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Titlebook: Biocombinatorial Approaches for Drug Finding; W. Wohlleben,T. Spellig,B. Müller-Tiemann Conference proceedings 2005 Springer-Verlag Berlin

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發(fā)表于 2025-3-25 03:38:06 | 只看該作者
Engineering Glycosylation in Bioactive Compounds by Combinatorial Biosynthesis,
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發(fā)表于 2025-3-25 08:43:28 | 只看該作者
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發(fā)表于 2025-3-25 11:46:58 | 只看該作者
From Glucose to Antibiotics: What Controls the Fluxes?,
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發(fā)表于 2025-3-25 18:34:45 | 只看該作者
Precursor-Directed Biosynthesis for the Generation of Novel Glycopetides,
25#
發(fā)表于 2025-3-25 22:59:20 | 只看該作者
26#
發(fā)表于 2025-3-26 02:00:44 | 只看該作者
Natural Product Biosynthetic Assembly Lines: Prospects and Challenges for Reprogramming,
27#
發(fā)表于 2025-3-26 04:41:04 | 只看該作者
Polyketide Synthases: Mechanisms and Models,ketide medicines. We are beginning to understand those features of subunit organization and structure and their linking and docking elements, which are critical for productive engineering efforts. Although mechanistic and specificity studies have shown that natural PKS domains are generally not best
28#
發(fā)表于 2025-3-26 12:22:57 | 只看該作者
Functional and Structural Basis for Targeted Modification of Non-Ribosomal Peptlde Synthetases,e chemistry, genetics and molecular biology are indispensable. The NRPSs can provide such interesting tools to generate and modify novel products. The recently gained structural and mechanistic information on NRPSs have made this class of multienzymes a powerful native tool box that would help to ac
29#
發(fā)表于 2025-3-26 13:05:55 | 只看該作者
Glycosyltransferases and Other Tailoring Enzymes as Tools for the Generation of Novel Compounds, these GTs show a remarkable flexibility towards the donor and the acceptor molecules making them most valuable for combinatorial biosynthesis. Future work is expected to focus on learning more about sugar biosynthesis, sugar modification and sugar attachment to support in vivo engineering of novel
30#
發(fā)表于 2025-3-26 18:07:55 | 只看該作者
Installing into an Existing Treet decade Artificial Intelligence (AI) has seen a rapid growth in adoption across a range of industry verticals such as automotive, telecommunications, aerospace, and health care. It has been acknowledged that while adoption of AI in the travel industry has been slow, the potential incremental value
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