Crysalis: an integrated server for computational analysis and design of protein crystallization
文献类型：期刊论文
| 作者 | Wang, Huilin1; Feng, Liubin1; Zhang, Ziding2; Webb, Geoffrey I.3; Lin, Donghai1; Song, Jiangning3,4,5 |
| 刊名 | SCIENTIFIC REPORTS
 |
| 出版日期 | 2016-02-24 |
| 卷号 | 6 |
| 英文摘要 | The failure of multi-step experimental procedures to yield diffraction-quality crystals is a major bottleneck in protein structure determination. Accordingly, several bioinformatics methods have been successfully developed and employed to select crystallizable proteins. Unfortunately, the majority of existing in silico methods only allow the prediction of crystallization propensity, seldom enabling computational design of protein mutants that can be targeted for enhancing protein crystallizability. Here, we present Crysalis, an integrated crystallization analysis tool that builds on support-vector regression (SVR) models to facilitate computational protein crystallization prediction, analysis, and design. More specifically, the functionality of this new tool includes: (1) rapid selection of target crystallizable proteins at the proteome level, (2) identification of site non-optimality for protein crystallization and systematic analysis of all potential single-point mutations that might enhance protein crystallization propensity, and (3) annotation of target protein based on predicted structural properties. We applied the design mode of Crysalis to identify site non-optimality for protein crystallization on a proteome-scale, focusing on proteins currently classified as non-crystallizable. Our results revealed that site non-optimality is based on biases related to residues, predicted structures, physicochemical properties, and sequence loci, which provides in-depth understanding of the features influencing protein crystallization. Crysalis is freely available at http://nmrcen.xmu.edu.cn/crysalis/. |
| WOS标题词 | Science & Technology |
| 类目[WOS] | Multidisciplinary Sciences |
| 研究领域[WOS] | Science & Technology - Other Topics |
| 关键词[WOS] | AMINO-ACID PAIRS ; PROPENSITY PREDICTION ; WEB SERVER ; STRUCTURAL GENOMICS ; GENE SYNTHESIS ; RANDOM FOREST ; SEQUENCE ; FEATURES ; SITES ; TARGETS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000370744300001 |
| 源URL | [http://124.16.173.210/handle/834782/1537]  |
| 专题 | 天津工业生物技术研究所_结构生物信息学和整合系统生物学实验室 宋江宁_期刊论文 |
| 作者单位 | 1.Xiamen Univ, Coll Chem & Chem Engn, Dept Biol Chem, Xiamen 361005, Peoples R China 2.China Agr Univ, Coll Biol Sci, State Key Lab Agrobiotechnol, Beijing 100193, Peoples R China 3.Monash Univ, Fac Informat Technol, Monash Ctr Data Sci, Melbourne, Vic 3800, Australia 4.Monash Univ, Sch Biomed Sci, Dept Microbiol, Melbourne, Vic 3800, Australia 5.Chinese Acad Sci, Tianjin Inst Ind Biotechnol, Natl Engn Lab Ind Enzymes, Tianjin 300308, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Huilin,Feng, Liubin,Zhang, Ziding,et al. Crysalis: an integrated server for computational analysis and design of protein crystallization[J]. SCIENTIFIC REPORTS,2016,6. |
| APA | Wang, Huilin,Feng, Liubin,Zhang, Ziding,Webb, Geoffrey I.,Lin, Donghai,&Song, Jiangning.(2016).Crysalis: an integrated server for computational analysis and design of protein crystallization.SCIENTIFIC REPORTS,6. |
| MLA | Wang, Huilin,et al."Crysalis: an integrated server for computational analysis and design of protein crystallization".SCIENTIFIC REPORTS 6(2016). |
入库方式： OAI收割
来源：天津工业生物技术研究所
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