An open-source drug discovery platform enables ultra-large virtual screens

开源 药物发现 计算机科学 药品 计算生物学 生物信息学 软件 生物 操作系统 药理学
作者
Christoph Gorgulla,Andras Boeszoermenyi,Zifu Wang,Patrick D. Fischer,Paul Coote,Krishna Mohan Das,Yehor S. Malets,Dmytro S. Radchenko,Yurii S. Moroz,David A. Scott,Konstantin Fackeldey,Moritz Hoffmann,Iryna Iavniuk,Gerhard Wagner,Haribabu Arthanari
出处
期刊:Nature [Springer Nature]
卷期号:580 (7805): 663-668 被引量:592
标识
DOI:10.1038/s41586-020-2117-z
摘要

On average, an approved drug currently costs US$2–3 billion and takes more than 10 years to develop1. In part, this is due to expensive and time-consuming wet-laboratory experiments, poor initial hit compounds and the high attrition rates in the (pre-)clinical phases. Structure-based virtual screening has the potential to mitigate these problems. With structure-based virtual screening, the quality of the hits improves with the number of compounds screened2. However, despite the fact that large databases of compounds exist, the ability to carry out large-scale structure-based virtual screening on computer clusters in an accessible, efficient and flexible manner has remained difficult. Here we describe VirtualFlow, a highly automated and versatile open-source platform with perfect scaling behaviour that is able to prepare and efficiently screen ultra-large libraries of compounds. VirtualFlow is able to use a variety of the most powerful docking programs. Using VirtualFlow, we prepared one of the largest and freely available ready-to-dock ligand libraries, with more than 1.4 billion commercially available molecules. To demonstrate the power of VirtualFlow, we screened more than 1 billion compounds and identified a set of structurally diverse molecules that bind to KEAP1 with submicromolar affinity. One of the lead inhibitors (iKeap1) engages KEAP1 with nanomolar affinity (dissociation constant (Kd) = 114 nM) and disrupts the interaction between KEAP1 and the transcription factor NRF2. This illustrates the potential of VirtualFlow to access vast regions of the chemical space and identify molecules that bind with high affinity to target proteins. VirtualFlow, an open-source drug discovery platform, enables the efficient preparation and virtual screening of ultra-large ligand libraries to identify molecules that bind with high affinity to target proteins.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
碧蓝贞完成签到,获得积分10
刚刚
Orange应助FUJIE采纳,获得10
刚刚
kove0928完成签到,获得积分10
刚刚
赵妍驳回了思源应助
刚刚
刚刚
1秒前
李爱国应助南北采纳,获得10
2秒前
量子星尘发布了新的文献求助10
3秒前
Hofer完成签到 ,获得积分20
3秒前
彭于晏应助蔚蓝采纳,获得10
3秒前
JamesPei应助somous采纳,获得10
4秒前
机智的觅风发布了新的文献求助100
5秒前
sea完成签到 ,获得积分10
5秒前
海棠先雪完成签到,获得积分10
6秒前
6秒前
香草可樂发布了新的文献求助10
6秒前
哈哈哈完成签到,获得积分10
6秒前
阿微发布了新的文献求助10
7秒前
秒文献是一种天赋完成签到 ,获得积分10
7秒前
yyyyy发布了新的文献求助10
8秒前
mark完成签到,获得积分10
8秒前
HRC发布了新的文献求助10
8秒前
酷波er应助醉眠采纳,获得10
9秒前
赘婿应助yyy采纳,获得10
10秒前
10秒前
10秒前
11秒前
学术小鱼关注了科研通微信公众号
11秒前
zhonglv7应助常乐采纳,获得10
11秒前
西门如豹发布了新的文献求助10
12秒前
Orange应助美丽采纳,获得10
12秒前
深情安青应助浚稚采纳,获得10
13秒前
xww完成签到,获得积分10
13秒前
棺姬发布了新的文献求助10
13秒前
所所应助MUWENYING采纳,获得10
13秒前
ldx完成签到,获得积分10
16秒前
cw完成签到 ,获得积分10
16秒前
16秒前
xxx发布了新的文献求助10
16秒前
大个应助jc哥采纳,获得10
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Iron toxicity and hematopoietic cell transplantation: do we understand why iron affects transplant outcome? 2000
List of 1,091 Public Pension Profiles by Region 1021
Teacher Wellbeing: Noticing, Nurturing, Sustaining, and Flourishing in Schools 800
Efficacy of sirolimus in Klippel-Trenaunay syndrome 500
上海破产法庭破产实务案例精选(2019-2024) 500
EEG in Childhood Epilepsy: Initial Presentation & Long-Term Follow-Up 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5478095
求助须知:如何正确求助?哪些是违规求助? 4579824
关于积分的说明 14371025
捐赠科研通 4508054
什么是DOI,文献DOI怎么找? 2470401
邀请新用户注册赠送积分活动 1457273
关于科研通互助平台的介绍 1431249