A computational method for the design of nested proteins by loop‐directed domain insertion

领域(数学分析) 计算机科学 循环(图论) 嵌套循环联接 计算生物学 并行计算 生物 数学 组合数学 数学分析
作者
Kristin Blacklock,Lu Yang,Vikram Khipple Mulligan,Sagar D. Khare
出处
期刊:Proteins [Wiley]
卷期号:86 (3): 354-369 被引量:4
标识
DOI:10.1002/prot.25445
摘要

Abstract The computational design of novel nested proteins—in which the primary structure of one protein domain (insert) is flanked by the primary structure segments of another (parent)—would enable the generation of multifunctional proteins. Here we present a new algorithm, called Loop‐Directed Domain Insertion (LooDo), implemented within the Rosetta software suite, for the purpose of designing nested protein domain combinations connected by flexible linker regions. Conformational space for the insert domain is sampled using large libraries of linker fragments for linker‐to‐parent domain superimposition followed by insert‐to‐linker superimposition. The relative positioning of the two domains (treated as rigid bodies) is sampled efficiently by a grid‐based, mutual placement compatibility search. The conformations of the loop residues, and the identities of loop as well as interface residues, are simultaneously optimized using a generalized kinematic loop closure algorithm and Rosetta EnzymeDesign, respectively, to minimize interface energy. The algorithm was found to consistently sample near‐native conformations and interface sequences for a benchmark set of structurally similar but functionally divergent domain‐inserted enzymes from the α/β hydrolase superfamily, and discriminates well between native and nonnative conformations and sequences, although loop conformations tended to deviate from the native conformations. Furthermore, in cross‐domain placement tests, native insert‐parent domain combinations were ranked as the best‐scoring structures compared to nonnative domain combinations. This algorithm should be broadly applicable to the design of multi‐domain protein complexes with any combination of inserted or tandem domain connections.
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
秋澄完成签到 ,获得积分10
1秒前
2秒前
时光中的微粒完成签到 ,获得积分10
3秒前
lixiaorui发布了新的文献求助10
3秒前
科研通AI2S应助山沟沟采纳,获得10
4秒前
百浪多息完成签到,获得积分10
6秒前
LL完成签到 ,获得积分10
6秒前
呼呼呼完成签到,获得积分10
6秒前
今后应助多情山蝶采纳,获得10
6秒前
6秒前
Ming完成签到,获得积分10
7秒前
geats发布了新的文献求助10
7秒前
9秒前
10秒前
果冻呀完成签到,获得积分10
10秒前
12秒前
13秒前
小马甲应助一个小胖子采纳,获得10
16秒前
完美世界应助TTUTT采纳,获得10
16秒前
18秒前
lixiaorui发布了新的文献求助10
20秒前
歪比巴卜发布了新的文献求助10
20秒前
悲凉的大有完成签到,获得积分10
21秒前
0128lun发布了新的文献求助10
23秒前
上上签完成签到,获得积分10
23秒前
细心怀亦完成签到 ,获得积分10
23秒前
星之茧发布了新的文献求助10
25秒前
26秒前
废H发布了新的文献求助10
26秒前
26秒前
歪比巴卜完成签到,获得积分10
29秒前
29秒前
土豆完成签到,获得积分20
31秒前
多情山蝶发布了新的文献求助10
31秒前
水水的完成签到 ,获得积分10
32秒前
恸哭的千鸟完成签到 ,获得积分10
32秒前
隐形曼青应助jiajia采纳,获得10
32秒前
XHL发布了新的文献求助10
34秒前
35秒前
35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
List of 1,091 Public Pension Profiles by Region 1581
以液相層析串聯質譜法分析糖漿產品中活性雙羰基化合物 / 吳瑋元[撰] = Analysis of reactive dicarbonyl species in syrup products by LC-MS/MS / Wei-Yuan Wu 1000
Current Trends in Drug Discovery, Development and Delivery (CTD4-2022) 800
Biology of the Reptilia. Volume 21. Morphology I. The Skull and Appendicular Locomotor Apparatus of Lepidosauria 600
The Scope of Slavic Aspect 600
Foregrounding Marking Shift in Sundanese Written Narrative Segments 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5536900
求助须知:如何正确求助?哪些是违规求助? 4624585
关于积分的说明 14592312
捐赠科研通 4565008
什么是DOI,文献DOI怎么找? 2502121
邀请新用户注册赠送积分活动 1480851
关于科研通互助平台的介绍 1452093