Jean Salzemann

PDB_REDO: automated re-refinement of X-ray structure models in the PDB.

The majority of previously deposited X-ray structures can be improved by applying current refinement methods.

Grid-Enabled High-Throughput In Silico Screening Against Influenza A Neuraminidase

Encouraged by the success of the first EGEE biomedical data challenge against malaria (WISDOM) , the second data challenge battling avian flu was kicked off in April 2006 to identify new drugs for the potential variants of the influenza A virus. Mobilizing thousands of CPUs on the Grid, the six-week-long high-throughput screening activity has fulfilled over 100 CPU years of computing power and produced around 600 gigabytes of results on the Grid for further biological analysis and testing. In the paper, we demonstrate the impact of a worldwide Grid infrastructure to efficiently deploy large-scale virtual screening to speed up the drug design process. Lessons learned through the data challenge activity are also discussed

The EMBRACE web service collection

The EMBRACE (European Model for Bioinformatics Research and Community Education) web service collection is the culmination of a 5-year project that set out to investigate issues involved in developing and deploying web services for use in the life sciences. The project concluded that in order for web services to achieve widespread adoption, standards must be defined for the choice of web service technology, for semantically annotating both service function and the data exchanged, and a mechanism for discovering services must be provided. Building on this, the project developed: EDAM, an ontology for describing life science web services; BioXSD, a schema for exchanging data between services; and a centralized registry (http://www.embraceregistry.net) that collects together around 1000 services developed by the consortium partners. This article presents the current status of the collection and its associated recommendations and standards definitions.

WISDOM-II: Screening against multiple targets implicated in malaria using computational grid infrastructures

BackgroundDespite continuous efforts of the international community to reduce the impact of malaria on developing countries, no significant progress has been made in the recent years and the discovery of new drugs is more than ever needed. Out of the many proteins involved in the metabolic activities of the Plasmodium parasite, some are promising targets to carry out rational drug discovery.MotivationRecent years have witnessed the emergence of grids, which are highly distributed computing infrastructures particularly well fitted for embarrassingly parallel computations like docking. In 2005, a first attempt at using grids for large-scale virtual screening focused on plasmepsins and ended up in the identification of previously unknown scaffolds, which were confirmed in vitro to be active plasmepsin inhibitors. Following this success, a second deployment took place in the fall of 2006 focussing on one well known target, dihydrofolate reductase (DHFR), and on a new promising one, glutathione-S-transferase.MethodsIn silico drug design, especially vHTS is a widely and well-accepted technology in lead identification and lead optimization. This approach, therefore builds, upon the progress made in computational chemistry to achieve more accurate in silico docking and in information technology to design and operate large scale grid infrastructures.ResultsOn the computational side, a sustained infrastructure has been developed: docking at large scale, using different strategies in result analysis, storing of the results on the fly into MySQL databases and application of molecular dynamics refinement are MM-PBSA and MM-GBSA rescoring. The modeling results obtained are very promising. Based on the modeling results, In vitro results are underway for all the targets against which screening is performed.ConclusionThe current paper describes the rational drug discovery activity at large scale, especially molecular docking using FlexX software on computational grids in finding hits against three different targets (PfGST, PfDHFR, PvDHFR (wild type and mutant forms) implicated in malaria. Grid-enabled virtual screening approach is proposed to produce focus compound libraries for other biological targets relevant to fight the infectious diseases of the developing world.

Virtual screening on large scale grids

Large scale grids for in silico drug discovery open opportunities of particular interest to neglected and emerging diseases. In 2005 and 2006, we have been able to deploy large scale virtual docking within the framework of the WISDOM initiative against malaria and avian influenza requiring about 100 years of CPU on the EGEE, Auvergrid and TWGrid infrastructures. These achievements demonstrated the relevance of large scale grids for the virtual screening by molecular docking. This also allowed evaluating the performances of the grid infrastructures and to identify specific issues raised by large scale deployment.

