From 825251953913f72e451f8e17c88ef4bd3c5ede10 Mon Sep 17 00:00:00 2001
From: Leiwei <47361617+BlueShark002@users.noreply.github.com>
Date: Mon, 7 Oct 2024 10:15:28 +0800
Subject: [PATCH] Update index.md
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docs/index.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
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@@ -8,4 +8,4 @@ Extremophiles, known for their ability to thrive in extreme environments, are va
In response, we developed iExtreme, a comprehensive database containing 1,030 genomes of extremophiles across three categories, alongside a deep learning method for their identification. This method achieved an accuracy of up to 0.99 in predicting extremophile living conditions. Through **iExtreme**, we identified 520 previously unknown extremophilic species and 4,419 extremophilic genomes from various databases. Additionally, we utilized structure-based clustering to discover novel D-psicose 3-epimerases (DPEase) and α-amylases. To further enhance enzyme activity, we developed a directed evolution method using phage-assisted non-continuous evolution in droplets. The evolved DPEase demonstrated a 3-fold increase in activity, a 5.4-fold extension in half-life, and achieved the highest reported yield of 243 g/L D-allulose.
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