{"title":"利用组合特征分析从低温电镜密度图中得到的原子结构。","authors":"Lin Chen, Jing He","doi":"10.1145/3233547.3233709","DOIUrl":null,"url":null,"abstract":"<p><p>Cryo-electron microscopy (cryo-EM) has become a major technique for protein structure determination. Many atomic structures have been derived from cryo-EM density maps of about 3Å resolution. Side-chain conformations are well determined in density maps with super-resolutions such as 1-2Å. It is desirable to have a statistical method to detect anomalous side-chains without a super-resolution density map. In this study, we analyzed structures derived from X-ray density maps with higher than 1.5Å resolution and those from cryo-EM density maps with 2-4 Å and 4-6 Å resolutions respectively. We introduce a histogram-based outlier score (HBOS) for anomaly detection in protein models built from cryo-EM density maps. This method uses the statistics derived from X-ray dataset (<1.5Å) as the reference and combines five features involving the distal block distance, side-chain length, phi, psi, and first chi angle of the residue. Higher percentages of anomalies were observed in the cryo-EM models than in the super-resolution X-ray models. Lower percentages of anomalies were observed in cryo-EM models derived after January 2017 than those derived before 2017.</p>","PeriodicalId":72044,"journal":{"name":"ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3233547.3233709","citationCount":"3","resultStr":"{\"title\":\"Using Combined Features to Analyze Atomic Structures Derived from Cryo-EM Density Maps.\",\"authors\":\"Lin Chen, Jing He\",\"doi\":\"10.1145/3233547.3233709\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Cryo-electron microscopy (cryo-EM) has become a major technique for protein structure determination. Many atomic structures have been derived from cryo-EM density maps of about 3Å resolution. Side-chain conformations are well determined in density maps with super-resolutions such as 1-2Å. It is desirable to have a statistical method to detect anomalous side-chains without a super-resolution density map. In this study, we analyzed structures derived from X-ray density maps with higher than 1.5Å resolution and those from cryo-EM density maps with 2-4 Å and 4-6 Å resolutions respectively. We introduce a histogram-based outlier score (HBOS) for anomaly detection in protein models built from cryo-EM density maps. This method uses the statistics derived from X-ray dataset (<1.5Å) as the reference and combines five features involving the distal block distance, side-chain length, phi, psi, and first chi angle of the residue. Higher percentages of anomalies were observed in the cryo-EM models than in the super-resolution X-ray models. Lower percentages of anomalies were observed in cryo-EM models derived after January 2017 than those derived before 2017.</p>\",\"PeriodicalId\":72044,\"journal\":{\"name\":\"ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1145/3233547.3233709\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3233547.3233709\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3233547.3233709","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using Combined Features to Analyze Atomic Structures Derived from Cryo-EM Density Maps.
Cryo-electron microscopy (cryo-EM) has become a major technique for protein structure determination. Many atomic structures have been derived from cryo-EM density maps of about 3Å resolution. Side-chain conformations are well determined in density maps with super-resolutions such as 1-2Å. It is desirable to have a statistical method to detect anomalous side-chains without a super-resolution density map. In this study, we analyzed structures derived from X-ray density maps with higher than 1.5Å resolution and those from cryo-EM density maps with 2-4 Å and 4-6 Å resolutions respectively. We introduce a histogram-based outlier score (HBOS) for anomaly detection in protein models built from cryo-EM density maps. This method uses the statistics derived from X-ray dataset (<1.5Å) as the reference and combines five features involving the distal block distance, side-chain length, phi, psi, and first chi angle of the residue. Higher percentages of anomalies were observed in the cryo-EM models than in the super-resolution X-ray models. Lower percentages of anomalies were observed in cryo-EM models derived after January 2017 than those derived before 2017.