Ultra-large library docking for ligand discovery
用于配体发现的超大文库对接
基本信息
- 批准号:10240701
- 负责人:
- 金额:$ 38.93万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-09-27 至 2023-08-31
- 项目状态:已结题
- 来源:
- 关键词:3-DimensionalAffinityAgonistBinding SitesBiologicalBiologyChargeChemicalsCommunitiesComputersCrystallographyDNADatabasesDockingDopamineDopamine ReceptorEnsureG-Protein-Coupled ReceptorsGrowthHydrophobicityIndividualInfrastructureJointsLeadLettersLibrariesLigandsMeasuresMethodsMolecularMorphologic artifactsOpioidOutcomePlanetsReactionResortTestingWorkbasechemical synthesiscombinatorial chemistrycomputing resourcesconformercostinnovationinterestkappa opioid receptorsnovelreceptorscaffoldsmall moleculesuccessthree dimensional structuretoolvirtual library
项目摘要
PROJECT SUMMARY / ABSTRACT
Despite much interest in expanding chemical space, diverse, billion molecule libraries remain inaccessible. In
principle, docking a virtual library could access some of this missing chemical space. This idea has until now
been vitiated by two key problems: 1. prediction of readily synthesized molecules has been challenging, without
resorting to strategies that collapse diversity; and 2. docking is notoriously inaccurate. Two recent advances
have made virtual library docking screens seem less fanciful. First, our collaborators at Enamine, a widely used
fine chemicals supplier, have defined a 0.7 billion molecule make-on-demand library based on >100 reactions
that they have under good control; >650,000 of these have been successfully synthesized. Second, while
docking retains serious errors, it has made pragmatic progress, and has found genuinely novel ligands for >100
targets. The specific aims are:
Aim 1. A robust, searchable, and dockable database of 3 billion diverse lead-like molecules. We will A.
Enumerate 3 billion vetted products from two- and three-component reactions. B. measure the diversity and
novelty of this library and how they differ from the world's in-stock molecules. C. Develop a community accessible
database and chemoinformatics infrastructure that can store, similarity search, and rapidly retrieve molecules
from this library. D. convert these molecules into biologically relevant 3D forms, including enumerating low-
energy conformers, partial atomic charges and other parameters, van der Waals parameters and solvation
energies for all library molecules, enabling their use for docking screens.
Aim 2. Dock and experimentally test the library against two targets. A. Screen the library against the dopamine
D4 and kappa-opioid receptors, seeking novel ligands. 250 to 500 library molecules will be tested per screen,
itself a 10-fold increase. A key question will be do we find novel, potent ligands, or are we overwhelmed by false
positives? B. As the library grows, do we continue to find ever more novel, in some sense ever more perfect,
high affinity ligands, or does discovery saturate? C. How does hit rate vary with docking score? As we will be
testing hundreds of molecules, we can afford to investigate not only those with the highest docking ranks, but
also molecules with mediocre and poor ranks. This has not been previously explored, certainly not at scale.
If successful, this project will increase the number of molecules available to the community by 1000-fold, and
demonstrate their utility for ligand discovery. Extensive preliminary results support its feasibility.
项目摘要/摘要
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
John J. Irwin其他文献
Docking for molecules that bind in a symmetric stack to Alzheimer’s disease tau fibrils with SymDOCK
- DOI:
10.1016/j.bpj.2023.11.1855 - 发表时间:
2024-02-08 - 期刊:
- 影响因子:
- 作者:
Matthew S. Smith;Peter Kunach;Ian S. Knight;Rian Kormos;Joseph G. Pepe;Isabella Glenn;John J. Irwin;William F. DeGrado;Marc I. Diamond;Sarah H. Shahmoradian;Brian K. Shoichet - 通讯作者:
Brian K. Shoichet
The impact of library size and scale of testing on virtual screening
图书馆规模和测试规模对虚拟筛选的影响
- DOI:
10.1038/s41589-024-01797-w - 发表时间:
2025-01-03 - 期刊:
- 影响因子:13.700
- 作者:
Fangyu Liu;Olivier Mailhot;Isabella S. Glenn;Seth F. Vigneron;Violla Bassim;Xinyu Xu;Karla Fonseca-Valencia;Matthew S. Smith;Dmytro S. Radchenko;James S. Fraser;Yurii S. Moroz;John J. Irwin;Brian K. Shoichet - 通讯作者:
Brian K. Shoichet
Modeling the expansion of virtual screening libraries
对虚拟筛选库的扩展进行建模
- DOI:
10.1038/s41589-022-01234-w - 发表时间:
2023-01-16 - 期刊:
- 影响因子:13.700
- 作者:
Jiankun Lyu;John J. Irwin;Brian K. Shoichet - 通讯作者:
Brian K. Shoichet
Virtual library docking for cannabinoid-1 receptor agonists with reduced side effects
具有减少副作用的大麻素 1 受体激动剂的虚拟库对接
- DOI:
10.1038/s41467-025-57136-7 - 发表时间:
2025-03-06 - 期刊:
- 影响因子:15.700
- 作者:
Tia A. Tummino;Christos Iliopoulos-Tsoutsouvas;Joao M. Braz;Evan S. O’Brien;Reed M. Stein;Veronica Craik;Ngan K. Tran;Suthakar Ganapathy;Fangyu Liu;Yuki Shiimura;Fei Tong;Thanh C. Ho;Dmytro S. Radchenko;Yurii S. Moroz;Sian Rodriguez Rosado;Karnika Bhardwaj;Jorge Benitez;Yongfeng Liu;Herthana Kandasamy;Claire Normand;Meriem Semache;Laurent Sabbagh;Isabella Glenn;John J. Irwin;Kaavya Krishna Kumar;Alexandros Makriyannis;Allan I. Basbaum;Brian K. Shoichet - 通讯作者:
Brian K. Shoichet
John J. Irwin的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('John J. Irwin', 18)}}的其他基金
Ultra-large library docking for ligand discovery
用于配体发现的超大文库对接
- 批准号:
10473611 - 财政年份:2019
- 资助金额:
$ 38.93万 - 项目类别:
Ultra-large library docking for ligand discovery
用于配体发现的超大文库对接
- 批准号:
10023266 - 财政年份:2019
- 资助金额:
$ 38.93万 - 项目类别:
Ultra-large library docking for ligand discovery
用于配体发现的超大文库对接
- 批准号:
9797487 - 财政年份:2019
- 资助金额:
$ 38.93万 - 项目类别:
A Web-Based Automatic Virtual Screening System
基于网络的自动虚拟筛选系统
- 批准号:
10297015 - 财政年份:2004
- 资助金额:
$ 38.93万 - 项目类别:
A Web-Based Automatic Virtual Screening System
基于网络的自动虚拟筛选系统
- 批准号:
10612058 - 财政年份:2004
- 资助金额:
$ 38.93万 - 项目类别:
A Web-Based Automatic Virtual Screening System
基于网络的自动虚拟筛选系统
- 批准号:
10434959 - 财政年份:2004
- 资助金额:
$ 38.93万 - 项目类别:
相似海外基金
Discovery of a High Affinity, Selective and β-arrestin Biased 5-HT7R Agonist
发现高亲和力、选择性和β-抑制蛋白偏向的 5-HT7R 激动剂
- 批准号:
10412227 - 财政年份:2022
- 资助金额:
$ 38.93万 - 项目类别:
Discovery of a High Affinity, Selective and β-arrestin Biased 5-HT7R Agonist
发现高亲和力、选择性和β-抑制蛋白偏向的 5-HT7R 激动剂
- 批准号:
10610473 - 财政年份:2022
- 资助金额:
$ 38.93万 - 项目类别:
Supplement to Discovery of a high affinity, selective and beta-arrestinbiased 5-HT7R Agonist Grant
对高亲和力、选择性和 β 抑制偏向 5-HT7R 激动剂发现的补充补助金
- 批准号:
10799162 - 财政年份:2022
- 资助金额:
$ 38.93万 - 项目类别:
NMDA RECEPTOR--AGONIST AFFINITY, EFFICACY/TRANSDUCTION
NMDA 受体——激动剂亲和力、功效/转导
- 批准号:
6639179 - 财政年份:2001
- 资助金额:
$ 38.93万 - 项目类别:
NMDA RECEPTOR--AGONIST AFFINITY, EFFICACY/TRANSDUCTION
NMDA 受体——激动剂亲和力、功效/转导
- 批准号:
6724797 - 财政年份:2001
- 资助金额:
$ 38.93万 - 项目类别:
General Anesthetics and nAcCHOR Agonist Affinity
全身麻醉药和 nAcCHOR 激动剂亲和力
- 批准号:
6636512 - 财政年份:2001
- 资助金额:
$ 38.93万 - 项目类别:
NMDA RECEPTOR--AGONIST AFFINITY, EFFICACY/TRANSDUCTION
NMDA 受体——激动剂亲和力、功效/转导
- 批准号:
6266928 - 财政年份:2001
- 资助金额:
$ 38.93万 - 项目类别:
NMDA RECEPTOR--AGONIST AFFINITY, EFFICACY/TRANSDUCTION
NMDA 受体——激动剂亲和力、功效/转导
- 批准号:
6539099 - 财政年份:2001
- 资助金额:
$ 38.93万 - 项目类别:
General Anesthetics and nAcCHOR Agonist Affinity
全身麻醉药和 nAcCHOR 激动剂亲和力
- 批准号:
6326889 - 财政年份:2001
- 资助金额:
$ 38.93万 - 项目类别:
General Anesthetics and nAcCHOR Agonist Affinity
全身麻醉药和 nAcCHOR 激动剂亲和力
- 批准号:
6520329 - 财政年份:2001
- 资助金额:
$ 38.93万 - 项目类别: