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Computational And Experimental Studies On Protein Structure, Stability And Dynamics

机译:蛋白质结构,稳定性和动力学的计算和实验研究

摘要

The work in this thesis focuses on the study of three main aspects of proteins, viz, Protein structure, stability, and dynamics. Chapter 1 is a general introduction to the topics studied in this thesis. Chapter 2 deals with the first aspect, i.e., protein structure in which we describe an approach to use saturation mutagenesis phenotypes to guide protein structure prediction. Chapters 3 and 4 discuss how to increase protein stability using surface electrostatics, and Chapter 5 details a method to predict whether a proline substitution in a given protein would be stabilizing or destabilizing. Hence, Chapters 3-5 can be associated with the second aspect, i.e., protein stability. The third aspect, namely protein dynamics, is dealt with in Chapters 6 and 7 which study conformational dynamics of adenylate kinase. Protein structure prediction is a difficult problem with two major bottlenecks, namely, generation of accurate models and the selection of the most appropriate models from a large pool of decoys. In Chapter 2, the problem of model discrimination is addressed using mutant phenotype information derived from saturation mutagenesis library. A library of ~1500 single-site mutants of the E. coli toxin CcdB (Controller of Cell Division or Death B) has been previously constructed in our lab. The pooled library was characterized in terms of individual mutant phenotypes at various expression levels which were derived from the relative populations of mutants at each expression level. The relative populations of mutants were estimated using deep sequencing. Mutational tolerances were derived from the phenotypic data and were used to define an empirical parameter which correlated with a structural parameter, residue depth. We further studied how this new parameter can be used for model discrimination. Increasing protein stability in a rational way is a challenging problem and has been addressed by various approaches. One of the most commonly used approaches is optimization of protein core residues. Recently, optimization of protein surface electrostatics has been shown to be a useful approach for increasing stability of proteins. In Chapter 3, from analyses of a dataset of ~1750 non-homologues proteins, we show that proteins having a pI away from physiological pH, possess a significant fraction of unfavorably placed charged amino acids on their surface. One way to increase protein stability in such cases might be to alter these surface charges. This hypothesis was validated experimentally by making charge reversal mutations at putative unfavorable positions on the surface of maltose binding protein, MBP. The observed stabilization can potentially be increased by combining multiple individually stabilizing mutations. Different combinations of such mutations were made and tested in Chapter 4 to decide which mutants can be combined to achieve net stabilization. Ideas were tested through systematic experimentation which involved generation of two-site, three-site, and four-site mutations. A maximum increase in melting temperature (Tm) of 3-4 °C over wild-type protein was achieved upon combination of individually stabilizing mutants. Proline (Pro) has two special stereo-chemical properties when it is a part of a polypeptide chain. First the φ value of Pro has a very constrained distribution and second, Pro lacks an amide hydrogen. Due to these properties, introduction of Pro might perturb stability/activity of the protein. In Chapter 5 we describe a procedure to accurately predict the effects of Pro introduction on protein stability. Pro scanning mutagenesis was carried out on the model protein CcdB and the in vivo