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[已转移到维基条目] FightMalaria@Home 项目官方网站

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发表于 2013-10-2 11:17:48 | 显示全部楼层 |阅读模式
本论坛 FightMalaria@Home [13/10/1~6] 国庆节挑战赛正在如火如荼开展中,但是我们的 Wiki 主站暂无 FightMalaria@Home 项目的任何介绍,为配合国庆节挑战赛,并丰富本站 Wiki,特开新帖组织 FightMalaria@Home 项目的相关资料翻译。

项目官网:http://boinc.ucd.ie/fmah/ 本页面与项目内容相关的内容不多,主要项目信息集中在 http://www.fight-malaria.org 网站。
以下页面需要翻译,愿意参与翻译的童鞋,请报名、回帖、占楼,谢谢!只翻译主体内容即可。

1、项目官网  ——  详见3#翻译
http://boinc.ucd.ie/fmah/
2、Home 页面  ——  详见14#翻译
http://www.fight-malaria.org/ind ... icle&id=1&Itemid=26
3、Getting involved 页面  ——  详见6#翻译
http://www.fight-malaria.org/ind ... cle&id=12&Itemid=29
4、About the FightMalaria@Home project 页面   ——  详见5#翻译
http://www.fight-malaria.org/ind ... cle&id=87&Itemid=31
5、Abstract 页面  ——  详见11#翻译
http://www.fight-malaria.org/ind ... e&id=100&Itemid=109
6、The Idea 页面  ——  详见10#翻译
http://www.fight-malaria.org/ind ... le&id=99&Itemid=108
7、Targets 页面  ——  详见4#翻译
http://www.fight-malaria.org/ind ... cle&id=90&Itemid=99
8、Molecules 页面  ——  详见8#翻译
http://www.fight-malaria.org/ind ... le&id=91&Itemid=100
9、Results 页面   ——  详见7#翻译
http://www.fight-malaria.org/ind ... le&id=92&Itemid=113
10、FAQ 页面   ——  详见9#翻译
http://www.fight-malaria.org/ind ... le&id=94&Itemid=106

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发表于 2013-10-2 11:42:56 | 显示全部楼层
本帖最后由 超哥不郁闷 于 2013-10-2 12:02 编辑

我来也 超人_副本2.jpg
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 楼主| 发表于 2013-10-2 11:54:36 | 显示全部楼层
1、项目官网
http://boinc.ucd.ie/fmah/

About FightMalaria@Home
关于 FightMalaria@Home

FightMalaria@Home is a research project that uses donated CPU time to perform docking simulations on malaria proteins. You can participate by downloading and running a free program on your computer.
FightMalaria@Home 是一个利用捐赠 CPU 时间来进行疟疾蛋白质对接模拟的研究项目。您可以用电脑下载并运行一个免费程序来参与。
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 楼主| 发表于 2013-10-2 12:06:43 | 显示全部楼层
7、Targets 页面
http://www.fight-malaria.org/ind ... cle&id=90&Itemid=99

Targets
目标

Targets for screening
筛选的目标

The target proteins will be processed in order of structural accuracy and reliability:
目标蛋白质的处理按结构的准确性和可靠性依次进行:

1. X-ray crysal structures
X射线晶体结构

2. Tropical Diseases Initiative MODPIPE/MODELLER homology models with active site
热带疾病 MODPIPE/MODELLER 同源模型活性部位

3. Tropical Diseases Initiative MODPIPE/MODELLER homology models with score > 1.0
热带疾病 MODPIPE/MODELLER 同源模型,蛋白质评分 > 1.0

4. DISTILL models of all remaining proteins
所有剩余蛋白质的分馏模型

These are available on our wiki. As this is an ongoing project, please contact Dr. Anthony Chubb for access.
这些信息都将发布在我们 Wiki 百科上,现在正在筹备中,如需访问,请联系 Dr. Anthony Chubb。
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发表于 2013-10-2 12:26:08 | 显示全部楼层
本帖最后由 超哥不郁闷 于 2013-11-9 08:18 编辑

4、About the FightMalaria@Home project 页面

About the FightMalaria@Home project  关于FightMalaria@Home计划

We are developing a distributed computation strategy for docking known hit compounds into models of malarial proteins to build a ranked list of novel targets for further investigation.
我们正在开发一个分布式计算项目,用来将已知的候选化合物与疟疾的蛋白质模型进行配对,以此列出一系列新奇的目标化合物用以进一步研究。


