解释-2-应用和前景 Clinical trial AMPs Indication Deliever Status identifiers Daptomyein Bacterial skin infections Intravenous Approved NCT01211470 Vancomycin Staphylococcal infections Intravenous Approved NCT00175370 Dalbavancin(B1397,Dalvance.Xydalba) Acute bacterial skin infections Intravenous Approved NCT03233438 Colistin Multidrug-resistant Gram-negative infections Intravenous Approved NCT03397914 Antibacterial and anti-inflammatory drugs 成本高 MP Antiviral dngs Skin acre and medical cosmetology 稳定性差 Medical tissue engincenng Anticancer drug Drug delivery syster 生物毒性 Protein Pept Lett.2019:26(2):79-87
解释-2 --- 应用和前景 成本高 稳定性差 生物毒性 严禁复制
解释3--生物合成及其它表达 Medical Application (a)Assembly of viral vectors 回点芯 APO Antibactedal& Biosynthesis anti-inflammatory 分泌胞外 Llactis Skin care (d)7 days incubation for Antiviral drugs E.coli AMPs medical (b)Growing plants and biomass growth cosmetology bacteria 莱茵依藻 Agroinfiltration Yeast 酿酒、毕赤酵母 Medical tissue engi (g)Peptide purification (e)Harvestin Drug delivery system (Extraction 降低成本 Protein Pept Lett.2019:26(2):79-87
解释-3 --- 生物合成及其它表达 分泌胞外 酿酒、毕赤酵母 莱茵依藻 降低成本 严禁复制
思考基因编辑+抗菌肽？ 特a学 Transformation Appropriate in bacteria cloning vector Recombinant expression CRISPR-Cas9. of AMP DTMA Transformation in yeast DNA sequence Target containing gene Cloned gene for AMP encoding vector Double AMP Transformation Transgenic stranded in plants expression @出▣ DNA of AMP break 岗H Figure 1 Dg Dacovery br Integrating CRISPR-Cas9 based gene editing with existing genetic engineering approaches for production of novel antimicrobial peptides AMPs 7 AMPs-gRNA gRNA Cas9 Mammal cells In vitro transcription Electroporation 约 基因编辑手段构建、改造 Protein Pept Lett.2019:26(2):79-87
思考 基因编辑 + 抗菌肽？ 基因编辑手段构建、改造 严禁复制
解释-4--如何预测设计序列？ >Med Biol Eng Comput..2021Now59(11-122397-2408.dot10.1007/s11517-021-02443-6. Epub 2021 Oct 11. Data Autoencoder Autoencoder Controlled In silico Machine learning-enabled predictive modeling to training evaluation generation screening precisely identify the antimicrobial peptides Mushtaq Ahmad Wani1,Prabha Garg 2,Kuldeep K Roy34 Discovery of novel,safe and Synthesis and testing broad-spectrum AMPs (wet laboratory) Affiliations expand PMlD:34632545D0:10.1007/s11517-021-02443-6 Abstract The ubiquitous antimicrobial peptides(AMPs),with a broad range of antimicrobial activities,represent a great promise for combating the multi-drug resistant infections.In this study,using a large and diverse set of AMPs (2638)and non-AMPs(3700),we have explored a variety of machine learning classifiers to build in silico models for AMP prediction,including Random Forest(RF).k-Nearest Neighbors(k-NN).Support Vector Machine (SVM)Decision Tree (OT Naive Bayes (NB).Quadratic Discriminant Analysis (QDA),and ensemble leaming.Among the various models generated,the RF classifier-based model top-performed in both the intemal [Accuracy:91.40%,Precision:89.37%. Sensitivity:90.05%and Specificity:92.36%]and external validations [Accuracy:89.43%,Precision Natural AMPs Novel AMPs 88.929,Sensitivity:85.21%,and Specificity:92.43%].In addition,the RF classifier-based model correctly predicted the known AMPs and non-AMPs:those kept aside as an additional external validation set.The performance assessment revealed three features viz.ChargeD2001,PAAC12 (pseudo amino acid composition).and polarity T13 that are likely to play vital roles in the antimicrobial activity of AMPs.The developed RF-based classification model may further be useful in the design and prediction of the novel potential AMPs. 计算机辅助及人工智能设计 改善稳定性等 Protein Pept Lett.2019:26(2):79-87
解释-4 --- 如何预测设计序列？ 计算机辅助及人工智能设计 改善稳定性等 严禁复制
内容 2.1.1氨基酸结构 2.1.2多肽 2.1蛋白质分子 2.1.3蛋白质 2.2核酸分子 2.3多糖分子
内容 2.1.1 氨基酸结构 2.1.3 蛋白质 2.1 蛋白质分子 2.2 核酸分子 2.1.2 多肽 2.3 多糖分子 严禁复制