Xavier Morelli

Structural basis of membrane binding by Gla domains of vitamin K-dependent proteins.

In a calcium-dependent interaction critical for blood coagulation, vitamin K–dependent blood coagulation proteins bind cell membranes containing phosphatidylserine via γ-carboxyglutamic acid–rich (Gla) domains. Gla domain–mediated protein-membrane interaction is required for generation of thrombin, the terminal enzyme in the coagulation cascade, on a physiologic time scale. We determined by X-ray crystallography and NMR spectroscopy the lysophosphatidylserine-binding site in the bovine prothrombin Gla domain. The serine head group binds Gla domain–bound calcium ions and Gla residues 17 and 21, fixed elements of the Gla domain fold, predicting the structural basis for phosphatidylserine specificity among Gla domains. Gla domains provide a unique mechanism for protein-phospholipid membrane interaction. Increasingly Gla domains are being identified in proteins unrelated to blood coagulation. Thus, this membrane-binding mechanism may be important in other physiologic processes.

Chemical and structural lessons from recent successes in protein–protein interaction inhibition (2P2I)

Worldwide research efforts have driven recent pharmaceutical successes, and consequently, the emerging role of Protein-Protein Interactions (PPIs) as drug targets has finally been widely embraced by the scientific community. Inhibitors of these Protein-Protein Interactions (2P2Is or i-PPIs) are likely to represent the next generation of highly innovative drugs that will reach the market over the next decade. This review describes up-to-date knowledge on this particular chemical space, with a specific emphasis on a subset of this ensemble. We also address current structural knowledge regarding both protein-protein and protein-inhibitor complexes, that is, the 2P2I database. Finally, ligand efficiency analyses permit us to relate potency to size and polarity and to discuss the need to co-develop nanoparticle drug delivery systems.

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.

Protein–protein interaction inhibition (2P2I) combining high throughput and virtual screening: Application to the HIV-1 Nef protein

Protein–protein recognition is the cornerstone of multiple cellular and pathological functions. Therefore, protein–protein interaction inhibition (2P2I) is endowed with great therapeutic potential despite the initial belief that 2P2I was refractory to small-molecule intervention. Improved knowledge of complex molecular binding surfaces has recently stimulated renewed interest for 2P2I, especially after identification of “hot spots” and first inhibitory compounds. However, the combination of target complexity and lack of starting compound has thwarted experimental results and created intellectual barriers. Here we combined virtual and experimental screening when no previously known inhibitors can be used as starting point in a structure-based research program that targets an SH3 binding surface of the HIV type I Nef protein. High-throughput docking and application of a pharmacophoric filter on one hand and search for analogy on the other hand identified drug-like compounds that were further confirmed to bind Nef in the micromolar range (isothermal titration calorimetry), to target the Nef SH3 binding surface (NMR experiments), and to efficiently compete for Nef–SH3 interactions (cell-based assay, GST pull-down). Initial identification of these compounds by virtual screening was validated by screening of the very same library of compounds in the cell-based assay, demonstrating that a significant enrichment factor was attained by the in silico screening. To our knowledge, our results identify the first set of drug-like compounds that functionally target the HIV-1 Nef SH3 binding surface and provide the basis for a powerful discovery process that should help to speed up 2P2I strategies and open avenues for new class of antiviral molecules.

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 2P2IDB, 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 2P2IDB 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. 2P2IDB 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 PPIs interfaces, with less charged residues and more non-polar atoms. Finally, fifty percent of the complexes in the 2P2IDB 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.

A novel approach for assesing macromolecular complexes combining soft-docking calculations with NMR data

We present a novel and efficient approach for assessing protein–protein complex formation, which combines ab initio docking calculations performed with the protein docking algorithm BiGGER and chemical shift perturbation data collected with heteronuclear single quantum coherence (HSQC) or TROSY nuclear magnetic resonance (NMR) spectroscopy. This method, termed “restrained soft‐docking,” is validated for several known protein complexes. These data demonstrate that restrained soft‐docking extends the size limitations of NMR spectroscopy and provides an alternative method for investigating macromolecular protein complexes that requires less experimental time, effort, and resources. The potential utility of this novel NMR and simulated docking approach in current structural genomic initiatives is discussed.