The main focus is on discovering novel therapeutic drugs. Initially we will screen all hit compounds against all models of plasmodial proteins. This should provide a list of potential new target proteins that will need further investigation and validation in the laboratory. Once these targets have been validated, resources can be focused on finding effective inhibitors and developing new 'first-in-class' drugs. We will need help from many research groups around the world for this important validation step, so all our data will be made freely available online.
关注的焦点在于发现新奇的治疗药物。项目开始时,我们会将所有的目标化合物与所有的疟原虫蛋白质模型进行配对。这应该会为我们提供一份需要在实验室里做进一步研究与确认的全新潜在目标蛋白的名单。一旦这些目标被确认,大家的计算资源就可以集中力量去发现高效抑制物和开发新型药物了。为了这关键的确认阶段,我们需要
世界各地研究团队的鼎力相助,所以我们的所有数据都会在互联网上免费分享给大家。


To answer our first question we will need to perform over 300 million docking calcuilations. This will clearly require staggering computational resources, thus the need to utilise the world’s ‘spare’ idle CPU resources. BOINC is a well established system for donating spare computation time (Sony even distribute BOINC as standard with new VAIO computers).
为了回答我们的第一个问题,我们将需要进行3亿多次的对接计算。这显然需要难以置信的惊人算力,因此我们需要联合世界上闲置的CPU资源。而BOINC是一个成熟的贡献闲置计算时间的平台(索尼甚至将BOINC视为新VAIO电脑的标准自带程序)。



The precedent has been set with fightHIV@home, Africa@home, GoFightAgainstMalaria and many other distributed computation programs. The pieces of the puzzle are readily available, including publicly available proteome information (Integr8), hit lists (MMV, ChEMBL), X-ray crystal structures (PDB), models of malarial proteins using MODELLER or DISTILL, compound libraries (ZINC, PubChem), docking programs (AutoDock VINA, eHiTS), and distributed computing software (BOINC). The challenges now involve connecting these pieces together, and getting the public involved.
在这之前已经发起了fightHIV@home,Africa@home以及GoFightAgainstMalaria等众多其他的分布式计算项目。但一些棘手的问题已经显现出来,其中包括“公开蛋白质组信息(Integr8)”,“候选名单(MMV,ChEMBL),X射线晶体结构(PDB),使用MODELLER或DISTILL的疟疾蛋白质模型,化合物数据库(ZINC,PubChem),对接程序(AutoDock VINA,eHiTS),以及分布式计算程序(BOINC)。当前的挑战包括联合这些资源以及让公众参与其中。



All data will be made freely available on our website and (hopefully) on the Tropical Diseases Initiative website to help encourage other 'wet-lab' researchers to test the suggested compound-protein interactions and hopefully confirm these novel targets.
所有的数据都将在我们的网站上免费发放,也希望热带疾病研究网站能去鼓励其他的热带疾病研究者去进一步测试潜在的目标蛋白,兴许能够确认这些新奇的目标蛋白。



Many thanks to Aniko Simon of SimBioSys who has customised their eHiTS docking program for the FightMalaria@Home project.
非常感谢来自SimBioSys的Aniko Simon,因为他将他们的eHiTS对接程序贡献给了FightMalaria@Home计划。



Future funding will be sought from charitable organisations such as the Bill and Melinda Gates foundation to validate the compound-target interactions.  An added benefit of having available computational power is that we may also be able to suggest potential ligands for previously uncharacterised hypothetical proteins - labelled ‘putative’ in the proteome annotation.
未来用以确认目标蛋白的资金将会来自于像“比尔与梅琳达盖茨基金会”这样的慈善机构。拥有利用闲置计算资源的附加好处就是我们也许能为先前那些特征不明的假想蛋白找到潜在配体。
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 楼主| 发表于 2013-10-2 12:26:24 | 显示全部楼层
3、Getting involved 页面
http://www.fight-malaria.org/ind ... icle&id=12&Itemid=2

Getting involved
开始吧

Donate spare CPU time
捐赠您的 CPU 空闲时间

If you would like to donate spare CPU time, then please follow the instructions here.
Else go directly to the BOINC server here.
如果您愿意捐赠您的 CPU 空闲时间,请看这里的详细介绍。或者点这里直接访问 BOINC 的主页了解详情。

Help validate the results
帮助验证结果

If you would like to donate money to our laboratory validation effort, then please go here.
如果您希望捐赠善款给我们实验室开展验证工作,请移步这里。

