Discovering patterns in drug-protein interactions based on their fingerprints

<p>Abstract</p> <p>Background</p> <p>The discovering of interesting patterns in drug-protein interaction data at molecular level can reveal hidden relationship among drugs and proteins and can therefore be of paramount importance for such application as drug design. To discover such patterns, we propose here a computational approach to analyze the molecular data of drugs and proteins that are known to have interactions with each other. Specifically, we propose to use a data mining technique called <it>Drug-Protein Interaction Analysis </it>(<it>D-PIA</it>) to determine if there are any commonalities in the fingerprints of the substructures of interacting drug and protein molecules and if so, whether or not any patterns can be generalized from them.</p> <p>Method</p> <p>Given a database of drug-protein interactions, <it>D-PIA </it>performs its tasks in several steps. First, for each drug in the database, the fingerprints of its molecular substructures are first obtained. Second, for each protein in the database, the fingerprints of its protein domains are obtained. Third, based on known interactions between drugs and proteins, an interdependency measure between the fingerprint of each drug substructure and protein domain is then computed. Fourth, based on the interdependency measure, drug substructures and protein domains that are significantly interdependent are identified. Fifth, the existence of interaction relationship between a previously unknown drug-protein pairs is then predicted based on their constituent substructures that are significantly interdependent.</p> <p>Results</p> <p>To evaluate the effectiveness of <it>D-PIA</it>, we have tested it with real drug-protein interaction data. <it>D-PIA </it>has been tested with real drug-protein interaction data including enzymes, ion channels, and protein-coupled receptors. Experimental results show that there are indeed patterns that one can discover in the interdependency relationship between drug substructures and protein domains of interacting drugs and proteins. Based on these relationships, a testing set of drug-protein data are used to see if <it>D-PIA </it>can correctly predict the existence of interaction between drug-protein pairs. The results show that the prediction accuracy can be very high. An AUC score of a ROC plot could reach as high as 75% which shows the effectiveness of this classifier.</p> <p>Conclusions</p> <p><it>D-PIA </it>has the advantage that it is able to perform its tasks effectively based on the fingerprints of drug and protein molecules without requiring any 3D information about their structures and <it>D-PIA </it>is therefore very fast to compute. <it>D-PIA </it>has been tested with real drug-protein interaction data and experimental results show that it can be very useful for predicting previously unknown drug-protein as well as protein-ligand interactions. It can also be used to tackle problems such as ligand specificity which is related directly and indirectly to drug design and discovery.</p

Intestinal parasitic infections in schoolchildren in different settings of Côte d'Ivoire : effect of diagnostic approach and implications for control

BACKGROUND: Social-ecological systems govern parasitic infections in humans. Within the frame of assessing the accuracy of a rapid diagnostic test for Schistosoma mansoni in Cote d'Ivoire, three different endemicity settings had to be identified and schoolchildren's intestinal parasitic infection profiles were characterized. METHODS: In September 2010, a rapid screening was conducted in 11 schools in the Azaguie district, south Cote d'Ivoire. In each school, 25 children were examined for S. mansoni and S. haematobium. Based on predefined schistosome endemicity levels, three settings were selected, where schoolchildren aged 8-12 years were asked to provide three stool and three urine samples for an in-depth appraisal of parasitic infections. Triplicate Kato-Katz thick smears were prepared from each stool sample for S. mansoni and soil-transmitted helminth diagnosis, whereas urine samples were subjected to a filtration method for S. haematobium diagnosis. Additionally, a formol-ether concentration method was employed on one stool sample for the diagnosis of helminths and intestinal protozoa. Multivariable logistic regression models were employed to analyse associations between schoolchildren's parasitic infections, age, sex and study setting. RESULTS: The prevalences of S. mansoni and S. haematobium infections in the initial screening ranged from nil to 88% and from nil to 56%, respectively. The rapid screening in the three selected areas revealed prevalences of S. mansoni of 16%, 33% and 78%. Based on a more rigorous diagnostic approach, the respective prevalences increased to 92%, 53% and 33%. S. haematobium prevalences were 0.8%, 4% and 65%. Prevalence and intensity of Schistosoma spp., soil-transmitted helminths and intestinal protozoan infections showed setting-specific patterns. Infections with two or more species concurrently were most common in the rural setting (84%), followed by the peri-urban (28.3%) and urban setting (18.2%). CONCLUSIONS: More sensitive diagnostic tools or rigorous sampling approaches are needed to select endemicity settings with high fidelity. The observed small-scale heterogeneity of helminths and intestinal protozoan infections has important implications for contro

Will all scientists working on snails and the diseases they transmit please stand up?

