diff --git a/.gitignore b/.gitignore
index 1b0c7406..fe8666be 100644
--- a/.gitignore
+++ b/.gitignore
@@ -3,6 +3,7 @@
 *.parquet
 *.dbs
 data/*
+!data/models/*png
 !data/.gitkeep
 logs/*
 *.log
diff --git a/README.md b/README.md
index e266150a..76bbbe4c 100644
--- a/README.md
+++ b/README.md
@@ -27,13 +27,6 @@ Create a virtual environment:
 uv sync
 ```
 
-> **Note:** This project requires PyArrow >= 23.0.1. If you encounter errors
-> related to parquet files, upgrade PyArrow by running:
->
-> ```sh
-> uv add --upgrade pyarrow
-> ```
-
 ## Scrape MD data repositories
 
 Currently, we are scraping the following data repositories:
@@ -50,6 +43,14 @@ Soon:
 - [OSF](docs/osf.md)
 - [NMRlipids](docs/nmrlipids.md)
 
+### Data model for scraped data
+
+Generate a visual diagram of the Pydantic model schema to see how scraped metadata are represented:
+
+```sh
+uv run draw-pydantic-schema --out-path data/models/pydantic_schema.png
+```
+
 ### Scraping Zenodo, Figshare and OSF
 
 To scrape Zenodo, Figshare and OSF, you need a token. Because these data repositories are generic data repositories,
@@ -83,14 +84,6 @@ Aggregated results are stored in the `data/` folder in `stats_*.tsv` files.
 
 The notebook `notebooks/scraper_stats.ipynb` provides more in-depth analysis and figures.
 
-### Visualise Pydantic schemas
-
-Generate a visual diagram of the Pydantic models schema to see how MDverse entities (datasets, simulations, files, and publications) link together:
-
-```sh
-uv run draw-pydantic-schema --out_path data/models/pydantic_schema.png
-```
-
 ## Analyze Gromacs mdp and gro files
 
 ### Download files
diff --git a/data/models/pydantic_schema.png b/data/models/pydantic_schema.png
index 71df5573..b8a5b322 100644
Binary files a/data/models/pydantic_schema.png and b/data/models/pydantic_schema.png differ
diff --git a/docs/atlas.md b/docs/atlas.md
index 19e0e924..79739cb9 100644
--- a/docs/atlas.md
+++ b/docs/atlas.md
@@ -40,7 +40,7 @@ Example with dataset id `1k5n_A`:
 Remarks:
 
 - The title of the dataset is the protein name.
-- No comment or description is provided. We used the organism name as description.
+- No description is provided. We generate one based on other available metadata.
 - Parameters of molecular dynamics simulations are provided through the API endpoint <https://www.dsimb.inserm.fr/ATLAS/api/MD_parameters>.
 
 ### Metadata for files
diff --git a/pyproject.toml b/pyproject.toml
index dfae8654..25d12584 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -43,7 +43,7 @@ dependencies = [
     "certifi>=2026.1.4",
     "html5lib>=1.1",
     "pandas>=2.3.3",
-    "pyarrow>=23.0.0",
+    "pyarrow>=23.0.1",
     "tqdm>=4.67.3",
     "sqlmodel>=0.0.37",
     "fastparquet>=2025.12.0",
@@ -62,7 +62,7 @@ dev = [
     "jupyterlab>=4.4.9",
     "matplotlib>=3.10.1",
     "plotly>=6.0.0",
-    "prek>=0.3.2",
+    "prek>=0.4.10",
     "pysankeybeta>=1.4.2",
     "pytest>=9.0.2",
     "ruff>=0.15.5",
diff --git a/src/mdverse/models/draw_pydantic_schema.py b/src/mdverse/models/draw_pydantic_schema.py
index 3301e134..9a35674a 100644
--- a/src/mdverse/models/draw_pydantic_schema.py
+++ b/src/mdverse/models/draw_pydantic_schema.py
@@ -14,14 +14,14 @@
 
 @click.command()
 @click.option(
-    "--out_path",
+    "--out-path",
     type=click.Path(writable=True, path_type=Path),
-    help="Path where the generated ERD image will be saved.",
+    help="Path where the generated data model image will be saved.",
 )
 def main(out_path: Path) -> None:
     """Generate and save an Entity-Relationship Diagram for Pydantic metadata models."""
     logger = create_logger()
-    logger.info("Initializing Entity-Relationship Diagram.")
+    logger.info("Building schema for data model...")
     diagram = erd.EntityRelationshipDiagram()
     # Add Pydantic models to the diagram
     diagram.add_model(DatasetMetadata)
diff --git a/src/mdverse/models/simulation.py b/src/mdverse/models/simulation.py
index 18378824..f485a774 100644
--- a/src/mdverse/models/simulation.py
+++ b/src/mdverse/models/simulation.py
@@ -77,6 +77,9 @@ class Molecule(BaseModel):
         None, description="Sequence of the molecule for protein and nucleic acid."
     )
     inchikey: str | None = Field(None, description="InChIKey of the molecule.")
+    organism: str | None = Field(
+        None, description="Organism the molecule is coming from."