Follow our progress
追踪我们的进展

If you would like to be kept up-to-date on the FightMalaria@Home project, please follow us on Twitter.
如果您希望随时得知 FightMalaria@Home 项目的最新进展,请关注我们的 Twitter。

Contact us
联系我们

If you would like to get involved with this volunteer based, open-sourced and non-commercial project, please contact Dr. Anthony Chubb.
如果您希望介入这个基于志愿者的、开源的、非商业性项目,请联系 Dr. Anthony Chubb。

Complex and Adaptive Systems Laboratory
UCD School of Medicine & Medical Science
UCD-CASL, 8 Belfield Office Park
Clonskeagh, Dublin 4
Ireland
Email: anthony.chubb @T ucd.ie
Telephone: + 353 1 716 5390
LinkedIn: http://ie.linkedin.com/in/chubbant
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 楼主| 发表于 2013-10-2 12:34:18 | 显示全部楼层
9、Results 页面
http://www.fight-malaria.org/ind ... d=92&Itemid=113

Results
结果

Docking Results
对接结果

Results will be integrated into ChEMBL.
结果将被整合发布到 ChEMBL 数据库网站。

We will also provide a searchable interface here.
我们也将在这里提供一个搜索接口。
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 楼主| 发表于 2013-10-2 12:36:28 | 显示全部楼层
8、Molecules 页面
http://www.fight-malaria.org/ind ... le&id=91&Itemid=112

Molecules
分子

Molecules for virtual screening
虚拟筛选的分子

The ligand small molecules that will be docked into the protein structures will be processed in order of importance:
将被对接到蛋白质结构中的小分子配体的处理过程,按重要性依次进行:

1. MMV MalariaBox best candidate hit compounds [200 drugs + 200 probes]
MMV(疟疾药物开发基金组织) MalariaBox 最佳候选命中化合物 [200药物 + 200探针]

2. Remainder of the MMV/GSK/Novartis/St.Judes hit compound list
剩余的 MMV(疟疾药物开发基金组织)/GSK(葛兰素史克)/Novartis(诺华)/St.Judes(圣犹达) 命中化合物列表

3. FDA approved drugs (these have already passed clinical trials in patients, compiled in the NPC)
FDA(美国食品药物管理局) 批准的药物(这些已经在患者身上进行过临床试验,已纳入 NPC 数据库)

4. ChEMBL Bioassay compounds not included in lists 1-3
ChEMBL 生物活性化合物,但不在 lists 1-3 内

5. ZINC Clean Drug Like diversity subset
ZINC 数据库,清洁制剂类,多样性子库

6. Head-to-tail cyclical peptides [CycloPs]
首尾相连环肽 [剑水蚤]

7. ZINC Clean Drug Like full library
ZINC 数据库,清洁制剂类,全数据库

These are available on our wiki. As this is an ongoing project, please contact Dr. Anthony Chubb for access.
这些信息都将发布在我们 Wiki 百科上,现在正在筹备中,如需访问,请联系 Dr. Anthony Chubb。

-----
译者注:
ZINC 是一个可以免费使用的用于虚拟筛选的化合物数据库,由美国加州大学药物化学系的 Shoichet 研究小组建立并维护。主页地址:http://zinc.docking.org/
ZINC 数据库其中所收录的化合物来自各大化合物合成公司,因此都是可以商业购买的。数据库既存储了化合物的结构信息,也包含了这些化合物的供应商信息。
由于 ZINC 在收录这些化合物的过程中进行了“类药性”过滤,可以以 SMILES、mol2、3D SDF 等多种文件格式免费下载,因此特别适用于以分子对接为主的虚拟筛选策略。

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 楼主| 发表于 2013-10-2 13:25:13 | 显示全部楼层
10、FAQ 页面
http://www.fight-malaria.org/ind ... le&id=94&Itemid=106

Frequently Asked Questions:
常见问题:

Q: Isn't there already a BOINC server running a malaria project? How is FM@H different?
问题:BOINC 上早就有研究疟疾的项目啦!和 FightMalaria@Home 项目有什么区别呢?

