酶活性设计的新方法——半理性设计

许多研究小组利用整基因随机突变形成和重组方法,已成功的进行了酶的定向进化。酶工程的最新进展就是使这些定向进化的方法相结合,并与理性酶修饰方法的要素随机结合,通过各种组合选择出适合的方法来避免定向进化和理性设计的限制。半理性方法是以多个特定的残基为靶标在结构或功能知识的基础上突变构建简洁库,它更有希望得到正确的结果。突变体的高效抽样可能对酶功能有影响,随着底物选择性和特异性的提高,及其在已知的结构中经过重新设计使酶活性有了显著提高,这种高效抽样可被引入实验,当规模较大时它会被引入计算机方法。     

基于计算机视觉算法的图像处理技术探析

在人工智能技术飞速发展的今天,图像处理已经成为了人工智能的重要功能之一,并在现实生活中得到了较为广泛的应用,而基于计算机视觉算法作为实现计算机图像处理的关键所在,自然也在行业内得到了高度重视。为此,本文对计算机视觉算法与图像处理技术进行见了简单介绍,并对基于计算机视觉算法的图像处理框架,最后还围绕计算机视觉现实系统的实现展开了探讨。     

人工智能与大数据在计算机网络中的应用

随着社会的不断发展以及科技的不断进步，计算机网络技术的应用范围也在不断扩大。随着人工智能的不断发展，计算机网络技术也迎来了新的机遇。在当前计算机网络技术的应用过程中，人工智能技术不断深入研究，同时大数据技术与人工智能的融合应用也为计算机网络的建设发展提供了新的思路和技术方法。     

利用工程酶改进有机合成的研究进展

修饰酶用于有机合成已经涉及了许多领域。它包括改变酶反应机制来催化新的反应,改变底物专一性、扩大底物专一性、改善底物专一性,例如动力学拆分中的对映选择性。酶修饰可以通过理性设计或随机突变方法来实现,前者需要知道酶的结构,后者则需要进行筛选。两种策略的酶工程都能成功,并且对于改进在催化中应用的酶非常有意义。最近,有例子表明这两种策略已经应用于许多酶中。     

人工智能技术在电力设备运维检修中的研究及应用

首先介绍了人工智能技术,为电力设备的运维检修提供了一种全新的技术手段与研究思路.按照数据层、算法层和应用层逐级展开论述和分析,给出了人工智能关键技术框架及各类算法的应用特点与范围,分析了人工智能在电力设备运行维护中的关键技术,以及人工智能技术在电力设备运行维护中的应用,对相关工作人员以及整个行业发展有所帮助.     

现代生物化工中酶工程技术研究与应用

作为生物内的重要催化剂,酶在日常生活中发挥着关键性作用。加强对酶的研究,不仅能够对生物新陈代谢过程进行了解,也能为其他行业的发展创造活力。在现代生物化工行业的发展中,酶工程技术已经成为行业发展的全新契机,同时也关乎广大人民的日常生活。加强对酶工程技术的研究不仅是生物化工行业的发展需求,更顺应了我国经济社会的发展潮流。主要结合我国生物化工行业的实际发展情况,以酶工程技术为切入点进行了研究。     

分子模拟技术在脂肪酶性质及催化机理研究中的应用进展

脂肪酶是一种重要的生物催化剂,其来源广泛,可在水相甚至非水介质中催化多种反应,并表现出很高的立体选择性和催化活性。有关脂肪酶的应用和基础研究备受重视,特别是脂肪酶催化机理和结构功能关系成为近年来研究热点,基于现代计算机技术的分子模拟计算在相关研究中扮演着越来越重要的角色。本文综述了计算机辅助分子模拟技术应用于脂肪酶性质及催化机理研究领域的3个发展阶段：早期的分子动力学模拟主要用于脂肪酶构象变化的研究;随后出现的柔性分子对接技术则可研究和预测脂肪酶的对映体选择性及简单的催化机理;近年来发展的运算时间更长的分子动力学和量子力学/分子力学（QM/MM）方法则可全面研究脂肪酶的酶学性质及催化机理。通过对上述技术发展的回顾与对比分析可以预见,分子模拟手段将在酶的性质及酶催化机理研究领域发挥更为重要的作用,并且多种模拟技术的综合应用和从头计算分子模拟技术的日益成熟,将为人们更加深入地认识蛋白质构效关系发挥不可替代的作用。     

