Open Computing Grid for Molecular Science and Engineering

Sild, Sulev; Maran, Uko; Lomaka, and Andre; Karelson, Mati

doi:10.1021/ci050354f

Cited by 31 publications

(22 citation statements)

References 36 publications

(49 reference statements)

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“…In this case, the grid is used as a user-friendly front end to submit computationally intensive jobs for available computer resources. A number of examples have been previously summarized elsewhere [12,13]. More recent examples include the calculation of protein-ligand binding affinities [14,15], virtual screening for plasmepsin inhibitors on the EGEE grid infrastructure in order to prevent malaria [16], and molecular dynamics simulations with CHARMM software on the Open Science Grid [17].…”

Section: Introductionmentioning

confidence: 99%

“…For example, the OpenMolGRID project has developed a data warehouse with relevant data for QSAR modeling [12] and the U.K. National Crystallography Service has developed a grid based e-science infrastructure for small molecule crystallography services [18]. The Common Instrument Middleware Architecture provides grid services to control scientific instruments and to access their data [19].…”

Section: Introductionmentioning

confidence: 99%

“…This is practical because many scientific workloads involve the execution of multiple applications in a predefined sequence. Relevant examples include the OpenMolGRID [12], SOMA [20] and GEMSTONE [21] systems. A new example of a workflow centric system oriented to molecular design and modeling is Chemomentum [22].…”

Section: Introductionmentioning

confidence: 99%

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Docking and Virtual Screening Using Distributed Grid Technology

2009

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Distributed grid technologies are gradually realizing their potential to provide innovative infrastructures for complex scientific and industrial applications in the field of computational chemistry and related application areas. The current paper gives examples of distributed solutions for docking and virtual screening applications in moving the computational paradigms towards collaborative research and grid computing environments. The Chemomentum collaborative computing environment including both hardware and software infrastructure is described. Examples of applications are given i) for docking and virtual screening on multiprotein and multilibrary cases for H5N1 avian influenza and HIV-1 viruses; and ii) QSAR model building related to HIV-1 protease activity and aquatic toxicity.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Docking and Virtual Screening Using Distributed Grid Technology

2009

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“…For example, automated workflows have been based on various open-source workflow development systems (e.g. Discovery Bus [37], OpenMolGrid [38], Taverna [39]). Further work is needed to develop and illustrate specific workflows (designed for specific compounds, endpoints and regulatory purposes).…”

Section: Conclusion and Recommendationsmentioning

confidence: 99%

The Integrated Use of Models for the Properties and Effects of Chemicals by means of a Structured Workflow

Bassan

Worth

2008

QSAR Comb. Sci.

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This paper reviews the applicability of different types of non-testing methods and in silico tools in the framework of a structured workflow that aids their exploitation for the prediction of properties that contribute to hazard and risk assessments of chemicals. These properties include basic physicochemical properties, metabolic and environmental fate, and ecological and health effects of chemicals. The workflow for the use of methods comprises a structured sequence of operations that integrates the functionalities of a wide array of in silico tools. The workflow could be used for in-house decision making (e.g. screening the properties of potential drugs and commercial chemicals) as well generating data required in regulatory submissions. The general workflow presented here is intended to broadly applicable to all endpoints and different regulatory frameworks, including the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) legislation in the European Union (EU). The general framework can be adapted to meet the needs of specific chemicals, endpoints and regulatory purposes. This review is one of a series of minireviews in this journal.

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“…[14][15][16]21,22 Since dedicated parallel computers are more difficult to access, grid systems are now a more popular way to cope with a growing requirement for high computational resources and to speed-up the drug development process. [21][22][23][24][25] Moreover, the flexibility of grid systems allows them to be configured as parallel computers. Parallel programming runtimes can be used to develop parallel applications that utilize the collection of processors simultaneously.…”

mentioning

confidence: 99%

Efficiency of a hierarchical protocol for high throughput structure-based virtual screening on GRID5000 cluster grid

Ghemtio¹,

Jeannot²,

Maigret³

2010

OAB

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Most modern computational techniques in the drug discovery areas put demands on large computer resources. Grid computing offers a powerful alternative way of running computationally intensive applications. One field of the drug innovation process that can benefit greatly from the use of grid resources is the high-throughput virtual screening approach for docking huge chemical compound libraries into known protein-binding sites. The use of computational grids is the combination of computer resources from multiple administrative domains, heterogeneous, and geographically dispersed applications to a common task that requires a great number of computer-processing cycles or the need to process large amounts of data. This study detailed a screening campaign, on Grid5000 cluster grid computing infrastructure, concerning the ZINC database, from which a subset of ∼600,000 "drug-like" molecules was extracted, against three structures of the liver-X receptor β (LXR β). A funnel strategy was used for that purpose, starting from a fast but simple shape matching procedure and achieved with more complex molecular dynamics simulations. From a total of ∼91 million three-dimensional conformations which were generated at the beginning of the funnel and after intermediate filtering steps, the process ended with 45 putative hits. The GRID5000 is a highly reconfigurable, controllable, and monitorable experimental cluster grid, connecting nine sites geographically distributed in France, and featuring more than 3,200 processors and 5,700 cores. To hide the complexity of the grid system from the user, the GRID5000 has been used through the virtual screening manager for grid computing (VSM-G) platform, dedicated to in silico screening and to provide maximum computing power by using grid resources efficiently. The whole screening process required around 82 days (78 days of pre-processing and 3.6 days for the docking funnel itself) and utilized 3,144 nodes over nine sites. The use of grid infrastructures and hierarchical filtering protocol enable us to perform evaluations of the binding capabilities of millions of compounds on several conformations of a given target and propose that, with a low cost, most promising compounds for in vitro tests.

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Open Computing Grid for Molecular Science and Engineering

Cited by 31 publications

References 36 publications

Docking and Virtual Screening Using Distributed Grid Technology

Docking and Virtual Screening Using Distributed Grid Technology

The Integrated Use of Models for the Properties and Effects of Chemicals by means of a Structured Workflow

Efficiency of a hierarchical protocol for high throughput structure-based virtual screening on GRID5000 cluster grid

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