A: The Africa@Home BOINC project uses distributed computation to develop epidemiology models to understand and predict the progression of an infectious disease through the human population. While this is also a very important and noble task, their computation will not provide novel therapeutic drugs.
回答:Africa@Home BOINC 项目采用分布式计算来研究流行病的传播模型,了解和预测传染性疾病在人群中的传播。虽然这也是一个非常重要和崇高的任务,但是他们的计算不会提供新的治疗药物。

The MalariaControl.net project is an application that makes use of network computing for stochastic modelling of the clinical epidemiology and natural history of Plasmodium falciparum malaria. Therefore they are not involved in drug or target protein discovery.
MalariaControl.net 项目是一个应用程序,利用网络计算来建模,研究临床恶性疟原虫疟疾的流行传播和自然发展。因此,他们也不参与药物或者目标蛋白质的发现。

The GoFightAgainstMalaria BOINC project also uses AutoDock Vina to dock compounds against protein targets in malaria. However, their focus is on finding new compound inhibitors that will bind to mutant proteins that have been found in drug resistant malaria. Essentially they are trying to fight back against drug resistance. FightMalaria@Home is different in that we are trying to find the target for each of the compounds that have already been found to be effective against malaria. This will help focus future drug discovery efforts on new target proteins.
GoFightAgainstMalaria BOINC 项目也使用 AutoDock Vina 对接化合物来寻找对抗疟疾的目标蛋白质。但是,他们的重点是寻找新的化合物抑制剂,将其绑定到已发现的抗药性疟疾的突变蛋白质内。从本质上讲,他们正在试图反击抗药性。FightMalaria@Home 与他们不同,因为我们正在努力寻找的目标,已经被公认为是有效抵御疟疾的化合物。这将有助于聚焦未来新的目标蛋白药物的发现工作。

Our FightMalaria@Home project aims to provide the poorest populations with extremely cheap medication by removing the expensive Research component from the drug discovery R&D pipeline. By crowd-sourcing the research - both with donated CPU time and volunteered scientific validation analysis and future clincal work - we hope to be able to kick-start drug discovery at an unimaginably cheap rate. Specifically, we hope to identify new targets that are inhibited by the available set of hit compounds. Once these targets have been identified, medicinal chemistry can be directed at improving the hits and providing novel drugs against new targets. The parasite should not have any resistance to these new drugs, as they will target a new protein/pathway.
我们的 FightMalaria@Home 项目,旨在为最贫困的人口提供最便宜的用药,从药物发现到生产线式生产,消除昂贵的研究组成费用。通过众包模式的研究——包括志愿者捐赠的 CPU 时间和用于科学验证分析的善款,以及未来的临床工作——我们希望能使得新药物的发现变得难以想象的便宜。具体而言,我们希望确定能在命中化合物中找到具有抑制效果的新的目标药物。一旦这些目标得到确定,药物化学可直接提供命中和提供新型目标药物。新药物针对寄生虫有新的杀灭通道,杀灭这些寄生虫将没有任何阻力。
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 楼主| 发表于 2013-10-2 14:35:46 | 显示全部楼层
6、The Idea 页面
http://www.fight-malaria.org/ind ... le&id=99&Itemid=108

The Idea
我们的想法

To find novel targets by docking known inhibitorsinto structures of malarial proteins
为了寻找新的目标,将已知的抑制剂对接到疟疾道白结构中去。

The target proteins will be processed in order of structural accuracy and reliability:
目标蛋白质的处理按结构的准确性和可靠性依次进行:
  • X-ray crysal structures
    X射线晶体结构
  • Tropical Diseases Initiative MODPIPE/MODELLER homology models with active site
    热带疾病 MODPIPE/MODELLER 同源模型活性部位
  • Tropical Diseases Initiative MODPIPE/MODELLER homology models with score > 1.0
    热带疾病 MODPIPE/MODELLER 同源模型,蛋白质评分 > 1.0
Similarly, the ligand small molecules that will be docked into the protein structures will be processed in order of importance:
同样的,
将被对接到蛋白质结构中的小分子配体的处理过程,按重要性依次进行:
  • MMV MalariaBox best candidate hit compounds [200 drugs + 200 probes]
    MMV(疟疾药物开发基金组织) MalariaBox 最佳候选命中化合物 [200药物 + 200探针]
  • Remainder of the MMV/GSK/Novartis/St.Judes hit compound list
    剩余的 MMV(疟疾药物开发基金组织)/GSK(葛兰素史克)/Novartis(诺华)/St.Judes(圣犹达) 命中化合物列表
  • FDA approved drugs (these have already passed clinical trials in patients, compiled in the NPC)
    FDA(美国食品药物管理局) 批准的药物(这些已经在患者身上进行过临床试验,已纳入 NPC 数据库)
  • ChEMBL Bioassay compounds not included in lists 1-3
    ChEMBL 生物活性化合物,但不在 lists 1-3 内
  • ZINC Clean Drug Like diversity subset
    ZINC 数据库,清洁制剂类,多样性子库
  • Head-to-tail cyclical peptides [CycloPs]
    首尾相连环肽 [剑水蚤]
  • ZINC Clean Drug Like full library
    ZINC 数据库,清洁制剂类,全数据库

List of planned experiments (and why we need your help!):
计划试验列表(我们需要您的帮助!)

