Ringtail: A Python']Python Tool for Efficient Management and Storage of Virtual Screening Results

被引:0
|
作者
Hansel-Harris, Althea T. [1 ]
Santos-Martins, Diogo [1 ]
Bruciaferri, Niccolo [1 ]
Tillack, Andreas F. [1 ]
Holcomb, Matthew [1 ]
Forli, Stefano [1 ]
机构
[1] Scripps Res, Dept Integrat Struct & Computat Biol, La Jolla, CA 92037 USA
基金
美国国家卫生研究院;
关键词
DISCOVERY; DOCKING;
D O I
10.1021/acs.jcim.3c00166
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Virtual screening using molecular docking is now routinely used for the rapid evaluation of very large ligand libraries in early stage drug discovery. As the size of compound libraries which can feasibly be screened grows, so do the challenges in result management and storage. Here we introduce Ringtail, a new Python tool in the AutoDock Suite for efficient storage and analysis of virtual screening data based on portable SQLite databases. Ringtail is designed to work with AutoDock-GPU and AutoDock Vina out-of-the-box. Its modular design also allows for easy extension to support input file types from other docking software, different storage solutions, and incorporation into other applications. Ringtail's SQLite database output can dramatically reduce the required disk storage (36-46 fold) by selecting individual poses to store and by taking advantage of the relational database format. Filtering times are also dramatically reduced, requiring minutes to filter millions of ligands. Thus, Ringtail is a tool that can immediately integrate into existing virtual screening pipelines using AutoDock-GPU and Vina, and is scriptable and modifiable to fit specific user needs.
引用
收藏
页码:1858 / 1864
页数:7
相关论文
共 24 条
  • [1] PyFaults: a Python']Python tool for stacking fault screening
    Combs, Sinclair R.
    Maughan, Annalise E.
    JOURNAL OF APPLIED CRYSTALLOGRAPHY, 2024, 57 : 1996 - 2009
  • [2] PyGOLD: a python']python based API for docking based virtual screening workflow generation
    Patel, Hitesh
    Brinkjost, Tobias
    Koch, Oliver
    BIOINFORMATICS, 2017, 33 (16) : 2589 - 2590
  • [3] Development of a Python']Python tool based on model predictive control for an optimal management of the Calais canal
    Pour, Fatemeh Karimi
    Duviella, Eric
    Segovia, Pablo
    IFAC PAPERSONLINE, 2022, 55 (33): : 1 - 6
  • [4] A Python']Python Tool for Simulation and Optimal Sizing of a Storage Equipped Grid Connected Photovoltaic Power System
    Belloni, Elisa
    Lozito, Gabriele Maria
    Reatti, Alberto
    2022 IEEE 21ST MEDITERRANEAN ELECTROTECHNICAL CONFERENCE (IEEE MELECON 2022), 2022, : 884 - 889
  • [5] Omilayers: a Python']Python package for efficient data management to support multi-omic analysis
    Kioroglou, Dimitrios
    BMC BIOINFORMATICS, 2025, 26 (01):
  • [6] MPInterfaces: A Materials Project based Python']Python tool for high-throughput computational screening of interfacial systems
    Mathew, Kiran
    Singh, Arunima K.
    Gabriel, Joshua J.
    Choudhary, Kamal
    Sinnott, Susan B.
    Davydov, Albert V.
    Tavazza, Francesca
    Hennig, Richard G.
    COMPUTATIONAL MATERIALS SCIENCE, 2016, 122 : 183 - 190
  • [7] easySCF: a tool for enhancing interoperability between R and Python']Python for efficient single-cell data analysis
    Zhang, Haoyun
    Zhang, Wentao
    Zhao, Shuai
    Xu, Guangyu
    Shen, Yi
    Jiang, Feng
    Qin, An
    Cui, Lei
    BIOINFORMATICS, 2024, 40 (12)
  • [8] ViSAPy: A Python']Python tool for biophysics-based generation of virtual spiking activity for evaluation of spike-sorting algorithms
    Hagen, Espen
    Ness, Torbjorn V.
    Khosrowshahi, Amir
    Sorensen, Christina
    Fyhn, Marianne
    Hafting, Torkel
    Franke, Felix
    Einevoll, Gaute T.
    JOURNAL OF NEUROSCIENCE METHODS, 2015, 245 : 182 - 204
  • [9] MUBD-DecoyMaker 2.0: A Python']Python GUI Application to Generate Maximal Unbiased Benchmarking Data Sets for Virtual Drug Screening
    Xia, Jie
    Li, Shan
    Ding, Yu
    Wu, Song
    Wang, Xiang Simon
    MOLECULAR INFORMATICS, 2020, 39 (04)
  • [10] An efficient and user-friendly software tool for ordered multi-class receiver operating characteristic analysis based on python']python
    Liu, Shun
    Yang, Junjie
    Zeng, Xianxian
    Song, Haiying
    Cen, Jian
    Xu, Weichao
    SOFTWAREX, 2022, 19