+    )
     external_identifiers: list[ExternalIdentifier] = Field(
         default_factory=list,
         description=("List of external database identifiers for this molecule."),
diff --git a/src/mdverse/scrapers/atlas.py b/src/mdverse/scrapers/atlas.py
index a4da9671..ecdde269 100644
--- a/src/mdverse/scrapers/atlas.py
+++ b/src/mdverse/scrapers/atlas.py
@@ -14,11 +14,13 @@
 from mdverse.models.dataset import DatasetMetadata
 from mdverse.models.enums import DatasetSourceName, ExternalDatabaseName, MoleculeType
 from mdverse.models.file import FileMetadata
+from mdverse.models.person import Person
 from mdverse.models.scraper import ScraperContext
 from mdverse.models.simulation import (
     ExternalIdentifier,
     ForceFieldModel,
     Molecule,
+    SimulationMetadata,
     Software,
 )
 from mdverse.models.utils import (
@@ -41,14 +43,48 @@
 BASE_URL = "https://www.dsimb.inserm.fr/ATLAS/"
 BASE_API_URL = "https://www.dsimb.inserm.fr/ATLAS/api"
 PDB_LIST_URL = "https://www.dsimb.inserm.fr/ATLAS/data/download/distributions/2024_11_18_ATLAS_pdb.txt"
+AFFILIATION = (
+    "Université Paris Cité and Université des Antilles and Université de la Réunion, "
+    "INSERM, BIGR, F-75014 Paris, France"
+)
 ATLAS_METADATA = {
     "license": "CC-BY-NC",  # https://www.dsimb.inserm.fr/ATLAS/download.html
-    "author_name": [  # https://academic.oup.com/nar/article/52/D1/D384/7438909
-        "Yann Vander Meersche",
-        "Gabriel Cretin",
-        "Aria Gheeraert",
-        "Jean-Christophe Gelly",
-        "Tatiana Galochkina",
+    "authors": [  # https://academic.oup.com/nar/article/52/D1/D384/7438909
+        Person(
+            full_name="Yann Vander Meersche",
+            first_name="Yann",
+            last_name="Vander Meersche",
+            orcid="0000-0002-6680-8104",
+            affiliation=AFFILIATION,
+        ),
+        Person(
+            full_name="Gabriel Cretin",
+            first_name="Gabriel",
+            last_name="Cretin",
+            orcid="0000-0002-3522-7083",
+            affiliation=AFFILIATION,
+        ),
+        Person(
+            full_name="Aria Gheeraert",
+            first_name="Aria",
+            last_name="Gheeraert",
+            orcid="0000-0001-7493-8702",
+            affiliation=AFFILIATION,
+        ),
+        Person(
+            full_name="Jean-Christophe Gelly",
+            first_name="Jean-Christophe",
+            last_name="Gelly",
+            orcid="0000-0001-5138-361X",
+            affiliation=AFFILIATION,
+        ),
+        Person(
+            full_name="Tatiana Galochkina",
+            first_name="Tatiana",
+            last_name="Galochkina",
+            orcid="0000-0002-3608-5208",
+            affiliation=AFFILIATION,
+        ),
     ],
     "doi": "10.1093/nar/gkad1084",  # https://academic.oup.com/nar/article/52/D1/D384/7438909
     "external_link": ["https://www.dsimb.inserm.fr/ATLAS/"],
@@ -106,6 +142,47 @@ def extract_files_from_html(
     return files_metadata
 
 
+def generate_description(
+    metadata: SimulationMetadata, logger: "loguru.Logger" = loguru.logger
+) -> str:
+    """Generate description for ATLAS dataset based on metadata.
+
+    Parameters
+    ----------
+    metadata : SimulationMetadata
+        Metadata object for the dataset.
+    logger : loguru.Logger
+        Logger for logging messages.
+
+    Returns
+    -------
+    str
+        Generated description string.
+    """
+    description = "[automatically generated] Molecular dynamics simulation of "
+    for molecule in metadata.molecules:
+        description += f"{molecule.name} "
+        description += f"from organism {molecule.organism} "
+        external_identifiers = [
+            f"{ext_id.database_name.value} ID: {ext_id.identifier}"
+            for ext_id in molecule.external_identifiers
+        ]
+        if external_identifiers:
+            description += "(" + ", ".join(external_identifiers) + ") "
+    description += f"with {metadata.software[0].name} {metadata.software[0].version} "
+    forcefields_models = [
+        f"{ffm.name} {ffm.version}" if ffm.version else f"{ffm.name}"
+        for ffm in metadata.forcefields_models
+    ]
+    if metadata.forcefields_models:
+        description += "using " + " and ".join(forcefields_models) + " "
+    description += f"at {metadata.simulation_temperatures_in_kelvin[0]} K "
+    description += f"for {metadata.simulation_times[0]}."
+    logger.debug("Dataset generated description:")
+    logger.debug(description)
+    return description
+
+
 def scrape_metadata_for_one_dataset(
     client: httpx.Client,
     chain_id: str,
@@ -150,13 +227,12 @@ def scrape_metadata_for_one_dataset(
         "dataset_id_in_repository": chain_id,
         "dataset_url_in_repository": dataset_url,
         "title": meta_json.get("protein_name"),
-        "description": meta_json.get("organism"),
         "license": ATLAS_METADATA["license"],
-        "author_names": ATLAS_METADATA["author_name"],
+        "authors": ATLAS_METADATA["authors"],
         "doi": ATLAS_METADATA["doi"],
         "external_links": ATLAS_METADATA["external_link"],
     }
-    # Add molecules.
+    # Gather metadata for molecules.
     external_identifiers = []
     if meta_json.get("PDB"):
         external_identifiers.append(
@@ -172,37 +248,39 @@ def scrape_metadata_for_one_dataset(
                 identifier=meta_json["UniProt"],
             )
         )
-    metadata["molecules"] = [
-        Molecule(
-            name=meta_json.get("protein_name"),
-            sequence=meta_json.get("sequence"),
-            external_identifiers=external_identifiers,
-            type=MoleculeType.PROTEIN,
-        )
-    ]
-    # Add software.
-    metadata["software"] = [
+    molecule = Molecule(
+        name=meta_json.get("protein_name"),
+        sequence=meta_json.get("sequence"),
+        organism=meta_json.get("organism"),
+        external_identifiers=external_identifiers,
+        type=MoleculeType.PROTEIN,
+    )
+    # Gather metadata for software.
+    software = [
         Software(
             name=ATLAS_METADATA["software_name"],
             version=ATLAS_METADATA["software_version"],
         )
     ]
-    # Add forcefields and models.
-    metadata["forcefields_models"] = [
+    # Gather metadata for forcefields and models.
+    forcefields_models = [
         ForceFieldModel(
             name=ATLAS_METADATA["forcefield_name"],
             version=ATLAS_METADATA["forcefield_version"],
         ),
         ForceFieldModel(name=ATLAS_METADATA["water_model"]),
     ]
-    # Add simulation temperature.