Paper
Exp
Target
recs
Ligands
mols
tautomers
Vina calcs
A
A
Xray_all [140]
140
Xray_ligs [41]
41
176
24,640
A
1
Xray_all [140]
140
MMV [400]
400
852
119,280
A
Ap
Xray_all_p [a]
138
Xray_ligs [41]
41
176
24,288
A
1p
Xray_all_p [a]
138
MMV [400]
400
852
117,576
A
2p
TDI_site_p [a]
28
MMV [400]
400
852
23,856
A
4p
TDI_good_p [a]
1,425
MMV [400]
400
852
1,214,100
B
8p
Xray_all_p [a]
138
NPC [2,646]
2,646
6,309
870,642
B
9p
TDI_site_p [a]
28
NPC [2,646]
2,646
6,309
176,652
B
10p
TDI_good_p[a]
1,425
NPC [2,646]
2,646
6,309
8,990,325
C
B
Xray_all [140]
140
MMV_all [18,924]
18,924
55,943
7,832,020
C
Bp
Xray_all_p [a]
138
MMV_all [18,924]
18,924
55,943
7,720,134
C
3p
TDI_site_p [a]
28
MMV_all [18,924]
18,924
55,943
1,566,404
C
5p
TDI_good_p [a]
1,425
MMV_all [18,924]
18,924
55,943
79,718,775
C
12p
Xray_all_p [a]
140
ChEMBLassay[4,262]
4,262
15,366
2,151,240
C
13p
TDI_site_p [a]
28
ChEMBLassay[4,262]
4,262
15,366
430,248
C
14p
TDI_good_p [a]
1,425
ChEMBLassay[4,262]
4,262
15,366
21,896,550



Abbreviations
缩略语

Xray_ligAll P. fal. proteins that have at least one X-ray crystal structure in RCSB with a co-crystalised ligand (one structure per protein)
Xray_all
All P. fal. proteins that have at least one X-ray crystal structure in RCSB (one structure per protein)
TDI_siteAll Tropical Diseases Initiative MODPIPE models with active site (one model per protein)
TDI_goodAll Tropical Diseases Initiative MODPIPE models with MPQS score > 1.0 (one model per protein)
DISTILLDISTILL models of all remaining proteins in the P. fal. proteome (one model per protein)
MMV
Medicines for Malaria 'Malaria Box' collection
MMV_all
Medicines for Malaria full collection of hit compounds from GSK, Novartis and St. Judes Children's Hospital screening studies
NPC
NCGC (NIH (National Institutes of Health) Chemical Genomics Center) Pharmaceutical Collection (NPC) of approved drugs (global)
ChEMBLassayPubChem/ChEMBL bioassay compounds not part of GSK screen, showing inhibition >90%, in whole P. fal.assays
Xray_lig_wetXray_lig with specific crystallographic waters included
TDI_site_flex5xTDI_site with conformational flexibility (5 conformations each)
TDI_good_flex3xTDI_good with conformational flexibility (3 conformations each)
ZINC_CDLdiv
ZINC version 12 Clean Drug Like compounds (subset #13) diversity subset (Tanimoto 90%)
ZINC_CDLZINC version 12 Clean Drug Like compounds (subset #13) full collection
CycloPs_HT
CycloPs head-to-tail cyclical peptides
剑水蚤首尾相连环肽



After completion of experiment 7 we will have achieved our primary goal. Thereafter we will improve the search by allowing taregt protein structure flexibility. Lastly, we will use the BOINC infrastructure to search for novel compounds using available X-ray structures and libraries of small molecules.
当实验7完成后,我们将实现我们的首要目标。此后,我们将提高通过允许目标蛋白质结构搜索的灵活性。最后,我们将使用 BOINC 的基础资源,来搜索新的化合物,使用小分子的X射线结构和库。

FAST and LIGHT approach:
Due to the staggering number of calculations that are planned, we soon realised that we would not have the data storage capacity to hold all the results. Instead we'll keep only two small pieces of information from each docking run:
  • the best pose docking energy
  • the Autodock Vina seed number
AutoDock Vina has a convenient function that allows one to start the docking run from a specific seed. By inserting the previous seed used during the virtual screening study, we can recreate the final docked pose, without having to keep huge amounts of data.  

