亚科
隐马尔可夫模型
计算生物学
计算机科学
序列(生物学)
生物
遗传学
人工智能
基因
作者
Dominik Gront,Khajamohiddin Syed,David R. Nelson
出处
期刊:Protein Science
[Wiley]
日期:2025-02-19
卷期号:34 (3): e70057-e70057
被引量:4
摘要
Abstract 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.
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