Add saving Protein to mmCIF file and reading Protein from mmCIF file.

PiperOrigin-RevId: 540873522
Change-Id: I502551e47df701cb39f72b380e9e4e818ea9c04c

alphafold/common/mmcif_metadata.py

@@ -0,0 +1,213 @@
+# Copyright 2021 DeepMind Technologies Limited
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""mmCIF metadata."""
+
+from typing import Mapping, Sequence
+from alphafold import version
+import numpy as np
+
+
+_DISCLAIMER = """ALPHAFOLD DATA, COPYRIGHT (2021) DEEPMIND TECHNOLOGIES LIMITED.
+THE INFORMATION PROVIDED IS THEORETICAL MODELLING ONLY AND CAUTION SHOULD BE
+EXERCISED IN ITS USE. IT IS PROVIDED "AS-IS" WITHOUT ANY WARRANTY OF ANY KIND,
+WHETHER EXPRESSED OR IMPLIED. NO WARRANTY IS GIVEN THAT USE OF THE INFORMATION
+SHALL NOT INFRINGE THE RIGHTS OF ANY THIRD PARTY. DISCLAIMER: THE INFORMATION IS
+NOT INTENDED TO BE A SUBSTITUTE FOR PROFESSIONAL MEDICAL ADVICE, DIAGNOSIS, OR
+TREATMENT, AND DOES NOT CONSTITUTE MEDICAL OR OTHER PROFESSIONAL ADVICE. IT IS
+AVAILABLE FOR ACADEMIC AND COMMERCIAL PURPOSES, UNDER CC-BY 4.0 LICENCE."""
+
+# Authors of the Nature methods paper we reference in the mmCIF.
+_MMCIF_PAPER_AUTHORS = (
+    'Jumper, John',
+    'Evans, Richard',
+    'Pritzel, Alexander',
+    'Green, Tim',
+    'Figurnov, Michael',
+    'Ronneberger, Olaf',
+    'Tunyasuvunakool, Kathryn',
+    'Bates, Russ',
+    'Zidek, Augustin',
+    'Potapenko, Anna',
+    'Bridgland, Alex',
+    'Meyer, Clemens',
+    'Kohl, Simon A. A.',
+    'Ballard, Andrew J.',
+    'Cowie, Andrew',
+    'Romera-Paredes, Bernardino',
+    'Nikolov, Stanislav',
+    'Jain, Rishub',
+    'Adler, Jonas',
+    'Back, Trevor',
+    'Petersen, Stig',
+    'Reiman, David',
+    'Clancy, Ellen',
+    'Zielinski, Michal',
+    'Steinegger, Martin',
+    'Pacholska, Michalina',
+    'Berghammer, Tamas',
+    'Silver, David',
+    'Vinyals, Oriol',
+    'Senior, Andrew W.',
+    'Kavukcuoglu, Koray',
+    'Kohli, Pushmeet',
+    'Hassabis, Demis',
+)
+
+# Authors of the mmCIF - we set them to be equal to the authors of the paper.
+_MMCIF_AUTHORS = _MMCIF_PAPER_AUTHORS
+
+
+def add_metadata_to_mmcif(
+    old_cif: Mapping[str, Sequence[str]], model_type: str
+) -> Mapping[str, Sequence[str]]:
+  """Adds AlphaFold metadata in the given mmCIF."""
+  cif = {}
+
+  # ModelCIF conformation dictionary.
+  cif['_audit_conform.dict_name'] = ['mmcif_ma.dic']
+  cif['_audit_conform.dict_version'] = ['1.3.9']
+  cif['_audit_conform.dict_location'] = [
+      'https://raw.githubusercontent.com/ihmwg/ModelCIF/master/dist/'
+      'mmcif_ma.dic'
+  ]
+
+  # License and disclaimer.
+  cif['_pdbx_data_usage.id'] = ['1', '2']
+  cif['_pdbx_data_usage.type'] = ['license', 'disclaimer']
+  cif['_pdbx_data_usage.details'] = [
+      'Data in this file is available under a CC-BY-4.0 license.',
+      _DISCLAIMER,
+  ]
+  cif['_pdbx_data_usage.url'] = [
+      'https://creativecommons.org/licenses/by/4.0/',
+      '?',
+  ]
+  cif['_pdbx_data_usage.name'] = ['CC-BY-4.0', '?']
+
+  # Structure author details.
+  cif['_audit_author.name'] = []
+  cif['_audit_author.pdbx_ordinal'] = []
+  for author_index, author_name in enumerate(_MMCIF_AUTHORS, start=1):
+    cif['_audit_author.name'].append(author_name)
+    cif['_audit_author.pdbx_ordinal'].append(str(author_index))
+
+  # Paper author details.
+  cif['_citation_author.citation_id'] = []
+  cif['_citation_author.name'] = []
+  cif['_citation_author.ordinal'] = []
+  for author_index, author_name in enumerate(_MMCIF_PAPER_AUTHORS, start=1):
+    cif['_citation_author.citation_id'].append('primary')
+    cif['_citation_author.name'].append(author_name)
+    cif['_citation_author.ordinal'].append(str(author_index))
+
+  # Paper citation details.
