来自用户 李翛然 的文献。
当前共找到 40 篇文献分享,本页显示第 1 - 20 篇。
1.
李翛然 (2025-05-30 21:13):
#paper NMRExtractor: leveraging large language models to construct an experimental NMR database from open-source scienti c publications† DOI: 10.1039/D4SC08802F 中国科学院上海药物研究所郑明月团队开发了NMRExtractor工具,基于微调的大型语言模型(Mistral-7b)从570万篇PubMed开源文献中自动提取实验核磁共振(NMR)数据,构建了目前规模最大的公开NMR数据库NMRBank,包含225,809条高质量记录。 1. 高效提取流程 ◦ 通过正则表达式筛选含NMR的段落(380,220条),利用LLM精准提取化合物IUPAC名称、1H/13C NMR化学位移及实验条件。 ◦ 引入置信度评分机制(0-1分),高置信度(>0.8)数据准确率达97%,媲美人工标注水平。 最近在看各种仪器数据处理
Abstract:
NMRExtractor is a large language model-powered pipeline that automatically extracts experimental NMR data from massive open-access publications, resulting in the construction of NMRBank—the largest open-access NMR dataset available to date. >>>
NMRExtractor is a large language model-powered pipeline that automatically extracts experimental NMR data from massive open-access publications, resulting in the construction of NMRBank—the largest open-access NMR dataset available to date. <<<
翻译
2.
李翛然 (2025-04-30 10:14):
#paper Computational design of serine hydrolases doi:doi/10.1126/science.adu2454 baker今年的大文章,这周我精读了一下。 哈哈 接了一个活,和这个非常类似,不过比这个难。 需要化学+酶进化+新的工业级纯化方法。 非常非常好。 baker我觉得自从或诺奖后,全面开挂,一定要证明AI在设计结构生物学上不可撼动的作用,绝不是,生物或者化学专家说的,我也能干~~~哈哈哈 这篇文章写的非常好,逻辑非常舒服
Science, 2025-4-18. DOI: 10.1126/science.adu2454
Abstract:
The design of enzymes with complex active sites that mediate multistep reactions remains an outstanding challenge. With serine hydrolases as a model system, we combined the generative capabilities of RFdiffusion … >>>
The design of enzymes with complex active sites that mediate multistep reactions remains an outstanding challenge. With serine hydrolases as a model system, we combined the generative capabilities of RFdiffusion with an ensemble generation method for assessing active site preorganization at each step in the reaction to design enzymes starting from minimal active site descriptions. Experimental characterization revealed catalytic efficiencies ( k cat / K m ) up to 2.2 × 10 5 M −1 s −1 and crystal structures that closely match the design models (Cα root mean square deviations <1 angstrom). Selection for structural compatibility across the reaction coordinate enabled identification of new catalysts remove with five different folds distinct from those of natural serine hydrolases. Our de novo approach provides insight into the geometric basis of catalysis and a roadmap for designing enzymes that catalyze multistep transformations. <<<
翻译
3.
李翛然 (2025-03-31 10:04):
#paper doi:doi.org/10.1038/s41467-025-58038-4 Robust enzyme discovery and engineering with deep learning using CataPro. 深度学习赋能酶工程——CataPro模型 1. 研究背景与挑战 酶作为高效生物催化剂在工业中应用广泛,但野生酶性能不足且传统改造方法成本高、效率低。现有深度学习模型在酶动力学参数(如kcat、Km)预测中存在数据偏差和泛化能力不足的问题,阻碍了理性设计进程。 2. 模型创新与优势 研究团队开发的CataPro模型通过整合预训练语言模型(如ProtT5、MolT5)与分子指纹,显著提升了酶动力学参数的预测精度。其核心突破在于采用无偏十折交叉验证数据集(按序列相似性聚类划分),避免模型对训练数据的“记忆性”过拟合,泛化能力优于现有工具。 3. 实际应用验证 在香兰素生物合成案例中,CataPro成功挖掘出活性提升的SsCSO酶,并通过预测指导突变设计获得活性提高3.34倍的突变体。这一成果展示了模型在酶定向进化与工业酶库筛选中的实用性,为生物制造提供高效工具。 4. 局限与未来方向 当前模型对复杂催化机制的表征仍有不足,且kcat预测精度受限于数据覆盖度。未来需融合更多物理化学机制特征,并拓展反应类型数据以增强普适性。 5. 总结评价 CataPro通过深度学习与无偏数据策略的结合,为酶工程提供了高可信度预测工具,推动生物催化从经验驱动向数据驱动转型。其成功案例为绿色化工、合成生物学等领域的高效酶设计开辟了新路径,标志着AI在生物制造中的深度渗透。
Abstract:
Abstract Accurate prediction of enzyme kinetic parameters is crucial for enzyme exploration and modification. Existing models face the problem of either low accuracy or poor generalization ability due to overfitting. … >>>
Abstract Accurate prediction of enzyme kinetic parameters is crucial for enzyme exploration and modification. Existing models face the problem of either low accuracy or poor generalization ability due to overfitting. In this work, we first developed unbiased datasets to evaluate the actual performance of these methods and proposed a deep learning model, CataPro, based on pre-trained models and molecular fingerprints to predict turnover number (k c a t ), Michaelis constant (K m ), and catalytic efficiency (k c a t /K m ). Compared with previous baseline models, CataPro demonstrates clearly enhanced accuracy and generalization ability on the unbiased datasets. In a representational enzyme mining project, by combining CataPro with traditional methods, we identified an enzyme (SsCSO) with 19.53 times increased activity compared to the initial enzyme (CSO2) and then successfully engineered it to improve its activity by 3.34 times. This reveals the high potential of CataPro as an effective tool for future enzyme discovery and modification. <<<
翻译
4.