浅析人工智能在计算机网络技术中的应用

近年来,计算机网络技术取得了极大的发展,与此同时其在多领域应用过程中所存在的问题也逐渐暴露并引发人们的关注,比如计算机网络信息安全问题等。然而由于应用以往的数据运算等功能已然无法解决现阶段计算机网络技术在实际应用中所出现的问题,因此便有了对人工智能应用的尝试。然而也正是在计算机网络技术发展日新月异的背景之下,人们对人工智能的应用优势也已然形成了较为成熟的认识,并于实际的计算机网络安全管理过程中扩大了对其的应用。本文首先从计算机网络安全管理技术与网络系统管理和评价技术两个角度介绍了人工智能的应用,接着对人工智能在计算机网络技术中的应用优势做了简要分析,以期能够推动人工智能应用的进一步发展。     

计算机辅助药物设计在新农用化合物开发中的应用

农药创新关系到我国农业可持续发展和生态环境安全,计算机辅助药物设计能够有效帮助农药创新.介绍了药物靶标的选择和预测、分子对接、分子动力学模拟、从头设计、基于药效团的虚拟筛选和定量构效关系模型等计算机辅助药物设计方法在农药创制过程中的应用,探讨了这些计算机辅助药物设计方法在农药创制过程中存在的问题,展望了计算机辅助药物设...     

人工智能驱动化学品创新设计的实践与展望

改进化学品研发模式，缩短化学品从发现到应用的时间是化工行业中所有科学研究者和产业人员的最终目标。本文提出：化学品设计是一个涉及多组分、多尺度和多物理场的复杂过程，现有的实验研究模式难以深入高效地揭示相关的物理化学机制；因此，需要借助多尺度计算机模拟技术，从微观分子层面的化学结构出发，耦合多种模拟方法来预测宏观产品的性能；同时，随着计算机算力的提升，将基于物化机制的多尺度计算机模拟方法与数据驱动的人工智能相结合的研发模式，具有广阔的应用前景，例如基于高精度多尺度模拟数据训练的机器学习模型能够指数级地缩短化学品结构-性质的预测。尽管如此，由于广阔的分子结构空间和复杂的分子作用力关系，新型化学品研发面临着众多独特的挑战。如何借助人工智能提高现有模拟技术的准确性与速度，更好地理解和预测材料的性质和特点，并将人工智能引入材料设计算法，以实现更高效地探索和优化复杂的化工设计参数，使其更适应实际需求，是化学品设计研究的前沿方向。本文从多尺度模拟、材料设计框架和科学计算软件开发三个方面，分析讨论了人工智能驱动化学品创新设计的发展现状，阐述了人工智能技术在实现化学品设计创新途径中所起的重要作用，并对人工...     

Facilitation of cascade biocatalysis by artificial multi-enzyme complexes—A review

Multi-enzyme complexes are the results of natural evolution to facilitate cascade biocatalysis. Through enzyme colocalization within a complex, the transfer efficiency of reaction intermediates between adjacent cascade enzymes can be promoted, resulting in enhanced overall reaction efficiency. Inspired by nature, a variety of approaches have been developed for the assembly of artificial multi-enzyme complexes with different spatial organizations, aiming at improving the catalytic efficiency of enzyme cascade. A recent trend of this research area is the creation of enzyme complexes with a controllable spatial organization which helps with the mechanistic studies and bears the potential to further increase metabolic productivity. In this review, we summarize versatile strategies for the assembly of artificial multi-enzyme complexes, followed by an inspection of the mechanistic studies of artificial multi-enzyme complexes for their enhancement of catalytic efficiency. Furthermore, we provide some highlighted in vivo, ex vivo, and in vitro examples that demonstrate the ability of artificial multi-enzyme complexes for enhancing the overall production efficiency of value-added compounds. Recent research progress has revealed the great biotechnological potential of artificial multi-enzyme complexes as a powerful tool for biomanufacturing.     

