化学结构相似性搜索用于基于配体的虚拟筛选：方法和计算资源

Title:Chemical Structure Similarity Search for Ligand-based Virtual Screening: Methods and Computational Resources

Volume: 17 Issue: 14

Author(s): Xin Yan, Chenzhong Liao, Zhihong Liu, Arnold T. Hagler, Qiong Gu, Jun Xu

Affiliation:

关键词: 化学信息学、药物发现，HPC，基于配体的虚拟筛选，结构相似性搜索。化学信息学、药物发现，HPC，基于配体的虚拟筛选，结构相似性搜索。

摘要: For many years the assumption that “Chemical compounds with similar structures may have similar activities” has been a foundation for lead identification. The similarity can be computed based upon topological, steric, electronic, and/or physical properties. The chemical structure similarity search differs from the chemical substructure search in that the former requires assessment of the properties of each compound and thus no filter can be applied for skipping structures before they are assessed to accelerate the computation. The latter can be accelerated by pre-screening compounds and omitting those that miss one (or more) specified fragments from the query. Moreover, three-dimensional similarity search requires superimposing many conformation pairs for each compound in the library. This makes 3-D similarity search algorithms time-consuming, and in general requires high performance computing (HPC) resources. This review will summarize recent progress in the techniques for HPC-supported two and three-dimensional chemical structure similarity search algorithms, and their applications in ligand-based virtual screening.

Cite this article as:

Xin Yan, Chenzhong Liao, Zhihong Liu, Arnold T. Hagler, Qiong Gu, Jun Xu , Chemical Structure Similarity Search for Ligand-based Virtual Screening: Methods and Computational Resources, Current Drug Targets 2016; 17 (14) . https://dx.doi.org/10.2174/1389450116666151102095555