李翛然 (2025-02-27 12:03):
#paper Biggest-ever AI biology model writes DNA on demand doi:https://doi.org/10.1038/d41586-025-00531-3 evo2 最近非常出名, 主要就是微软的ev2该研究可能开发了当前规模最大的基因组语言模型(Genomic Language Model, GLM),通过深度学习技术实现按需设计功能性DNA序列。其核心思路借鉴了大型语言模型(如ChatGPT)的自监督预训练方法,利用海量基因组数据学习DNA序列的“语法规则”,从而预测或生成具有特定调控功能的序列 。 虽然文章中揭示了bcra基因的突变相关影响基因。但是临床实践上,其实方法很多,暂时没有看出来哪些碾压的存在,倒是twitter讨论的很多,说是可以预测病毒突变,这个我有待观察。论文原文并没有提到这个
5.
李翛然 (2025-01-27 09:46):
#paper https://github.com/deepseek-ai/DeepSeek-R1/blob/main/DeepSeek_R1.pdf 最近最火的r1论文,好处就不说了,我说几个问题吧。 1 编程。 编程最大的问题是过渡理解? 就是简单的问题复杂化,无法精确快速匹配我需要的答案,这可能是深度思考造成的问题 2 过拟合。过拟合比较明显,就是个热门的学科和资料回答的很棒。冷门学科的横向联想能力有待提高。 整体来说未来可期!
6.
李翛然 (2024-12-27 13:05):
#paper DOI: 10.1093/database/baaa102 NPBS database: a chemical data resource with relational data between natural products and biological sources. Database 2020, baaa102. 一个天然产物数据库,最近我在研究天然产物的一些方案,发现上海药物所把世界上主要的天然产物搞了个数据集,这个还是不错的。给大家也推荐一下, 但是搜索还是没做好,还是字符串相似度搜索,拉丁翻译和中文对应的比较差劲。 应该上Vector search了。
Abstract:
Abstract NPBS (Natural Products & Biological Sources) database is a chemical data resource with relational data between natural products and biological sources, manually curated from literatures of natural product researches. … >>>
Abstract NPBS (Natural Products & Biological Sources) database is a chemical data resource with relational data between natural products and biological sources, manually curated from literatures of natural product researches. The relational data link a specific species and all the natural products derived from it and contrarily link a specific natural product and all the biological sources. The biological sources cover diverse species of plant, bacterial, fungal and marine organisms; the natural molecules have proper chemical structure data and computable molecular properties and all the relational data have corresponding references. NPBS database provides a wider choice of biological sources and can be used for dereplication to prevent re-isolation and re-characterization of already known natural products. Database URL: http://www.organchem.csdb.cn/scdb/NPBS <<<
翻译
7.
李翛然 (2024-11-28 11:23):
#paper Extraction of bioactive compounds from plant materials using combination of various novel methods: A review doi:https://doi.org/10.1016/j.tifs.2021.11.019 这文章不错,比较好的整理了植物提取物的方法,很适合化妆品市场。提取技术: 提取技术的选择对提取效率至关重要,影响因素包括提取技术、植物成分矩阵属性、提取溶剂、温度、压力和时间。 传统提取技术(如索氏提取、浸泡、水蒸气蒸馏等)与新颖技术(如超声辅助提取、脉冲电场辅助提取、超临界流体提取等)的比较。 新颖提取技术: 新颖技术因其环境友好性、操作时间短、提取效率高和质量改善而受到关注。 超声波辅助提取(UAE)、脉冲电场提取(PEF)、酶辅助提取(EAE)、微波辅助提取(MAE)、超临界流体提取(SFE)等技术的应用和优势。 组合提取技术: 结合使用不同的提取技术可以提高提取效率和选择性,例如超声-微波辅助提取(UMAE)、酶-超声-微波辅助提取(EUMAE)等。 这些组合技术可以更有效地从植物材料中提取生物活性化合物。 结论: 新颖提取技术能够在更短的时间内获得更大的提取产量、更好的产品质量,并减少环境问题。 越来越多的研究关注这些创新提取方法的组合使用,这些方法具有快速、方便和安全的优势。 文章强调了在提取植物材料中的生物活性化合物时,选择合适提取技术的重要性,并比较了不同方法的优缺点。同时,文章也指出了这些新颖提取技术在实际应用中仍需进一步开发和优化。
8.