Copyright © 2012 Adema et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.No abstract available

Phenotypic Screens, Chemical Genomics, and Antimalarial Lead Discovery

No grant i

Ecology: a prerequisite for malaria elimination and eradication

* Existing front-line vector control measures, such as insecticide-treated nets and residual sprays, cannot break the transmission cycle of Plasmodium falciparum in the most intensely endemic parts of Africa and the Pacific * The goal of malaria eradication will require urgent strategic investment into understanding the ecology and evolution of the mosquito vectors that transmit malaria * Priority areas will include understanding aspects of the mosquito life cycle beyond the blood feeding processes which directly mediate malaria transmission * Global commitment to malaria eradication necessitates a corresponding long-term commitment to vector ecolog

Structural Requirements for Dihydrobenzoxazepinone Anthelmintics: Actions against Medically Important and Model Parasites: Trichuris muris, Brugia malayi, Heligmosomoides polygyrus, and Schistosoma mansoni.

Nine hundred million people are infected with the soil-transmitted helminths Ascaris lumbricoides (roundworm), hookworm, and Trichuris trichiura (whipworm). However, low single-dose cure rates of the benzimidazole drugs, the mainstay of preventative chemotherapy for whipworm, together with parasite drug resistance, mean that current approaches may not be able to eliminate morbidity from trichuriasis. We are seeking to develop new anthelmintic drugs specifically with activity against whipworm as a priority and previously identified a hit series of dihydrobenzoxazepinone (DHB) compounds that block motility of ex vivo Trichuris muris. Here, we report a systematic investigation of the structure-activity relationship of the anthelmintic activity of DHB compounds. We synthesized 47 analogues, which allowed us to define features of the molecules essential for anthelmintic action as well as broadening the chemotype by identification of dihydrobenzoquinolinones (DBQs) with anthelmintic activity. We investigated the activity of these compounds against other parasitic nematodes, identifying DHB compounds with activity against Brugia malayi and Heligmosomoides polygyrus. We also demonstrated activity of DHB compounds against the trematode Schistosoma mansoni, a parasite that causes schistosomiasis. These results demonstrate the potential of DHB and DBQ compounds for further development as broad-spectrum anthelmintics

Mycobacterial dihydrofolate reductase inhibitors identified using chemogenomic methods and in vitro validation.

The lack of success in target-based screening approaches to the discovery of antibacterial agents has led to reemergence of phenotypic screening as a successful approach of identifying bioactive, antibacterial compounds. A challenge though with this route is then to identify the molecular target(s) and mechanism of action of the hits. This target identification, or deorphanization step, is often essential in further optimization and validation studies. Direct experimental identification of the molecular target of a screening hit is often complex, precisely because the properties and specificity of the hit are not yet optimized against that target, and so many false positives are often obtained. An alternative is to use computational, predictive, approaches to hypothesize a mechanism of action, which can then be validated in a more directed and efficient manner. Specifically here we present experimental validation of an in silico prediction from a large-scale screen performed against Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis. The two potent anti-tubercular compounds studied in this case, belonging to the tetrahydro-1,3,5-triazin-2-amine (THT) family, were predicted and confirmed to be an inhibitor of dihydrofolate reductase (DHFR), a known essential Mtb gene, and already clinically validated as a drug target. Given the large number of similar screening data sets shared amongst the community, this in vitro validation of these target predictions gives weight to computational approaches to establish the mechanism of action (MoA) of novel screening hit