已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

De novo designed proteins neutralize lethal snake venom toxins

抗蛇毒血清 毒液 蛇毒 多克隆抗体 神经毒素 生物 计算生物学 药理学 抗体 医学 毒理 免疫学 生物化学
作者
David Baker,Susana Vázquez Torres,Melisa Benard Valle,Stephen P. Mackessy,Stefanie K. Menzies,Nicholas R. Casewell,Shirin Ahmadi,Nick J. Burlet,Edin Muratspahić,Isaac Sappington,Max D. Overath,Esperanza Rivera‐de‐Torre,Jann Ledergerber,Andreas H. Laustsen,Kim Boddum,Asim K. Bera,Alex Kang,Evans Brackenbrough,Iara Aimê Cardoso,Edouard Crittenden
出处
期刊:Research Square - Research Square 被引量:3
标识
DOI:10.21203/rs.3.rs-4402792/v1
摘要

Abstract Snakebite envenoming remains a devastating and neglected tropical disease, claiming over 100,000 lives annually and causing severe complications and long-lasting disabilities for many more1,2. Three-finger toxins (3FTx) are highly toxic components of elapid snake venoms that can cause diverse pathologies, including severe tissue damage3 and inhibition of nicotinic acetylcholine receptors (nAChRs) resulting in life-threatening neurotoxicity4. Currently, the only available treatments for snakebite consist of polyclonal antibodies derived from the plasma of immunized animals, which have high cost and limited efficacy against 3FTxs5,6,7. Here, we use deep learning methods to de novo design proteins to bind short- and long-chain α-neurotoxins and cytotoxins from the 3FTx family. With limited experimental screening, we obtain protein designs with remarkable thermal stability, high binding affinity, and near-atomic level agreement with the computational models. The designed proteins effectively neutralize all three 3FTx sub-families in vitro and protect mice from a lethal neurotoxin challenge. Such potent, stable, and readily manufacturable toxin-neutralizing proteins could provide the basis for safer, cost-effective, and widely accessible next-generation antivenom therapeutics. Beyond snakebite, our computational design methodology should help democratize therapeutic discovery, particularly in resource-limited settings, by substantially reducing costs and resource requirements for development of therapies to neglected tropical diseases
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
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
郑哲楷完成签到,获得积分10
1秒前
望TIAN完成签到,获得积分10
2秒前
爆米花应助ssk采纳,获得10
2秒前
栀晴完成签到 ,获得积分10
3秒前
5秒前
Yyyyyyyyy发布了新的文献求助10
5秒前
6秒前
小小完成签到,获得积分10
7秒前
tRNA完成签到 ,获得积分10
8秒前
顾矜应助Ryy采纳,获得10
8秒前
文静皮卡丘完成签到,获得积分10
9秒前
CodeCraft应助fatdudu采纳,获得10
9秒前
jixuzhuixun完成签到 ,获得积分10
9秒前
今后应助fortune采纳,获得10
11秒前
12秒前
烬然然发布了新的文献求助10
13秒前
隐形曼青应助yunjian1583采纳,获得10
13秒前
14秒前
HEIKU应助林狗采纳,获得10
14秒前
16秒前
云人类发布了新的文献求助30
17秒前
17秒前
研友_LjDyNZ发布了新的文献求助10
18秒前
18秒前
似画完成签到 ,获得积分10
19秒前
李某完成签到 ,获得积分10
20秒前
ssk发布了新的文献求助10
23秒前
烟花应助Yyyyyyyyy采纳,获得10
25秒前
火星上的摩托完成签到 ,获得积分10
29秒前
qcl发布了新的文献求助10
31秒前
HEIKU应助林狗采纳,获得10
31秒前
35秒前
lixia完成签到 ,获得积分10
35秒前
漂亮的雁露完成签到,获得积分20
38秒前
39秒前
starry完成签到,获得积分10
39秒前
悦耳的亦旋完成签到,获得积分10
40秒前
SYLH应助LLL采纳,获得10
40秒前
称心曼安应助LLL采纳,获得10
40秒前
润润润发布了新的文献求助80
41秒前
高分求助中
Technologies supporting mass customization of apparel: A pilot project 600
Izeltabart tapatansine - AdisInsight 500
Chinesen in Europa – Europäer in China: Journalisten, Spione, Studenten 500
Arthur Ewert: A Life for the Comintern 500
China's Relations With Japan 1945-83: The Role of Liao Chengzhi // Kurt Werner Radtke 500
Two Years in Peking 1965-1966: Book 1: Living and Teaching in Mao's China // Reginald Hunt 500
Epigenetic Drug Discovery 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 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3815420
求助须知:如何正确求助?哪些是违规求助? 3359189
关于积分的说明 10400678
捐赠科研通 3076839
什么是DOI,文献DOI怎么找? 1690041
邀请新用户注册赠送积分活动 813577
科研通“疑难数据库(出版商)”最低求助积分说明 767674