李翛然 (2024-10-28 13:54):
#paper Modeling protein-small molecule conformational ensembles with ChemNet doi:10.1101/2024.09.25.614868 baker 又一力作,直接把我们最近正在想的共形几何问题引入蛋白质结构与小分子互作,已经直接实现出来了, 下一步其实就是把这个和Diffusion结合,那么小分子de-novo设计就可以完全自动化了。 baker帮我完成了50%的工作~~~
Abstract:
AbstractModeling the conformational heterogeneity of protein-small molecule systems is an outstanding challenge. We reasoned that while residue level descriptions of biomolecules are efficient for de novo structure prediction, for probing … >>>
AbstractModeling the conformational heterogeneity of protein-small molecule systems is an outstanding challenge. We reasoned that while residue level descriptions of biomolecules are efficient for de novo structure prediction, for probing heterogeneity of interactions with small molecules in the folded state an entirely atomic level description could have advantages in speed and generality. We developed a graph neural network called ChemNet trained to recapitulate correct atomic positions from partially corrupted input structures from the Cambridge Structural Database and the Protein Data Bank; the nodes of the graph are the atoms in the system. ChemNet accurately generates structures of diverse organic small molecules given knowledge of their atom composition and bonding, and given a description of the larger protein context, and builds up structures of small molecules and protein side chains for protein-small molecule docking. Because ChemNet is rapid and stochastic, ensembles of predictions can be readily generated to map conformational heterogeneity. In enzyme design efforts described here and elsewhere, we find that using ChemNet to assess the accuracy and pre-organization of the designed active sites results in higher success rates and higher activities; we obtain a preorganized retroaldolase with akcat/KMof 11000 M-1min- 1, considerably higher than any pre-deep learning design for this reaction. We anticipate that ChemNet will be widely useful for rapidly generating conformational ensembles of small molecule and small molecule-protein systems, and for designing higher activity preorganized enzymes. <<<
翻译
9.
李翛然 (2024-09-27 21:35):
#paper doi:10.13345/j.cjb.220582 《工程菌种自动化高通量编辑与筛选研究进展》该论文主要讨论了合成生物学领域中工程菌种的自动化高通量编辑与筛选技术的研究进展。合成生物学通过标准化和模块化生物实验对象、方法、技术和流程,创建自动化与高通量的合成生物铸造模式。 这种模式结合了复杂生物过程与自动化设施,颠覆了传统的劳动密集型研究方式,提高了技术迭代能力,促进了合成生物学的发展和产业化应用。 研究进展: 自动化基因编辑: 论文回顾了天津工业生物技术研究所在自动化高通量编辑与筛选领域的工作进展。 讨论了基因克隆、基因组编辑、编辑序列设计的自动化实现。 介绍了CRISPR/Cas9系统等基因编辑技术在自动化操作中的应用。 高通量筛选技术: 论文分析了流式细胞、液滴微流控、全基因组规模扰动测序等高通量筛选技术。 讨论了这些技术在筛选工程菌株中的应用和效果。 最近在读博,高级制药工程需要读中文论文…………
10.
李翛然 (2024-08-31 14:38):
#paper Development of Free Energy calculation methods for the study of monosaccharidesconformation in computer simulations Doi:10.3389/fmolb.2021.712085 六元环状单糖的褶皱构象开发新的计算工具来研究和描述在分子动力学模拟里碳水化合物的构象特性。 最重要的问题是力场选择问题,目前力场参数(GROMOS 45a4参数集),不能复现糖成分的偏好构象对葡萄糖构象的研究存在的困难: 无论从实验上(第二流行的构象极其少见的出现)和理论计算模拟上(构象由少数结构主导,导致非遍历性的性能瓶颈 因此加速采样方法比如 metadynamics其中集体变量(CV)和对应坐标系的选择很重要, 要考虑到分子环的非平面和褶皱构象 1. 采用了新的坐标系Cremer-Pole(θ,φ) 2. 采用了新的坐标系Strauss-Pickett(α1,α2,α3) 3. 采用了笛卡尔压缩的Cremer-Pole(qx,qy)
Abstract:
The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading … >>>
The grand challenge in structure-based drug design is achieving accurate prediction of binding free energies. Molecular dynamics (MD) simulations enable modeling of conformational changes critical to the binding process, leading to calculation of thermodynamic quantities involved in estimation of binding affinities. With recent advancements in computing capability and predictive accuracy, MD based virtual screening has progressed from the domain of theoretical attempts to real application in drug development. Approaches including the Molecular Mechanics Poisson Boltzmann Surface Area (MM-PBSA), Linear Interaction Energy (LIE), and alchemical methods have been broadly applied to model molecular recognition for drug discovery and lead optimization. Here we review the varied methodology of these approaches, developments enhancing simulation efficiency and reliability, remaining challenges hindering predictive performance, and applications to problems in the fields of medicine and biochemistry. <<<
翻译
11.
