Evidence map›Paper›PMID 23762864›Full record

ArticleBioMed research international2013

A high performance cloud-based protein-ligand docking prediction algorithm.

Jui-Le Chen, Chun-Wei Tsai, Ming-Chao Chiang, Chu-Sing Yang

Abstract read
In one paragraph

Article in BioMed research international, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Jui-Le ChenDepartment of Electrical Engineer, National Cheng Kung University, Institute of Computer and Communication Engineering, Tainan 70101, Taiwan.
Chun-Wei Tsai
Ming-Chao Chiang
Chu-Sing Yang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The potential of predicting druggability for a particular disease by integrating biological and computer science technologies has witnessed success in recent years. Although the computer science technologies can be used to reduce the costs of the pharmaceutical research, the computation time of the structure-based protein-ligand docking prediction is still unsatisfied until now. Hence, in this paper, a novel docking prediction algorithm, named fast cloud-based protein-ligand docking prediction algorithm (FCPLDPA), is presented to accelerate the docking prediction algorithm. The proposed algorithm works by leveraging two high-performance operators: (1) the novel migration (information exchange) operator is designed specially for cloud-based environments to reduce the computation time; (2) the efficient operator is aimed at filtering out the worst search directions. Our simulation results illustrate that the proposed method outperforms the other docking algorithms compared in this paper in terms of both the computation time and the quality of the end result.

Indexed as

AlgorithmsInternetMolecular Docking SimulationLigandsProteinsTime FactorsLigandsProteins

Identifiers

PMID23762864
PMCPMC3666298

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.