Large Scale Deployment of Molecular Docking Application on Computational Grid infrastructures for Combating Malaria

Computational grids are solutions for several biological applications like virtual screening or molecular dynamics where large amounts of computing power and storage are required. The WISDOM project successfully deployed virtual screening at large scale on EGEE grid infrastructures in the summer 2005 and achieved 46 million dockings in 45 days, which is equivalent to 80 CPU years. WISDOM is one good example of a successful deployment of an embarrassingly parallel application. In this paper, we describe the improvements in our deployment. We screened ZINC database against four targets implicated in malaria. During more than 2 months and a half, we have achieved 140 million dockings, representing an average throughput of almost 80,000 dockings per hour. This was made possible by the availability of thousands of CPUs through different infrastructures worldwide. Through the acquired experience, the WISDOM production environment is evolving to enable an easy and fault- tolerant deployment of biological tools.

Grid-enabled high throughput virtual screening

Large scale grids for in silico drug discovery open opportunities of particular interest to neglected and emerging diseases. In 2005 and 2006, we have been able to deploy large scale virtual docking within the framework of the WISDOM initiative against malaria and avian influenza requiring about 100 years of CPU on the EGEE, Auvergrid and TWGrid infrastructures. These achievements demonstrated the relevance of large scale grids for the virtual screening by molecular docking. This also allowed evaluating the performances of the grid infrastructures and to identify specific issues raised by large scale deployment.

WISDOM-II: a large in silico docking effort for finding novel hits against malaria using computational grid infrastructure

After having deployed a first data challenge on malaria and a second one on avian flu, respectively in summer 2005 and spring 2006, we are demonstrating here again how efficiently the computational grids can be used to produce massive docking data at a high-throughput. During more than 2 months and a half, we have achieved at least 140 million dockings, representing an average throughput of almost 80,000 dockings per hour. This was made possible by the availability of thousands of CPUs through different infrastructures worldwide. Through the acquired experience, the WISDOM production environment is evolving to enable an easy and fault-tolerant deployment of biological tools; in this case it is the FlexX commercial docking software which is used to dock the whole ZINC database against 4 different targets.

Replication and Update of Molecular Biology Databases

Update of molecular biology databases is a growing burden on the biomedical research community. As the grid allows to share and replicate data, we propose a service to automatically update the molecular biology databases from a single changing reference using Web services. In this paper we report the components, the architecture, and the deployment of the update service on the french RUGBI grid infrastructure. RUGBI is a computing grid infrastructure based on existing middleware and technologies for the community of scientists in bioinformatics.

A grid-enabled problem solving environment for in-silico screening in drug discovery

WISDOM is an international initiative to deploy large-scale in-silico docking on a public grid infrastructure in an attempt to find potential drugs against neglected or emerging diseases such as Malaria and Avian Flu. Within the framework of the WISDOM initiative, large-scale deployments of in silico docking have been done on production grid infrastructures, demonstrating the relevance of large scale grids for high throughput virtual screening from scientific and grid deployment perspective. However, from the usability point of view, there still seems to be a lot to be done in order to be able to get the grid-enabled large-scale virtual screening approach handier for non-experts of grid computing. To address this issue, we have developed an intuitive and easy-to-use grid-enabled virtual screening tool called Drugscreener-G (DSG), aiming to help scientists in drug discovery including biologists and biochemists to more easily carryout large-scale deployment of molecular docking on grids without having to know details of grid middleware services and tools. With the help of DSG, scientists can easily have access to the PDB database, download and view the 3D structure of target proteins of their interest, launch and manage millions of in-silico docking simulations on the Grid. To facilitate the analysis of docking results, visualization and molecular modeling tools such as Jmol and Chimera have been integrated into DSG as well. The DSG client tool is now being used and tested by biologists in Chonnam National University, one of long-time partners of the WISDOM collaboration. With the help of tools like DSG, their long-time dream of large-scale virtual screening on their own at any time with any help from grid experts is to be made realized in the near future.