Dominique Douguet

HELIQUEST: a web server to screen sequences with specific α-helical properties

SUMMARYnHELIQUEST calculates the physicochemical properties and amino acid composition of an alpha-helix and screens databank to identify protein segments possessing similar features. This server is also dedicated to mutating helices manually or automatically by genetic algorithm to design analogues of defined features.nnnAVAILABILITYnhttp://heliquest.ipmc.cnrs.fr.

Osh4p exchanges sterols for phosphatidylinositol 4-phosphate between lipid bilayers

The yeast Kes1p/Osh4p protein functions as a sterol/PI(4)P exchanger between lipid membranes, which suggests the possibility of creating a sterol gradient via phosphoinositide metabolism.

Host Cell Invasion by Apicomplexan Parasites: Insights from the Co-Structure of Ama1 with a Ron2 Peptide

The structure of a eukaryotic pathogen adhesin bound to its receptor provides a basis for design of therapeutics. Apicomplexan parasites such as Toxoplasma gondii and Plasmodium species actively invade host cells through a moving junction (MJ) complex assembled at the parasite–host cell interface. MJ assembly is initiated by injection of parasite rhoptry neck proteins (RONs) into the host cell, where RON2 spans the membrane and functions as a receptor for apical membrane antigen 1 (AMA1) on the parasite. We have determined the structure of TgAMA1 complexed with a RON2 peptide at 1.95 angstrom resolution. A stepwise assembly mechanism results in an extensive buried surface area, enabling the MJ complex to resist the mechanical forces encountered during host cell invasion. Besides providing insights into host cell invasion by apicomplexan parasites, the structure offers a basis for designing therapeutics targeting these global pathogens.

Extracellular acidification exerts opposite actions on TREK1 and TREK2 potassium channels via a single conserved histidine residue

Mechanosensitive K+ channels TREK1 and TREK2 form a subclass of two P-domain K+ channels. They are potently activated by polyunsaturated fatty acids and are involved in neuroprotection, anesthesia, and pain perception. Here, we show that acidification of the extracellular medium strongly inhibits TREK1 with an apparent pK near to 7.4 corresponding to the physiological pH. The all-or-none effect of pH variation is steep and is observed within one pH unit. TREK2 is not inhibited but activated by acidification within the same range of pH, despite its close homology with TREK1. A single conserved residue, H126 in TREK1 and H151 in TREK2, is involved in proton sensing. This histidine is located in the M1P1 extracellular loop preceding the first P domain. The differential effect of acidification, that is, activation for TREK2 and inhibition for TREK1, involves other residues located in the P2M4 loop, linking the second P domain and the fourth membrane-spanning segment. Structural modeling of TREK1 and TREK2 and site-directed mutagenesis strongly suggest that attraction or repulsion between the protonated side chain of histidine and closely located negatively or positively charged residues in P2M4 control outer gating of these channels. The differential sensitivity of TREK1 and TREK2 to external pH variations discriminates between these two K+ channels that otherwise share the same regulations by physical and chemical stimuli, and by hormones and neurotransmitters.

Easier threading through web-based comparisons and cross-validations

UNLABELLEDnWe have developed a WWW server for the integration and comparison of protein structure predictions performed by five different servers. Users submit an amino acid sequence to a selected set of these prediction methods. Results are gathered on a web-based page in order to facilitate comparison and analysis. All the alignments are further evaluated through a common threading tool making their comparisons easier.nnnAVAILABILITYnThe meta-server is available free at http://www.infobiosud.cnrs.fr/bioservernnnSUPPLEMENTARY INFORMATIONnhttp://www.infobiosud.cnrs.fr/bioserver/hah1.html

A genetic algorithm for the automated generation of small organic molecules: Drug design using an evolutionary algorithm

Rational drug design involves finding solutions to large combinatorial problems for which an exhaustive search is impractical. Genetic algorithms provide a novel tool for the investigation of such problems. These are a class of algorithms that mimic some of the major characteristics of Darwinian evolution. LEA has been designed in order to conceive novel small organic molecules which satisfy quantitative structure-activity relationship based rules (fitness). The fitness consists of a sum of constraints that are range properties. The algorithm takes an initial set of fragments and iteratively improves them by means of crossover and mutation operators that are related to those involved in Darwinian evolution. The basis of the algorithm, its implementation and parameterization, are described together with an application in de novo molecular design of new retinoids. The results may be promising for chemical synthesis and show that this tool may find extensive applications in de novo drug design projects.

