• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

文库大小和测试规模对虚拟筛选的影响。

The impact of library size and scale of testing on virtual screening.

作者信息

Liu Fangyu, Mailhot Olivier, Glenn Isabella S, Vigneron Seth F, Bassim Violla, Xu Xinyu, Fonseca-Valencia Karla, Smith Matthew S, Radchenko Dmytro S, Fraser James S, Moroz Yurii S, Irwin John J, Shoichet Brian K

机构信息

Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA.

Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA.

出版信息

Nat Chem Biol. 2025 Jan 3. doi: 10.1038/s41589-024-01797-w.

DOI:10.1038/s41589-024-01797-w
PMID:39753705
Abstract

Virtual ligand libraries for ligand discovery have recently increased 10,000-fold. Whether this has improved hit rates and potencies has not been directly tested. Meanwhile, typically only dozens of docking hits are assayed, clouding hit-rate interpretation. Here we docked a 1.7 billion-molecule virtual library against β-lactamase, testing 1,521 new molecules and comparing the results to a 99 million-molecule screen where 44 molecules were tested. In a larger screen, hit rates improved twofold, more scaffolds were discovered and potency improved. Fifty-fold more inhibitors were found, supporting the idea that the large libraries harbor many more ligands than are being tested. In sampling smaller sets from the 1,521, hit rates only converged when several hundred molecules were tested. Hit rates and affinities improved steadily with docking score. It may be that as the scale of docking libraries and their testing grows, both ligands and our ability to rank them will improve.

摘要

用于配体发现的虚拟配体库最近增加到了原来的10000倍。这是否提高了命中率和效力尚未得到直接验证。与此同时,通常只对几十种对接命中物进行检测,这使得命中率的解读变得模糊。在此,我们针对β-内酰胺酶对接了一个包含17亿个分子的虚拟库,测试了1521个新分子,并将结果与一个包含9900万个分子的筛选结果进行比较,后者测试了44个分子。在更大规模的筛选中,命中率提高了两倍,发现了更多的支架结构,效力也有所提高。发现的抑制剂数量增加了50倍,这支持了这样一种观点,即大型库中含有的配体比正在测试的要多得多。从1521个分子中抽取较小的样本集时,只有在测试了几百个分子后,命中率才会趋于一致。命中率和亲和力随着对接分数的提高而稳步提升。随着对接库规模及其测试规模的扩大,配体以及我们对它们进行排序的能力可能都会得到提升。

相似文献

1
The impact of library size and scale of testing on virtual screening.文库大小和测试规模对虚拟筛选的影响。
Nat Chem Biol. 2025 Jan 3. doi: 10.1038/s41589-024-01797-w.
2
The impact of Library Size and Scale of Testing on Virtual Screening.文库大小和测试规模对虚拟筛选的影响。
bioRxiv. 2024 Jul 11:2024.07.08.602536. doi: 10.1101/2024.07.08.602536.
3
Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.系统性药理学治疗慢性斑块状银屑病:网络荟萃分析。
Cochrane Database Syst Rev. 2021 Apr 19;4(4):CD011535. doi: 10.1002/14651858.CD011535.pub4.
4
Systemic treatments for metastatic cutaneous melanoma.转移性皮肤黑色素瘤的全身治疗
Cochrane Database Syst Rev. 2018 Feb 6;2(2):CD011123. doi: 10.1002/14651858.CD011123.pub2.
5
Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.慢性斑块状银屑病的全身药理学治疗:一项网状Meta分析。
Cochrane Database Syst Rev. 2020 Jan 9;1(1):CD011535. doi: 10.1002/14651858.CD011535.pub3.
6
Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.慢性斑块状银屑病的全身药理学治疗:一项网状荟萃分析。
Cochrane Database Syst Rev. 2017 Dec 22;12(12):CD011535. doi: 10.1002/14651858.CD011535.pub2.
7
An artificial intelligence accelerated virtual screening platform for drug discovery.人工智能加速药物发现的虚拟筛选平台。
Nat Commun. 2024 Sep 5;15(1):7761. doi: 10.1038/s41467-024-52061-7.
8
Home treatment for mental health problems: a systematic review.心理健康问题的居家治疗:一项系统综述
Health Technol Assess. 2001;5(15):1-139. doi: 10.3310/hta5150.
9
A rapid and systematic review of the clinical effectiveness and cost-effectiveness of paclitaxel, docetaxel, gemcitabine and vinorelbine in non-small-cell lung cancer.对紫杉醇、多西他赛、吉西他滨和长春瑞滨在非小细胞肺癌中的临床疗效和成本效益进行的快速系统评价。
Health Technol Assess. 2001;5(32):1-195. doi: 10.3310/hta5320.
10
Exploring Type II Diabetes Inhibitors from Genus Daphne Plant-species: An Integrated Computational Study.探索瑞香属植物物种中的II型糖尿病抑制剂:一项综合计算研究。
Comb Chem High Throughput Screen. 2025;28(8):1413-1442. doi: 10.2174/0113862073262227231005074024.

