wFReDoW: A Cloud-Based Web Environment to Handle Molecular Docking Simulations of a Fully Flexible Receptor Model

Molecular docking simulations of fully flexible protein receptor (FFR) models are coming of age. In our studies, an FFR model is represented by a series of different conformations derived from a molecular dynamic simulation trajectory of the receptor. For each conformation in the FFR model, a dockin...

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Published in:BioMed Research International
Main Authors: De Paris, Renata, Frantz, Fábio A., Norberto de Souza, Osmar, Ruiz, Duncan D. A.
Format: Text
Language:English
Published: Hindawi Publishing Corporation 2013
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3652109
http://www.ncbi.nlm.nih.gov/pubmed/23691504
https://doi.org/10.1155/2013/469363
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spelling ftpubmed:oai:pubmedcentral.nih.gov:3652109 2023-05-15T18:11:34+02:00 wFReDoW: A Cloud-Based Web Environment to Handle Molecular Docking Simulations of a Fully Flexible Receptor Model De Paris, Renata Frantz, Fábio A. Norberto de Souza, Osmar Ruiz, Duncan D. A. 2013 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3652109 http://www.ncbi.nlm.nih.gov/pubmed/23691504 https://doi.org/10.1155/2013/469363 en eng Hindawi Publishing Corporation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3652109 http://www.ncbi.nlm.nih.gov/pubmed/23691504 http://dx.doi.org/10.1155/2013/469363 Copyright © 2013 Renata De Paris et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. CC-BY Methodology Report Text 2013 ftpubmed https://doi.org/10.1155/2013/469363 2013-09-04T23:39:48Z Molecular docking simulations of fully flexible protein receptor (FFR) models are coming of age. In our studies, an FFR model is represented by a series of different conformations derived from a molecular dynamic simulation trajectory of the receptor. For each conformation in the FFR model, a docking simulation is executed and analyzed. An important challenge is to perform virtual screening of millions of ligands using an FFR model in a sequential mode since it can become computationally very demanding. In this paper, we propose a cloud-based web environment, called web Flexible Receptor Docking Workflow (wFReDoW), which reduces the CPU time in the molecular docking simulations of FFR models to small molecules. It is based on the new workflow data pattern called self-adaptive multiple instances (P-SaMIs) and on a middleware built on Amazon EC2 instances. P-SaMI reduces the number of molecular docking simulations while the middleware speeds up the docking experiments using a High Performance Computing (HPC) environment on the cloud. The experimental results show a reduction in the total elapsed time of docking experiments and the quality of the new reduced receptor models produced by discarding the nonpromising conformations from an FFR model ruled by the P-SaMI data pattern. Text sami PubMed Central (PMC) BioMed Research International 2013 1 12
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Methodology Report
spellingShingle Methodology Report
De Paris, Renata
Frantz, Fábio A.
Norberto de Souza, Osmar
Ruiz, Duncan D. A.
wFReDoW: A Cloud-Based Web Environment to Handle Molecular Docking Simulations of a Fully Flexible Receptor Model
topic_facet Methodology Report
description Molecular docking simulations of fully flexible protein receptor (FFR) models are coming of age. In our studies, an FFR model is represented by a series of different conformations derived from a molecular dynamic simulation trajectory of the receptor. For each conformation in the FFR model, a docking simulation is executed and analyzed. An important challenge is to perform virtual screening of millions of ligands using an FFR model in a sequential mode since it can become computationally very demanding. In this paper, we propose a cloud-based web environment, called web Flexible Receptor Docking Workflow (wFReDoW), which reduces the CPU time in the molecular docking simulations of FFR models to small molecules. It is based on the new workflow data pattern called self-adaptive multiple instances (P-SaMIs) and on a middleware built on Amazon EC2 instances. P-SaMI reduces the number of molecular docking simulations while the middleware speeds up the docking experiments using a High Performance Computing (HPC) environment on the cloud. The experimental results show a reduction in the total elapsed time of docking experiments and the quality of the new reduced receptor models produced by discarding the nonpromising conformations from an FFR model ruled by the P-SaMI data pattern.
format Text
author De Paris, Renata
Frantz, Fábio A.
Norberto de Souza, Osmar
Ruiz, Duncan D. A.
author_facet De Paris, Renata
Frantz, Fábio A.
Norberto de Souza, Osmar
Ruiz, Duncan D. A.
author_sort De Paris, Renata
title wFReDoW: A Cloud-Based Web Environment to Handle Molecular Docking Simulations of a Fully Flexible Receptor Model
title_short wFReDoW: A Cloud-Based Web Environment to Handle Molecular Docking Simulations of a Fully Flexible Receptor Model
title_full wFReDoW: A Cloud-Based Web Environment to Handle Molecular Docking Simulations of a Fully Flexible Receptor Model
title_fullStr wFReDoW: A Cloud-Based Web Environment to Handle Molecular Docking Simulations of a Fully Flexible Receptor Model
title_full_unstemmed wFReDoW: A Cloud-Based Web Environment to Handle Molecular Docking Simulations of a Fully Flexible Receptor Model
title_sort wfredow: a cloud-based web environment to handle molecular docking simulations of a fully flexible receptor model
publisher Hindawi Publishing Corporation
publishDate 2013
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3652109
http://www.ncbi.nlm.nih.gov/pubmed/23691504
https://doi.org/10.1155/2013/469363
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op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3652109
http://www.ncbi.nlm.nih.gov/pubmed/23691504
http://dx.doi.org/10.1155/2013/469363
op_rights Copyright © 2013 Renata De Paris et al.
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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op_doi https://doi.org/10.1155/2013/469363
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