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.

Background: The sc-PDB database is an annotated archive of druggable binding sites extracted from the Protein Data Bank. It contains all-atoms coordinates for 8166 protein–ligand complexes, chosen for their geometrical and physico-chemical properties. The sc-PDB provides a functional annotation for proteins, a chemical description for ligands and the detailed intermolecular interactions for complexes. The sc-PDB now includes a hierarchical classification of all the binding sites within a functional class. Method: The sc-PDB entries were first clustered according to the protein name indifferent of the species. For each cluster, we identified dissimilar sites (e.g. catalytic and allosteric sites of an enzyme). Scope and applications: The classification of sc-PDB targets by binding site diversity was intended to facilitate chemogenomics approaches to drug design. In ligand-based approaches, it avoids comparing ligands that do not share the same binding site. In structure-based approaches, it permits to quantitatively evaluate the diversity of the binding site definition (variations in size, sequence and/or structure). Availability: The sc-PDB database is freely available at: http://bioinfo-pharma.u-strasbg.fr/scPDB. Contact:ekellen@unistra.fr

Maraviroc is a nonpeptidic small molecule human immunodeficiency virus type 1 (HIV-1) entry inhibitor that has just entered the therapeutic arsenal for the treatment of patients. We recently demonstrated that maraviroc binding to the HIV-1 coreceptor, CC chemokine receptor 5 (CCR5), prevents it from binding the chemokine CCL3 and the viral envelope glycoprotein gp120 by an allosteric mechanism. However, incomplete knowledge of ligand-binding sites and the lack of CCR5 crystal structures have hampered an in-depth molecular understanding of how the inhibitor works. Here, we addressed these issues by combining site-directed mutagenesis (SDM) with homology modeling and docking. Six crystal structures of G-protein-coupled receptors were compared for their suitability for CCR5 modeling. All CCR5 models had equally good geometry, but that built from the recently reported dimeric structure of the other HIV-1 coreceptor CXCR4 bound to the peptide CVX15 (Protein Data Bank code 3OE0) best agreed with the SDM data and discriminated CCR5 from non-CCR5 binders in a virtual screening approach. SDM and automated docking predicted that maraviroc inserts deeply in CCR5 transmembrane cavity where it can occupy three different binding sites, whereas CCL3 and gp120 lie on distinct yet overlapped regions of the CCR5 extracellular loop 2. Data suggesting that the transmembrane cavity remains accessible for maraviroc in CCL3-bound and gp120-bound CCR5 help explain our previous observation that the inhibitor enhances dissociation of preformed ligand-CCR5 complexes. Finally, we identified residues in the predicted CCR5 dimer interface that are mandatory for gp120 binding, suggesting that receptor dimerization might represent a target for new CCR5 entry inhibitors.

G protein-coupled receptors (GPCRs) constitute a functionally diverse protein family and are targets for a broad spectrum of pharmaceuticals. Technological progress in X-ray crystallography and cryogenic electron microscopy has enabled extensive, high-resolution structural characterisation of GPCRs in different conformational states. However, as highly dynamic events underlie GPCR signalling, a complete understanding of GPCR functionality requires insights into their conformational dynamics. Here, we present a large dataset of molecular dynamics simulations covering 60% of currently available GPCR structures. Our analysis reveals extensive local “breathing” motions of the receptor on a nano- to microsecond timescale and provides access to numerous previously unexplored receptor conformational states. Furthermore, we reveal that receptor flexibility impacts the shape of allosteric drug binding sites, which frequently adopt partially or completely closed states in the absence of a molecular modulator. We demonstrate that exploring membrane lipid dynamics and their interaction with GPCRs is an efficient approach to expose such hidden allosteric sites and even lateral ligand entrance gateways. The obtained insights and generated dataset on conformations, allosteric sites and lateral entrance gates in GPCRs allows us to better understand the functionality of these receptors and opens new therapeutic avenues for drug-targeting strategies.

In the last 20 years, Fragment-Based Drug Discovery (FBDD) has established itself as a key approach for finding high-quality lead candidates [1]. Two drugs on the market today originate from fragme...