.png){kind=icon}
返回
Efficient iterative virtual screening with Apache Spark and conformal prediction
.png){kind=icon}
OA
AI
DOI：10.1186/s13321-018-0265-z.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Background: Docking and scoring large libraries of ligands against target proteins forms the basis of structure-based virtual screening. The problem is trivially parallelizable, and calculations are generally carried out on computer clusters or on large workstations in a brute force manner, by docking and scoring all available ligands. Contribution: In this study we propose a strategy that is based on iteratively docking a set of ligands to form a training set, training a ligand-based model on this set, and predicting the remainder of the ligands to exclude those predicted as 'low-scoring' ligands. Then, another set of ligands are docked, the model is retrained and the process is repeated until a certain model efficiency level is reached. Thereafter, the remaining ligands are docked or excluded based on this model. We use SVM and conformal prediction to deliver valid prediction intervals for ranking the predicted ligands, and Apache Spark to parallelize both the docking and the modeling. Results: We show on 4 different targets that conformal prediction based virtual screening (CPVS) is able to reduce the number of docked molecules by 62.61% while retaining an accuracy for the top 30 hits of 94% on average and a speedup of 3.7. The implementation is available as open source via GitHub (https://github.com/laeeq80/spark-cpvs) and can be run on high-performance computers as well as on cloud resources.
Keyword:
Virtual screening
Docking
Conformal prediction
Cloud computing
Apache Spark
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
5.7
论文数:
1.5K
被引数:
1.1W
机构
引用论文
Constructing and Validating High-Performance MIEC-SVM Models in Virtual Screening for Kinases: A Better Way for Actives Discovery.png)
SCIENTIFIC REPORTSOAAI
SCIENTIFIC REPORTSIF3.9
OAAI分享收藏Freestanding chemiresistive polymer composite ribbons as high‐flux sensors作为高通量传感器的独立式化学电阻聚合物复合带
PREAI
分享收藏Support vector machine models in drug design: applications to drug transport processes and QSAR using simplex optimisations and variable selectionNEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
分享收藏Discovery of Novel ROCK1 Inhibitors via Integrated Virtual Screening Strategy and BioassaysSCIENTIFIC REPORTSOAAI
SCIENTIFIC REPORTSIF3.9
OAAI分享收藏
查看更多内容