典型湿法脱硫系统存在的问题及人工智能在优化运行中的应用

石灰石-石膏湿法烟气脱硫是我国最主要的脱硫方式，随着该法的不断改进与简化，脱硫系统运行更加稳定，造价也在不断降低，但运行过程中依然存在诸多问题。本文概括总结了石灰石-石膏湿法烟气脱硫系统运行过程中发生的典型问题，诸如结垢堵塞、腐蚀磨损、起泡溢流和石膏品质差等，指出了这些问题的具体分类类型以及主要影响因素；继而从系统运行机理角度阐述了这些问题的相互关系和交互影响，并将这些问题归因于脱硫系统的紊乱。随后结合电厂目前条件、当前研究基础以及可以实现的技术手段从四个方面论证了人工智能应用于脱硫系统的可行性，建议借助人工智能建立系统运行的诊断模型解决已有问题，并提出了基于人工智能的脱硫系统概念模型及具体实施思路。     

Cell-free synthetic biology in the new era of enzyme engineering

With the gradual rise of enzyme engineering, it has played an essential role in synthetic biology, medicine, and biomanufacturing. However, due to the limitation of the cell membrane, the complexity of cellular metabolism, the difficulty of controlling the reaction environment, and the toxicity of some metabolic products in traditional in vivo enzyme engineering, it is usually problematic to express functional enzymes and produce a high yield of synthesized compounds. Recently, cell-free synthetic biology methods for enzyme engineering have been proposed as alternative strategies. This cell-free method has no limitation of the cell membrane and no need to maintain cell viability, and each biosynthetic pathway is highly flexible. This property makes cell-free approaches suitable for the production of valuable products such as functional enzymes and chemicals that are difficult to synthesize. This article aims to discuss the latest advances in cell-free enzyme engineering, assess the trend of this developing topical filed, and analyze its prospects.     

Calculating porosity and permeability from synthetic micro-CT scan images based on a hybrid artificial intelligence

Nowadays, lattice Boltzmann is one of the standard and exact methods of simulation in micro-CT images of rock. However, it has a high weakness in run time. Therefore, the effort in this article is to reach a comprehensive substitute method for permeability calculation with less run time than the lattice Boltzmann method. The other purposes are the automation of processing operations, preparation of images, and in the end, the calculation of porosity. The best way to achieve these outcomes is to use hybrid artificial intelligence. In this research work, comprehensive model architecture has been used to design a hybrid artificial intelligence to be able to calculate permeability and porosity in complex images. A thousand images were randomly generated with high complexity, which makes the model comprehensive and extensible, and image processing was applied. After that, the lattice Boltzmann method as the direct simulation was selected. Finally, the convolutional neural network and multilayer perceptron based on a new and comprehensive model were evaluated for the first time; the mean squared error resulting from the evaluation of training data is 0.01, and the test data is 0.03. Expert systems have been used as a subset of artificial intelligence for automated image processing and porosity calculation. In this way, problems related to the direct implementation of classical algorithms for image processing, models, and patterns related to machine learning and needing an expert were solved to an acceptable extent, and an error of less than 5% was achieved.     

利用分子机器的组装与分解构建pH敏感性谷胱甘肽过氧化物人工酶

谷胱甘肽过氧化物酶（GPx）是体内一种重要的抗氧化酶,对GPx的人工模拟能够拓展其体外应用,利用生命体内天然pH差异实现响应的pH敏感性GPx人工酶更是有着广泛的潜在应用。然而目前制备的pH敏感性GPx人工酶普遍存在活性较低的缺点,本文设计合成了同时含有高活性GPx催化中心和两个伯胺基团的乙胺单碲醚分子,酶促反应动力学的分析结果表明其二级反应速率常数高达10¹ L·mol^-1·min^-1数量级。pH=6时,乙胺单碲醚分子能够与葫芦[6]脲分子（CB[6]）组装形成分子机器,此时活性中心被包埋于CB[6]的疏水空腔之中,仅能展现出（0.04±0.02）μmol·min^-1·μmol^-1的活性;pH=7时,分子机器部分分解,能够展现出高达（0.35±0.06）μmol·min^-1·μmol^-1的活性。因此,通过调控体系pH在6和7之间变化,借助分子机器的组装及部分分解调控人工酶活性的关闭与开启,从而构建了高活性的pH敏感性GPx人工酶。     

