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  • 标题:IMPROvER: the Integral Membrane Protein Stability Selector
  • 本地全文:下载
  • 作者:Steven P. D. Harborne ; Jannik Strauss ; Jessica C. Boakes
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2020
  • 卷号:10
  • 期号:1
  • DOI:10.1038/s41598-020-71744-x
  • 出版社:Springer Nature
  • 摘要:Identifying stabilising variants of membrane protein targets is often required for structure determination. Our new computational pipeline, the Integral Membrane Protein Stability Selector (IMPROvER) provides a rational approach to variant selection by employing three independent approaches: deep-sequence, model-based and data-driven. In silico tests using known stability data, and in vitro tests using three membrane protein targets with 7, 11 and 16 transmembrane helices provided measures of success. In vitro, individual approaches alone all identified stabilising variants at a rate better than expected by random selection. Low numbers of overlapping predictions between approaches meant a greater success rate was achieved (fourfold better than random) when approaches were combined and selections restricted to the highest ranked sites. The mix of information IMPROvER uses can be extracted for any helical membrane protein. We have developed the first general-purpose tool for selecting stabilising variants of $$\upalpha$$ -helical membrane proteins, increasing efficiency and reducing workload. IMPROvER can be accessed at http://improver.ddns.net/IMPROvER/ .
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