李翛然 (2024-07-30 20:10):
#paper DOI:10.1101/2023.08.08.552403 Identifying small-molecules binding sites in RNA conformational ensembles with SHAMAN 这篇文章怎么说呢,一看就是搞计算机人写的。我来说说为啥。 介绍了一种名为SHAMAN的计算技术,可以识别RNA结构集合中的潜在小分子结合位点。与依赖静态结构的其他计算工具不同,SHAMAN旨在解决RNA分子动态性带来的挑战。该技术通过分析RNA结构的构象集合,而不仅仅是单一静态结构,来识别潜在的结合位点。这种方法对于理解小分子与RNA柔性和动态性之间的相互作用特别有用。 这里面的关键点,是RNA的构象如何确定的,但是他是使用这个方法确定rna构象的: 1.使用分子动力学(MD)模拟来生成RNA的构象集合。论文中提到使用了Amber力场和TIP3P水模型进行了100 ns的MD模拟。 2.从MD轨迹中提取出具有代表性的RNA构象集合。作者使用了聚类算法来对MD轨迹进行聚类,选择了聚类中心作为代表性构象。 3. 这些代表性构象进行分析,识别小分子可能结合的位点。SHAMAN工具就是用来分析这些构象集合,预测小分子的可能结合位点。 这就很扯了, 用聚类的方法来选取最有可能的rna 结构,这不扯呢么! 邮箱TIP3P水模型就已经是生物容忍的最低限度了,居然在这个状态下模拟rna,然后用数学聚类的方法来选取构想。 有点扯!缺乏 实验室人员的嘲讽~~~哈哈
Abstract:
AbstractThe rational targeting of RNA with small molecules is hampered by our still limited understanding of RNA structural and dynamic properties. Mostin silicotools for binding site identification rely on static … >>>
AbstractThe rational targeting of RNA with small molecules is hampered by our still limited understanding of RNA structural and dynamic properties. Mostin silicotools for binding site identification rely on static structures and therefore cannot face the challenges posed by the dynamic nature of RNA molecules. Here, we present SHAMAN, a computational technique to identify potential small-molecule binding sites in RNA structural ensembles. SHAMAN enables exploring the conformational landscape of RNA with atomistic molecular dynamics and at the same time identifying RNA pockets in an efficient way with the aid of probes and enhanced-sampling techniques. In our benchmark composed of large, structured riboswitches as well as small, flexible viral RNAs, SHAMAN successfully identified all the experimentally resolved pockets and ranked them among the most favorite probe hotspots. Overall, SHAMAN sets a solid foundation for future drug design efforts targeting RNA with small molecules, effectively addressing the long-standing challenges in the field. <<<
翻译
12.
李翛然 (2024-06-28 14:45):
#paper: doi.org/10.1080/13543776.2024.2369630 Inhibition of GTPase KRASG12D: a review of patent literature 最近发了篇paper 专利回顾的。我们做了个国产替代, 药物上市太墨迹了,就用ai设计了一个荧光探针试剂盒,以后所有想做KRAS,以及KRAS的多突变药物的,直接买这个试剂盒可以测试药物活性,很方便,对标产品1.6万一盒,我们才6000. 国际上就我们2家。 欢迎大家采购。 核心原理不难,就是把一个对标的有效抑制剂,尾部挂上荧光探针,用AI把linker设计出来,再加一些好合成的条件。 今年这个AI也要发一个paper ,大家别急,带条件生成的ai,也是国际上第一个。另外预告一下,今年我们会用光量子计算机,设计蛋白质~~
Abstract:
INTRODUCTION: KRAS is a critical oncogenic protein intricately involved in tumor progression, and the difficulty in targeting KRAS has led it to be classified as an 'undruggable target.' Among the … >>>
INTRODUCTION: KRAS is a critical oncogenic protein intricately involved in tumor progression, and the difficulty in targeting KRAS has led it to be classified as an 'undruggable target.' Among the various KRAS mutations, KRASG12D is highly prevalent and represents a promising therapeutic target, yet there are currently no approved inhibitors for it.AREA COVERED: This review summarizes numerous patents and literature featuring inhibitors or degraders of KRASG12D through searching relevant information in PubMed, SciFinder and Web of Science databases from 2021 to February 2024, providing an overview of the research progress on inhibiting KRASG12D in terms of design strategies, chemical structures, biological activities, and clinical advancements.EXPERT OPINION: Since the approval of AMG510 (Sotorasib), there has been an increasing focus on the inhibition of KRASG12D, leading to numerous reports of related inhibitors and degraders. Among them, MRTX1133, as the first KRASG12D inhibitor to enter clinical trials, has demonstrated excellent tumor suppression in various KRASG12D-bearing human tumor xenograft models. It is important to note, however, that understanding the mechanisms of acquired resistance caused by KRAS inhibition and developing additional combination therapies is crucial. Moreover, seeking covalent inhibition of KRASG12D also holds significant potential. <<<
翻译
13.