利用分子机器的组装与分解构建pH敏感性谷胱甘肽过氧化物人工酶

谷胱甘肽过氧化物酶（GPx）是体内一种重要的抗氧化酶,对GPx的人工模拟能够拓展其体外应用,利用生命体内天然pH差异实现响应的pH敏感性GPx人工酶更是有着广泛的潜在应用。然而目前制备的pH敏感性GPx人工酶普遍存在活性较低的缺点,本文设计合成了同时含有高活性GPx催化中心和两个伯胺基团的乙胺单碲醚分子,酶促反应动力学的分析结果表明其二级反应速率常数高达10¹ L·mol^-1·min^-1数量级。pH=6时,乙胺单碲醚分子能够与葫芦[6]脲分子（CB[6]）组装形成分子机器,此时活性中心被包埋于CB[6]的疏水空腔之中,仅能展现出（0.04±0.02）μmol·min^-1·μmol^-1的活性;pH=7时,分子机器部分分解,能够展现出高达（0.35±0.06）μmol·min^-1·μmol^-1的活性。因此,通过调控体系pH在6和7之间变化,借助分子机器的组装及部分分解调控人工酶活性的关闭与开启,从而构建了高活性的pH敏感性GPx人工酶。     

人工智能在电化学水处理过程中的应用

近年来，通过人工智能建立的模型可以对工业过程进行精确调控，人工智能应用于电化学水处理技术过程得到了广泛关注。在电化学水处理过程中，人工智能模型可以降低电化学过程的能耗，获取最优能效比。本文对人工智能在电化学水处理的应用进行了综述、分类和归纳，并介绍了其应用方法，概述了人工智能应用于电化学水处理过程的特点、优势以及局限性，比较了用于电化学水处理的人工智能建模与响应面模型、回归模型和经验动力学模型的优劣。进而提出了人工智能在工程应用上的改进思路，为相关研究提供了参考。     

Peptide-capped gold nanoparticles: towards artificial proteins

Peptides can be designed to form self-assembled monolayers on gold nanoparticles to give nanomaterials with some chemical properties analogous to those of proteins. A variety of molecular-recognition properties are readily integrated within the peptide monolayer. Monofunctionalized nanoparticles are obtained by using separation methods that have been optimized for proteins. Recent applications as artificial enzymes and artificial enzyme substrates are presented. The limitations and long-term potential of peptide-capped nanoparticles as artificial proteins are discussed.     

Design and regulation of the surface and interfacial behavior of protein molecules

Surface and interfacial behavior of protein molecules are crucial for the protein function involved in many biochemical processes and biomedical products such as enzyme design, bio-separation, drug design and delivery. This article is devoted to an overview of design and regulation of the surface and interfacial behavior of protein molecules. The improvement of enzyme surface such as the directed evolution and the rational design of enzymes is introduced at first, followed by the rational design of protein interface for the protein assembly. Thereafter, the design of micro-environment and ligands are described as two examples for the design guided by protein surface. Then the design of protein surface and interface with the help of artificial intelligence will be discussed.     

Design and regulation of the surface and interfacial behavior of protein molecules

Surface and interfacial behavior of protein molecules are crucial for the protein function involved in many biochemical processes and biomedical products such as enzyme design, bio-separation, drug design and delivery. This article is devoted to an overview of design and regulation of the surface and interfacial behavior of protein molecules. The improvement of enzyme surface such as the directed evolution and the rational design of enzymes is introduced at first, followed by the rational design of protein interface for the protein assembly. Thereafter, the design of micro-environment and ligands are described as two examples for the design guided by protein surface. Then the design of protein surface and interface with the help of artificial intelligence will be discussed.