Merge pull request #135 from volkamerlab/joss-review-issues-133-134

Revise OpenCADD-KLIFS manuscript (issues #133 and #134)

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.

paper/paper.bib

@@ -9,14 +9,28 @@ @article{Cohen:2021
     doi={10.1038/s41573-021-00195-4},
 }
 
-@article{Kooistra:2017,
-    author = {Kooistra, Albert J. and Volkamer, Andrea},
-    title = {{Kinase-Centric Computational Drug Development}},
-    journal = {Annu. Rep. Med. Chem.},
+@incollection{Kooistra:2017,
+    booktitle = {Platform Technologies in Drug Discovery and Validation},
+    series = {Annual Reports in Medicinal Chemistry},
+    editor = {Robert A. Goodnow},
+    title = {Chapter Six - Kinase-Centric Computational Drug Development},
+    author = {Kooistra, {A. J.} and Volkamer, A.},
+    publisher = {Academic Press},
     volume = {50},
-    pages = {197--236},
+    pages = {197-236},
     year = {2017},
-    doi = {10.1016/BS.ARMC.2017.08.001},
+    doi = {10.1016/bs.armc.2017.08.001},
+}
+
+@inproceedings{Kluyver:2016,
+    booktitle = {Positioning and Power in Academic Publishing: Players, Agents and Agendas},
+    editor = {Fernando Loizides and Birgit Scmidt},
+    title = {Jupyter Notebooks - a publishing format for reproducible computational workflows},
+    author = {Thomas Kluyver and Benjamin Ragan-Kelley and Fernando P{\'e}rez and Brian Granger and Matthias Bussonnier and Jonathan Frederic and Kyle Kelley and Jessica Hamrick and Jason Grout and Sylvain Corlay and Paul Ivanov and Dami{\'a}n Avila and Safia Abdalla and Carol Willing and  Jupyter development team},
+    publisher = {IOS Press},
+    year = {2016},
+    pages = {87--90},
+    url = {https://eprints.soton.ac.uk/403913/},
 }
 
 @article{Kanev:2021,
@@ -31,7 +45,7 @@ @article{Kanev:2021
 }
 
 @article{vanLinden:2014,
-    author={van Linden, Oscar P. J. and Kooistra, Albert J. and Leurs, Rob and de Esch, Iwan J. P. and de Graaf, Chris},
+    author={{van Linden}, Oscar P. J. and Kooistra, Albert J. and Leurs, Rob and de Esch, Iwan J. P. and de Graaf, Chris},
     title={KLIFS: A Knowledge-Based Structural Database To Navigate Kinase--Ligand Interaction Space},
     journal={Journal of Medicinal Chemistry},
     volume={57},
@@ -51,15 +65,48 @@ @article{Raschka:2017
     doi = {10.21105/joss.00279},
 }
 
-@inproceedings{Kluyver:2016,
-    booktitle = {Positioning and Power in Academic Publishing: Players, Agents and Agendas},
-    editor = {Fernando Loizides and Birgit Scmidt},
-    title = {Jupyter Notebooks - a publishing format for reproducible computational workflows},
-    author = {Thomas Kluyver and Benjamin Ragan-Kelley and Fernando P{\'e}rez and Brian Granger and Matthias Bussonnier and Jonathan Frederic and Kyle Kelley and Jessica Hamrick and Jason Grout and Sylvain Corlay and Paul Ivanov and Dami{\'a}n Avila and Safia Abdalla and Carol Willing and  Jupyter development team},
-    publisher = {IOS Press},
-    year = {2016},
-    pages = {87--90},
-    url = {https://eprints.soton.ac.uk/403913/},
+@article{Mendez:2018,
+    author = {Mendez, David and Gaulton, Anna and Bento, A Patrícia and Chambers, Jon and De Veij, Marleen and Félix, Eloy and Magariños, María Paula and Mosquera, Juan F and Mutowo, Prudence and Nowotka, Michał and Gordillo-Marañón, María and Hunter, Fiona and Junco, Laura and Mugumbate, Grace and Rodriguez-Lopez, Milagros and Atkinson, Francis and Bosc, Nicolas and Radoux, Chris J and Segura-Cabrera, Aldo and Hersey, Anne and Leach, Andrew R},
+    title = "{ChEMBL: towards direct deposition of bioassay data}",
+    journal = {Nucleic Acids Research},
+    volume = {47},
+    number = {D1},
+    pages = {D930-D940},
+    year = {2018},
+    doi = {10.1093/nar/gky1075},
+}
+
+@article{Carles:2018,
+    author = {Carles, Fabrice and Bourg, St{\'{e}}phane and Meyer, Christophe and Bonnet, Pascal},
+    title = {{PKIDB: A Curated, Annotated and Updated Database of Protein Kinase Inhibitors in Clinical Trials}},
+    journal = {Molecules},
+    volume = {23},
+    number = {4},
+    pages = {908},
+    year = {2018},
+    doi = {10.3390/molecules23040908},
+}
+
+@article{McGuire:2017,
+    author = {McGuire, Ross and Verhoeven, Stefan and Vass, Márton and Vriend, Gerrit and de Esch, Iwan J. P. and Lusher, Scott J. and Leurs, Rob and Ridder, Lars and Kooistra, Albert J. and Ritschel, Tina and de Graaf, Chris},
+    title = {3D-e-Chem-VM: Structural Cheminformatics Research Infrastructure in a Freely Available Virtual Machine},
+    journal = {Journal of Chemical Information and Modeling},
+    volume = {57},
+    number = {2},
+    pages = {115-121},
+    year = {2017},
+    doi = {10.1021/acs.jcim.6b00686},
+}
+
+@article{Kooistra:2018,
+   author = {Kooistra, {A. J.} and Vass, M.  and McGuire, R. and Leurs, R. and de Esch, I. J. P. and Vriend, G. and Verhoeven, S. and de Graaf, C. },
+   title = {{3{D}-e-{C}hem: {S}tructural {C}heminformatics {W}orkflows for {C}omputer-{A}ided {D}rug {D}iscovery}},
+   journal = {ChemMedChem},
+   volume = {13},
+   number = {6},
+   pages = {614--626},
+   year = {2018},
+   doi = {10.1002/cmdc.201700754},
 }
 
 @misc{klifsswagger,
@@ -70,6 +117,15 @@ @misc{klifsswagger
     url = {https://dev.klifs.net/swagger_v2/},
 }
 
+@misc{requests,
+    author = {requests},
+    title = {{requests}},
+    year = 2021,
+    publisher = {GitHub},
+    journal = {GitHub repository},
+    url = {https://github.com/psf/requests},
+}
+
 @misc{bravado,
     author = {bravado},
     title = {{bravado}},