{"title":"探索超分子多肽材料的化学空间和结构多样性","authors":"Mengyue Zhu, Jing Chen, Yiyang Lin","doi":"10.1016/j.supmat.2022.100030","DOIUrl":null,"url":null,"abstract":"<div><p>Searching chemical space and expanding the structural diversity of supramolecular self-assembly based on the development of combinatorial libraries is significant to the guided design of bio-inspired materials. Here we discuss the peptide self-assembly into a diversity of nanostructures, as well as their network organization into macroscopic hydrogel using secondary structures of α-helix, β-sheet, and coiled-coil peptides. In particular, we highlight the recent advances in developing computational and experimental tools to explore the vast combinatorial space, uncover structure-activity relationships and identify the factors that determine peptide self-assembly. We envision that the integration of newly developed techniques such as high throughput screening, automated flow chemistry, and machine learning into the screening of peptide libraries will offer new opportunities to discover peptide-based functional materials.</p></div>","PeriodicalId":101187,"journal":{"name":"Supramolecular Materials","volume":"2 ","pages":"Article 100030"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Exploring chemical space and structural diversity of supramolecular peptide materials\",\"authors\":\"Mengyue Zhu, Jing Chen, Yiyang Lin\",\"doi\":\"10.1016/j.supmat.2022.100030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Searching chemical space and expanding the structural diversity of supramolecular self-assembly based on the development of combinatorial libraries is significant to the guided design of bio-inspired materials. Here we discuss the peptide self-assembly into a diversity of nanostructures, as well as their network organization into macroscopic hydrogel using secondary structures of α-helix, β-sheet, and coiled-coil peptides. In particular, we highlight the recent advances in developing computational and experimental tools to explore the vast combinatorial space, uncover structure-activity relationships and identify the factors that determine peptide self-assembly. We envision that the integration of newly developed techniques such as high throughput screening, automated flow chemistry, and machine learning into the screening of peptide libraries will offer new opportunities to discover peptide-based functional materials.</p></div>\",\"PeriodicalId\":101187,\"journal\":{\"name\":\"Supramolecular Materials\",\"volume\":\"2 \",\"pages\":\"Article 100030\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Supramolecular Materials\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S266724052200023X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Supramolecular Materials","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S266724052200023X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exploring chemical space and structural diversity of supramolecular peptide materials
Searching chemical space and expanding the structural diversity of supramolecular self-assembly based on the development of combinatorial libraries is significant to the guided design of bio-inspired materials. Here we discuss the peptide self-assembly into a diversity of nanostructures, as well as their network organization into macroscopic hydrogel using secondary structures of α-helix, β-sheet, and coiled-coil peptides. In particular, we highlight the recent advances in developing computational and experimental tools to explore the vast combinatorial space, uncover structure-activity relationships and identify the factors that determine peptide self-assembly. We envision that the integration of newly developed techniques such as high throughput screening, automated flow chemistry, and machine learning into the screening of peptide libraries will offer new opportunities to discover peptide-based functional materials.