-    metadata["simulation_temperatures_in_kelvin"] = [
-        ATLAS_METADATA["simulation_temperature"]
-    ]
-    # Add simulation time.
-    metadata["simulation_times"] = [ATLAS_METADATA["simulation_time"]]
-    # Add simulation time step.
-    metadata["simulation_timesteps_in_fs"] = [ATLAS_METADATA["simulation_timestep"]]
+    # Create simulation metadata.
+    simulation_metadata = SimulationMetadata(
+        molecules=[molecule],
+        software=software,
+        forcefields_models=forcefields_models,
+        simulation_temperatures_in_kelvin=[ATLAS_METADATA["simulation_temperature"]],
+        simulation_times=[ATLAS_METADATA["simulation_time"]],
+        simulation_timesteps_in_fs=[ATLAS_METADATA["simulation_timestep"]],
+    )
+    metadata["simulation"] = simulation_metadata
+    metadata["description"] = generate_description(simulation_metadata)
     logger.info("Done.")
     return metadata
 
diff --git a/src/mdverse/scrapers/figshare.py b/src/mdverse/scrapers/figshare.py
index 41628691..f59dd621 100644
--- a/src/mdverse/scrapers/figshare.py
+++ b/src/mdverse/scrapers/figshare.py
@@ -12,6 +12,7 @@
 from mdverse.core.logger import create_logger
 from mdverse.models.enums import DatasetSourceName
 from mdverse.models.file import FileMetadata
+from mdverse.models.person import Person
 from mdverse.models.scraper import ScraperContext
 from mdverse.models.utils import (
     export_list_of_models_to_parquet,
@@ -200,7 +201,7 @@ def scrap_zip_files_content(
             f"({zip_files_counter:,}/{len(zip_files):,}"
             f":{zip_files_counter / len(zip_files):.0%})"
         )
-    logger.success("Done extracting files from zip archives.")
+    logger.success("Done extracting files from zip archives")
     return files_in_zip_metadata
 
 
@@ -244,8 +245,13 @@ def extract_metadata_from_single_dataset_record(
         "date_created": record_json.get("created_date"),
         "date_last_updated": record_json.get("modified_date"),
         "title": clean_text(record_json.get("title", "")),
-        "author_names": [
-            clean_text(author.get("full_name"))
+        "authors": [
+            Person(
+                full_name=clean_text(author.get("full_name")),
+                first_name=clean_text(author.get("first_name")),
+                last_name=clean_text(author.get("last_name")),
+                orcid=clean_text(author.get("orcid_id")),
+            )
             for author in record_json.get("authors", [])
         ],
         # Remove far too many line breaks in description.
@@ -365,7 +371,7 @@ def search_all_datasets(
                 found_datasets_per_keyword += found_datasets_per_keyword_per_page
                 logger.info(
                     f"Page {page} fetched "
-                    f"({len(found_datasets_per_keyword_per_page)} datasets)."
+                    f"({len(found_datasets_per_keyword_per_page)} datasets)"
                 )
                 page += 1
             found_datasets_per_filetype.update(found_datasets_per_keyword)
@@ -430,7 +436,7 @@ def get_metadata_for_datasets_and_files(
         dataset_metadata, files_metadata = extract_metadata_from_single_dataset_record(
             resp_json_article, scraper
         )
-        logger.info("Done.")
+        logger.info("Done")
         # Append non-empty metadata to datasets and files lists.
         if dataset_metadata:
             datasets_lst.append(dataset_metadata)
diff --git a/src/mdverse/scrapers/gpcrmd.py b/src/mdverse/scrapers/gpcrmd.py
index eea8b559..aae91825 100644
--- a/src/mdverse/scrapers/gpcrmd.py
+++ b/src/mdverse/scrapers/gpcrmd.py
@@ -5,6 +5,7 @@
 """
 
 import json
+import re
 import sys
 from pathlib import Path
 from typing import Any
@@ -16,8 +17,15 @@
 
 from mdverse.core.logger import create_logger
 from mdverse.models.enums import DatasetSourceName
+from mdverse.models.person import Person
 from mdverse.models.scraper import ScraperContext
-from mdverse.models.simulation import ForceFieldModel, Molecule, Software
+from mdverse.models.simulation import (
+    ExternalIdentifier,
+    ForceFieldModel,
+    Molecule,
+    SimulationMetadata,
+    Software,
+)
 from mdverse.models.utils import (
     export_list_of_models_to_parquet,
     normalize_datasets_metadata,
@@ -45,24 +53,12 @@ def scrape_all_datasets(
     """
     Scrape Molecular Dynamics-related datasets from the GPCRmd API.
 
-    Parameters
-    ----------
-    client : httpx.Client
-        The HTTPX client to use for making requests.
-    url : str
-        The URL of the API request.
-    logger: "loguru.Logger"
-        Logger for logging messages.
-    scraper: ScraperContext
-        Pydantic model describing the context of a scraper
-
     Returns
     -------
     list[dict]:
         A list of GPCRmd entries.
     """
     logger.info("Scraping molecular dynamics datasets from GPCRmd.")
-    logger.info("Requesting all datasets in a single fetch...")
     all_datasets = []
     response = make_http_request_with_retries(
         client,
@@ -83,13 +79,20 @@ def scrape_all_datasets(
             logger.error("Cannot find datasets.")
             logger.critical("Aborting.")
             sys.exit(1)
+    if not all_datasets:
+        logger.critical("No datasets found in GPCRmd.")
+        logger.critical("Aborting.")
+        sys.exit(1)
+    else:
+        # Log the first dataset raw metadata.
+        logger.debug("First dataset raw metadata:")
+        logger.debug(all_datasets[0])
+        logger.success(f"Scraped {len(all_datasets)} datasets in GPCRmd.")
 
     if scraper and scraper.is_in_debug_mode and len(all_datasets) >= 10:
         logger.warning("Debug mode is ON: stopping after 10 datasets.")
         # Return only the first 10 datasets for testing purposes.
         return all_datasets[:10]
-
-    logger.success(f"Scraped {len(all_datasets)} datasets in GPCRmd.")
     return all_datasets
 
 
@@ -98,27 +101,18 @@ def fetch_all_datasets_html_pages(
 ) -> list[list[str] | None]:
     """Fetch all datasets HTML pages.
