Allosteric Binding Sites of the SARS-CoV-2 Main Protease: Potential Targets for Broad-Spectrum Anti-Coronavirus Agents

变构调节 可药性 药物发现 冠状病毒 2019年冠状病毒病(COVID-19) 严重急性呼吸综合征冠状病毒2型(SARS-CoV-2) 蛋白酶 计算生物学 化学 生物 生物化学 医学 疾病 传染病(医学专业) 基因 病理
作者
Lara Alzyoud,Mohammad A. Ghattas,Noor Atatreh
出处
期刊:Drug Design Development and Therapy [Dove Medical Press]
卷期号:Volume 16: 2463-2478 被引量:17
标识
DOI:10.2147/dddt.s370574
摘要

Abstract: The current pandemic caused by the COVID-19 disease has reached everywhere in the world and has affected every aspect of our lives. As of the current data, the World Health Organization (WHO) has reported more than 300 million confirmed COVID-19 cases worldwide and more than 5 million deaths. M pro is an enzyme that plays a key role in the life cycle of the SARS-CoV-2 virus, and it is vital for the disease progression. The M pro enzyme seems to have several allosteric sites that can hinder the enzyme catalytic activity. Furthermore, some of these allosteric sites are located at or nearby the dimerization interface which is essential for the overall M pro activity. In this review paper, we investigate the potential of the M pro allosteric site to act as a drug target, especially since they interestingly appear to be resistant to mutation. The work is illustrated through three subsequent sections: First, the two main categories of M pro allosteric sites have been explained and discussed. Second, a total of six pockets have been studied and evaluated for their druggability and cavity characteristics. Third, the experimental and computational attempts for the discovery of new allosteric inhibitors have been illustrated and discussed. To sum up, this review paper gives a detailed insight into the feasibility of developing new M pro inhibitors to act as a potential treatment for the COVID-19 disease. Graphical Abstract: Keywords: COVID-19, M pro , SARS-CoV-2, allosteric sites, druggability, antiviral
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
星辰大海应助qiyumeng采纳,获得10
2秒前
自由山槐发布了新的文献求助10
3秒前
酷酷薯片发布了新的文献求助10
3秒前
Zg8279发布了新的文献求助50
4秒前
量子星尘发布了新的文献求助10
6秒前
活泼的飞双完成签到,获得积分10
7秒前
8秒前
从容的子轩完成签到,获得积分10
8秒前
英俊的铭应助janan33采纳,获得10
8秒前
9秒前
10秒前
嘟嘟喂嘟嘟应助收声采纳,获得10
11秒前
11秒前
Re发布了新的文献求助10
13秒前
13秒前
NexusExplorer应助无辜紫菜采纳,获得10
13秒前
今后应助灰灰采纳,获得10
14秒前
14秒前
15秒前
16秒前
陈丽陈丽完成签到,获得积分10
16秒前
17秒前
18秒前
LL完成签到,获得积分10
19秒前
小潘同学发布了新的文献求助10
20秒前
落寞丹萱发布了新的文献求助10
20秒前
wschenau应助Re采纳,获得10
21秒前
螃螃发布了新的文献求助10
21秒前
loki完成签到,获得积分10
21秒前
z落水无痕发布了新的文献求助10
21秒前
夕夜蟹完成签到,获得积分10
22秒前
22秒前
mu发布了新的文献求助10
23秒前
CodeCraft应助落寞丹萱采纳,获得10
24秒前
明理念桃发布了新的文献求助10
26秒前
Jasper应助小白采纳,获得10
27秒前
微笑的觅露完成签到 ,获得积分10
27秒前
隐形曼青应助研友_VZG64n采纳,获得10
27秒前
JINGTAO发布了新的文献求助10
27秒前
28秒前
高分求助中
【提示信息,请勿应助】关于scihub 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 3000
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
徐淮辽南地区新元古代叠层石及生物地层 2000
A new approach to the extrapolation of accelerated life test data 1000
Robot-supported joining of reinforcement textiles with one-sided sewing heads 400
北师大毕业论文 基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 390
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 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4024340
求助须知:如何正确求助?哪些是违规求助? 3564210
关于积分的说明 11344678
捐赠科研通 3295369
什么是DOI,文献DOI怎么找? 1815104
邀请新用户注册赠送积分活动 889673
科研通“疑难数据库(出版商)”最低求助积分说明 813097