李翛然 (2024-05-30 11:40):
#paper Alpha2beta1 integrin is the major collagen-binding integrin expressed on human Th17 https://doi.org/10.1002/eji.201040307 这篇论文研究了人类Th17细胞中胶原结合整合素α1β1和α2β1的表达和功能。主要发现如下: Th17细胞在分化过程中更倾向于上调α2β1整合素(也称为VLA-2),而不是α1β1整合素(VLA-1)。 大多数Th17细胞表达α2整合素亚基,而只有少数表达α1整合素亚基。 Th17细胞通过α2β1整合素粘附于I型和II型胶原,但不粘附于IV型胶原。 α2β1整合素与I型和II型胶原的结合可共刺激人类Th17细胞产生IL-17A、IL-17F和IFN-γ。 我说过很多次,胶原蛋白用作敷料和护肤品根本就不是为了透皮吸收!!!!!!!就是卡在细胞间就能起作用!!!!这帮白痴 ,气死我了!
Abstract:
Growing evidence indicates that collagen-binding integrins are important costimulatory molecules of effector T cells. In this study, we demonstrate that the major collagen-binding integrin expressed by human Th17 cells is … >>>
Growing evidence indicates that collagen-binding integrins are important costimulatory molecules of effector T cells. In this study, we demonstrate that the major collagen-binding integrin expressed by human Th17 cells is alpha2beta1 (α2β1) or VLA-2, also known as the receptor for collagen I on T cells. Our results show that human naïve CD4(+) T cells cultured under Th17 polarization conditions preferentially upregulate α2β1 integrin rather than α1β1 integrin, which is the receptor for collagen IV on T cells. Double staining analysis for integrin receptors and intracellular IL-17 showed that α2 integrin but not α1 integrin is associated with Th17 cells. Cell adhesion experiments demonstrated that Th17 cells attach to collagen I and collagen II using α2β1 integrin but did not attach to collagen IV. Functional studies revealed that collagens I and II but not collagen IV costimulate the production of IL-17A, IL-17F and IFN-γ by human Th17 cells activated with anti-CD3. These results identify α2β1 integrin as the major collagen receptor expressed on human Th17 cells and suggest that it can be an important costimulatory molecule of Th17 cell responses. <<<
翻译
14.
李翛然 (2024-04-28 18:09):
#paper doi:10. 1186/s42825-019-0012-x Nature Communication. Quantitative and structural analysis of isotopically labelled natural crosslinks in type I skin collagen using LC-HRMS and SANS 本文介绍了对使用LC-HRMS和SANS对标记同位素的天然交联物在I型皮肤胶原蛋白中进行定量和结构分析的研究。研究重点放在皮肤中的两种主要交联物HLNL和HHMD上,它们被同位素标记并进行分析,以了解它们的结构变化以及与硫酸铬的相互作用。研究强调了开发一种良性交联方法的重要性,以保留胶原蛋白的固有物理特性,特别是在皮革制造行业。主要发现包括确认HLNL和HHMD中各有一个亚胺基,使它们容易在低pH值下降解,并由于极端pH值变化和铬鞣制造导致胶原蛋白的结构变化。本研究使用的分析方法也可应用于研究其他胶原组织中的人工交联,用于生物医学应用。 这个算是人类第一篇弄清楚了胶原蛋白到底有哪些交联键~~所以化学交联的方法基本没戏,还是生物方法吧。~
Abstract:
Abstract Collagen structure in biological tissues imparts its intrinsic physical properties by the formation of several covalent crosslinks. For the first time, two major crosslinks in the skin dihydroxylysinonorleucine (HLNL) … >>>
Abstract Collagen structure in biological tissues imparts its intrinsic physical properties by the formation of several covalent crosslinks. For the first time, two major crosslinks in the skin dihydroxylysinonorleucine (HLNL) and histidinohydroxymerodesmosine (HHMD), were isotopically labelled and then analysed by liquid-chromatography high-resolution accurate-mass mass spectrometry (LC-HRMS) and small-angle neutron scattering (SANS). The isotopic labelling followed by LC-HRMS confirmed the presence of one imino group in both HLNL and HHMD, making them more susceptible to degrade at low pH. The structural changes in collagen due to extreme changes in the pH and chrome tanning were highlighted by the SANS contrast variation between isotopic labelled and unlabelled crosslinks. This provided a better understanding of the interaction of natural crosslinks with the chromium sulphate in collagen suggesting that the development of a benign crosslinking method can help retain the intrinsic physical properties of the leather. This analytical method can also be applied to study artificial crosslinking in other collagenous tissues for biomedical applications. Graphical abstract <<<
翻译
15.