 
-    Parameters
-    ----------
-    client : httpx.Client
-        The HTTPX client to use for making requests.
-    datasets : List[Dict[str, Any]]
-        List of raw GPCRmd datasets metadata.
-    logger: "loguru.Logger"
-        Logger for logging messages.
-
     Returns
     -------
     list[list[str] | None]
         The HTML content of datasets pages.
     """
-    logger.info("Fetching HTML content for all datasets from the GPCRmd repository")
+    logger.info("Fetching HTML content for all datasets.")
     datasets_html_pages = []
 
     for dataset_counter, dataset in enumerate(datasets, start=1):
         # Get the URL of the current dataset
         dataset_id = str(dataset.get("dyn_id"))
-        logger.info(f"Scraping dataset {dataset_id}:")
+        logger.info(f"Scraping dataset ID `{dataset_id}`.")
         url = dataset.get("url")
         page_content = None
         # If the dataset has a URL, attempt to fetch its HTML content
@@ -134,7 +128,6 @@ def fetch_all_datasets_html_pages(
             if response:
                 # Store the HTML text
                 html_content = response.text
-                logger.success(f"Dataset {dataset_id} fetched successfully")
                 logger.debug(f"HTML length: {len(html_content)} characters")
                 # Extract HTML page content.
                 soup = BeautifulSoup(html_content, "html.parser")
@@ -150,11 +143,13 @@ def fetch_all_datasets_html_pages(
                         page_content.append(stripped_line)
                 page_content.extend(link_targets)
             else:
-                logger.warning(f"Failed to fetch HTML page for dataset {dataset_id}")
+                logger.warning(
+                    f"Failed to fetch HTML page for dataset ID `{dataset_id}`."
+                )
         datasets_html_pages.append(page_content)
-        logger.info(
+        logger.success(
             f"Scraped {dataset_counter:,}/{len(datasets):,} "
-            f"({dataset_counter / len(datasets):.0%}) datasets"
+            f"datasets ({dataset_counter / len(datasets):.0%})."
         )
     return datasets_html_pages
 
@@ -167,11 +162,6 @@ def _extract_molecules_from_lines(lines: list[str]) -> list[Molecule] | None:
     subsequent lines expected to follow the format "Name: count".
     Parsing stops as soon as the format no longer matches this pattern.
 
-    Parameters
-    ----------
-    lines : list[str]
-        Text lines extracted from the HTML content.
-
     Returns
     -------
     list[Molecule] | None
@@ -183,16 +173,13 @@ def _extract_molecules_from_lines(lines: list[str]) -> list[Molecule] | None:
 
     for line in lines:
         clean_line = line.strip()
-
         # Skip empty lines
         if not clean_line:
             continue
-
         # Start capturing after the "Number of molecules" header
         if "Number of molecules" in clean_line:
             capture = True
             continue
-
         if capture:
             # Stop when the expected "Name: number" pattern is no longer found.
             if ":" not in clean_line or "Total" in clean_line:
@@ -216,30 +203,18 @@ def retrieve_metadata_from_html_dataset_page(
     field_name: str | None,
     dataset_id: str,
     logger: "loguru.Logger" = loguru.logger,
-) -> list[str] | list[Molecule] | None:
+) -> list[str] | list[Molecule]:
     """
     Retrieve a specific metadata field from a webpage.
 
-    Parameters
-    ----------
-    html_content : list[str] | None
-        The HTML content of the page.
-    field_name : str | None
-        The name of the metadata field to extract (case-sensitive).
-        Must appear in the HTML content in the exact format "Field_name:".
-    dataset_id: str
-        The unique identifier of the dataset in GPCRmd.
-    logger: "loguru.Logger"
-        Logger for logging messages.
-
     Returns
     -------
-    list[str] | list[Molecule] | None
-        The value of the metadata field in a list if found, otherwise None.
+    list[str] | list[Molecule]
+        The value of the metadata field in a list if found, otherwise an empty list.
 
     """
     if not html_content or not field_name:
-        return None
+        return []
     try:
         # Special case for molecules and their number of atoms
         if field_name == "Number of molecules":
@@ -269,7 +244,7 @@ def retrieve_metadata_from_html_dataset_page(
             f"Error parsing field '{field_name}' for dataset {dataset_id}: {exc}"
         )
 
-    return None
+    return []
 
 
 def scrape_files_metadata_for_one_dataset(
@@ -281,26 +256,11 @@ def scrape_files_metadata_for_one_dataset(
     """
     Scrape files metadata for a given dataset.
 
-    Parameters
-    ----------
-    client : httpx.Client
-        The HTTPX client to use for making requests.
-    html_content: list[str] | None
-        Html content of the dataset web page.
-    core_metadata : dict[str, Any]
-        Dictionary of dataset core metadata.
-    logger: "loguru.Logger"
-        Logger for logging messages.
-
     Returns
     -------
     list[dict]
         List of files metadata dictionaries.
     """
-    logger.info(
-        "Scraping files metadata for dataset: "
-        f"{core_metadata['dataset_id_in_repository']}"
-    )
     files_metadata = []
     # Extract metadata from dataset url page if available.
     if not html_content:
@@ -308,15 +268,11 @@ def scrape_files_metadata_for_one_dataset(
         return files_metadata
 
