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Optimizing Electrostatic Similarity for Virtual Screening: A New Methodology

机译:优化虚拟筛选的静电相似性:一种新方法

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摘要

Ligand Based Virtual Screening methods are widely used in drug discovery as filters for subsequent in-vitro and in-vivo characterization. Since the databases processed are enormously large, this pre-selection process requires the use of fast and precise methodologies. In this work, the similarity between compounds is measured in terms of electrostatic potential. To do so, we propose a new and alternative methodology, called LBVS-Electrostatic. Accordingly to the obtained results, we are able to conclude that many of the compounds proposed with our novel approach could not be discovered with the classical one.
机译:基于配体的虚拟筛选方法广泛用于药物发现作为过滤器,用于随后的体外和体内表征。 由于处理的数据库非常大,因此该预选过程需要使用快速和精确的方法。 在这项工作中,化合物之间的相似性在静电势方面测量。 为此,我们提出了一种新的和替代方法,称为LBVS-eyretatic。 因此,对于所得的结果,我们能够得出结论,许多通过古典的方法无法发现我们的新方法提出的化合物。

著录项

  • 来源
    《Informatica》 |2020年第4期|821-839|共19页
  • 作者单位

    Supercomputing -Algorithms Research Group (SAL) University of Almeria Agrifood Campus of International Excellence ceiA3 Spain;

    Supercomputing -Algorithms Research Group (SAL) University of Almeria Agrifood Campus of International Excellence ceiA3 Spain;

    Structural Bioinformatics and High Performance Computing Research Group (BIO-HPC) Universidad Catolica de Murcia (UCAM) Spain;

    Supercomputing -Algorithms Research Group (SAL) University of Almeria Agrifood Campus of International Excellence ceiA3 Spain;

  • 收录信息 美国《科学引文索引》(SCI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    virtual screening; shape similarity; electrostatic similarity;

    机译:虚拟筛选;形状相似;静电相似性;

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