Pierre Ducrot

Encoding protein-ligand interaction patterns in fingerprints and graphs.

We herewith present a novel and universal method to convert protein-ligand coordinates into a simple fingerprint of 210 integers registering the corresponding molecular interaction pattern. Each interaction (hydrophobic, aromatic, hydrogen bond, ionic bond, metal complexation) is detected on the fly and physically described by a pseudoatom centered either on the interacting ligand atom, the interacting protein atom, or the geometric center of both interacting atoms. Counting all possible triplets of interaction pseudoatoms within six distance ranges, and pruning the full integer vector to keep the most frequent triplets enables the definition of a simple (210 integers) and coordinate frame-invariant interaction pattern descriptor (TIFP) that can be applied to compare any pair of protein-ligand complexes. TIFP fingerprints have been calculated for ca. 10,000 druggable protein-ligand complexes therefore enabling a wide comparison of relationships between interaction pattern similarity and ligand or binding site pairwise similarity. We notably show that interaction pattern similarity strongly depends on binding site similarity. In addition to the TIFP fingerprint which registers intermolecular interactions between a ligand and its target protein, we developed two tools (Ishape, Grim) to align protein-ligand complexes from their interaction patterns. Ishape is based on the overlap of interaction pseudoatoms using a smooth Gaussian function, whereas Grim utilizes a standard clique detection algorithm to match interaction pattern graphs. Both tools are complementary and enable protein-ligand complex alignments capitalizing on both global and local pattern similarities. The new fingerprint and companion alignment tools have been successfully used in three scenarios: (i) interaction-biased alignment of protein-ligand complexes, (ii) postprocessing docking poses according to known interaction patterns for a particular target, and (iii) virtual screening for bioisosteric scaffolds sharing similar interaction patterns.

2P2IHUNTER: 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.

Use of reduced graphs to encode bioisosterism for similarity-based virtual screening

This paper describes a project to include explicit information about bioisosteric equivalences between pairs of fragment substructures in a system for similarity-based virtual screening. Data from the BIOSTER database show that reduced graphs provide a simple way of encoding known bioisosteric equivalences in a manner that can be used during similarity searching. Scaffold-hopping experiments with the WOMBAT database show that including such information enables similarities to be identified between the reference structures and active structures from the database that contain different, but equivalent, fragment substructures. However, such equivalences also contribute to the similarities between the reference structures and inactives, and the latter equivalences can swamp those involving the actives. This presents serious problems for the routine use of information about bioisosteric fragments in similarity-based virtual screening.

Identification of target-specific bioisosteric fragments from ligand–protein crystallographic data

Bioisosteres are functional groups or atoms that are structurally different but that can form similar intermolecular interactions. Potential bioisosteres were identified here from analysing the X-ray crystallographic structures for sets of different ligands complexed with a fixed protein. The protein was used to align the ligands with each other, and then pairs of ligands compared to identify substructural features with high volume overlap that occurred in approximately the same region of geometric space. The resulting pairs of substructural features can suggest potential bioisosteric replacements for use in lead-optimisation studies. Experiments with 12 sets of ligand–protein complexes from the Protein Data Bank demonstrate the effectiveness of the procedure.

Dynamics of hERG Closure Allow Novel Insights into hERG Blocking by Small Molecules

Today, drug discovery routinely uses experimental assays to determine very early if a lead compound can yield certain types of off-target activity. Among such off targets is hERG. The ion channel plays a primordial role in membrane repolarization and altering its activity can cause severe heart arrhythmia and sudden death. Despite routine tests for hERG activity, rather little information is available for helping medicinal chemists and molecular modelers to rationally circumvent hERG activity. In this article novel insights into the dynamics of hERG channel closure are described. Notably, helical pairwise closure movements have been observed. Implications and relations to hERG inactivation are presented. Based on these dynamics novel insights on hERG blocker placement are presented, compared to literature, and discussed. Last, new evidence for horizontal ligand positioning is shown in light of former studies on hERG blockers.

Alternative Radioligands for Investigating the Molecular Pharmacology of Melatonin Receptors.

