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| {{Stub|Arthur200000|新页面,内容暂缺}}
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| {{Project | | {{Project |
| | name ={{PAGENAME}} | | | name ={{PAGENAME}} |
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| | platform ={{Platform/BOINC}} | | | platform ={{Platform/BOINC}} |
| | subproject =SHAFTS | | | subproject =SHAFTS |
| | status =试运行/Alpha | | | status =已结束&官方网站消失 |
| | genre ={{Genre/医学}} | | | genre ={{Genre/医学}} |
| | website =http://lilab.ecust.edu.cn:8082/dhome/ | | | website =http://lilab.ecust.edu.cn:8082/dhome/ |
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| 加入 Team China:http://59.78.96.61:8082/dhome/team_display.php?teamid=1 | | 加入 Team China:http://59.78.96.61:8082/dhome/team_display.php?teamid=1 |
| ==子项目== | | |
| {{Box|该段英文当[http://lilab.ecust.edu.cn:8082/dhome/test_community_wiki.php 官方网站]中文版放出后会立即更新。 |#BBDDBB|#DDFFDD}}
| | ==项目结束== |
| ===SHAFTS===
| | 在华东理工 HongLin LI 的研究成果列表内的 Drug Discovery 中,有着一些该项目的[http://lilab.ecust.edu.cn:8082/home/research.html 研究成果]。 |
| SHAFTS (SHApe-FeaTure Similarity) is a program for 3D molecular similarity calculation and ligand-based virtual screening. SHAFTS adopts hybrid similarity metric combined with molecular shape and colored (labeled) chemistry groups annotated by pharmacophore features for 3D similarity calculation and ranking, which is designed to integrate the strength of pharmacophore matching and volumetric overlay approaches. A feature triplet hashing method is used for fast molecular alignment poses enumeration, and the optimal superposition between the target and the query molecules can be prioritized by calculating corresponding “hybrid similarities”. SHAFTS is suitable for large-scale virtual screening with single or multiple bioactive compounds as the query “templates” regardless of whether corresponding experimentally determined conformations are available. Two public test sets (DUD and Jain’s sets) including active and decoy molecules from a panel of useful drug targets were adopted to evaluate the virtual screening performance. SHAFTS outperformed several other widely used virtual screening methods in terms of enrichment of known active compounds as well as novel chemotypes, thereby indicating its robustness in hit compounds identification and potential of scaffold hopping in virtual screening.
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| ===新药开发===
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| Drug design, sometimes referred to as rational drug design or more simply rational design, is the inventive process of finding new medications based on the knowledge of a biological target.[1] The drug is most commonly an organic small molecule that activates or inhibits the function of a biomolecule such as a protein, which in turn results in a therapeutic benefit to the patient. In the most basic sense, drug design involves the design of small molecules that are complementary in shape and charge to the biomolecular target with which they interact and therefore will bind to it. Drug design frequently but not necessarily relies on computer modeling techniques.[2] This type of modeling is often referred to as computer-aided drug design. Finally, drug design that relies on the knowledge of the three-dimensional structure of the biomolecular target is known as structure-based drug design.
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| {{BOINC topics}} | | {{BOINC topics}} |
| | [[Category:已结束项目]] |
Drug@Home是华东理工大学的分子模拟BOINC分布式计算项目,用与计算机辅助药物设计中,目前处于试运行阶段,不定时有计算任务发布,欢迎大家的积极参与,为新药的的设计研发做出贡献。
如何加入项目
该项目基于 BOINC 平台,简要的加入步骤如下(已完成的步骤可直接跳过):
- 下载并安装 BOINC 的客户端软件(官方下载页面或程序下载)
- 点击客户端简易视图下的“Add Project”按钮,或高级视图下菜单中的“工具->加入项目”,将显示向导对话框
- 点击下一步后在项目列表中找到并单击选中 Drug@Home 项目(如未显示该项目,则在编辑框中输入项目网址:http://lilab.ecust.edu.cn:8082/dhome/ ),然后点击下一步
- 输入您可用的电子邮件地址,并设置您在该项目的登录密码(并非您的电子邮件密码)
- 再次点击下一步,如项目服务器工作正常(并且有适合自身操作系统的计算程序),即已成功加入项目
更详细的加入方法说明,请访问 BOINC 新手指南 或 BOINC 使用教程。
本站推荐您加入 Team China 团队,请访问项目官方网站的 团队检索页面,搜索(Search)并进入 Team China 的团队页面,点击页面中的 Join 并输入用户登录信息即可加入!
项目目前处于内测阶段,也许会产生少量Bug或收不到任务包的情况。欢迎您提出宝贵的意见和建议!
加入 Team China:http://59.78.96.61:8082/dhome/team_display.php?teamid=1
项目结束
在华东理工 HongLin LI 的研究成果列表内的 Drug Discovery 中,有着一些该项目的研究成果。