How is this different from exisiting research?
To our knowledge, only the WISDOM grid project and the GoFightAgainstMalaria BOINC project lead by Alex Perryman (Scripps) are directly aimed at finding novel drugs that could be active against malaria. We had initially planned to do very similar work, but on 16th November 2011 Alex started his WorldCommunityGrid project aimed at finding novel compounds that could be used to combat drug resistant malaria. Details about the targets he is using can be found here. This will involve identifying compounds that may be effective against malaria, and then purchasing and testing these hit compounds in the laboratory.
据我们所知,只有 WISDOM 网格计算项目和 GoFightAgainstMalaria BOINC 项目是由 Alex Perryman (Scripps) 主持的,直接目的就是寻找能够有效对抗疟疾的新药物。我们最初曾打算做非常类似的工作,但是在2011年11月16日,Alex Perryman 启动了他的 WCG 项目,目的在于寻找能用来对付抗药性疟疾的新的化合物。他正使用的目标的细节,请看这里。这将有助于识别能有效对抗疟疾的化合物,然后在实验室内合成和测试这些命中化合物。

While Alex is docking millions of compounds against a small number of target proteins, we are asking if we can find the target protein that is inhibited by a specific compound. In essence it's the same question - backwards.
当 Alex 正在将成千上万种化合物与少数目标蛋白质配对的时候,我们都在问,我们是否能找到一种特殊化合物能够抑制的目标蛋白质。在本质上,这是相同的问题——追溯。

We know from the massively high throughtput assay results from GSK (Tres Cantos), Novartis-GNF and St. Jude's Children's Research hospital that there are 18,924 compounds that inhibit the Plasmodium falciparum parasite in whole cell assays. But we don't know where each of these compounds are affecting the parasite. So in essence we're asking the question "can we find the protein that is inhibited by this compound?" nearly 19,000 times.
我们从 GSK (Tres Cantos)、Novartis-GNF、St. Jude's Children's Research hospital 的大规模数据吞吐量的化验结果中发现,有 18924 种化合物能够抑制恶性疟原虫寄生在细胞的中。但是我们不知道这些化合物如何对寄生虫产生影响。因此,从本质上说,我们正在做的工作,是问“我们能否找到通过这种化合物抑制的蛋白质?”约19000次。

To do that we need structural information about a whole genome... something that is just not available yet. What we do have are 141 very good X-ray crystal structures (PDB) and models for 4,657 plasmodial proteins (of which 818 are similar to known active sites) [Nat. Biotech, 2009]. So we can be fairly confident about 87% of the proteome. Beyond that we'll use other modelling software (DISTILL) to propose structures for the remaining 13% of the 5,363 proteins in the plasmodial proteome.
要完成这项工作,我们需要一套完整的基因结构信息……只是目前尚未问世。现在我们有的,是141种很好的X射线晶体结构(PDB)和4657种疟原虫的蛋白质模型(其中818种和已知的活性部位相似)[Nat. Biotech, 2009]。因此,我们可以相当有信心

We will also use Autodock Vina to do the docking using our own BOINC distributed computation server. In addition, we will use eHiTS on a PS3 cluster to corroborate the findings from the Vina screen.


The result of our work will be a list of proteins that are likely to be the enzymes/receptors targeted by each of the 19,000 hit compounds. These will each have at least one known hit compound. After confirmation in the laboratory, these proteins will then make excellent targets for further drug discovery and development, using the skills of medicinal chemists to optimise the interactions found by the lead compound. Hopefully in the future this will lead to a novel drug that inhibits an as yet unknown protein target in malaria.

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参与人数 1维基拼图 +35 收起 理由
昂宿星团人 + 35 辛苦了!一起算了。。

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发表于 2013-10-2 16:07:23 | 显示全部楼层


