A divergent CheW confers plasticity to nucleoid-associated chemosensory arrays.

Chemosensory systems are highly organized signaling pathways that allow bacteria to adapt to environmental changes. The Frz chemosensory system from M. xanthus possesses two CheW-like proteins, FrzA (the core CheW) and FrzB. We found that FrzB does not interact with FrzE (the cognate CheA) as it lacks the amino acid region responsible for this interaction. FrzB, instead, acts upstream of FrzCD in the regulation of M. xanthus chemotaxis behaviors and activates the Frz pathway by allowing the formation and distribution of multiple chemosensory clusters on the nucleoid. These results, together, show that the lack of the CheA-interacting region in FrzB confers new functions to this small protein.

Protein-Protein Interaction Inhibition (2P2I)-Oriented Chemical Library Accelerates Hit Discovery.

Protein-protein interactions (PPIs) represent an enormous source of opportunity for therapeutic intervention. We and others have recently pinpointed key rules that will help in identifying the next generation of innovative drugs to tackle this challenging class of targets within the next decade. We used these rules to design an oriented chemical library corresponding to a set of diverse "PPI-like" modulators with cores identified as privileged structures in therapeutics. In this work, we purchased the resulting 1664 structurally diverse compounds and evaluated them on a series of representative protein-protein interfaces with distinct "druggability" potential using homogeneous time-resolved fluorescence (HTRF) technology. For certain PPI classes, analysis of the hit rates revealed up to 100 enrichment factors compared with nonoriented chemical libraries. This observation correlates with the predicted "druggability" of the targets. A specific focus on selectivity profiles, the three-dimensional (3D) molecular modes of action resolved by X-ray crystallography, and the biological activities of identified hits targeting the well-defined "druggable" bromodomains of the bromo and extraterminal (BET) family are presented as a proof-of-concept. Overall, our present study illustrates the potency of machine learning-based oriented chemical libraries to accelerate the identification of hits targeting PPIs. A generalization of this method to a larger set of compounds will accelerate the discovery of original and potent probes for this challenging class of targets.

2P2Idb v2: update of a structural database dedicated to orthosteric modulation of protein-protein interactions.

2P2Idb is a hand-curated structural database dedicated to protein-protein interactions with known small molecule orthosteric modulators. It compiles the structural information related to orthosteric inhibitors and their target [i.e. related 3D structures available in the RCSB Protein Data Bank (PDB)] and provides links to other useful databases. 2P2Idb includes all interactions for which both the protein-protein and protein-inhibitor complexes have been structurally characterized. Since its first release in 2010, the database has grown constantly and the current version contains 27 protein-protein complexes and 274 protein-inhibitor complexes corresponding to 242 unique small molecule inhibitors which represent almost a 5-fold increase compared to the previous version. A number of new data have been added, including new protein-protein complexes, binding affinities, molecular descriptors, precalculated interface parameters and links to other webservers. A new query tool has been implemented to search for inhibitors within the database using standard molecular descriptors. A novel version of the 2P2I-inspector tool has been implemented to calculate a series of physical and chemical parameters of the protein interfaces. Several geometrical parameters including planarity, eccentricity and circularity have been added as well as customizable distance cutoffs. This tool has also been extended to protein-ligand interfaces. The 2P2I database thus represents a wealth of structural source of information for scientists interested in the properties of protein-protein interactions and the design of protein-protein interaction modulators. Database URL: http://2p2idb.cnrs-mrs.fr.

2P2I HUNTER: a tool for filtering orthosteric protein-protein interaction modulators via a dedicated support vector machine.

Over the last 10 years, protein-protein interactions (PPIs) have shown increasing potential as new therapeutic targets. As a consequence, PPIs are today the most screened target class in high-throughput screening (HTS). The development of broad chemical libraries dedicated to these particular targets is essential; however, the chemical space associated with this 'high-hanging fruit' is still under debate. Here, we analyse the properties of 40 non-redundant small molecules present in the 2P2I database (http://2p2idb.cnrs-mrs.fr/) to define a general profile of orthosteric inhibitors and propose an original protocol to filter general screening libraries using a support vector machine (SVM) with 11 standard Dragon molecular descriptors. The filtering protocol has been validated using external datasets from PubChem BioAssay and results from in-house screening campaigns. This external blind validation demonstrated the ability of the SVM model to reduce the size of the filtered chemical library by eliminating up to 96% of the compounds as well as enhancing the proportion of active compounds by up to a factor of 8. We believe that the resulting chemical space identified in this paper will provide the scientific community with a concrete support to search for PPI inhibitors during HTS campaigns.