Melatonin exerts a variety of physiologic activities that are mainly relayed through the melatonin receptors MT1 and MT2 Low expressions of these receptors in tissues have led to widespread experimental use of the agonist 2-[125I]-iodomelatonin as a substitute for melatonin. We describe three iodinated ligands: 2-(2-[(2-iodo-4,5-dimethoxyphenyl)methyl]-4,5-dimethoxy phenyl) (DIV880) and (2-iodo-N-2-[5-methoxy-2-(naphthalen-1-yl)-1H-pyrrolo[3,2-b]pyridine-3-yl])acetamide (S70254), which are specific ligands at MT2 receptors, and N-[2-(5-methoxy-1H-indol-3-yl)ethyl]iodoacetamide (SD6), an analog of 2-[125I]-iodomelatonin with slightly different characteristics. Here, we further characterized these new ligands with regards to their molecular pharmacology. We performed binding experiments, saturation assays, association/dissociation rate measurements, and autoradiography using sheep and rat tissues and recombinant cell lines. Our results showed that [125I]-S70254 is receptor, and can be used with both cells and tissue. This radioligand can be used in autoradiography. Similarly, DIV880, a partial agonist [43% of melatonin on guanosine 5′-3-O-(thio)triphosphate binding assay], selective for MT2, can be used as a tool to selectively describe the pharmacology of this receptor in tissue samples. The molecular pharmacology of both human melatonin receptors MT1 and MT2, using a series of 24 ligands at these receptors and the new radioligands, did not lead to noticeable variations in the profiles. For the first time, we described radiolabeled tools that are specific for one of the melatonin receptors (MT2). These tools are amenable to binding experiments and to autoradiography using sheep or rat tissues. These specific tools will permit better understanding of the role and implication in physiopathologic processes of the melatonin receptors.

CoMFA and CoMSIA 3D-quantitative structure-activity relationship model on benzodiazepine derivatives, inhibitors of phosphodiesterase IV.

Recently, we reported structurally novel PDE4 inhibitors based on 1,4-benzodiazepine derivatives. The main interest in developing bezodiazepine-based PDE4 inhibitors is in their lack of adverse effects of emesis with respect to rolipram-like compounds. A large effort has thus been made toward the structural optimization of this series. In the absence of structural information on the inhibitor binding mode into the PDE4 active site, 2D-QSAR (H-QSAR) and two 3D-QSAR (CoMFA and CoMSIA) methods were applied to improve our understanding of the molecular mechanism controlling the PDE4 affinity of the benzodiazepine derivatives. As expected, the CoMSIA 3D contour maps have provided more information on the benzodiazepine interaction mode with the PDE4 active site whereas CoMFA has built the best tool for activity prediction. The 2D pharmacophoric model derived from CoMSIA fields is consistent with the crystal structure of the PDE4 active site reported recently. The combination of the 2D and 3D-QSAR models was used not only to predict new compounds from the structural optimization process, but also to screen a large library of bezodiazepine derivatives.

Binding mode prediction and MD/MMPBSA-based free energy ranking for agonists of REV-ERBα/NCoR

The knowledge of the free energy of binding of small molecules to a macromolecular target is crucial in drug design as is the ability to predict the functional consequences of binding. We highlight how a molecular dynamics (MD)-based approach can be used to predict the free energy of small molecules, and to provide priorities for the synthesis and the validation via in vitro tests. Here, we study the dynamics and energetics of the nuclear receptor REV-ERBα with its co-repressor NCoR and 35 novel agonists. Our in silico approach combines molecular docking, molecular dynamics (MD), solvent-accessible surface area (SASA) and molecular mechanics poisson boltzmann surface area (MMPBSA) calculations. While docking yielded initial hints on the binding modes, their stability was assessed by MD. The SASA calculations revealed that the presence of the ligand led to a higher exposure of hydrophobic REV-ERB residues for NCoR recruitment. MMPBSA was very successful in ranking ligands by potency in a retrospective and prospective manner. Particularly, the prospective MMPBSA ranking-based validations for four compounds, three predicted to be active and one weakly active, were confirmed experimentally.

Towards a complete structure of the hERG channel

A lot of attention has been drawn to the voltage gated potassium channel Kv11.1 during the last decades. In the past, both, ligand and structure based methods intended to predict if a small molecule could cause fatal heart arrhythmias, “torsades de pointe” and sudden death. However, despite the wide interest for hERG, still no experimental 3D structure is available and therefore homology modelling of parts of the channel (generally only the pore domain) is currently used to gain structural insights [1]. Here a novel structural model of hERG is presented encompassing the full transmembrane segment of hERG, including the conduction pore and the voltage sensitive domain. Furthermore, cytoplasmic domains like the cyclic nucleotide binding domain and the PAS domain have been positioned in the overall structure. Subsequent molecular dynamics simulations allow gaining novel structural and dynamic insights into hERG functioning and perturbation.