FightMalaria@Home
Elevator Pitch
Malaria kills more than half a million people in sub-Saharan Africa each year. Plasmodium falciparum has developed resistance to all antimalarial agents, and multi-drug resistance is increasing. It is imperative that new medications – against novel targets - are discovered and developed now, to mitigate disaster in the near future. A number of pharmaceutical companies have tested millions of compounds against the parasite that causes malaria, and have made the results publicly available. These 18,924 confirmed hits show promise as potential new drugs, but no one knows what proteins these compounds bind. To help further drug discovery, we plan to identify as many of these targets as possible by docking each compound into structural models of each protein in the genome.
疟疾每年会夺去非洲撒哈拉以南地区五十多万人的宝贵生命。恶性疟原虫已经对所有抗疟药物产生了抗性,多耐药率正在提高。开发新药物以应对未来疾病的挑战是势在必行的。一些制药公司已经测试了数百万种针对疟原虫的复合物,并且已将其结果公之于众了。18,924种已被确认的复合物展现了其作为新型药物的潜力,但是没人知道这些复合物究竟由哪些蛋白质构成。为了进一步助力药物的开发,我们打算用对接计算的方式来尽可能多地鉴定这些目标复合物。

Docking 18,924 compounds into 5,363 protein structures is a staggeringly huge task. We therefore need help with the computation from public volunteers who are willing to donate their space computer power to our project. We have built a BOINC distributed computation server that divides the massive docking problem into tiny individual parts, and sends each of these to PCs that are connected to our server.
将这18,924种复合物与5,363种蛋白质的结构进行对接是一个极为繁重的任务。因此我们需要那些愿意贡献出他们电脑闲置计算资源的公众志愿者所带来的帮助。我们建立了一个BOINC服务器,用以将繁杂的对接问题分割成细小的独立任务,再将其发送给每一个与我们服务器相连的个人电脑。

Once all the docking results are complete, we'll validate the target proteins in the laboratory and hopefully provide the world with novel protein targets to focus drug discovery efforts(www.fight-malaria.org). Inhibitors of these novel targets should provide ‘first-in-class’ drugs to combat malaria.
一旦所有的对接计算完成,我们将在实验室里验证这些目标蛋白,以希望为全世界找出新奇的目标蛋白质供进一步的药物研究(http://www.fight-malaria.org/ )。采用这些新型目标化合物的抑制剂应该能够成为对抗疟疾这一疾病的新利器。

For Scientists 对于科学家来说
The ChEMBL Neglected Tropical Disease repository contains the results of High Throughput Screening from three groups – St. Jude Children’s hospital, GSK and Novartis. These 18,924 confirmed hits show promise as potential new drugs, although each are 'orphan ligands as the target protein is unknown. Further rational drug development will be significantly advanced if the target for each of these compounds can be identified.
The ChEMBL Neglected Tropical Disease包含了来自于三个团队的高通量筛选结果,这三个团队分别是St.Jude Children's hospital,GSK以及Novartis。尽管每一种目标蛋白的配体结构都还不清楚,但这18,924种已被确认的蛋白质展现了它们成为新型药物的潜力。如果每一种复合物都能够被鉴定出来,那么药物发展领域将会取得长足进步。  

We propose to use modeled structures of Plasmodial proteins as receptors for virtual high throughput screening. We have already prepared 4,657 protein structures for the docking pipeline, including 141 X-ray structures (of which 49 contain at least one small molecule ligand),  and 743 reliable homology models. We are extending further into the 5,363 protein genome using DISTILL homology modelling. As we plan to cross-validate with two docking programmes (Vina and eHiTS) the ~300 million docking calculations will be performed using the ICHEC supercomputing cluster, a PS3 cluster, and BOINC distributed computation server (http://boinc.ucd.ie/fmah/)
我们打算用疟原虫的蛋白质作为受体来进行虚拟高通量筛选。我们已经准备了4,657种蛋白质结构用以对接模拟,其中包括141种X射线结构模型(其中有49种至少含有一个小型分子配合体),以及743种可靠的同源模型。我们正在用DISTILL同源建模技术将其进一步扩展为5363种蛋白质结构。因为我们打算用两个对接程序(Vina和eHiTS)进行交叉验证,所以大约有3亿多次对接计算将会在ICHEC超级计算集群,PS3集群以及BOINC分布式计算平台上进行。

Docking results that are again cross-validated using numerous scoring functions will be tested in vitro using recombinant protein and Surface Plasmon Resonance and Isothermal Titration Calorimetry. All data will be made publicly available on our website www.fight-malaria.org and integrated into ChEMBL.
通过海量计算交叉验证过的对接结果将在试管内用recombinant protein and Surface Plasmon Resonance and Isothermal Titration Calorimetry做进一步验证。所有的数据都会在我们的网站上公之于众,并且用于完善ChEMBL的数据。

Inhibitors of these novel targets should provide ‘first-in-class’ drugs to combat malaria.
我们相信,采用这些新型目标化合物的抑制剂应该能够成为对抗疟疾这一疾病的新利器。