李翛然 (2024-03-31 01:07):
#paper doi:doi.org/10.1021/acs.analchem.2c05065 RETURN TO ISSUEPREVARTICLENEXT Simultaneous Dual-Wavelength Source Raman Spectroscopy with a Handheld Confocal Probe for Analysis of the Chemical Composition of In Vivo Human Skin 介绍了一种便携式共焦拉曼光谱系统,具有同时双波长光源和迷你手持探头,用于分析体内人体皮肤的化学成分。该系统能够同时获取指纹区(450−1750 cm−1)和高波数区(2800−3800 cm−1)的光谱,解决了当前商用CRS系统的局限性。关键点包括创新设计结合671和785 nm激光、精确的拉曼光谱分离算法(PRSSA)用于解耦FP和HW光谱,以及数据采集时间减少超过50%。该系统在快速和超宽带光谱采集方面表现出色,显示了在临床工作流程中整合CRS的潜力。 最近可能搞个拉曼光谱仪做美容
IF:6.700Q1 Analytical chemistry, 2023-03-28. DOI: 10.1021/acs.analchem.2c05065 PMID: 36930570
Abstract:
Confocal Raman spectroscopy (CRS) is a powerful tool that has been widely used for biological tissue analysis because of its noninvasive nature, high specificity, and rich biochemical information. However, current … >>>
Confocal Raman spectroscopy (CRS) is a powerful tool that has been widely used for biological tissue analysis because of its noninvasive nature, high specificity, and rich biochemical information. However, current commercial CRS systems suffer from limited detection regions (450-1750 cm), bulky sizes, nonflexibilities, slow acquisitions by consecutive excitations, and high costs if using a Fourier transform (FT) Raman spectroscopy with an InGaAs detector, which impede their adoption in clinics. In this study, we developed a portable CRS system with a simultaneous dual-wavelength source and a miniaturized handheld probe (120 mm × 60 mm × 50 mm) that can acquire spectra in both fingerprint (FP, 450-1750 cm) and high wavenumber (HW, 2800-3800 cm) regions simultaneously. An innovative design combining 671 and 785 nm lasers for simultaneous excitation through a compact and high-efficiency (>90%) wavelength combiner was implemented. Moreover, to decouple the fused FP and HW spectra, a first-of-its-kind precise Raman spectra separation algorithm (PRSSA) was developed based on the maximum probability (MAP) estimate. The accuracy of spectra separation was greater than 99%, demonstrated in both phantom experiments and human skin measurements. The total data acquisition time was reduced by greater than 50% compared to other CRS systems. The results proved our proposed CRS system and PRSSA's superior capability in fast and ultrawideband spectra acquisition will significantly improve the integration of CRS in the clinical workflow. <<<
翻译
16.
李翛然 (2024-02-28 18:11):
#paper A computational framework for neural network-based variational Monte Carlo with Forward Laplacian doi: https://doi.org/10.1038/s42256-024-00794-x 北大和字节跳动合作的文章,关注是因为一直在看计算化学领域的一些新进展。字节跳动和北京大学团队共同研究,针对神经网络变分蒙特卡罗(NN-VMC)在处理大规模量子系统时计算成本高的问题。 2. 研究团队创新性地提出了“Forward Laplacian”计算框架,通过前向传播直接高效计算神经网络相关拉普拉斯部分,显著提升NN-VMC计算效率。 3. 他们还设计了名为“LapNet”的高效神经网络结构,利用Forward Laplacian优势,大幅减少了模型训练所需的计算资源。 4. 结合Forward Laplacian和LapNet的NN-VMC方法在多种化学系统中展现出优越的性能,可准确计算绝对能量和相对能量,与实验数据和金标准计算方法吻合度高。 5. 尽管已有显著进步,但团队指出,未来还需要将更多化学和物理知识融入NN-VMC方法中以解决部分应用场景中的差异问题,同时Forward Laplacian有望在更广泛的量子力学及基于神经网络的偏微分方程求解领域发挥作用。
17.
