A Novel Design Method for Protein-Like Molecules from the Perspective of Sheaf Theory

Proteins perform a variety of functions in living organisms and their functions are largely determined by their shape. In this paper, we propose a novel mathematical method for designing protein-like molecules of a given shape. In the mathematical model, molecules are represented as loops of n-simplices (2-simplices are triangles and 3-simplices are tetrahedra). We design a new molecule of a given shape by patching together a set of smaller molecules that cover the shape. The covering set of small molecules is defined using a binary relation between sets of molecules. A new molecule is then obtained as a sum of the smaller molecules, where addition of molecules is defined using transformations acting on a set of (n + 1)-dimensional cones. Due to page limitations, only the two-dimensional case (i.e., loops of triangles) is considered. No prior knowledge of Sheaf Theory, Category Theory, or Protein Science is required. The author hopes that this paper will encourage further collaboration between Mathematics and Protein Science.

A new approach for protein design based on the relative entropy

A new effective and fast minimization approach completely based on the physical theory is proposed for protein design. The sequence space is essentially searched according to the Boltzmann distribution. In this approach, the relative entropy is used as a minimization object function. The method has been tested on an off-lattice model of proteins and the results are better than those obtained from other similar work. Therefore, it can be applied as a uniform frame for both folding and inverse folding of proteins.

Functional tuning and expanding of myoglobin by rational protein design

Rational protein design is a powerful strategy,not only for revealing the structure and function relationship of natural metalloproteins,but also for creating artificial metalloproteins with improved properties and functions.Myoglobin(Mb),a small heme protein created by nature with diverse functions,has been shown to be an ideal scaffold for rational protein design.The progress reviewed herein includes fine-tuning its native functions of O2binding and transport,peroxidase activity and nitrite reductase(NIR)activity,and rational expanding its functionalities to peroxygenase,heme-copper oxidase(HCO),nitric oxide reductase(NOR),as well as hydroxylamine reductase.These studies have enhanced our understanding of how metalloproteins work in nature,and provided insights for rational design of functional metalloproteins for practical applications in the future.

Computational design of proteins with novel structure and functions

Computational design of proteins is a relatively new field, where scientists search the enormous sequence space for sequences that can fold into desired structure and perform desired functions. With the computational approach, proteins can be designed, for example, as regulators of biological processes, novel enzymes, or as biotherapeutics. These approaches not only provide valuable information for understanding of sequence–structure–function relations in proteins, but also hold promise for applications to protein engineering and biomedical research. In this review, we briefly introduce the rationale for computational protein design, then summarize the recent progress in this field, including de novo protein design, enzyme design, and design of protein–protein interactions. Challenges and future prospects of this field are also discussed.

A generalized approach for protein design based on the relative entropy

In the present study, we have developed the method brought forward recently for protein design based on the relative entropy. The new approach can be used in more common situation other than the special limits in the anterior method. The results indicate that our generalized method has increased the prediction precision for protein sequence and will be in favor of the study for protein design.

Structural Insight into the Design on Oleanolic Acid Derivatives as Potent Protein Tyrosine Phosphatase 1B Inhibitors

Oleanolic acid derivatives act as newer protein tyrosine phosphatase 1B(PTP-1B) inhibitors for type 2 diabetes mellitus(T2DM). In order to understand the structural requirement of PTP-1B inhibitors, 52 oleanolic acid derivatives were divided into a training set(34 compounds) and a test set(18 compounds). The highly reliable and predictive 3D-QSAR models were constructed by CoM FA, CoM SIA and topomer Co MFA methods, respectively. The results showed that the cross validated coefficient(q2) and non-cross-validated coefficient(R^2) were 0.554 and 0.999 in the CoM FA model, 0.675 and 0.971 in the CoM SIA model, and 0.628 and 0.939 in the topomer Co MFA model, which suggests that three models are robust and have good exterior predictive capabilities. Furthermore, ten novel inhibitors with much higher inhibitory potency were designed. Our design strategy was that(i) the electronegative substituents(Cl,-CH_2OH, OH and-CH_2Cl) were introduced into the double bond of ring C,(ii) the hydrogen bond acceptor groups(C≡N and N atom), electronegative groups(C≡N, N atom,-COOH and-COOCH_3) and bulky substituents(C_6H_5N) were connected to the C-3 position, which would result in generating potent and selective PTP-1B inhibitors. We expect that the results in this paper have the potential to facilitate the process of design and to develop new potent PTP-1B inhibitors.

