Identification of active sites interaction of different protein molecules in case of formation Nap1-Nap1, Mdm2-Mdm2 and P53-Mdm2

pT V Koshlan, K. G. Kulikovp
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The mobility range can be different beginning with a small adjustment of the side chains and ending with scale domain movements. These movements play an important role. At first glance, the most logical solution to this problem is to take into account the mobility of the protein in a docking program. Unfortunately, modern computational tools do not allow such modeling to be performed in an acceptable time frame since a protein molecule is very large, and allowing for mobility over all degrees of freedom can lead to a so-called combinatorial explosion (an astronomical increase in the number of possible variants). Only in some programs is there a limited mobility of protein binding sites (usually at the level of a small adaptation of conformations of the side chains of the active center residues). Another approach to this problem consists in docking the same protein in several different conformations and then selecting the best solutions from each docking run. The third approach is to find a universal structure of the target protein in which docking would produce fairly good results for different classes of ligands. In this case, the number of missed (but correct) solutions decreases, but the number of incorrect options also increases significantly. It should also be noted that most programs for the theoretical docking of proteins work according to the following principle: one protein is fixed in space, and the second is rotated around it in a variety of ways. At the same time, for each rotation configuration, estimates are made for the evaluation function. The evaluation function is based on surface complementarity (the mutual correspondence of complementary structures (macromolecules, radicals), determined by their chemical properties), electrostatic interactions, van der Waals repulsion and so on. 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In contrast to the above computer simulation algorithms, mathematical algorithms have been developed in this chapter that allow determining the detection of proteins active regions and detecting the stability of different regions of protein complexes (linear docking) by analyzing the potential energy matrix of pairwise electrostatic interaction between different sites of the biological complex, such as the homodimer of the histone chaperone Nap1-Nap1, the heterodimer of the p53 Mdm2 proteins, and the homodimer Mdm2 Mdm2, which are responsible for the entry of a whole protein molecule into biochemical reactions.","PeriodicalId":73911,"journal":{"name":"Journal of proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of proteomics & bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4172/0974-276X-C3-118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract

In this report, two algorithms are developed, algorithm 1 and algorithm 2. Algorithm 1 was developed in order to search for the interaction of a polypeptide chain of a full-length protein with short active region. Algorithm 2 was developed to determine the most active sites of interaction between fulllength proteins when dimers are formed in the direction from the N terminus to C terminus. Numerical calculations were made using proteins Mdm2, Nap1, P53. For modern proteomics, research and prediction of protein interactions are very important tasks, since they determine the function of proteins at levels from the cell to the whole organism. For proteins whose structure is known, the search for intermolecular interactions according to known data on the conformation of their tertiary structure reduces to the problem of searching for geometric complementarity of the sections of two interacting molecular surfaces and modeling their contacts, the so-called molecular docking. The task of molecular docking is the task of a conformational search algorithm, which reduces to a search for the conformational space of the formed biological complex due to the variation of the torsion angles of protein molecules. Modern conformational search algorithms in most cases find conformations that are generally close to the experimentally found structures in a relatively short time. However, there are factors that also have a significant impact on the success of the docking, which are often not taken into account in standard algorithms. One such factor is the conformational mobility of the target protein. The mobility range can be different beginning with a small adjustment of the side chains and ending with scale domain movements. These movements play an important role. At first glance, the most logical solution to this problem is to take into account the mobility of the protein in a docking program. Unfortunately, modern computational tools do not allow such modeling to be performed in an acceptable time frame since a protein molecule is very large, and allowing for mobility over all degrees of freedom can lead to a so-called combinatorial explosion (an astronomical increase in the number of possible variants). Only in some programs is there a limited mobility of protein binding sites (usually at the level of a small adaptation of conformations of the side chains of the active center residues). Another approach to this problem consists in docking the same protein in several different conformations and then selecting the best solutions from each docking run. The third approach is to find a universal structure of the target protein in which docking would produce fairly good results for different classes of ligands. In this case, the number of missed (but correct) solutions decreases, but the number of incorrect options also increases significantly. It should also be noted that most programs for the theoretical docking of proteins work according to the following principle: one protein is fixed in space, and the second is rotated around it in a variety of ways. At the same time, for each rotation configuration, estimates are made for the evaluation function. The evaluation function is based on surface complementarity (the mutual correspondence of complementary structures (macromolecules, radicals), determined by their chemical properties), electrostatic interactions, van der Waals repulsion and so on. The problem with this approach is that calculations throughout the configuration space require a lot of time, rarely leading to a single solution, which in turn does not allow us to speak of the uniqueness of the target protein and ligand interaction variant. So in the work while modeling by the methods of molecular dynamics, from 200 to 10 000 possible combinations of the formation of a protein complex with a ligand were found. Such a large number of modifications, along with the lack of a criterion for selecting the most probable variants of the bound structures of biological complexes (which would allow a radical reduction in their number) makes it very difficult to interpret the theoretical results obtained for practical use, namely, the finding of catalytic centers and a qualitative assessment of the dissociation constant of interacting substances. In contrast to the above computer simulation algorithms, mathematical algorithms have been developed in this chapter that allow determining the detection of proteins active regions and detecting the stability of different regions of protein complexes (linear docking) by analyzing the potential energy matrix of pairwise electrostatic interaction between different sites of the biological complex, such as the homodimer of the histone chaperone Nap1-Nap1, the heterodimer of the p53 Mdm2 proteins, and the homodimer Mdm2 Mdm2, which are responsible for the entry of a whole protein molecule into biochemical reactions.
