Engineering inhibitory proteins with InSiPS: the in-silico protein synthesizer

Andrew Schoenrock, Daniel J. Burnside, H. Moteshareie, A. Wong, A. Golshani, F. Dehne
{"title":"Engineering inhibitory proteins with InSiPS: the in-silico protein synthesizer","authors":"Andrew Schoenrock, Daniel J. Burnside, H. Moteshareie, A. Wong, A. Golshani, F. Dehne","doi":"10.1145/2807591.2807630","DOIUrl":null,"url":null,"abstract":"Engineered proteins are synthetic novel proteins (not found in nature) that are designed to fulfill a predetermined biological function. Such proteins can be used as molecular markers, inhibitory agents, or drugs. For example, a synthetic protein could bind to a critical protein of a pathogen, thereby inhibiting the function of the target protein and potentially reducing the impact of the pathogen. In this paper we present the In-Silico Protein Synthesizer (InSiPS), a massively parallel computational tool for the IBM Blue Gene/Q that is aimed at designing inhibitory proteins. More precisely, InSiPS designs proteins that are predicted to interact with a given target protein (and may inhibit the target's cellular functions) while leaving non-target proteins unaffected (to minimize side-effects). As proof-of-concepts, two InSiPS designed proteins have been synthesized in the lab and their inhibitory properties have been experimentally verified through wet-lab experimentation.","PeriodicalId":117494,"journal":{"name":"SC15: International Conference for High Performance Computing, Networking, Storage and Analysis","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SC15: International Conference for High Performance Computing, Networking, Storage and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2807591.2807630","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

Engineered proteins are synthetic novel proteins (not found in nature) that are designed to fulfill a predetermined biological function. Such proteins can be used as molecular markers, inhibitory agents, or drugs. For example, a synthetic protein could bind to a critical protein of a pathogen, thereby inhibiting the function of the target protein and potentially reducing the impact of the pathogen. In this paper we present the In-Silico Protein Synthesizer (InSiPS), a massively parallel computational tool for the IBM Blue Gene/Q that is aimed at designing inhibitory proteins. More precisely, InSiPS designs proteins that are predicted to interact with a given target protein (and may inhibit the target's cellular functions) while leaving non-target proteins unaffected (to minimize side-effects). As proof-of-concepts, two InSiPS designed proteins have been synthesized in the lab and their inhibitory properties have been experimentally verified through wet-lab experimentation.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
用硅蛋白合成器insps工程抑制蛋白
工程蛋白是合成的新型蛋白质(不存在于自然界中),旨在实现预定的生物功能。这些蛋白质可用作分子标记、抑制剂或药物。例如,合成蛋白可以与病原体的关键蛋白结合,从而抑制目标蛋白的功能并潜在地减少病原体的影响。在本文中,我们介绍了In- silicon Protein Synthesizer (insps),这是IBM Blue Gene/Q的大规模并行计算工具,旨在设计抑制蛋白。更准确地说,insps设计的蛋白质可以与给定的靶蛋白相互作用(并可能抑制靶蛋白的细胞功能),而不影响非靶蛋白(以减少副作用)。作为概念验证,两种insps设计的蛋白质已经在实验室合成,并通过湿实验室实验验证了它们的抑制特性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Optimal scheduling of in-situ analysis for large-scale scientific simulations Monetary cost optimizations for MPI-based HPC applications on Amazon clouds: checkpoints and replicated execution IOrchestra: supporting high-performance data-intensive applications in the cloud via collaborative virtualization An input-adaptive and in-place approach to dense tensor-times-matrix multiply Scalable sparse tensor decompositions in distributed memory systems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1