Open Science doesn’t make publishing easier. That that’s all for the better: our research efforts are complex, so why should the publishing be. Sure, I am not talking about references formatting or moving the Methods section to the right location, or some silly statement that all authors agree with the manuscript when you are the only author. No, let’s talk about data. What should you publish? How, and when?
AbstractA key concept in drug design is how natural variants, especially the ones occurring in the binding site of drug targets, affect the inter-individual drug response and efficacy by altering binding affinity. These effects have been studied on very limited and small datasets while, ideally, a large dataset of binding affinity changes due to binding site single-nucleotide polymorphisms (SNPs) is needed for evaluation. However, to the best of our knowledge, such a dataset does not exist. Thus, a reference dataset of ligands binding affinities to proteins with all their reported binding sites’ variants was constructed using a molecular docking approach. Having a large database of protein–ligand complexes covering a wide range of binding pocket mutations and a large small molecules’ landscape is of great importance for several types of studies. For example, developing machine learning algorithms to predict protein–ligand affinity or a SNP effect on it requires an extensive amount of data. In this work, we present PSnpBind: A large database of 0.6 million mutated binding site protein–ligand complexes constructed using a multithreaded virtual screening workflow. It provides a web interface to explore and visualize the protein–ligand complexes and a REST API to programmatically access the different aspects of the database contents. PSnpBind is open source and freely available at https://psnpbind.org.
Monthly data release from WikiPathways.org
BridgeDb ID mapping database for metabolites, using HMDB 5.0 (Release of April 2024), ChEBI 236 (Release of August 2024), and Wikidata (3 September 2024) as data sources.
ChemPedia was a project by Rich Apodaca for crowd sourcing names of chemical compounds. Users were able to contribute names and up- or downvote names. When the service was discontinued, Rich released the data under the CCZero license.
New release with more JRC nanomaterials annotated with ENM ontology terms, and data from a 2013 NanoQSAR study from Small by Lin et al. on 24 metal oxides.
Additional file 1. The supporting information for the paper entitled: PubChemRDF: towards the semantic annotation of PubChem compound and substance databases.
Additional file 1. Example of exported SDF file from XMetDB.