2P2Idb: a structural database dedicated to orthosteric modulation of protein-protein interactions.

Protein-protein interactions are considered as one of the next generation of therapeutic targets. Specific tools thus need to be developed to tackle this challenging chemical space. In an effort to derive some common principles from recent successes, we have built 2P2Idb (freely accessible at http://2p2idb.cnrs-mrs.fr), a hand-curated structural database dedicated to protein-protein interactions with known orthosteric modulators. It includes all interactions for which both the protein-protein and protein-ligand complexes have been structurally characterized. A web server provides links to related sites of interest, binding affinity data, pre-calculated structural information about protein-protein interfaces and 3D interactive views through java applets. Comparison of interfaces in 2P2Idb to those of representative datasets of heterodimeric complexes has led to the identification of geometrical parameters and residue properties to assess the druggability of protein-protein complexes. A tool is proposed to calculate a series of biophysical and geometrical parameters that characterize protein-protein interfaces. A large range of descriptors are computed including, buried accessible surface area, gap volume, non-bonded contacts, hydrogen-bonds, atom and residue composition, number of segments and secondary structure contribution. All together the 2P2I database represents a structural source of information for scientists from academic institutions or pharmaceutical industries.

Atomic analysis of protein-protein interfaces with known inhibitors: the 2P2I database.

BACKGROUND: In the last decade, the inhibition of protein-protein interactions (PPIs) has emerged from both academic and private research as a new way to modulate the activity of proteins. Inhibitors of these original interactions are certainly the next generation of highly innovative drugs that will reach the market in the next decade. However, in silico design of such compounds still remains challenging. METHODOLOGY/PRINCIPAL FINDINGS: Here we describe this particular PPI chemical space through the presentation of 2P2I(DB), a hand-curated database dedicated to the structure of PPIs with known inhibitors. We have analyzed protein/protein and protein/inhibitor interfaces in terms of geometrical parameters, atom and residue properties, buried accessible surface area and other biophysical parameters. The interfaces found in 2P2I(DB) were then compared to those of representative datasets of heterodimeric complexes. We propose a new classification of PPIs with known inhibitors into two classes depending on the number of segments present at the interface and corresponding to either a single secondary structure element or to a more globular interacting domain. 2P2I(DB) complexes share global shape properties with standard transient heterodimer complexes, but their accessible surface areas are significantly smaller. No major conformational changes are seen between the different states of the proteins. The interfaces are more hydrophobic than general PPI's interfaces, with less charged residues and more non-polar atoms. Finally, fifty percent of the complexes in the 2P2I(DB) dataset possess more hydrogen bonds than typical protein-protein complexes. Potential areas of study for the future are proposed, which include a new classification system consisting of specific families and the identification of PPI targets with high druggability potential based on key descriptors of the interaction. CONCLUSIONS: 2P2I database stores structural information about PPIs with known inhibitors and provides a useful tool for biologists to assess the potential druggability of their interfaces. The database can be accessed at http://2p2idb.cnrs-mrs.fr.

ABCdb: an online resource for ABC transporter repertories from sequenced archaeal and bacterial genomes.

The ATP-binding cassette (ABC) transporters are one of the major classes of active transporters. They are widespread in archaea, bacteria, and eukaryota, indicating that they have arisen early in evolution. They are involved in many essential physiological processes, but the majority import or export a wide variety of compounds across cellular membranes. These systems share a common architecture composed of four (exporters) or five (importers) domains. To identify and reconstruct functional ABC transporters encoded by archaeal and bacterial genomes, we have developed a bioinformatic strategy. Cross-reference to the transport classification system is used to predict the type of compound transported. A high quality of annotation is achieved by manual verification of the predictions. However, in order to face the rapid increase in the number of published genomes, we also include analyses of genomes issuing directly from the automated strategy. Querying the database (http://www-abcdb.biotoul.fr) allows to easily retrieve ABC transporter repertories and related data. Additional query tools have been developed for the analysis of the ABC family from both functional and evolutionary perspectives.