sc-PDB: a 3D-database of ligandable binding sites—10 years on

TLDR

The sc‑PDB database is a comprehensive, up‑to‑date catalogue of ligandable binding sites from the Protein Data Bank, launched in 2004 to supply structure files for computational drug‑design methods such as docking. This paper presents the latest enhancements to the database, focusing on improved representation of molecular interactions and on the similarity of ligand‑protein binding patterns. The database defines sites from protein–ligand complexes, provides all‑atom descriptions of proteins, ligands, binding sites and modes, and has standardized processes for site identification, structure correction, functional annotation, ligand property annotation and binding‑mode characterization, with a new website that emphasizes pictorial data analysis. The updated sc‑PDB archive now contains 9,283 binding sites from 3,678 unique proteins and 5,608 unique ligands.

Abstract

The sc-PDB database (available at http://bioinfo-pharma.u-strasbg.fr/scPDB/) is a comprehensive and up-to-date selection of ligandable binding sites of the Protein Data Bank. Sites are defined from complexes between a protein and a pharmacological ligand. The database provides the all-atom description of the protein, its ligand, their binding site and their binding mode. Currently, the sc-PDB archive registers 9283 binding sites from 3678 unique proteins and 5608 unique ligands. The sc-PDB database was publicly launched in 2004 with the aim of providing structure files suitable for computational approaches to drug design, such as docking. During the last 10 years we have improved and standardized the processes for (i) identifying binding sites, (ii) correcting structures, (iii) annotating protein function and ligand properties and (iv) characterizing their binding mode. This paper presents the latest enhancements in the database, specifically pertaining to the representation of molecular interaction and to the similarity between ligand/protein binding patterns. The new website puts emphasis in pictorial analysis of data.