{"title":"使用P450Atlas探索P450超家族多样性-用于自动亚家族分配的在线工具。","authors":"Dominik Gront, Khajamohiddin Syed, David R Nelson","doi":"10.1002/pro.70057","DOIUrl":null,"url":null,"abstract":"<p><p>Cytochrome P450 monooxygenases (CYPs/P450s) are heme-containing enzymes known to biology for more than six decades. Their stereo- and regio-specific enzymatic activities on various compounds led to exploring their potential in almost all areas of life. The P450 superfamily, encompassing nearly 10,000 known families, boasts a staggering diversity represented by numerous families, highlighting its immense scale within the realm of enzymes. In this contribution, we describe the P450Atlas website: the ultimate source of information about all named P450 families and subfamilies. The website's main functionality is the automated assignment of a query sequence to one of the known subfamilies. The new subfamily assignment algorithm relies on Hidden Markov Models (HMM) and has been extensively tested and compared to an approach based on the BLAST program. Extensive validation shows that the HMM approach is more sensitive than the latter one, offering almost perfect automated P450 sequence assignment to subfamilies. A user can also browse and search through the online list of families across the Tree of Life. We believe that the P450Atlas website (https://p450atlas.org) will become a comprehensive and unified source of information on cytochrome 450 nomenclature.</p>","PeriodicalId":20761,"journal":{"name":"Protein Science","volume":"34 3","pages":"e70057"},"PeriodicalIF":4.5000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11837033/pdf/","citationCount":"0","resultStr":"{\"title\":\"Exploring P450 superfamily diversity with P450Atlas - Online tool for automated subfamily assignment.\",\"authors\":\"Dominik Gront, Khajamohiddin Syed, David R Nelson\",\"doi\":\"10.1002/pro.70057\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Cytochrome P450 monooxygenases (CYPs/P450s) are heme-containing enzymes known to biology for more than six decades. Their stereo- and regio-specific enzymatic activities on various compounds led to exploring their potential in almost all areas of life. The P450 superfamily, encompassing nearly 10,000 known families, boasts a staggering diversity represented by numerous families, highlighting its immense scale within the realm of enzymes. In this contribution, we describe the P450Atlas website: the ultimate source of information about all named P450 families and subfamilies. The website's main functionality is the automated assignment of a query sequence to one of the known subfamilies. The new subfamily assignment algorithm relies on Hidden Markov Models (HMM) and has been extensively tested and compared to an approach based on the BLAST program. Extensive validation shows that the HMM approach is more sensitive than the latter one, offering almost perfect automated P450 sequence assignment to subfamilies. A user can also browse and search through the online list of families across the Tree of Life. We believe that the P450Atlas website (https://p450atlas.org) will become a comprehensive and unified source of information on cytochrome 450 nomenclature.</p>\",\"PeriodicalId\":20761,\"journal\":{\"name\":\"Protein Science\",\"volume\":\"34 3\",\"pages\":\"e70057\"},\"PeriodicalIF\":4.5000,\"publicationDate\":\"2025-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11837033/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Protein Science\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1002/pro.70057\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Protein Science","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1002/pro.70057","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Exploring P450 superfamily diversity with P450Atlas - Online tool for automated subfamily assignment.
Cytochrome P450 monooxygenases (CYPs/P450s) are heme-containing enzymes known to biology for more than six decades. Their stereo- and regio-specific enzymatic activities on various compounds led to exploring their potential in almost all areas of life. The P450 superfamily, encompassing nearly 10,000 known families, boasts a staggering diversity represented by numerous families, highlighting its immense scale within the realm of enzymes. In this contribution, we describe the P450Atlas website: the ultimate source of information about all named P450 families and subfamilies. The website's main functionality is the automated assignment of a query sequence to one of the known subfamilies. The new subfamily assignment algorithm relies on Hidden Markov Models (HMM) and has been extensively tested and compared to an approach based on the BLAST program. Extensive validation shows that the HMM approach is more sensitive than the latter one, offering almost perfect automated P450 sequence assignment to subfamilies. A user can also browse and search through the online list of families across the Tree of Life. We believe that the P450Atlas website (https://p450atlas.org) will become a comprehensive and unified source of information on cytochrome 450 nomenclature.
期刊介绍:
Protein Science, the flagship journal of The Protein Society, is a publication that focuses on advancing fundamental knowledge in the field of protein molecules. The journal welcomes original reports and review articles that contribute to our understanding of protein function, structure, folding, design, and evolution.
Additionally, Protein Science encourages papers that explore the applications of protein science in various areas such as therapeutics, protein-based biomaterials, bionanotechnology, synthetic biology, and bioelectronics.
The journal accepts manuscript submissions in any suitable format for review, with the requirement of converting the manuscript to journal-style format only upon acceptance for publication.
Protein Science is indexed and abstracted in numerous databases, including the Agricultural & Environmental Science Database (ProQuest), Biological Science Database (ProQuest), CAS: Chemical Abstracts Service (ACS), Embase (Elsevier), Health & Medical Collection (ProQuest), Health Research Premium Collection (ProQuest), Materials Science & Engineering Database (ProQuest), MEDLINE/PubMed (NLM), Natural Science Collection (ProQuest), and SciTech Premium Collection (ProQuest).