生物统合加工嵌合纤维小体组装模块反应机制探究

为探究生物统合加工嵌合纤维小体中重组蛋白粘连模块与对接模块的分子相互作用及其对嵌合纤维小体组装效率的影响,采用酿酒酵母细胞分泌表达支架蛋白和酶分子催化模块,在胞外通过非变性蛋白凝胶电泳和等温滴定量热法测定分析二级支架蛋白、纤维素酶分别与一级支架蛋白结合时的相互作用反应。结果显示,分别连接二级支架蛋白和纤维素酶蛋白的对接模块与粘连模块的亲和力常数增大,亲和力减小,组装反应为焓变驱动的放热反应并产生氢键,证明这些蛋白分子间亲和力减小是导致二级支架蛋白与一级支架蛋白组装效率较低的主要影响因素。

火麻仁黄嘌呤氧化酶抑制肽的酶解制备工艺研究

为寻找开发火麻仁蛋白,提高火麻应用价值的最佳条件,以火麻蛋白为原料,通过酶解法制备火麻仁黄嘌呤氧化酶抑制肽,采用正交试验法优化中性蛋白酶酶解火麻蛋白制备多肽的最佳工艺条件。以中性蛋白酶用量、酶解时间、酶解温度进行单因素试验,通过正交试验分析获得制备火麻仁黄嘌呤氧化酶抑制肽的最佳酶解条件为pH值6.5,料液比1∶5,酶用量6000 U/g,酶解温度50℃,酶解时间5 h。在此条件下进行的验证试验中,多肽抑制率为78.98%,表明该工艺稳定、可行,具有较高的应用价值。

蛋白质结构稳定性检测的实验课程设计

随着生物技术的突破和发展,多肽蛋白类药物的出现使得人类疾病的诊断和治疗发生了翻天覆地的变化。为了顺应多肽蛋白类药物的飞速发展,加强生命科学等专业本科生对此类药物制剂相关知识的普及已势在必行。此实验课程设计利用稳定性热检测法分析蛋白质结构的稳定性,为生命科学等专业本科生设计一堂深入了解蛋白质结构与功能关系的课程,以促进本科生拓宽学术视野,提升完成相关科学研究和适应医药产业发展新形势的能力。

基于生成对抗网络的噬菌体尾部蛋白序列设计

生成对抗网络(GAN)在图像生成、蛋白质设计领域有着广泛应用,但是对于噬菌体尾部蛋白的生成少有研究。提出一种基于GAN的噬菌体尾部蛋白序列生成方法。首先使用Wasserstein距离作为模型的目标函数。其次采用多层感知机(MLP)作为模型的基本结构。然后将MLP扩展为多路径结构。实验结果表明,上述方法取得了0.9241的质量得分、0.8498的多样性得分和1.7739的总得分,优于其它常用的生成方法。相较于单路径MLP,多路径MLP提高了序列的生成效果。所提方法能够生成高质量噬菌体尾部蛋白序列,同时保证生成序列的多样性。

Insights into the structural biology of G-protein coupled receptors impacts drug design for central nervous system neurodegenerative processes

In the last few years, there have been important new insights into the structural biology of G-protein coupled receptors. It is now known that allosteric binding sites are involved in the affinity and selectivity of ligands for G-protein coupled receptors, and that signaling by these receptors involves both G-protein dependent and independent pathways. The present review outlines the physiological and pharmacological implications of this perspective for the design of new drugs to treat disorders of the central nervous system. Specifically, new possibilities are explored in relation to allosteric and orthosteric binding sites on dopamine receptors for the treatment of Parkinson's disease, and on muscarinic receptors for Alzheimer's disease. Future research can seek to identify ligands that can bind to more than one site on the same receptor, or simultaneously bind to two receptors and form a dimer. For example, the design of bivalent drugs that can reach homo/hetero-dimers of D2 dopamine receptor holds promise as a relevant therapeutic strategy for Parkinson's disease. Regarding the treatment of Alzheimer's disease, the design of dualsteric ligands for mono-oligomeric muscarinic receptors could increase therapeutic effectiveness by generating potent compounds that could activate more than one signaling pathway.