     # Find all <a> tags with href containing the files path.
-    # Example of files found for dataset 2316:
-    # Dataset URL: https://www.gpcrmd.org/dynadb/dynamics/id/2316/
-    # /dynadb/files/Dynamics/dyn2667/tmp_dyn_0_2667.pdb
-    # /dynadb/files/Dynamics/dyn2667/25399_dyn_2316.psf
-    # /dynadb/files/Dynamics/dyn2667/25400_trj_2316.dcd
-    # /dynadb/files/Dynamics/dyn2667/25401_trj_2316.dcd
-    # /dynadb/files/Dynamics/dyn2667/25402_trj_2316.dcd
-    # /dynadb/files/Dynamics/dyn2667/25403_prm_2316.prmtop
-    # /dynadb/files/Dynamics/dyn2667/25404_prt_2316.tgz
+    # Example of files found for dataset ID `17``:
+    # Dataset URL: https://www.gpcrmd.org/dynadb/dynamics/id/7/
+    # /dynadb/files/Dynamics/10166_trj_7.dcd
+    # /dynadb/files/Dynamics/10167_dyn_7.psf
+    # /dynadb/files/Dynamics/10168_dyn_7.pdb
     for line in html_content:
         if "/dynadb/files/Dynamics/" not in line:
             continue
@@ -331,11 +287,64 @@ def scrape_files_metadata_for_one_dataset(
             client, metadata["file_url_in_repository"], logger=logger
         )
         files_metadata.append(metadata)
-
-    logger.info(f"Total files found: {len(files_metadata):,}")
+    logger.info(f"Total files found: {len(files_metadata)}.")
     return files_metadata
 
 
+def _parse_authors(raw_authors: str | None) -> list[Person]:
+    """Parse raw author string into a list of Person models.
+
+    Returns
+    -------
+    list[Person]
+        A list of Person objects representing the authors.
+    """
+    if not raw_authors or not raw_authors.strip():
+        return []
+    raw_str = raw_authors.strip()
+
+    # Handle comma case: left = authors, right = affiliation
+    if "," in raw_str:
+        names_part, _, aff_part = raw_str.partition(",")
+        affiliation = aff_part.strip() or None
+        words = names_part.strip().split()
+        n_words = len(words)
+        # Multiple authors case: >= 4 words and even count (pairs of first/last names)
+        if n_words >= 4 and n_words % 2 == 0:
+            return [
+                Person(
+                    first_name=words[i],
+                    last_name=words[i + 1],
+                    full_name=f"{words[i]} {words[i + 1]}",
+                    affiliation=affiliation,
+                )
+                for i in range(0, n_words, 2)
+            ]
+        # Single author case
+        elif words:
+            first = words[0] if n_words > 1 else None
+            last = " ".join(words[1:]) if n_words > 1 else words[0]
+            return [
+                Person(
+                    first_name=first,
+                    last_name=last,
+                    full_name=names_part.strip(),
+                    affiliation=affiliation,
+                )
+            ]
+
+    # No comma: handle parenthesized affiliation exception (e.g. "Group Name (Univ)")
+    if match := re.search(r"^(.*?)\s*\((.*?)\)$", raw_str):
+        return [
+            Person(
+                full_name=match.group(1).strip(),
+                affiliation=match.group(2).strip() or None,
+            )
+        ]
+    # No comma, no parentheses: fallback to plain full_name only
+    return [Person(full_name=raw_str)]
+
+
 def extract_datasets_and_files_metadata(
     client: httpx.Client,
     datasets: list[dict[str, Any]],
@@ -345,17 +354,6 @@ def extract_datasets_and_files_metadata(
     """
     Extract relevant metadata from raw GPCRmd datasets metadata.
 
-    Parameters
-    ----------
-    client : httpx.Client
-        The HTTPX client to use for making requests.
-    datasets : list[dict[str, Any]]
-        List of raw GPCRmd datasets metadata.
-    datasets_html_content: list[list[str] | None]
-        List of html content of the dataset web page.
-    logger: "loguru.Logger"
-        Logger for logging messages.
-
     Returns
     -------
     list[dict]
@@ -365,112 +363,133 @@ def extract_datasets_and_files_metadata(
     """
     datasets_metadata = []
     files_metadata = []
-
     for dataset, html_content in zip(datasets, datasets_html_content, strict=True):
         dataset_id = str(dataset.get("dyn_id"))
-        logger.info(f"Extracting metadata for dataset: {dataset_id}")
-        dataset_source_name = DatasetSourceName.GPCRMD
+        logger.info(f"Extracting metadata for dataset ID `{dataset_id}`.")
         dataset_url = dataset.get("url")
+        # Add core metadata for the dataset.
         core_metadata = {
-            "dataset_repository_name": dataset_source_name,
+            "dataset_repository_name": DatasetSourceName.GPCRMD,
             "dataset_id_in_repository": dataset_id,
             "dataset_url_in_repository": dataset_url,
         }
-        metadata = {
+        # Initialize dataset metadata.
+        dataset_dict = {
             **core_metadata,
             "title": dataset.get("modelname"),
             "date_created": dataset.get("creation_timestamp"),
-            "total_number_of_atoms": dataset.get("atom_num"),
         }
-        # Convert the timestep string (e.g., "4.0 fs")
-        # to a float representing the number of femtoseconds
-        timestep = dataset.get("timestep")
-        if not isinstance(timestep, float) and timestep is not None:
-            timestep = float(dataset.get("timestep").split()[0])
-        metadata["simulation_timesteps_in_fs"] = [timestep]
+        # Extract other metadata from dataset url page if available.
+        if html_content is None:
+            logger.warning(f"Cannot parse HTML metadata for dataset `{dataset_id}`.")
+            logger.warning(dataset_url)
+            logger.warning("Skipping this step.")
+            datasets_metadata.append(dataset_dict)
+            continue
+        # Description.
+        dataset_dict["description"] = retrieve_metadata_from_html_dataset_page(
+            html_content=html_content, field_name="Description", dataset_id=dataset_id
+        )[0]
+        # Reference links.
+        dataset_dict["external_links"] = retrieve_metadata_from_html_dataset_page(
+            html_content=html_content, field_name="doi", dataset_id=dataset_id
+        )
+        # Author names.
+        raw_authors = retrieve_metadata_from_html_dataset_page(
+            html_content=html_content, field_name="Submitted by", dataset_id=dataset_id
+        )[0]
+        dataset_dict["authors"] = _parse_authors(raw_authors)
+        # Retrieve the files metadata from the html content of the dataset page.