李翛然 (2024-01-30 16:22):
#paper: doi:doi.org/10.1186/s42825-019-0012-x Quantitative and structural analysis of isotopically labelled natural crosslinks in type I skin collagen using LC-HRMS and SANS 这篇文章主要介绍了使用液相色谱-高分辨质谱(LC-HRMS)和小角散射(SANS)技术对I型皮肤胶原蛋白中的同位素标记天然交联物进行定量和结构分析的方法和结果。这项研究对于了解皮肤胶原蛋白的结构和功能具有重要意义。 1. 样品制备:研究使用了同位素标记的I型皮肤胶原蛋白样品,通过特定的实验方法进行制备。 2. 液相色谱-高分辨质谱(LC-HRMS)分析:研究使用LC-HRMS技术对样品中的同位素标记天然交联物进行定量分析。LC-HRMS技术能够提供高分辨率和高灵敏度的分析结果。 3. 小角散射(SANS)分析:研究使用SANS技术对样品中的同位素标记天然交联物进行结构分析。SANS技术能够提供关于样品中交联物的大小、形状和分布等信息。 这篇论文的优势包括: 1. 综合分析方法:研究采用了LC-HRMS和SANS两种不同的分析技术,能够从定量和结构两个方面全面地研究同位素标记天然交联物。 2. 高分辨率和高灵敏度:LC-HRMS技术具有高分辨率和高灵敏度的特点,能够提供准确的定量分析结果。 3. 结构信息获取:SANS技术能够提供关于交联物的结构信息,有助于深入了解其在皮肤胶原蛋白中的分布和作用。 然而,这篇论文也存在一些局限性: 1. 样品限制:研究中使用的是同位素标记的I型皮肤胶原蛋白样品,可能无法完全代表自然状态下的胶原蛋白。 2. 技术限制:虽然LC-HRMS和SANS技术在分析同位素标记天然交联物方面具有优势,但仍然存在一定的局限性,如分析时间较长、设备成本较高等。 3. 结果解释:由于同位素标记天然交联物的复杂性,对于分析结果的解释可能存在一定的挑战,需要进一步的研究和验证。 总体而言,这篇论文通过综合应用LC-HRMS和SANS技术,提供了一种定量和结构分析同位素标记天然交联物的方法,并揭示了其在I型皮肤胶原蛋白中的特征和作用,为进一步研究皮肤胶原蛋白的结构和功能提供了重要的参考。 这文章证是我的研究方向,帮助很大
Abstract:
Abstract Collagen structure in biological tissues imparts its intrinsic physical properties by the formation of several covalent crosslinks. For the first time, two major crosslinks in the skin dihydroxylysinonorleucine (HLNL) … >>>
Abstract Collagen structure in biological tissues imparts its intrinsic physical properties by the formation of several covalent crosslinks. For the first time, two major crosslinks in the skin dihydroxylysinonorleucine (HLNL) and histidinohydroxymerodesmosine (HHMD), were isotopically labelled and then analysed by liquid-chromatography high-resolution accurate-mass mass spectrometry (LC-HRMS) and small-angle neutron scattering (SANS). The isotopic labelling followed by LC-HRMS confirmed the presence of one imino group in both HLNL and HHMD, making them more susceptible to degrade at low pH. The structural changes in collagen due to extreme changes in the pH and chrome tanning were highlighted by the SANS contrast variation between isotopic labelled and unlabelled crosslinks. This provided a better understanding of the interaction of natural crosslinks with the chromium sulphate in collagen suggesting that the development of a benign crosslinking method can help retain the intrinsic physical properties of the leather. This analytical method can also be applied to study artificial crosslinking in other collagenous tissues for biomedical applications. Graphical abstract <<<
翻译
18.
李翛然 (2023-12-30 10:31):
#paper doi:10.4161/bioe.28791 Bioengineered collagens: Emerging directions for biomedical materials 1. 胶原蛋白作为生物医学材料的历史和应用。 2. 动物胶原蛋白的局限性及疾病传播风险。 3. 重组胶原蛋白技术的发展,特别是在大肠杆菌中表达的细菌胶原蛋白的特性和潜在应用。 4. 生物工程方法改善胶原蛋白稳定性和功能的可能性。 5. 不同系统(如酵母、昆虫细胞、植物、微生物)用于胶原蛋白的生产。 6. 细菌胶原蛋白的特性、稳定性、非免疫原性和生产方法。 7. 结合生物工程技术,设计出具有特定功能的胶原蛋白结构。
IF:4.200Q2 Bioengineered, 2014 Jul-Aug. DOI: 10.4161/bioe.28791 PMID: 24717980
Abstract:
Mammalian collagen has been widely used as a biomedical material. Nevertheless, there are still concerns about the variability between preparations, particularly with the possibility that the products may transmit animal-based … >>>
Mammalian collagen has been widely used as a biomedical material. Nevertheless, there are still concerns about the variability between preparations, particularly with the possibility that the products may transmit animal-based diseases. Many groups have examined the possible application of bioengineered mammalian collagens. However, translating laboratory studies into large-scale manufacturing has often proved difficult, although certain yeast and plant systems seem effective. Production of full-length mammalian collagens, with the required secondary modification to give proline hydroxylation, has proved difficult in E. coli. However, recently, a new group of collagens, which have the characteristic triple helical structure of collagen, has been identified in bacteria. These proteins are stable without the need for hydroxyproline and are able to be produced and purified from E. coli in high yield. Initial studies indicate that they would be suitable for biomedical applications. <<<
翻译
19.
