Xin-Chun Chen , Xiang-Wei Kong , Pin Chen , Zi-Qian Li , Nan Huang , Zheng Zhao , Jie Yang , Ge-Xin Zhao , Qing Mo , Yu-Tong Lu , Xiao-Ming Huang , Guo-Kai Feng , Mu-Sheng Zeng
{"title":"设计并鉴定具有内在细胞渗透性的定义α-螺旋小蛋白。","authors":"Xin-Chun Chen , Xiang-Wei Kong , Pin Chen , Zi-Qian Li , Nan Huang , Zheng Zhao , Jie Yang , Ge-Xin Zhao , Qing Mo , Yu-Tong Lu , Xiao-Ming Huang , Guo-Kai Feng , Mu-Sheng Zeng","doi":"10.1016/j.compbiolchem.2024.108271","DOIUrl":null,"url":null,"abstract":"<div><div>Proteins with intrinsic cell permeability that can access intracellular targets represent a promising strategy for novel drug development; however, a general design principle is still lacking. Here, we established a library of 46,678 <em>de novo</em>-designed mini-proteins and performed cell permeability screening via phage display. Analyses revealed a characteristic neighboring distribution of positive charges across helices among enriched mini-proteins of CPP7, CPP11, CPP55, CPP109 and CPP112. Compared with the state-of-the-art cell-penetrating mini-protein ZF5.3, the optimized mini-protein CPP11D36R exhibited a sevenfold increase in cell permeability. Endocytosis uptake and early endosome release are the key penetrating mechanisms. A machine learning model with high-throughput data achieved an F1 score of 0.41, significantly outperforming the previously reported CPP prediction models, including MLACP, CPPpred and CellPPD, by 41 %. Overall, our findings validate the effectiveness of a helical structure with a cationic distribution as a design principle on a large scale and present a robust approach for the development of cell-permeable mini-protein drugs.</div></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":"113 ","pages":"Article 108271"},"PeriodicalIF":2.6000,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design and characterization of defined alpha-helix mini-proteins with intrinsic cell permeability\",\"authors\":\"Xin-Chun Chen , Xiang-Wei Kong , Pin Chen , Zi-Qian Li , Nan Huang , Zheng Zhao , Jie Yang , Ge-Xin Zhao , Qing Mo , Yu-Tong Lu , Xiao-Ming Huang , Guo-Kai Feng , Mu-Sheng Zeng\",\"doi\":\"10.1016/j.compbiolchem.2024.108271\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Proteins with intrinsic cell permeability that can access intracellular targets represent a promising strategy for novel drug development; however, a general design principle is still lacking. Here, we established a library of 46,678 <em>de novo</em>-designed mini-proteins and performed cell permeability screening via phage display. Analyses revealed a characteristic neighboring distribution of positive charges across helices among enriched mini-proteins of CPP7, CPP11, CPP55, CPP109 and CPP112. Compared with the state-of-the-art cell-penetrating mini-protein ZF5.3, the optimized mini-protein CPP11D36R exhibited a sevenfold increase in cell permeability. Endocytosis uptake and early endosome release are the key penetrating mechanisms. A machine learning model with high-throughput data achieved an F1 score of 0.41, significantly outperforming the previously reported CPP prediction models, including MLACP, CPPpred and CellPPD, by 41 %. Overall, our findings validate the effectiveness of a helical structure with a cationic distribution as a design principle on a large scale and present a robust approach for the development of cell-permeable mini-protein drugs.</div></div>\",\"PeriodicalId\":10616,\"journal\":{\"name\":\"Computational Biology and Chemistry\",\"volume\":\"113 \",\"pages\":\"Article 108271\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Biology and Chemistry\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1476927124002597\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Biology and Chemistry","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1476927124002597","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
Design and characterization of defined alpha-helix mini-proteins with intrinsic cell permeability
Proteins with intrinsic cell permeability that can access intracellular targets represent a promising strategy for novel drug development; however, a general design principle is still lacking. Here, we established a library of 46,678 de novo-designed mini-proteins and performed cell permeability screening via phage display. Analyses revealed a characteristic neighboring distribution of positive charges across helices among enriched mini-proteins of CPP7, CPP11, CPP55, CPP109 and CPP112. Compared with the state-of-the-art cell-penetrating mini-protein ZF5.3, the optimized mini-protein CPP11D36R exhibited a sevenfold increase in cell permeability. Endocytosis uptake and early endosome release are the key penetrating mechanisms. A machine learning model with high-throughput data achieved an F1 score of 0.41, significantly outperforming the previously reported CPP prediction models, including MLACP, CPPpred and CellPPD, by 41 %. Overall, our findings validate the effectiveness of a helical structure with a cationic distribution as a design principle on a large scale and present a robust approach for the development of cell-permeable mini-protein drugs.
期刊介绍:
Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered.
Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered.
Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.