Dockground resource for studying protein--protein interfaces

MOTIVATIONnPublic resources for studying protein interfaces are necessary for better understanding of molecular recognition and developing intermolecular potentials, search procedures and scoring functions for the prediction of protein complexes.nnnRESULTSnThe first release of the DOCKGROUND resource implements a comprehensive database of co-crystallized (bound-bound) protein-protein complexes, providing foundation for the upcoming expansion to unbound (experimental and simulated) protein-protein complexes, modeled protein-protein complexes and systematic sets of docking decoys. The bound-bound part of DOCKGROUND is a relational database of annotated structures based on the Biological Unit file (Biounit) provided by the RCSB as a separated file containing probable biological molecule. DOCKGROUND is automatically updated to reflect the growth of PDB. It contains 67,220 pairwise complexes that rely on 14,913 Biounit entries from 34,778 PDB entries (January 30, 2006). The database includes a dynamic generation of non-redundant datasets of pairwise complexes based either on the structural similarity (SCOP classification) or on user-defined sequence identity. The growing DOCKGROUND resource is designed to become a comprehensive public environment for developing and validating new methodologies for modeling of protein interactions.nnnAVAILABILITYnDOCKGROUND is available at http://dockground.bioinformatics.ku.edu. The current first release implements the bound-bound part.

Inhibition of adrenocortical carcinoma cell proliferation by steroidogenic factor-1 inverse agonists.

CONTEXTnTranscription factor steroidogenic factor-1 (SF-1) plays a pivotal role in the control of adrenocortical cell steroidogenesis and proliferation. SF-1 amplification and overexpression are found in most cases of childhood adrenocortical tumors (ACTs).nnnOBJECTIVEnOur objective was to investigate the effect of SF-1 inverse agonists of the alkyloxyphenol and isoquinolinone classes on the proliferation of human adrenocortical cell lines expressing SF-1 (H295R), in conditions of basal and increased SF-1 expression, or negative for SF-1 expression (SW-13).nnnMAIN OUTCOME MEASURESnProliferation assays, immunoblots, flow cytometric analyses, steroid hormone assays, and reverse transcription quantitative PCR were used.nnnRESULTSnSF-1 inhibitors of the alkyloxyphenol class displayed a dose-dependent inhibitory effect on both SF-1-positive and -negative ACT cells, whereas SF-1 inverse agonists of the isoquinolinone class selectively inhibited cell proliferation elicited by SF-1 overexpression. These drugs also inhibited stimulated steroid hormone secretion and CYP21 and CYP17 mRNA expression.nnnCONCLUSIONnSF-1 inhibitors may represent a useful tool in the chemotherapy of ACTs.

Substituted benzyl-pyrimidines targeting thymidine monophosphate kinase of Mycobacterium tuberculosis : Synthesis and in vitro anti-mycobacterial activity

A series of N(1)-(4-substituted-benzyl)-pyrimidines were synthesized as potential inhibitors of thymidine monophosphate kinase of Mycobacterium tuberculosis (TMPKmt). Key SAR parameters included the chain length substitution in para position of the benzyl ring, the functional group terminating the alkyl chain, and the substituent on the C-5 pyrimidine ring. Synthesized molecules were assayed against both recombinant enzyme and mycobacteria cultures. The most potent compounds have K(i) values in the micromolar range and an MIC(50) of 50microg/mL against Mycobacterium bovis. These results will guide the design of a new generation of lead compounds.

DOCKGROUND system of databases for protein recognition studies: unbound structures for docking.

Computational docking approaches are important as a source of protein–protein complexes structures and as a means to understand the principles of protein association. A key element in designing better docking approaches, including search procedures, potentials, and scoring functions is their validation on experimentally determined structures. Thus, the databases of such structures (benchmark sets) are important. The previous, first release of the DOCKGROUND resource (Douguet et al., Bioinformatics 2006; 22:2612–2618) implemented a comprehensive database of cocrystallized (bound) protein–protein complexes in a relational database of annotated structures. The current release adds important features to the set of bound structures, such as regularly updated downloadable datasets: automatically generated nonredundant set, built according to most common criteria, and a manually curated set that includes only biological nonobligate complexes along with a number of additional useful characteristics. The main focus of the current release is unbound (experimental and simulated) protein–protein complexes. Complexes from the bound dataset are used to identify crystallized unbound analogs. If such analogs do not exist, the unbound structures are simulated by rotamer library optimization. Thus, the database contains comprehensive sets of complexes suitable for large scale benchmarking of docking algorithms. Advanced methodologies for simulating unbound conformations are being explored for the next release. The future releases will include datasets of modeled protein–protein complexes, and systematic sets of docking decoys obtained by different docking algorithms. The growing DOCKGROUND resource is designed to become a comprehensive public environment for developing and validating new docking methodologies. Proteins 2007.