Sync statement of need with OpenCADD-KLIFS paper

docs/databases_klifs_statement_of_need.rst

@@ -1,24 +1,25 @@
 Statement of need
 ================= 
 
-OpenCADD-KLIFS is aimed at current and future users of the KLIFS database who seek to 
-integrate kinase resources into Python-based research projects.
-This module offers access to KLIFS data [Kanev_2021]_ such as information about kinases, 
-structures, ligands, 
+The KLIFS resource [Kanev_2021]_ contains information about kinases, structures, ligands, 
 interaction fingerprints, and bioactivities. 
 KLIFS thereby focuses especially on the ATP binding site, defined as a set of 85 residues and 
-aligned across all structures using a multiple sequence alignment (MSA) [vanLinden_2014]_.
-With OpenCADD-KLIFS, KLIFS data can be queried either locally from a KLIFS download or remotely 
-from the KLIFS webserver. 
-The presented module provides identical APIs for the remote and local queries for KLIFS data and 
-streamlines all output into 
-standardized `Pandas <https://doi.org/10.5281/zenodo.5574486>`_ DataFrames to allow for easy and 
-quick downstream data analyses (Figure 1). This Pandas-focused setup is ideal to work with in 
-Jupyter notebooks [Kluyver_2016]_. 
+aligned across all structures using a multiple sequence alignment [vanLinden_2014]_.
+Fetching, filtering, and integrating the KLIFS content on a larger scale into Python-based 
+pipelines is currently not straight-forward, especially for users without a background in 
+online queries. 
+Furthermore, switching between data queries from a *local* KLIFS download and 
+the *remote* KLIFS database is not readily possible.
 
-`OpenCADD-KLIFS <https://opencadd.readthedocs.io/en/latest/databases_klifs.html>`_  
-(``opencadd.databases.klifs``) is a part of the `OpenCADD <https://opencadd.readthedocs.io/>`_ 
-package, a collection of Python modules for structural cheminformatics. 
+OpenCADD-KLIFS is aimed at current and future users of the KLIFS database who seek to 
+integrate kinase resources into Python-based research projects.
+With OpenCADD-KLIFS, KLIFS data can be queried either locally from a KLIFS download or 
+remotely from the KLIFS webserver. 
+The presented module provides identical APIs for the remote and local queries and 
+streamlines all output into standardized Pandas DataFrames 
+`Pandas <https://doi.org/10.5281/zenodo.5574486>`_  to allow for easy and quick 
+downstream data analyses (Figure 1). 
+This Pandas-focused setup is ideal if you work with Jupyter notebooks [Kluyver_2016]_.
 
 .. raw:: html
 
@@ -29,45 +30,6 @@ package, a collection of Python modules for structural cheminformatics.
 *Figure 1*: OpenCADD-KLIFS fetches KLIFS data offline from a KLIFS download or 
 online from the KLIFS database and formats the output as user-friendly Pandas DataFrames.
 
-The KLIFS database offers a REST API compliant with the OpenAPI specification 
-(`KLIFS OpenAPI <https://dev.klifs.net/swagger_v2/>`_). 
-Our module OpenCADD-KLIFS uses `bravado <https://github.com/Yelp/bravado>`_ to dynamically 
-generate a Python client based on the OpenAPI definitions and adds wrappers to enable the 
-following functionalities:
-
-- A session is set up, which allows access to various KLIFS *data sources* by different 
-  *identifiers* with the API ``session.data_source.by_identifier``. *Data sources* currently 
-  include kinases, structures and annotated conformations, modified residues, pockets, ligands, 
-  drugs, and bioactivities; *identifiers* refer to kinase names, PDB IDs, KLIFS IDs, and more. 
-  For example, ``session.structures.by_kinase_name`` fetches information on all structures for a 
-  query kinase.
-- The same API is used for local and remote sessions.
-- The returned data follows the same schema regardless of the session type (local/remote); all 
-  results obtained with bravado are formatted as Pandas DataFrames with standardized column names, 
-  data types, and handling of missing data.
-- Files with the structural 3D coordinates deposited on KLIFS include full complexes or selections 
-  such as proteins, pockets, ligands, and more. These files can be downloaded to disc or loaded 
-  via biopandas [Raschka_2017]_ or `RDKit <http://www.rdkit.org>`_. 
-
-OpenCADD-KLIFS is especially convenient whenever users are interested in multiple or more 
-complex queries such as "fetching all structures for the kinase EGFR in the DFG-in conformation" 
-or "fetching the measured bioactivity profiles for all ligands that are structurally resolved in 
-complex with EGFR". Formatting the output as DataFrames facilitates subsequent filtering steps 
-and DataFrame merges in case multiple KLIFS datasets need to be combined.
-OpenCADD-KLIFS is currently used in several projects 
-from the `Volkamer Lab <https://volkamerlab.org/>`_ 
-including 
-`TeachOpenCADD <https://github.com/volkamerlab/teachopencadd>`_, 
-`OpenCADD-pocket <https://github.com/volkamerlab/opencadd>`_, 
-`KiSSim <https://github.com/volkamerlab/kissim>`_, 
-`KinoML <https://github.com/openkinome/kinoml>`_, and 
-`PLIPify <https://github.com/volkamerlab/plipify>`_.
-For example, OpenCADD-KLIFS is applied in a 
-`TeachOpenCADD tutorial <https://projects.volkamerlab.org/teachopencadd/talktorials/T012_query_klifs.html>`_ 
-to demonstrate how to fetch all kinase-ligand interaction profiles for all available EGFR kinase 
-structures to visualize the per-residue interaction types and frequencies with only a few 
-lines of code.
-
 .. [Kanev_2021] Kanev et al., (2021),
    KLIFS: an overhaul after the first 5 years of supporting kinase research,
    Nucleic Acids Research, 
@@ -80,7 +42,4 @@ lines of code.
 .. [Kluyver_2016] Kluyver et al., (2016),
    Jupyter Notebooks – a publishing format for reproducible computational workflows,
    In Positioning and Power in Academic Publishing: Players, Agents and Agendas. IOS Press. pp. 87-90,
-   doi:10.3233/978-1-61499-649-1-87.
-.. [Raschka_2017] Raschka, (2017), 
-   BioPandas: Working with molecular structures in pandas DataFrames, Journal of Open Source Software, 
-   2(14), 279, doi:10.21105/joss.00279.
+   doi:10.3233/978-1-61499-649-1-87.