+        files_metadata_for_this_dataset = scrape_files_metadata_for_one_dataset(
+            client, html_content, core_metadata, logger=logger
+        )
+        files_metadata.extend(files_metadata_for_this_dataset)
+        dataset_dict["number_of_files"] = len(files_metadata_for_this_dataset)
         # Extract simulation metadata from the API if available.
         # Software names with their versions.
-        software = None
         if dataset.get("mysoftware"):
             software = [
                 Software(
-                    name=dataset["mysoftware"],
-                    version=dataset.get("software_version"),
+                    name=dataset["mysoftware"], version=dataset.get("software_version")
                 )
             ]
-        metadata["software"] = software
         # Forcefields and models.
         forcefields_and_models = []
         if dataset.get("forcefield"):
-            forcefields_and_models = [
+            forcefields_and_models.append(
                 ForceFieldModel(
                     name=dataset["forcefield"],
                     version=dataset.get("forcefield_version"),
                 )
-            ]
-        metadata["forcefields_models"] = forcefields_and_models
-
-        # Extract other metadata from dataset url page if available.
-        if html_content is None:
-            logger.warning(
-                "Cannot parse additional metadata from HTML page for dataset:"
-                f" {dataset_id}"
             )
-            logger.warning(dataset_url)
-            logger.warning("Skipping this step.")
-            datasets_metadata.append(metadata)
-            continue
         # Get solvent model from the HTML content of the dataset page.
         solvent_model = retrieve_metadata_from_html_dataset_page(
             html_content=html_content, field_name="Solvent type", dataset_id=dataset_id
         )
         if solvent_model:
-            metadata["forcefields_models"].append(
+            forcefields_and_models.append(
                 ForceFieldModel(name=solvent_model[0], version=None)
             )
-        # Molecule names with their number of molecules.
-        metadata["molecules"] = retrieve_metadata_from_html_dataset_page(
-            html_content=html_content,
-            field_name="Number of molecules",
-            dataset_id=dataset_id,
-        )
-        # Author names.
-        metadata["author_names"] = retrieve_metadata_from_html_dataset_page(
-            html_content=html_content, field_name="Submitted by", dataset_id=dataset_id
-        )
-        # Description.
-        description = retrieve_metadata_from_html_dataset_page(
-            html_content=html_content, field_name="Description", dataset_id=dataset_id
+        # Molecules.
+        # Get Uniprot ID and PDB ID from the API metadata.
+        db_links = []
+        uniprot_id = dataset.get("uniprot")
+        if uniprot_id:
+            db_links.append(
+                ExternalIdentifier(
+                    database_name="uniprot",
+                    identifier=uniprot_id,
+                    url=f"https://www.uniprot.org/uniprotkb/{uniprot_id}/entry",
+                )
+            )
+        pdb_id = dataset.get("pdb_namechain")
+        if pdb_id:
+            db_links.append(
+                ExternalIdentifier(
+                    database_name="pdb",
+                    identifier=pdb_id,
+                    url=f"https://www.rcsb.org/structure/{pdb_id}",
+                )
+            )
+        molecules = [
+            Molecule(
+                name=dataset.get("protname"),
+                organism=dataset.get("species"),
+                external_identifiers=db_links,
+            )
+        ]
+        # Add other molecules scraped from HTML.
+        # Like membrane lipids, ions, water, etc.
+        html_mols = retrieve_metadata_from_html_dataset_page(
+            html_content, "Number of molecules", dataset_id
         )
-        metadata["description"] = description[0] if description else None
+        if html_mols:
+            molecules.extend(html_mols)
         # Simulation time.
-        metadata["simulation_times"] = retrieve_metadata_from_html_dataset_page(
+        simulation_times = retrieve_metadata_from_html_dataset_page(
             html_content=html_content,
             field_name="Accumulated simulation time",
             dataset_id=dataset_id,
         )
-        # Reference links.
-        metadata["external_links"] = retrieve_metadata_from_html_dataset_page(
-            html_content=html_content, field_name="doi", dataset_id=dataset_id
-        )
-        # Retrieve the files metadata from the html content of the dataset page.
-        files_metadata_for_this_dataset = scrape_files_metadata_for_one_dataset(
-            client, html_content, core_metadata, logger=logger
-        )
-        files_metadata.extend(files_metadata_for_this_dataset)
-        # Number of files.
-        if files_metadata_for_this_dataset:
-            metadata["number_of_files"] = len(files_metadata_for_this_dataset)
+        # Convert the timestep string (e.g., "4.0 fs")
+        # to a float representing the number of femtoseconds
+        timestep = dataset.get("timestep")
+        if not isinstance(timestep, float) and timestep is not None:
+            timestep = float(dataset.get("timestep").split()[0])
         # Adding full metadata for the dataset.
-        datasets_metadata.append(metadata)
-        logger.info(
+        dataset_dict["simulation"] = SimulationMetadata(
+            total_number_of_atoms=dataset.get("atom_num"),
+            simulation_timesteps_in_fs=[timestep],
+            software=software,
+            forcefields_models=forcefields_and_models,
+            molecules=molecules,
+            simulation_times=simulation_times,
+        )
+        datasets_metadata.append(dataset_dict)
+        logger.success(
             f"Scraped metadata for {len(datasets_metadata):,}/{len(datasets):,} "
-            f"({len(datasets_metadata) / len(datasets):.0%}) datasets "
-            f"({len(files_metadata):,} files)"
+            f"datasets ({len(datasets_metadata) / len(datasets):.0%})."
         )
-
-    logger.info(f"Extracted metadata for {len(datasets_metadata)} datasets.")
-    logger.info(f"Extracted metadata for {len(files_metadata)} files.")
     return datasets_metadata, files_metadata
 
 
@@ -501,16 +520,14 @@ def main(output_dir_path: Path, *, is_in_debug_mode: bool = False) -> None:
         is_in_debug_mode=is_in_debug_mode,
     )
     # Create logger.
-    level = "INFO"
-    if scraper.is_in_debug_mode:
-        level = "DEBUG"
+    level = "DEBUG" if scraper.is_in_debug_mode else "INFO"
     logger = create_logger(logpath=scraper.log_file_path, level=level)
     # Print scraper configuration.
     logger.debug(scraper.model_dump_json(indent=4, exclude={"token"}))
     logger.info("Starting GPCRmd scraping...")