确定性筛选设计在Purcise Q膜纯化抗体的应用

目的:通过确定性筛选设计(DSD)方法建立单抗的Purcise Q膜阴离子交换工艺,进一步降低残留宿主细胞蛋白(HCP)含量。方法:将亲和层析洗脱过滤液作为样品,进行Purcise Q膜层析,选取上样pH、上样电导、载量、流速、峰收集条件5个因子为输入因子,以回收率、HCP去除率、多聚体含量为输出响应值,使用确定性筛选设计DOE模型进行实验。结果:在实验参数范围内,多聚体含量没有明显的变化,HCP含量显著降低。上样电导和载量显著影响HCP去除率,而载量、流速和峰收集条件则显著影响层析回收率。利用JMP的模拟实验功能获得了稳健工艺参数组合(上样电导3 ms/cm、载量300 g/L、流速25 MV/min、峰收集50 mAU/mm),进一步利用决策树机器学习方法自动获得设计空间(上样电导3.0~3.6 ms/cm、载量300~460 g/L、流速5~25 MV/min、峰收集50~180 mAU/mm)。结论:确定性筛选设计实验方法适用于膜层析的工艺开发,能够一段式快速获得稳健工艺参数组合和设计空间,对于工艺放大、工艺转移和降低生产风险极具指导意义。

On the Defining Equations of Protein’s Shape from a Category Theoretical Point of View

This paper proposes a novel category theoretic approach to describe protein’s shape, i.e., a description of their shape by a set of algebraic equations. The focus of the approach is on the relations between proteins, rather than on the proteins themselves. Knowledge of category theory is not required as mathematical notions are defined concretely. In this paper, proteins are represented as closed trajectories (i.e., loops) of flows of triangles. The relations between proteins are defined using the fusion and fission of loops of triangles, where allostery occurs naturally. The shape of a protein is then described with quantities that are measurable with unity elements called “unit loops”. That is, protein’s shape is described with the loops that are obtained by the fusion of unit loops. Measurable loops are called “integral”. In the approach, the unit loops play a role similar to the role “1” plays in the set Z of integers. In particular, the author considers two categories of loops, the “integral” loops and the “rational” loops. Rational loops are then defined using algebraic equations with “integral loop” coefficients. Because of the approach, our theory has some similarities to quantum mechanics, where only observable quantities are admitted in physical theory. The author believes that this paper not only provides a new perspective on protein engineering, but also promotes further collaboration between biology and other disciplines.

以学生为主体的高职院校生物化学课程教学设计--以“蛋白质的结构与功能”为例

高职院校学生的学习能力差、知识点掌握不牢固、接受新知识的能力弱、上课注意力不集中,因此在进行授课时,应该摒弃传统的“以教师为中心”的教授方式,转为“以学生为中心”。采用案例教学法、项目驱动教学法和参与式教学法等多样化教学手段,用学生感兴趣的案例,用学生能听懂的语言,充分调动学生的积极性,加深学生对知识点的理解与记忆,让课堂变成有趣的课堂。

植物肉挤出机双螺杆结构设计与验证

针对现有植物肉挤出机双螺杆结构挤出物料存在纤维结构差、挤出稳定性低等问题,设计一种基于植物蛋白肉纤维成型工艺的双螺杆。面向纤维成型工艺过程中螺杆进料混合段、升温熔融输送段、高温熔融剪切段、计量段不同的作用,对螺杆构型及其参数进行设计优化,并进行螺杆强度初步校核;建立物料在高温熔融剪切段的流道模型,分析流道内压力场、速度场及流体迹线分布,探究其元件组合对纤维成型的影响;研制螺杆样机并分析样品宏观纤维结构与组织化指数,验证植物蛋白肉纤维成型效果。螺杆强度达标且流场最高压力可达到391.8 MPa,正向螺旋元件+正向捏合块+反向螺旋元件的排列组合具有良好的建压输送及熔融剪切能力,挤出样品组织化指数高达2.582 4 g,且宏观纤维结构丰富。研究为食品级挤出机的双螺杆设计提供参考。

