Alanine scanning of the yeast killer toxin K2 reveals key residues for activity, gain-of-function variants, and supports prediction of precursor processing and 3D structure
{"title":"Alanine scanning of the yeast killer toxin K2 reveals key residues for activity, gain-of-function variants, and supports prediction of precursor processing and 3D structure","authors":"Rianne C. Prins , Tycho Marinus , Eyal Dafni , Iftach Yacoby , Sonja Billerbeck","doi":"10.1016/j.yjsbx.2025.100142","DOIUrl":null,"url":null,"abstract":"<div><div>Yeast killer toxins (YKTs) are antimicrobial proteins secreted by yeast with potential applications ranging from food preservation to therapeutic agents in human health. However, the practical use of many YKTs is limited by specific pH requirements, low temperature stability, low production yields, and narrow target specificity. While protein engineering could potentially overcome these challenges, progress is hindered by a lack of detailed knowledge about sequence-function relationships and structural data for these often multi-step processed proteins. In this study, we focused on the YKT K2, encoded by the M2 satellite dsRNA in <em>Saccharomyces cerevisiae</em>. Using alanine scanning mutagenesis of the full open reading frame and structure predictions combined with molecular dynamics simulations, we generated a comprehensive sequence-structure–function map, refined the model for the proteolytic processing of the K2 precursor, and predicted the mature toxin structure. Our findings also demonstrate that K2 can be engineered toward enhanced toxicity and altered target specificity through single-site mutations. Furthermore, we identified structural homology between K2 and other killer toxins, including the SMK toxin from the yeast <em>Millerozyma farinosa</em>. Our cost-effective workflow provides a platform to broadly map YKT sequence-structure–function relationships.</div></div>","PeriodicalId":17238,"journal":{"name":"Journal of Structural Biology: X","volume":"13 ","pages":"Article 100142"},"PeriodicalIF":5.1000,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Structural Biology: X","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590152425000236","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/12/18 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Yeast killer toxins (YKTs) are antimicrobial proteins secreted by yeast with potential applications ranging from food preservation to therapeutic agents in human health. However, the practical use of many YKTs is limited by specific pH requirements, low temperature stability, low production yields, and narrow target specificity. While protein engineering could potentially overcome these challenges, progress is hindered by a lack of detailed knowledge about sequence-function relationships and structural data for these often multi-step processed proteins. In this study, we focused on the YKT K2, encoded by the M2 satellite dsRNA in Saccharomyces cerevisiae. Using alanine scanning mutagenesis of the full open reading frame and structure predictions combined with molecular dynamics simulations, we generated a comprehensive sequence-structure–function map, refined the model for the proteolytic processing of the K2 precursor, and predicted the mature toxin structure. Our findings also demonstrate that K2 can be engineered toward enhanced toxicity and altered target specificity through single-site mutations. Furthermore, we identified structural homology between K2 and other killer toxins, including the SMK toxin from the yeast Millerozyma farinosa. Our cost-effective workflow provides a platform to broadly map YKT sequence-structure–function relationships.