李翛然 (2023-11-28 20:26):
#paper doi:10.1016/j.heliyon.2023.e17575 AI in drug discovery and its clinical relevance 一篇综述,这篇文章是近年来我觉得还不错的从临床角度介绍了一下目前AI制药行业的发展,基本上涵盖了几种AI的功能目标。 虽然能看出来作者的AI药物设计水平不够深入,但是不方案从这件事情的本院入手,即FDA的评审通过及临床角度来进行评价。 所以作为一个入门的综述还是非常好的,大家对这个行业感兴趣都可以看一看
IF:3.400Q1 Heliyon, 2023-Jul. DOI: 10.1016/j.heliyon.2023.e17575 PMID: 37396052
Abstract:
The COVID-19 pandemic has emphasized the need for novel drug discovery process. However, the journey from conceptualizing a drug to its eventual implementation in clinical settings is a long, complex, … >>>
The COVID-19 pandemic has emphasized the need for novel drug discovery process. However, the journey from conceptualizing a drug to its eventual implementation in clinical settings is a long, complex, and expensive process, with many potential points of failure. Over the past decade, a vast growth in medical information has coincided with advances in computational hardware (cloud computing, GPUs, and TPUs) and the rise of deep learning. Medical data generated from large molecular screening profiles, personal health or pathology records, and public health organizations could benefit from analysis by Artificial Intelligence (AI) approaches to speed up and prevent failures in the drug discovery pipeline. We present applications of AI at various stages of drug discovery pipelines, including the inherently computational approaches of design and prediction of a drug's likely properties. Open-source databases and AI-based software tools that facilitate drug design are discussed along with their associated problems of molecule representation, data collection, complexity, labeling, and disparities among labels. How contemporary AI methods, such as graph neural networks, reinforcement learning, and generated models, along with structure-based methods, (i.e., molecular dynamics simulations and molecular docking) can contribute to drug discovery applications and analysis of drug responses is also explored. Finally, recent developments and investments in AI-based start-up companies for biotechnology, drug design and their current progress, hopes and promotions are discussed in this article. <<<
翻译
20.
李翛然 (2023-10-31 13:21):
#paper doi:10.1093/bioinformatics/btad596 DeepCCI: a deep learning framework for identifying cell-cell interactions from single-cell RNA sequencing data 一个新的框架,在用scRNA的数据来解释细胞互作,不过我觉得最大的问题是,看了一下他的训练集和数据集,还是通过对于scRNA的初步处理数据,即做到uMAP的降维分类后就来训练,还是非常初级的想法,真正的细胞互作的机理在这个颗粒度下的解释会很糟糕。不过也算是一个跨领域的应用 值得鼓励
Abstract:
MOTIVATION: Cell-cell interactions (CCIs) play critical roles in many biological processes such as cellular differentiation, tissue homeostasis, and immune response. With the rapid development of high throughput single-cell RNA sequencing … >>>
MOTIVATION: Cell-cell interactions (CCIs) play critical roles in many biological processes such as cellular differentiation, tissue homeostasis, and immune response. With the rapid development of high throughput single-cell RNA sequencing (scRNA-seq) technologies, it is of high importance to identify CCIs from the ever-increasing scRNA-seq data. However, limited by the algorithmic constraints, current computational methods based on statistical strategies ignore some key latent information contained in scRNA-seq data with high sparsity and heterogeneity.RESULTS: Here, we developed a deep learning framework named DeepCCI to identify meaningful CCIs from scRNA-seq data. Applications of DeepCCI to a wide range of publicly available datasets from diverse technologies and platforms demonstrate its ability to predict significant CCIs accurately and effectively. Powered by the flexible and easy-to-use software, DeepCCI can provide the one-stop solution to discover meaningful intercellular interactions and build CCI networks from scRNA-seq data.AVAILABILITY AND IMPLEMENTATION: The source code of DeepCCI is available online at https://github.com/JiangBioLab/DeepCCI. <<<
翻译
回到顶部