-    # Create HTTPX client
+    # Create HTTPX client.
     client = create_httpx_client()
-    # Check connection to GPCRmd API
+    # Check connection to GPCRmd API.
     if is_connection_to_server_working(
         client, f"{BASE_GPCRMD_URL}/pdbs/", logger=logger
     ):
@@ -519,7 +536,6 @@ def main(output_dir_path: Path, *, is_in_debug_mode: bool = False) -> None:
         logger.critical("Connection to GPCRmd API failed.")
         logger.critical("Aborting.")
         sys.exit(1)
-
     # Scrape GPCRmd datasets metadata.
     datasets_raw_metadata = scrape_all_datasets(
         client=client,
@@ -527,13 +543,6 @@ def main(output_dir_path: Path, *, is_in_debug_mode: bool = False) -> None:
         scraper=scraper,
         logger=logger,
     )
-    if not datasets_raw_metadata:
-        logger.critical("No datasets found in GPCRmd.")
-        logger.critical("Aborting.")
-        sys.exit(1)
-    # Send the first dataset raw metadata to the debug log.
-    logger.debug("First dataset raw metadata:")
-    logger.debug(datasets_raw_metadata[0])
     # Fetch the dataset HTML page for all datasets
     datasets_html_content = fetch_all_datasets_html_pages(
         client, datasets_raw_metadata, logger=logger
diff --git a/src/mdverse/scrapers/network.py b/src/mdverse/scrapers/network.py
index 66f15261..c8f2a8e9 100644
--- a/src/mdverse/scrapers/network.py
+++ b/src/mdverse/scrapers/network.py
@@ -310,7 +310,7 @@ def get_zip_file_content_from_http_request(
             file_list.append(
                 {"file_name": file_item.filename, "file_size": file_item.file_size}
             )
-    logger.debug(f"Found {len(file_list)} files in the ZIP file.")
+    logger.debug(f"Found {len(file_list)} files in the ZIP file")
     return file_list
 
 
diff --git a/src/mdverse/scrapers/nomad.py b/src/mdverse/scrapers/nomad.py
index ff47ab08..e94690da 100644
--- a/src/mdverse/scrapers/nomad.py
+++ b/src/mdverse/scrapers/nomad.py
@@ -16,8 +16,9 @@
 from mdverse.core.logger import create_logger
 from mdverse.models.dataset import DatasetMetadata
 from mdverse.models.enums import DatasetSourceName
+from mdverse.models.person import Person
 from mdverse.models.scraper import ScraperContext
-from mdverse.models.simulation import Molecule, Software
+from mdverse.models.simulation import Molecule, SimulationMetadata, Software
 from mdverse.models.utils import (
     export_list_of_models_to_parquet,
     normalize_datasets_metadata,
@@ -248,7 +249,7 @@ def scrape_files_for_one_dataset(
 
 def extract_software_and_version(
     dataset: dict, entry_id: str, logger: "loguru.Logger" = loguru.logger
-) -> list[Software] | None:
+) -> list[Software]:
     """
     Extract software name and version from the nested dataset dictionary.
 
@@ -263,8 +264,9 @@ def extract_software_and_version(
 
     Returns
     -------
-    list[Software] | None
-        A list of Software instances with `name` and `version` fields, None otherwise.
+    list[Software]
+        A list of Software instances with `name` and `version` fields.
+        Returns an empty list if not found.
     """
     name = None
     version = None
@@ -272,12 +274,13 @@ def extract_software_and_version(
         software_info = (
             dataset.get("results", {}).get("method", {}).get("simulation", {})
         )
-        name = software_info.get("program_name")
+        # Trigger KeyError if "program_name" is missing.
+        name = software_info["program_name"]
         version = software_info.get("program_version")
         return [Software(name=name, version=version)]
     except (ValueError, KeyError) as e:
         logger.warning(f"Error parsing software info for entry {entry_id}: {e}")
-    return None
+    return []
 
 
 def extract_molecules_and_total_atoms(
@@ -315,7 +318,7 @@ def extract_molecules_and_total_atoms(
             # Extract molecules.
             for topology in topologies:
                 if topology.get("structural_type") == "molecule":
-                    molecules.append(  # noqa: PERF401
+                    molecules.append(
                         Molecule(
                             name=topology.get("label", "unknown"),
                             number_of_atoms=topology.get("n_atoms"),
@@ -334,7 +337,7 @@ def extract_molecules_and_total_atoms(
 
 def extract_time_step(
     dataset: dict, entry_id: str, logger: "loguru.Logger" = loguru.logger
-) -> list[float] | None:
+) -> list[float]:
     """
     Extract the simulation time step from a dataset entry.
 
@@ -351,12 +354,12 @@ def extract_time_step(
 
     Returns
     -------
-    list[float] | None
-        A list contained the time step in fs, or None if not found.
+    list[float]
+        A list containing the time step in fs. Returns an empty list if not found.
     """
-    time_step = None
+    time_steps = []
     try:
-        time_step = (
+        step = (
             dataset.get("results", {})
             .get("properties", {})
             .get("thermodynamic", {})
@@ -365,12 +368,12 @@ def extract_time_step(
             .get("molecular_dynamics", {})
             .get("time_step")
         )
-        time_step = float(time_step) * 1e15 if time_step is not None else None
+        # Time step is provided in seconds, convert to femtoseconds (1 fs = 1e-15 s).
+        if step is not None:
+            time_steps.append(float(step) * 1e15)
     except (ValueError, KeyError, IndexError) as e:
         logger.warning(f"Could not extract time step for entry {entry_id}: {e}")
-    if time_step is None:
-        return None
-    return [time_step]
+    return time_steps
 
 
 def extract_datasets_metadata(
@@ -408,26 +411,32 @@ def extract_datasets_metadata(
             "date_created": dataset.get("entry_create_time"),
             "date_last_updated": dataset.get("last_processing_time"),
             "number_of_files": len(dataset.get("files", [])),
-            "author_names": [a.get("name") for a in dataset.get("authors", [])],
             "license": dataset.get("license"),
             "description": dataset.get("comment"),
         }
-        # Extract simulation metadata if available.
