC=C(N2C3=C(C(C(N)=O)=N2)CCN(C4=CC=C(N5CCCCC5=O)C=C4)C3=O)C=C1", + ], +) +def test_smiles_ligand_bonds_match_molecular_graph(smiles: str): + """SMILES ligand bonds must match the molecular graph, not a clique (#313).""" + spi = StructurePredictionInput(sequences=[LigandInput(id="B", smiles=smiles)]) + chains, tokens, atoms = build_chains_from_input(spi, seed=0) + token_bonds = compute_token_bonds(tokens, atoms, spi, chains) + + mol = Chem.MolFromSmiles(smiles) + assert len(tokens) == mol.GetNumAtoms() + n_edges = int(token_bonds.sum().item()) // 2 # symmetric matrix + assert n_edges == mol.GetNumBonds() + assert n_edges < len(tokens) * (len(tokens) - 1) // 2 # not a clique diff --git a/pixi.lock b/pixi.lock index 6e10e783..f4356818 100644 --- a/pixi.lock +++ b/pixi.lock @@ -146,7 +146,7 @@ environments: - conda: https://conda.anaconda.org/conda-forge/noarch/wheel-0.45.1-pyhd8ed1ab_1.conda - conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.21.0-pyhd8ed1ab_1.conda - pypi: . - - pypi: git+https://github.com/Biohub/transformers.git?rev=3a8956fb4d4ea16b0ec8e71deef2c2909b6a5cbf#3a8956fb4d4ea16b0ec8e71deef2c2909b6a5cbf + - pypi: git+https://github.com/Biohub/transformers.git?rev=main#3a8956fb4d4ea16b0ec8e71deef2c2909b6a5cbf - pypi: https://files.pythonhosted.org/packages/00/78/9cbcc1c073b9d4918e925af1a059762265dc65004e020511b2a06fbfd020/pydssp-0.9.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/02/e9/367e81e114deb92a6e0d5740f0bff4548af710be318af65265b9aad72237/botocore-1.40.9-py3-none-any.whl @@ -346,7 +346,7 @@ environments: - 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conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.21.0-pyhd8ed1ab_1.conda - pypi: . - - pypi: git+https://github.com/Biohub/transformers.git?rev=3a8956fb4d4ea16b0ec8e71deef2c2909b6a5cbf#3a8956fb4d4ea16b0ec8e71deef2c2909b6a5cbf + - pypi: git+https://github.com/Biohub/transformers.git?rev=main#3a8956fb4d4ea16b0ec8e71deef2c2909b6a5cbf - pypi: https://files.pythonhosted.org/packages/00/78/9cbcc1c073b9d4918e925af1a059762265dc65004e020511b2a06fbfd020/pydssp-0.9.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/02/e9/367e81e114deb92a6e0d5740f0bff4548af710be318af65265b9aad72237/botocore-1.40.9-py3-none-any.whl @@ -863,7 +863,7 @@ environments: - conda: https://conda.anaconda.org/conda-forge/osx-arm64/zstandard-0.23.0-py312hea69d52_2.conda - conda: https://conda.anaconda.org/conda-forge/osx-arm64/zstd-1.5.7-h6491c7d_2.conda - pypi: . - - pypi: git+https://github.com/Biohub/transformers.git?rev=3a8956fb4d4ea16b0ec8e71deef2c2909b6a5cbf#3a8956fb4d4ea16b0ec8e71deef2c2909b6a5cbf + - pypi: git+https://github.com/Biohub/transformers.git?rev=main#3a8956fb4d4ea16b0ec8e71deef2c2909b6a5cbf - pypi: https://files.pythonhosted.org/packages/00/78/9cbcc1c073b9d4918e925af1a059762265dc65004e020511b2a06fbfd020/pydssp-0.9.1-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl - pypi: https://files.pythonhosted.org/packages/02/e9/367e81e114deb92a6e0d5740f0bff4548af710be318af65265b9aad72237/botocore-1.40.9-py3-none-any.whl @@ -5297,7 +5297,7 @@ packages: name: esm requires_dist: - torch>=2.2.0 - - transformers @ git+https://github.com/Biohub/transformers.git@3a8956fb4d4ea16b0ec8e71deef2c2909b6a5cbf + - transformers @ git+https://github.com/Biohub/transformers.git@main - ipython - einops - biotite>=1.0.0 @@ -5320,7 +5320,7 @@ packages: - dna-features-viewer - accelerate requires_python: '>=3.12,<3.13' -- pypi: git+https://github.com/Biohub/transformers.git?rev=3a8956fb4d4ea16b0ec8e71deef2c2909b6a5cbf#3a8956fb4d4ea16b0ec8e71deef2c2909b6a5cbf +- pypi: git+https://github.com/Biohub/transformers.git?rev=main#3a8956fb4d4ea16b0ec8e71deef2c2909b6a5cbf name: transformers version: 4.57.6 requires_dist: diff --git a/pyproject.toml b/pyproject.toml index 6c99712e..7ab6d609 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -22,7 +22,7 @@ classifiers = [ dependencies = [ "torch>=2.2.0", - "transformers @ git+https://github.com/Biohub/transformers.git@3a8956fb4d4ea16b0ec8e71deef2c2909b6a5cbf", + "transformers @ git+https://github.com/Biohub/transformers.git@main", "ipython", "einops", "biotite>=1.0.0",