Interaction between the C-terminal domains of N and P proteins of measles virus investigated by NMR

MINT‐7009780, MINT‐7009793, MINT‐7009808: N‐tail (uniprotkb:Q89933) and P (uniprotkb:P03422) bind (MI:0407) by nuclear magnetic resonance (MI:0077)

Modified Cap Group Suberoylanilide Hydroxamic Acid Histone Deacetylase Inhibitor Derivatives Reveal Improved Selective Antileukemic Activity

A series of SAHA cap derivatives was designed and prepared in good-to-excellent yields that varied from 49% to 95%. These derivatives were evaluated for their antiproliferative activity in several human cancer cell lines. Antiproliferative activity was observed for concentrations varying from 0.12 to >100 microM, and a molecular modeling approach of selected SAHA derivatives, based on available structural information of human HDAC8 in complex with SAHA, was performed. Strikingly, two compounds displayed up to 10-fold improved antileukemic activity with respect to SAHA; however, these compounds displayed antiproliferative activity similar to SAHA when assayed against solid tumor-derived cell lines. A 10-fold improvement in the leukemic vs peripheral blood mononuclear cell therapeutic ratio, with no evident in vivo toxicity toward blood cells, was also observed. The herein-described compounds and method of synthesis will provide invaluable tools to investigate the molecular mechanism responsible for the reported selectively improved antileukemic activity.

GFscore: a general nonlinear consensus scoring function for high-throughput docking.

Most of the recent published works in the field of docking and scoring protein/ligand complexes have focused on ranking true positives resulting from a Virtual Library Screening (VLS) through the use of a specified or consensus linear scoring function. In this work, we present a methodology to speed up the High Throughput Screening (HTS) process, by allowing focused screens or for hitlist triaging when a prohibitively large number of hits is identified in the primary screen, where we have extended the principle of consensus scoring in a nonlinear neural network manner. This led us to introduce a nonlinear Generalist scoring Function, GFscore, which was trained to discriminate true positives from false positives in a data set of diverse chemical compounds. This original Generalist scoring Function is a combination of the five scoring functions found in the CScore package from Tripos Inc. GFscore eliminates up to 75% of molecules, with a confidence rate of 90%. The final result is a Hit Enrichment in the list of molecules to investigate during a research campaign for biological active compounds where the remaining 25% of molecules would be sent to in vitro screening experiments. GFscore is therefore a powerful tool for the biologist, saving both time and money.

Conotoxins and Structural Biology: A Prospective Paradigm for Drug Discovery

Understanding the interactions between activating or antagonizing ligands and their cognate receptors at a molecular level offers promise for the development of pharmacological therapeutics for CNS disorders. The discovery of novel molecules that are capable of discriminating between the varied molecular subunits or isoforms of ion channels should provide a more detailed understanding of the pathophysiology of many CNS disorders. Abundant natural sources of pharmacologically active agents that demonstrate this refined selectivity and specificity are found in the animal toxins of venomous species including: snakes, spiders and the marine snail of the genus Conus. The uniquely fascinating combinatorial ability of the marine snail, genus Conus to modify the pharmacological properties of these neurotoxins or conopeptides within its venom is depicted throughout this review. The myriad of posttranslational modifications and disulfide bonded architectures that have been identified in the conopeptides, are described with an emphasis on the unique pharmacological properties and receptor target specificities that have been ascribed to each of these modifications. The ability of NMR spectroscopy to provide three-dimensional structural information within the interaction interface for both the ligand and target protein following complex formation and its application to conopeptide drug discovery are discussed. Similarly, the strength of merging NMR spectroscopy data with ab initio restrained soft-docking for rational pharmacophore design and the identification of lead compounds from in silico library screens will also be discussed. The initial phases of this stratagem are illustrated using two toxin antagonists and the recently determined structure of the KcsA potassium channel. These data exemplify the utility of this approach in elucidating important molecular interfaces of specific toxin-receptor/ion channel complexes, which can be further exploited in drug discovery initiatives.