NLDB: a database for 3D protein–ligand interactions in enzymatic reactions

Abstract

NLDB (Natural Ligand DataBase; URL: http://nldb.hgc.jp) is a database of automatically collected and predicted 3D protein–ligand interactions for the enzymatic reactions of metabolic pathways registered in KEGG. Structural information about these reactions is important for studying the molecular functions of enzymes, however a large number of the 3D interactions are still unknown. Therefore, in order to complement such missing information, we predicted protein–ligand complex structures, and constructed a database of the 3D interactions in reactions. NLDB provides three different types of data resources; the natural complexes are experimentally determined protein–ligand complex structures in PDB, the analog complexes are predicted based on known protein structures in a complex with a similar ligand, and the ab initio complexes are predicted by docking simulations. In addition, NLDB shows the known polymorphisms found in human genome on protein structures. The database has a flexible search function based on various types of keywords, and an enrichment analysis function based on a set of KEGG compound IDs. NLDB will be a valuable resource for experimental biologists studying protein–ligand interactions in specific reactions, and for theoretical researchers wishing to undertake more precise simulations of interactions.

VaProS: a database-integration approach for protein/genome information retrieval

“…Natural Ligand Database (NLDB) [ 25 ] provides the model of protein structures with natural ligands. The idea stemmed from the fact that many ligands in PDB are modified ligands for the sake of crystallisation and the bridge between those modified ligands and natural ligands should be provided to enhance the 3D structural information in PDB.…”

Deep learning and knowledge-based methods for computer-aided molecular design—toward a unified approach: State-of-the-art and future directions

“…Given the successful applications of text and image-mining in extracting novel compounds and synthesis routes [138], [225], the task of extracting property data from published literature remains a potential route to substantially increase the volume of readily available data. Additional progress in property data mining and aggregation is expected to mitigate some of the challenges associated with the absence of engineering knowledge in structure-property relationships for different classes of molecules, such as crystal structures [226], alloys [227], proteins and nucleic acids [228], [229], polymers [230],…”

Biomolecule and Bioentity Interaction Databases in Systems Biology: A Comprehensive Review

“…In addition to the above, a number of structural databases also exist that complement crystallographic evidence with computational predictions derived from energy calculations, protein-ligand docking predictions or ab initio simulations. NLDB (Natural Ligand Database) [197] is a predictive database focusing on 3D protein-ligand interactions specifically in enzymatic reactions of metabolic pathways registered in KEGG. Based on the latest update, NLDB offers data about known human genome polymorphisms on protein structures, as well as 87,400 experimentally validated protein-ligand complex structures in PDB, defined as natural complexes, while 31,672 analog complexes and 70,570 ab initio complexes were predicted based on known protein structures in a complex with a similar ligand and by docking simulations accordingly.…”