基于核磁共振饱和转移差谱技术筛选Protein A仿生多肽配基

核磁共振饱和转移差谱(STD-NMR)技术能够用于检测小分子配基与大分子蛋白之间的亲和性。利用STD⁃NMR技术评价了基于Protein A设计的仿生肽段与人抗体(hIgG)的亲和力以及结合机制,从中筛选出了与抗体亲和性最强的仿生六肽FYEILH,利用静态吸附试验确定了此六肽与抗体的亲和力(Kd)为0.8×10^-6 mol/L,静态结合载量为61.22 mg/mL,与目前文献中报道的许多多肽配基相比,具有明显的优势。在本研究中成功将Protein A最小化,获得了与抗体具有高亲和性的Protein A仿生多肽配基。

蛋白质计算中的机器学习

蛋白质计算一直以来都是科学领域中的重要课题,而近年来其与机器学习的结合,更是极大地推进了相关学科的发展.本综述主要讨论了机器学习在四个重要的蛋白质计算领域内的研究进展,这四个领域包括:分子动力学模拟、结构预测、性质预测和分子设计.分子动力学模拟依赖于力场参数,准确的力场参数是分子动力学模拟的必需品,而机器学习可以帮助研究者得到更加准确的力场参数.在分子动力学模拟中,机器学习也可以从复杂的体系中以较小的代价计算出所需求解的自由能.结构预测一般是给定蛋白质序列预测其结构.结构预测复杂度高、数据量大,而这恰恰是机器学习所擅长的.在机器学习的协助下,近年来科研人员已经在单个蛋白质三维结构预测上取得了不错的成果.性质预测则是指通过给定的已知蛋白质信息,推断其可能拥有的性质,这对于蛋白质的研究也是至关重要的.更具挑战性的是分子设计,虽然近年来机器学习在蛋白质设计上取得突破,但这一领域还有很大空间值得探索.本综述将针对以上四点分别展开论述,并对蛋白质计算中的机器学习研究进行展望.

Investigation of Highly Designable Dented Structures in HP Model with Hydrogen Bond Energy

Some highly designable protein structures have dented on the surface of their native structures, and are not full compactly folded. According to hydrophobic-polar (HP) model the most de-signable structures are full compactly folded. To investigate the designability of the dented structures, we introduce the hydrogen bond energy in the secondary structures by using the secon-dary-structure-favored HP model proposed by Ou-yang etc. The result shows that the average designability increases with the strength of the hydrogen bond. The designabilities of the structures with same dented shape increase exponentially with the number of secondary structure sites. The dented structures can have the highest designabilities for a certain value of hydrogen bond energy density.

药用植物分子农场研究进展

植物分子农场可以利用植物生产具有药物用途的重组蛋白或者次生代谢化合物,应用广泛。随着对动植物中具有药物用途的代谢途径的深入解析,代谢途径中关键限速酶或调控蛋白的功能不断被明确,如何选择植物分子农场的底盘植物和遗传改造途径等问题,特别是如何协同提高植物制药产量与品质一直是植物分子农场体系建立中面临的关键科学问题。综述了药用的植物分子农场的最新研究进展,着重介绍了底盘植物的选择与药用植物分子农场的构建策略,以期为提高分子农场应用效果提供有力的科技支撑。

In silico design of anti-tumor mini-protein targeting MDM2

We designed a disulfide-crosslinked mini-protein with a two-helical topology consisting of L-and Damino acids,which was exceptionally stable in serum.Therefore,we further used it as a scaffold to design mini-proteins targeting p53 positive tumor cells.Based on bifunctional grafting,key residues from the transactivation domain of p53 and a designed unnatural amino acid were grafted into the helix constituted by L-amino acids to confer the mini-protein with MDM2 inhibitory activity.Meanwhile,ten Arg residues were introduced to improve its membrane penetrating capacity.Among the mini-proteins,UPROL-10e showed nano-molar binding affinity on MDM2 and cellular toxicity on p53 expressing HCT116cells.