Interactive Poster: Visualizing the Interaction Between Two Proteins

Colloque avec actes et comité de lecture. internationale.International audienceProtein docking is a fundamental biological process that links two proteins in order to change their properties. The link is defined by a set of forces between two large areas of the protein boundaries. Two docked proteins are very close to each other due to the VdW forces. This makes the understanding of the phenomenon difficult using classical molecular visualization. We present a way to focus on the most interesting area: the interface between the proteins. Visualizing the interface is useful both to understand the process thanks to co-crystallized proteins and to estimate the quality of docking simulation result. The interface may be defined by a surface that separates the two proteins. The geometry of the surface is induced by the VdW forces, while other forces can be represented by attributes mapped onto the surface. We present a very fast algorithm that extracts the interface surface. Moreover, the result of a rigid docking simulation can be improved using the flexibility of the residues. We show how the interface surface geometry and attributes can be updated in real-time when the user interactively moves the residues. This way, we allow expert knowledge to be intuitively introduced in the process to enhance the quality of the docking

A Feature Selection Method based on Tree Decomposition of Correlation Graph

International audienceThis paper presents a new method for feature selection where only relevant features are kept in the dataset and all other features are discarded. The proposed method uses tree decomposition heuristics to reveal subsets of highly connected features. These subsets are replaced by selecting representatives to reduce feature redundancy. Experiments performed on various datasets show promising results for our proposals

Intersurf: dynamic interface between proteins

Protein docking is a fundamental biological process that links two proteins. This link is typically defined by an interaction between two large zones of the protein boundaries. Visualizing such an interface is useful to understand the process thanks to 3D protein structures, to estimate the quality of docking simulation results, and to classify interactions in order to predict docking affinity between classes of interacting zones. Since the interface may be defined by a surface that separates the two proteins, it is possible to create a map of interaction that allows comparisons to be performed in 2D. This paper presents a very fast algorithm that extracts an interface surface and creates a valid and low-distorted interaction map. Another benefit of our approach is that a pre-computed part of the algorithm enables the surface to be updated in real-time while residues are moved

Comparative genomics allowed the identification of drug targets against human fungal pathogens

<p>Abstract</p> <p>Background</p> <p>The prevalence of invasive fungal infections (IFIs) has increased steadily worldwide in the last few decades. Particularly, there has been a global rise in the number of infections among immunosuppressed people. These patients present severe clinical forms of the infections, which are commonly fatal, and they are more susceptible to opportunistic fungal infections than non-immunocompromised people. IFIs have historically been associated with high morbidity and mortality, partly because of the limitations of available antifungal therapies, including side effects, toxicities, drug interactions and antifungal resistance. Thus, the search for alternative therapies and/or the development of more specific drugs is a challenge that needs to be met. Genomics has created new ways of examining genes, which open new strategies for drug development and control of human diseases.</p> <p>Results</p> <p><it>In silico </it>analyses and manual mining selected initially 57 potential drug targets, based on 55 genes experimentally confirmed as essential for <it>Candida albicans </it>or <it>Aspergillus fumigatus </it>and other 2 genes (<it>kre2 </it>and <it>erg6</it>) relevant for fungal survival within the host. Orthologs for those 57 potential targets were also identified in eight human fungal pathogens (<it>C. albicans</it>, <it>A. fumigatus</it>, <it>Blastomyces dermatitidis</it>, <it>Paracoccidioides brasiliensis</it>, <it>Paracoccidioides lutzii, Coccidioides immitis</it>, <it>Cryptococcus neoformans </it>and <it>Histoplasma capsulatum</it>). Of those, 10 genes were present in all pathogenic fungi analyzed and absent in the human genome. We focused on four candidates: <it>trr1 </it>that encodes for thioredoxin reductase, <it>rim8 </it>that encodes for a protein involved in the proteolytic activation of a transcriptional factor in response to alkaline pH, <it>kre2 </it>that encodes for α-1,2-mannosyltransferase and <it>erg6 </it>that encodes for Δ(24)-sterol C-methyltransferase.</p> <p>Conclusions</p> <p>Our data show that the comparative genomics analysis of eight fungal pathogens enabled the identification of four new potential drug targets. The preferred profile for fungal targets includes proteins conserved among fungi, but absent in the human genome. These characteristics potentially minimize toxic side effects exerted by pharmacological inhibition of the cellular targets. From this first step of post-genomic analysis, we obtained information relevant to future new drug development.</p

New Binding Site Conformations of the Dengue Virus NS3 Protease Accessed by Molecular Dynamics Simulation

International audienceDengue fever is caused by four distinct serotypes of the dengue virus (DENV1-4), and is estimated to affect over 500 million people every year. Presently, there are no vaccines or antiviral treatments for this disease. Among the possible targets to fight dengue fever is the viral NS3 protease (NS3PRO), which is in part responsible for viral processing and replication. It is now widely recognized that virtual screening campaigns should consider the flexibility of target protein by using multiple active conformational states. The flexibility of the DENV NS3PRO could explain the relatively low success of previous virtual screening studies. In this first work, we explore the DENV NS3PRO conformational states obtained from molecular dynamics (MD) simulations to take into account protease flexibility during the virtual screening/docking process. To do so, we built a full NS3PRO model by multiple template homology modeling. The model comprised the NS2B cofactor (essential to the NS3PRO activation), a glycine flexible link and the proteolytic domain. MD simulations had the purpose to sample, as closely as possible, the ligand binding site conformational landscape prior to inhibitor binding. The obtained conformational MD sample was clustered into four families that, together with principal component analysis of the trajectory, demonstrated protein flexibility. These results allowed the description of multiple binding modes for the Bz-Nle-Lys-Arg-Arg-H inhibitor, as verified by binding plots and pair interaction analysis. This study allowed us to tackle protein flexibility in our virtual screening campaign against the dengue virus NS3 proteas

Carbohydrate-based peptidomimetics targeting neuropilin-1: synthesis, molecular docking study and in vitro biological activities

International audienceNeuropilin-1 (NRP-1), a transmembrane glycoprotein acting as a co-receptor of VEGF-A, is expressed by cancer and angiogenic endothelial cells and is involved in the angiogenesis process. Taking advantage of functionalities and stereodiversities of sugar derivatives, the design and the synthesis of carbohydrate based peptidomimetics are here described. One of these compounds (56) demonstrated inhibition of VEGF-A165 binding to NRP-1 (IC50 = 39 μM) and specificity for NRP-1 over VEGF-R2. Biological evaluations were performed on human umbilical vein endothelial cells (HUVECs) through activation of downstream proteins (AKT and ERK phosphorylation), viability/proliferation assays and in vitro measurements of anti-angiogenic abilities

Community-wide assessment of GPCR structure modelling and ligand docking: GPCR Dock 2008

Recent breakthroughs in the determination of the crystal structures of G protein-coupled receptors (GPCRs) have provided new opportunities for structure-based drug design strategies targeting this protein family. With the aim of evaluating the current status of GPCR structure prediction and ligand docking, a community-wide, blind prediction assessment - GPCR Dock 2008 - was conducted in coordination with the publication of the crystal structure of the human adenosine A2Areceptor bound to the ligand ZM241385. Twenty-nine groups submitted 206 structural models before the release of the experimental structure, which were evaluated for the accuracy of the ligand binding mode and the overall receptor model compared with the crystal structure. This analysis highlights important aspects for success and future development, such as accurate modelling of structurally divergent regions and use of additional biochemical insight such as disulphide bridges in the extracellular loops

Should structure-based virtual screening techniques be used more extensively in modern drug discovery ?

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