引用本文的文献

1
Qsarna: An Online Tool for Smart Chemical Space Navigation in Drug Design.Qsarna:药物设计中智能化学空间导航的在线工具。
J Chem Inf Model. 2025 Aug 11;65(15):7811-7816. doi: 10.1021/acs.jcim.5c00720. Epub 2025 Jul 29.
2
Docking 14 Million Virtual Isoquinuclidines against the μ and κ Opioid Receptors Reveals Dual Antagonists-Inverse Agonists with Reduced Withdrawal Effects.针对μ和κ阿片受体对接1400万个虚拟异喹核碱,发现具有减轻戒断效应的双重拮抗剂 - 反向激动剂。
ACS Cent Sci. 2025 Apr 29;11(5):770-790. doi: 10.1021/acscentsci.5c00052. eCollection 2025 May 28.
3
Cross-disciplinary perspectives on the potential for artificial intelligence across chemistry.

本文引用的文献

1
Identifying Artifacts from Large Library Docking.从大型库对接中识别伪影。
J Med Chem. 2024 Sep 26;67(18):16796-16806. doi: 10.1021/acs.jmedchem.4c01632. Epub 2024 Sep 10.
2
Thompson Sampling─An Efficient Method for Searching Ultralarge Synthesis on Demand Databases.Thompson 抽样─一种高效的按需搜索超大规模合成数据库的方法。
J Chem Inf Model. 2024 Feb 26;64(4):1158-1171. doi: 10.1021/acs.jcim.3c01790. Epub 2024 Feb 5.
3
Docking for EP4R antagonists active against inflammatory pain.针对炎症性疼痛的 EP4R 拮抗剂的对接。
关于人工智能在化学领域潜力的跨学科观点。
Chem Soc Rev. 2025 Apr 25. doi: 10.1039/d5cs00146c.
4
A Database for Large-Scale Docking and Experimental Results.一个用于大规模对接和实验结果的数据库。
J Chem Inf Model. 2025 May 12;65(9):4458-4467. doi: 10.1021/acs.jcim.5c00394. Epub 2025 Apr 24.
5
A database for large-scale docking and experimental results.一个用于大规模对接和实验结果的数据库。
bioRxiv. 2025 Feb 27:2025.02.25.639879. doi: 10.1101/2025.02.25.639879.
6
Docking 14 million virtual isoquinuclidines against the mu and kappa opioid receptors reveals dual antagonists-inverse agonists with reduced withdrawal effects.将1400万个虚拟异喹核碱与μ和κ阿片受体进行对接,发现了具有降低戒断效应的双重拮抗剂-反向激动剂。
bioRxiv. 2025 Jan 14:2025.01.09.632033. doi: 10.1101/2025.01.09.632033.
7
Identifying Artifacts from Large Library Docking.从大型库对接中识别伪影。
J Med Chem. 2024 Sep 26;67(18):16796-16806. doi: 10.1021/acs.jmedchem.4c01632. Epub 2024 Sep 10.
Nat Commun. 2023 Dec 6;14(1):8067. doi: 10.1038/s41467-023-43506-6.
4
Structure-based discovery of conformationally selective inhibitors of the serotonin transporter.基于结构的 5-羟色胺转运体构象选择性抑制剂的发现。
Cell. 2023 May 11;186(10):2160-2175.e17. doi: 10.1016/j.cell.2023.04.010. Epub 2023 May 2.
5
Computational approaches streamlining drug discovery.计算方法简化药物发现。
Nature. 2023 Apr;616(7958):673-685. doi: 10.1038/s41586-023-05905-z. Epub 2023 Apr 26.
6
ZINC-22─A Free Multi-Billion-Scale Database of Tangible Compounds for Ligand Discovery.ZINC-22─一个免费的、数十亿规模的有形化合物数据库,用于配体发现。
J Chem Inf Model. 2023 Feb 27;63(4):1166-1176. doi: 10.1021/acs.jcim.2c01253. Epub 2023 Feb 15.
7
Modeling the expansion of virtual screening libraries.建立虚拟筛选库的扩展模型。
Nat Chem Biol. 2023 Jun;19(6):712-718. doi: 10.1038/s41589-022-01234-w. Epub 2023 Jan 16.
8
Structure-based discovery of nonopioid analgesics acting through the α-adrenergic receptor.基于结构的非阿片类镇痛药通过 α-肾上腺素能受体作用的发现。
Science. 2022 Sep 30;377(6614):eabn7065. doi: 10.1126/science.abn7065.
9
Prioritizing Virtual Screening with Interpretable Interaction Fingerprints.基于可解释相互作用指纹的虚拟筛选优先级排序。
J Chem Inf Model. 2022 Sep 26;62(18):4300-4318. doi: 10.1021/acs.jcim.2c00695. Epub 2022 Sep 14.
10
CACHE (Critical Assessment of Computational Hit-finding Experiments): A public-private partnership benchmarking initiative to enable the development of computational methods for hit-finding.CACHE(计算命中发现实验的批判性评估):一项公私合作的基准测试计划,旨在推动用于命中发现的计算方法的开发。
Nat Rev Chem. 2022 Apr;6(4):287-295. doi: 10.1038/s41570-022-00363-z. Epub 2022 Feb 15.