+  cif['_citation.id'] = ['primary']
+  cif['_citation.title'] = [
+      'Highly accurate protein structure prediction with AlphaFold'
+  ]
+  cif['_citation.journal_full'] = ['Nature']
+  cif['_citation.journal_volume'] = ['596']
+  cif['_citation.page_first'] = ['583']
+  cif['_citation.page_last'] = ['589']
+  cif['_citation.year'] = ['2021']
+  cif['_citation.journal_id_ASTM'] = ['NATUAS']
+  cif['_citation.country'] = ['UK']
+  cif['_citation.journal_id_ISSN'] = ['0028-0836']
+  cif['_citation.journal_id_CSD'] = ['0006']
+  cif['_citation.book_publisher'] = ['?']
+  cif['_citation.pdbx_database_id_PubMed'] = ['34265844']
+  cif['_citation.pdbx_database_id_DOI'] = ['10.1038/s41586-021-03819-2']
+
+  # Type of data in the dataset including data used in the model generation.
+  cif['_ma_data.id'] = ['1']
+  cif['_ma_data.name'] = ['Model']
+  cif['_ma_data.content_type'] = ['model coordinates']
+
+  # Description of number of instances for each entity.
+  cif['_ma_target_entity_instance.asym_id'] = old_cif['_struct_asym.id']
+  cif['_ma_target_entity_instance.entity_id'] = old_cif[
+      '_struct_asym.entity_id'
+  ]
+  cif['_ma_target_entity_instance.details'] = ['.'] * len(
+      cif['_ma_target_entity_instance.entity_id']
+  )
+
+  # Details about the target entities.
+  cif['_ma_target_entity.entity_id'] = cif[
+      '_ma_target_entity_instance.entity_id'
+  ]
+  cif['_ma_target_entity.data_id'] = ['1'] * len(
+      cif['_ma_target_entity.entity_id']
+  )
+  cif['_ma_target_entity.origin'] = ['.'] * len(
+      cif['_ma_target_entity.entity_id']
+  )
+
+  # Details of the models being deposited.
+  cif['_ma_model_list.ordinal_id'] = ['1']
+  cif['_ma_model_list.model_id'] = ['1']
+  cif['_ma_model_list.model_group_id'] = ['1']
+  cif['_ma_model_list.model_name'] = ['Top ranked model']
+
+  cif['_ma_model_list.model_group_name'] = [
+      f'AlphaFold {model_type} v{version.__version__} model'
+  ]
+  cif['_ma_model_list.data_id'] = ['1']
+  cif['_ma_model_list.model_type'] = ['Ab initio model']
+
+  # Software used.
+  cif['_software.pdbx_ordinal'] = ['1']
+  cif['_software.name'] = ['AlphaFold']
+  cif['_software.version'] = [f'v{version.__version__}']
+  cif['_software.type'] = ['package']
+  cif['_software.description'] = ['Structure prediction']
+  cif['_software.classification'] = ['other']
+  cif['_software.date'] = ['?']
+
+  # Collection of software into groups.
+  cif['_ma_software_group.ordinal_id'] = ['1']
+  cif['_ma_software_group.group_id'] = ['1']
+  cif['_ma_software_group.software_id'] = ['1']
+
+  # Method description to conform with ModelCIF.
+  cif['_ma_protocol_step.ordinal_id'] = ['1', '2', '3']
+  cif['_ma_protocol_step.protocol_id'] = ['1', '1', '1']
+  cif['_ma_protocol_step.step_id'] = ['1', '2', '3']
+  cif['_ma_protocol_step.method_type'] = [
+      'coevolution MSA',
+      'template search',
+      'modeling',
+  ]
+
+  # Details of the metrics use to assess model confidence.
+  cif['_ma_qa_metric.id'] = ['1', '2']
+  cif['_ma_qa_metric.name'] = ['pLDDT', 'pLDDT']
+  # Accepted values are distance, energy, normalised score, other, zscore.
+  cif['_ma_qa_metric.type'] = ['pLDDT', 'pLDDT']
+  cif['_ma_qa_metric.mode'] = ['global', 'local']
+  cif['_ma_qa_metric.software_group_id'] = ['1', '1']
+
+  # Global model confidence metric value.
+  cif['_ma_qa_metric_global.ordinal_id'] = ['1']
+  cif['_ma_qa_metric_global.model_id'] = ['1']
+  cif['_ma_qa_metric_global.metric_id'] = ['1']
+  global_plddt = np.mean(
+      [float(v) for v in old_cif['_atom_site.B_iso_or_equiv']]
+  )
+  cif['_ma_qa_metric_global.metric_value'] = [f'{global_plddt:.2f}']
+
+  cif['_atom_type.symbol'] = sorted(set(old_cif['_atom_site.type_symbol']))
+
+  return cif