Advances in the understanding of protein misfolding and aggregation through molecular dynamics simulation

蛋白质折叠 蛋白质聚集 淀粉样纤维 计算生物学 分子动力学 淀粉样蛋白(真菌学) 折叠(DSP实现) 功能(生物学) 亨廷顿蛋白 化学 生物 淀粉样β 生物化学 医学 细胞生物学 疾病 基因 工程类 电气工程 病理 突变体 无机化学 计算化学
作者
Aziza Rahman,Bondeepa Saikia,Chimi Rekha Gogoi,Anupaul Baruah
出处
期刊:Progress in Biophysics & Molecular Biology [Elsevier]
卷期号:175: 31-48 被引量:38
标识
DOI:10.1016/j.pbiomolbio.2022.08.007
摘要

Aberrant protein folding known as protein misfolding is counted as one of the striking factors of neurodegenerative diseases. The extensive range of pathologies caused by protein misfolding, aggregation and subsequent accumulation are mainly classified into either gain of function diseases or loss of function diseases. In order to seek for novel strategies for treatment and diagnosis of neurodegenerative diseases, insights into the mechanism of misfolding and aggregation is essential. A comprehensive knowledge on the factors influencing misfolding and aggregation is required as well. An extensive experimental study on protein aggregation is somewhat challenging due the insoluble and noncrystalline nature of amyloid fibrils. Thus there has been a growing use of computational approaches including Thermodynamic Integration, Monte Carlo simulation, docking simulation, Molecular dynamics simulation in the study of protein misfolding and aggregation. The review presents a discussion on molecular dynamics simulation alone as to how it has emerged as a promising tool in the understanding of protein misfolding and aggregation in general, detailing upon three different aspects considering four misfold prone proteins in particular. It is noticeable that all four proteins considered in this review i.e prion, superoxide dismutase1, Huntingtin and Amyloid beta are linked to chronic neurodegenerative diseases with debilitating effects. Initially the review elaborates on the factors influencing the misfolding and aggregation. Next, it addresses our current understanding of the amyloid structures and the associated aggregation mechanisms, finally, summarizing the contribution of this computational tool in the search for therapeutic strategies against the respective protein-deposition 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
111完成签到,获得积分10
刚刚
刚刚
哈哈发布了新的文献求助10
1秒前
酷酷菲音完成签到,获得积分10
1秒前
深情紫菜发布了新的文献求助10
1秒前
秋菜菜完成签到,获得积分10
1秒前
xiaoxiao完成签到,获得积分10
2秒前
2秒前
2秒前
2秒前
2秒前
MI完成签到,获得积分10
3秒前
可爱的函函应助阳光土豆采纳,获得30
3秒前
执着的千万完成签到,获得积分10
3秒前
七li发布了新的文献求助10
4秒前
潇潇完成签到,获得积分10
4秒前
认真的小刺猬完成签到,获得积分10
4秒前
慎独579发布了新的文献求助10
4秒前
5秒前
静听松风寒完成签到 ,获得积分10
6秒前
Matrix发布了新的文献求助10
6秒前
7秒前
哇哦发布了新的文献求助10
7秒前
高镜涵发布了新的文献求助10
7秒前
JK157发布了新的文献求助10
7秒前
offred完成签到,获得积分10
7秒前
桐桐应助Axuan采纳,获得10
7秒前
chenhouhan发布了新的文献求助10
7秒前
大模型应助褚友菱采纳,获得10
8秒前
8秒前
斯文败类应助taozi采纳,获得30
8秒前
田様应助明芬采纳,获得10
8秒前
Mason完成签到 ,获得积分10
9秒前
9秒前
9秒前
9秒前
慕青应助YuuuY采纳,获得10
10秒前
量子星尘发布了新的文献求助10
10秒前
LI发布了新的文献求助10
10秒前
11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
Encyclopedia of Reproduction Third Edition 3000
化妆品原料学 1000
《药学类医疗服务价格项目立项指南(征求意见稿)》 1000
花の香りの秘密―遺伝子情報から機能性まで 800
1st Edition Sports Rehabilitation and Training Multidisciplinary Perspectives By Richard Moss, Adam Gledhill 600
nephSAP® Nephrology Self-Assessment Program - Hypertension The American Society of Nephrology 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5630828
求助须知:如何正确求助?哪些是违规求助? 4723716
关于积分的说明 14975757
捐赠科研通 4789049
什么是DOI,文献DOI怎么找? 2557396
邀请新用户注册赠送积分活动 1518110
关于科研通互助平台的介绍 1478700