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发表于 2013-10-4 10:46:53 | 显示全部楼层
这是本人做的维基条目,翻译目前还未到位,不过其他的还请大家多多指正 http://www.equn.com/wiki/FightMalaria@Home
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发表于 2013-10-5 21:58:18 | 显示全部楼层
@昂宿星团人 哈哈~给分~....顺便校对一下吧
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发表于 2013-10-6 17:18:14 | 显示全部楼层
本帖最后由 超哥不郁闷 于 2013-10-6 19:05 编辑

2.Homepage 首页    (明天就要回学校了,所以今天给自己这一阶段的翻译工作画上一个完美的句号~
   友情链接http://www.fight-malaria.org/indexbed3.html?option=com_content&view=article&id=1&Itemid=26

Crowd-sourcing antimalarial drug discovery

抗疟药物分布式大搜索
Goal:To discover novel targets for antimalarial drugs.

目标:为抗疟药物寻找全新化合物。


Context:Malaria kills a child every 45 seconds. The disease is most prevalent in poorer countries, where it infects 216 million people and kills 650,000 each year, mostly African children under 5 years old [WHO]. And Plasmodium falciparum continues to evolve resistance to available medication. We therefore urgently need to discover new drugs to replace existing drugs. Importantly, these new drugs need to target NEW proteins in the parasite. The FightMalaria@Home project is aimed at finding these new targets.


背景:疟疾每45秒就会夺走一个孩童的宝贵生命。该疾病在穷困国家中最为肆虐,在那里每年都会有2.16亿人感染并且有65万人死于该疾病,而且大多数都是5岁以下的非洲儿童【WHO统计结果】。而且恶性疟原虫对现有药物的抵抗力仍在持续加强。因此,发现新的药物用以取代现有药物是件迫在眉睫的事。重要的是,这些全新的药物要能有效针对寄生虫体内新的蛋白质。而FightMalaria@Home的目标就是发现这些新的药物。

Resources:The Plasmodium falciparum genome has been sequenced, the proteome has been mapped, and protein expression has been confirmed at various stages in this apicoplexan's life cycle. Numerous crystal structures of target proteins are also available, and the remainder have been modelled using available structural templates. Excitingly, large research organisations (GSK, Novartis) have already tested millions of compounds and found nearly 19,000 hits that show promising activity against Plasmodium falciparum [MMV]. But they don't know which target protein is inhibited by these compounds. Drug discoveryand development will be significantly enhanced by knowing the target protein for each of these hits.


资源:恶性疟原虫基因组的测序工作已经完成,蛋白质组已被标记,除此之外,其蛋白质的表达在不同层面上都已有所认识。许多目标蛋白的晶体结构同样被我们所了解,并且剩下来的都已经用现有的结构模型模拟过。令人兴奋的是,大型研究机构(GSK,Novartis)已经对数百万种复合物进行了测试,并且发现了大约19,000种显示出对恶性疟原虫具有活跃抗性的复合物。【消息来自于MMV】。但是他们并不清楚这些复合物会对哪一种目标蛋白质产生抑制作用。如果把这些地方都弄清楚了,那么药物研制工作将取得长足进步。


Problem:We plan to dock each of the 18,924 hits into structures of each of the 5,363 proteinsin the malaria parasite. The computational power needed is enormous.


问题:我们计划将18,924种复合物与5,363种疟原虫蛋白质进行结构配对。其所需的算力是十分巨大的。


Solution:We aim to harness the donated computational power of the world's personal computers. Most computers only use a fraction of their available CPU power for day-to-day computation. We have built a BOINC server that distributes the docking jobs to donated 'client' computers, which then do the work in the background. By connecting 1000s of computers this way, we'll be able harness the equivalent power of large supercomputers. If you would like to get involved, please follow the very quick installation instructionshere.


解决方案:我们打算汇集世界各地个人电脑所捐献的算力。大多数电脑每天的CPU使用率并不高。所以我们建立了一个BOINC服务器用以将配对任务分发给用户的电脑,而之后其便在后台运行。通过这种方式联合数以千计的电脑,我们就将获得相当于超级计算机的强大算力。如果您想参与进来,那就赶快下载吧。



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参与人数 1维基拼图 +22 收起 理由
昂宿星团人 + 22 迟到的给分。。

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发表于 2013-10-13 10:32:56 | 显示全部楼层
@昂宿星团人 校对辛苦
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