activity of the individual mutants was also examined. A decision tree was constructed, using the special stereo-chemical properties of Pro to maximize correlation of predicted phenotype with the in vivo activity. Binary classification as perturbing or non-perturbing of every Pro substitution was possible using the decision tree. The performance of the decision tree was assessed on various test systems, and the average accuracy was found to be ~75%. The role of conformational dynamics in enzyme catalysis has been explored in great detail in the literature. In Chapter 6, with the help of very long (350 ns), fully atomistic, explicit solvent molecular dynamics simulations, we studied conformational dynamics of adenylate kinase. We found the existence of a relatively stable state which lies intermediate between the open and closed conformations of the enzyme. The finding was further confirmed by computing a two dimensional configurational free energy surface when motions along each of the two movable domains (LID and NMP) are considered as reaction coordinates. We also discussed possible roles of the intermediate state during enzyme catalysis. The role of water in stabilization of intermediate states was also discussed. In Chapter 7, we studied dynamical coupling between LID and NMP domains of adenylate kinase during domain opening. Our observation suggests that the LID domain should start opening prior to the NMP domain. On the domain opening trajectory, the free energy surface of LID domain was found to be very rugged. We discuss a possible role of water in the ruggedness of the domain motions. The Appendix contains 3 supplementary parts of the thesis. Appendix I is a mutant dataset obtained from 454 sequencing analysis. It includes the normalized number of reads per mutation at each expression level along with mutational sensitivity score. Appendix II is parameters used for one of the electrostatic calculations. Appendix III contains a list of PDB ids used for database analysis in surface electrostatics work discussed in Chapter 3.
机译:本文的工作主要集中在蛋白质三个主要方面的研究,即蛋白质结构,稳定性和动力学。第1章是对本文研究主题的概述。第2章涉及第一个方面,即蛋白质结构,其中我们描述了使用饱和诱变表型指导蛋白质结构预测的方法。第3章和第4章讨论了如何使用表面静电来提高蛋白质的稳定性,第5章详细介绍了一种预测给定蛋白质中脯氨酸取代是稳定还是不稳定的方法。因此,第3-5章可以与第二方面相关,即蛋白质稳定性。第三个方面,即蛋白质动力学,在第6章和第7章中讨论,它们研究腺苷酸激酶的构象动力学。蛋白质结构预测是一个棘手的问题,存在两个主要瓶颈,即生成准确的模型和从大量诱饵中选择最合适的模型。在第2章中,使用源自饱和诱变库的突变表型信息解决了模型识别问题。以前在我们的实验室中已构建了约1500个大肠杆菌毒素CcdB单点突变体(细胞分裂或死亡B的控制者)的文库。汇集的文库根据在各个表达水平的个体突变表型来表征,所述表型衍生自在每个表达水平的突变体的相对群体。使用深度测序估计突变体的相对种群。从表型数据得出变异容差,并用于定义与结构参数(残基深度)相关的经验参数。我们进一步研究了如何将此新参数用于模型判别。以合理的方式增加蛋白质的稳定性是一个具有挑战性的问题,并且已经通过各种方法解决了。最常用的方法之一是优化蛋白核心残基。近来,已经证明优化蛋白质表面静电是增加蛋白质稳定性的有用方法。在第3章中,通过对约1750个非同源蛋白质蛋白质数据集的分析,我们显示了pI值与生理pH值不同的蛋白质在其表面上具有很大一部分不利的带电氨基酸。在这种情况下增加蛋白质稳定性的一种方法可能是改变这些表面电荷。通过在麦芽糖结合蛋白MBP的表面上的假定不利位置进行电荷反转突变,通过实验验证了该假设。通过组合多个单独稳定的突变,可能会提高观察到的稳定度。制作了此类突变的不同组合并在第4章中进行了测试,以确定可以组合哪些突变以实现净稳定。通过系统的实验测试了想法,该实验涉及生成两点,三点和四点突变。单独稳定化的突变体组合后,与野生型蛋白相比,解链温度(Tm)最高提高了3-4°C。当脯氨酸(Pro)是多肽链的一部分时,具有两个特殊的立体化学性质。首先,Pro的φ值分布非常受限,其次,Pro缺少酰胺氢。由于这些特性,Pro的引入可能会扰乱蛋白质的稳定性/活性。在第5章中,我们描述了一种准确预测Pro导入对蛋白质稳定性的影响的过程。在模型蛋白CcdB上进行前扫描诱变,还检查了单个突变体的体内活性。使用Pro的特殊立体化学特性,构建决策树,以最大程度地提高预测表型与体内活性的相关性。使用决策树可以对每个Pro替换进行干扰或不干扰的二进制分类。在各种测试系统上评估了决策树的性能,发现平均准确性为〜75%。构象动力学在酶催化中的作用已在文献中进行了详细探讨。在第六章中,借助很长的时间(350 ns),完全原子的,明确的溶剂分子动力学模拟,我们研究了腺苷酸激酶的构象动力学。我们发现存在相对稳定的状态,该状态位于酶的开放和闭合构象之间。当将沿两个可移动域(LID和NMP)中的每一个的运动视为反应坐标时,通过计算二维构型自由能表面进一步证实了这一发现。我们还讨论了中间态在酶催化过程中的可能作用。还讨论了水在稳定中间态中的作用。在第七章,我们研究了域开放期间LID和腺苷酸激酶NMP域之间的动力学耦合。我们的观察表明,LID域应该在NMP域之前开始打开。在畴开放轨迹上,发现LID畴的自由能表面非常坚固。我们讨论了水在域运动的坚固性中的可能作用。附录包含论文的三个补充部分。附录I是从454测序分析获得的突变数据集。它包括每个表达水平上每个突变的标准化读取数以及突变敏感性评分。附录二是用于静电计算之一的参数。附录III包含了第3章中讨论的用于表面静电工作中的数据库分析的PDB ID列表。

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    Adkar Bharat V;

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  • 年度 2011
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