Current Therapeutic Molecules and Targets in Neurodegenerative Diseases Based on in silico Drug Design.

肌萎缩侧索硬化 疾病 生物信息学 亨廷顿病 药物发现 小分子 药物重新定位 神经保护 帕金森病 神经退行性变 计算生物学 药理学 计算机科学 神经科学 生物信息学 药物开发 医学 药效团 对接(动物) 药物靶点 可药性 虚拟筛选 化学
作者
Sheikh Arslan Sehgal,Mirza Ahmed Hammad,Rana Adnan Tahir,Hafiza Nisha Akram,Faheem Ahmad
出处
期刊:Current Neuropharmacology [Bentham Science Publishers]
卷期号:16 (6): 649-663 被引量:18
标识
DOI:10.2174/1570159x16666180315142137
摘要

As the number of elderly persons increases, neurodegenerative diseases are becoming ubiquitous. There is currently a great need for knowledge concerning management of oldage neurodegenerative diseases; the most important of which are: Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis, and Huntington's disease.To summarize the potential of computationally predicted molecules and targets against neurodegenerative diseases.Review of literature published since 1997 against neurodegenerative diseases, utilizing as keywords: in silico, Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis ALS, and Huntington's disease was conducted.Due to the costs associated with experimentation and current ethical law, performing experiments directly on living organisms has become much more difficult. In this scenario, in silico techniques have been successful and have become powerful tools in the search to cure disease. Researchers use the Computer Aided Drug Design pipeline which: 1) generates 3- dimensional structures of target proteins through homology modeling 2) achieves stabilization through molecular dynamics simulation, and 3) exploits molecular docking through large compound libraries. Next generation sequencing is continually producing enormous amounts of raw sequence data while neuroimaging is producing a multitude of raw image data. To solve such pressing problems, these new tools and algorithms are required. This review elaborates precise in silico tools and techniques for drug targets, active molecules, and molecular docking studies, together with future prospects and challenges concerning possible breakthroughs in Alzheimer's, Parkinson's, Amyotrophic Lateral Sclerosis, and Huntington's disease.

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
可靠桐发布了新的文献求助10
刚刚
平常心完成签到,获得积分10
刚刚
1秒前
向日葵发布了新的文献求助10
1秒前
dxy完成签到 ,获得积分10
1秒前
李健的应助被小明同学采纳,获得10
2秒前
无极微光的应助被阿午采纳,获得20
2秒前
研友_VZG7GZ的应助被虚心楼房采纳,获得10
2秒前
yanxi完成签到,获得积分10
2秒前
2秒前
ron完成签到,获得积分10
2秒前
亿点点困发布了新的文献求助20
3秒前
3秒前
3秒前
3秒前
4秒前
4秒前
七听的应助被火星上冥茗采纳,获得50
4秒前
4秒前
三一完成签到 ,获得积分10
4秒前
4秒前
4秒前
zoes完成签到 ,获得积分10
5秒前
石原妮美完成签到,获得积分10
5秒前
HHH完成签到,获得积分10
5秒前
5秒前
yizimm发布了新的文献求助10
6秒前
Jasper的应助被密斯范德颖采纳,获得20
6秒前
6秒前
7秒前
小羊同学发布了新的文献求助10
7秒前
Lclars发布了新的文献求助10
8秒前
8秒前
小笼包完成签到 ,获得积分10
8秒前
8秒前
8秒前
晨晨发布了新的文献求助10
8秒前
8秒前
言午发布了新的文献求助10
9秒前
Zy189完成签到,获得积分10
9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
Das Matthäusevangelium: Kapitel 1:1–17 1000
IRTSD: Open-Source Data and Toolset for Electromagnetic Transient Analysis of Disturbances and IBR Control Malfunctions in Transmission Systems 1000
Entre Praga y Madrid : los contactos checoslovaco-españoles (1948-1977) 600
Les Mots du discours 600
A Consideration on Use of Material Grades for Hull Structural Members Based on Fracture Toughness(Second Report) 500
AI Disclosure in Annual Reports: Evolution, Determinants, and Capital Market Participants’ Perceptions 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8117074
求助须知:如何正确求助?哪些是违规求助? 9522913
关于积分的说明 21541414
捐赠科研通 7695510
什么是DOI,文献DOI怎么找? 3414060
关于科研通互助平台的介绍 2540312
邀请新用户注册赠送积分活动 2453986