鉴定不同蛋白分子在形成Nap1-Nap1、Mdm2-Mdm2和P53-Mdm2时的活性位点相互作用
在本报告中,我们开发了两个算法,算法1和算法2。算法1是为了寻找具有短活性区域的全长蛋白多肽链的相互作用而开发的。算法2用于确定从N端到C端形成二聚体时全长蛋白之间相互作用最活跃的位点。利用Mdm2、Nap1、P53蛋白进行数值计算。对于现代蛋白质组学来说,蛋白质相互作用的研究和预测是非常重要的任务,因为它们决定了从细胞到整个生物体水平上蛋白质的功能。对于结构已知的蛋白质,根据其三级结构构象的已知数据寻找分子间相互作用可以简化为寻找两个相互作用的分子表面各部分的几何互补性并对其接触建模的问题,即所谓的分子对接。分子对接的任务是构象搜索算法的任务,由于蛋白质分子扭转角的变化,它简化为对形成的生物复合物的构象空间的搜索。现代构象搜索算法在大多数情况下可以在相对较短的时间内找到与实验发现的结构大致接近的构象。然而,还有一些因素也会对对接的成功与否产生重大影响,而这些因素在标准算法中往往没有考虑到。其中一个因素是目标蛋白的构象流动性。迁移范围可以从侧链的小调整开始,以规模域运动结束。这些运动起着重要的作用。乍一看,这个问题最合乎逻辑的解决方案是在对接程序中考虑蛋白质的移动性。不幸的是,现代计算工具不允许在可接受的时间框架内进行这样的建模,因为蛋白质分子非常大,并且允许在所有自由度上的移动可能导致所谓的组合爆炸(可能的变体数量的天文数字增加)。只有在某些程序中,蛋白质结合位点的流动性有限(通常在活性中心残基侧链构象的小适应水平上)。解决这个问题的另一种方法是将相同的蛋白质以几种不同的构象进行对接,然后从每次对接运行中选择最佳解决方案。第三种方法是找到一种靶蛋白的通用结构,在这种结构中,对接不同类型的配体会产生相当好的结果。在这种情况下,错过的(但正确的)解决方案的数量减少,但不正确的选项的数量也显著增加。还应该指出的是,大多数蛋白质理论对接的程序都是按照以下原则工作的:一个蛋白质在空间中固定,另一个以各种方式围绕它旋转。同时,对于每个旋转构型,对评价函数进行估计。评价函数基于表面互补性(由其化学性质决定的互补结构(大分子、自由基)的相互对应)、静电相互作用、范德华斥力等。这种方法的问题在于,整个构型空间的计算需要大量的时间,很少导致单一的解决方案,这反过来又不允许我们谈论目标蛋白质和配体相互作用变异的独特性。因此,在通过分子动力学方法建模的工作中,发现了200到10000种与配体形成蛋白质复合物的可能组合。如此大量的修饰,加上缺乏选择生物复合物结合结构的最可能变体的标准(这将允许它们的数量急剧减少),使得很难解释实际应用中获得的理论结果,即催化中心的发现和相互作用物质解离常数的定性评估。与上述计算机模拟算法相比,本章开发了数学算法,通过分析生物复合体不同位点之间的两两静电相互作用的势能矩阵,例如组蛋白伴侣蛋白Nap1-Nap1的同型二聚体、p53 Mdm2蛋白的异源二聚体、以及同二聚体Mdm2 Mdm2,它们负责整个蛋白质分子进入生化反应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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