-        # Software names with their versions.
-        metadata["software"] = extract_software_and_version(dataset, entry_id, logger)
-        # Molecules with their nb of atoms and number total of atoms.
+        # Add authors metadata.
+        authors = [
+            Person(full_name=author.get("name"))
+            for author in dataset.get("authors", [])
+        ]
+        metadata["authors"] = authors
+        # Gather software metadata.
+        software = extract_software_and_version(dataset, entry_id, logger)
+        # Gather molecule metadata.
         molecules, total_atoms = extract_molecules_and_total_atoms(
             dataset, entry_id, logger
         )
-        metadata["total_number_of_atoms"] = total_atoms
-        metadata["molecules"] = molecules
-        # Time step in fs.
-        metadata["simulation_timesteps_in_fs"] = extract_time_step(
-            dataset, entry_id, logger
+        # Gather time steps metadata.
+        simulation_timesteps_in_fs = extract_time_step(dataset, entry_id, logger)
+        # It looks like the simulation temperature is not available!
+        # Extract simulation metadata if available.
+        metadata["simulation"] = SimulationMetadata(
+            molecules=molecules,
+            total_number_of_atoms=total_atoms,
+            software=software,
+            simulation_timesteps_in_fs=simulation_timesteps_in_fs,
         )
-        # Temperatures.
-        metadata["simulation_temperatures_in_kelvin"] = None  # TODO?
-
+        # Append the extracted metadata to the list of datasets metadata.
         datasets_metadata.append(metadata)
     logger.info(f"Extracted metadata for {len(datasets_metadata)} datasets.")
     return datasets_metadata
diff --git a/src/mdverse/scrapers/toolbox.py b/src/mdverse/scrapers/toolbox.py
index e0b9deb0..04ff12bb 100644
--- a/src/mdverse/scrapers/toolbox.py
+++ b/src/mdverse/scrapers/toolbox.py
@@ -29,6 +29,7 @@
 def make_http_get_request_with_retries(
     url: str,
     params: dict | None = None,
+    headers: dict | None = None,
     timeout: int = 10,
     delay_before_request: int = 1,
     max_attempts: int = 3,
@@ -42,6 +43,8 @@ def make_http_get_request_with_retries(
         The URL to send the GET request to.
     params : dict | None
         Optional dictionary of query parameters to include in the request.
+    headers : dict | None
+        Optional dictionary of HTTP headers to include in the request.
     timeout : int
         Timeout for the HTTP request in seconds.
     max_attempts : int
@@ -61,12 +64,17 @@ def make_http_get_request_with_retries(
         indicating the request is accepted but not ready yet.
         This error is caught and retried.
     """
-    headers = {
+    default_headers = {
         "User-Agent": (
-            "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 "
-            "(KHTML, like Gecko) Chrome/111.0.0.0 Safari/537.36"
+            "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 "
+            "(KHTML, like Gecko) Chrome/150.0.0.0 Safari/537.36"
         ),
     }
+    if headers is not None:
+        default_headers.update(headers)
+        headers = default_headers
+    else:
+        headers = default_headers
     logger.info("Making HTTP GET request to:")
     logger.info(url)
     for attempt in range(1, max_attempts + 1):
diff --git a/src/mdverse/scrapers/zenodo.py b/src/mdverse/scrapers/zenodo.py
index a9591cd6..3a03a5ef 100644
--- a/src/mdverse/scrapers/zenodo.py
+++ b/src/mdverse/scrapers/zenodo.py
@@ -14,6 +14,7 @@
 from mdverse.core.logger import create_logger
 from mdverse.models.enums import DatasetSourceName
 from mdverse.models.file import FileMetadata
+from mdverse.models.person import Person
 from mdverse.models.scraper import ScraperContext
 from mdverse.models.utils import (
     export_list_of_models_to_parquet,
@@ -223,7 +224,10 @@ def is_zenodo_connection_working(
     logger.info("Trying connection to Zenodo...")
     response = make_http_get_request_with_retries(
         url="https://zenodo.org/api/deposit/depositions",
-        params={"access_token": token},
+        headers={
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {token}",
+        },
         timeout=10,
         max_attempts=2,
         logger=logger,
@@ -327,10 +331,14 @@ def extract_metadata_from_json(
             "date_created": hit.get("created", None),
             "date_last_updated": hit.get("modified", None),
             "title": clean_text(hit.get("metadata", {}).get("title", "")),
-            "author_names": [
-                author.get("name")
+            "authors": [
+                Person(
+                    full_name=author.get("name"),
+                    affiliation=author.get("affiliation"),
+                    orcid=author.get("orcid"),
+                )
                 for author in hit.get("metadata", {}).get("creators", [])
-                if author.get("name", None)
+                if author.get("name")
             ],
             "description": strip_html(hit.get("metadata", {}).get("description", "")),
             "keywords": [
diff --git a/uv.lock b/uv.lock
index 41d731aa..a67d700b 100644
--- a/uv.lock
+++ b/uv.lock
@@ -33,15 +33,15 @@ wheels = [
 
 [[package]]
 name = "anyio"
-version = "4.13.0"
+version = "4.14.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "idna" },
     { name = "typing-extensions", marker = "python_full_version < '3.13'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/19/14/2c5dd9f512b66549ae92767a9c7b330ae88e1932ca57876909410251fe13/anyio-4.13.0.tar.gz", hash = "sha256:334b70e641fd2221c1505b3890c69882fe4a2df910cba14d97019b90b24439dc", size = 231622, upload-time = "2026-03-24T12:59:09.671Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/61/cc/a381afa6efea9f496eff839d4a6a1aed3bfafc7b3ab4b0d1b243a12573dd/anyio-4.14.2.tar.gz", hash = "sha256:cfa139f3ed1a23ee8f88a145ddb5ac7605b8bbfd8592baacd7ce3d8bb4313c7f", size = 260176, upload-time = "2026-07-12T20:29:07.082Z" }
 wheels = [
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