【作者】 李泉；

【导师】 陈海峰；

【作者基本信息】 上海交通大学 ， 生物学， 2019， 博士

【摘要】 蛋白质的功能是由它们的三维结构的构象决定的,蛋白质可以对外界环境的各种变化作出响应,通过改变自身的构象来切换自己的功能角色。特别是作为受体的蛋白质,在结合配体(小分子或短肽)之后,构象会发生相应的变化,最后使蛋白达到特定的状态,如结合激动剂或拮抗剂后,构象变化并使蛋白受体激活或失活,而构象变化并不是在所有区域发生的。追踪这些区域发生的变化以及探索构象变化的分子机制并对构象变化与残基间的互作网络方面的联系进行解释和说明是非常重要的生物学课题。蛋白质作为柔性分子可以经受复杂的构象变化,除了来自于内部氨基酸残基之间的相互作用外,还有一部分来自于其它蛋白质或者配体分子间的相互作用。而构象变化可能是由主链中的一些残基发生了翻转(改变了方向)或者是侧链的二面角发生了变化引发的,而后者的变化会引起蛋白质局部构象变化并向周围扩展而形成大规模的结构变化。追踪和鉴别这些引起蛋白构象变化的关键残基对我们理解和研究蛋白质的结构变化与其生物学功能之间的联系有着极其重要的意义。为了揭示蛋白构象变化的分子机制,我们需要找到和发现那些对蛋白质构象变化的发生起主要作用的关键残基以及驱使这些关键残基变化的驱动力。很多基于计算机模拟的计算方法如分子动力学模拟和蒙特卡罗模拟,以及相应的分析方法如简正模式分析、弹性网络分析,在近十年来被开发出来用以研究蛋白质的构象变化,还有一些方法用以发现引起构象变化的关键氨基酸的残基,如二面角动态分析(Torsion angle dynamics),Bee算法(Bee Algorithm)、残基互作网络分析(Residues interaction network)以及动态相关性网络分析(Dynamic cross-correlation network)等。上述方法大致可以分为两类,一类是通过相互作用构建全残基的网络模型,再利用相关网络指标或参数来发现重要残基;另一种是通过二面角数据的拉式构象图对比来发现差异氨基酸。但前者是通过残基的网络属性来推断结构属性,并不能直接反映蛋白的构象变化,亦不能反映残基的构象是否变化,更不能解释蛋白构象变化的分子机制;在应用层面上则需要计算每一对残基间的距离并耗费大量的机时,而且计算结果并不能准确地用以鉴定对构象变化起主要作用的关键残基;而后者的比对方法只停留在图像的比对上,不能精确进行量化。因此,我们开发了动态关键残基互作网络-Dynamic Important Residues Network(DIRN)用以识别引起构象变化的关键残基,它以结构数据作为比对对象,包括二级结构(DSSP)、二面角(Dihedral torsion,用Dih表示)、三联氨基酸夹角(Angles of three consecutive amino acids,用T-ang表示)、各侧链二面角(第一至第四侧链二面角,分别用Chi1、Chi2、Chi3、Chi4表示)、欧米伽张力角(用Omega表示)、各NMR数据(包括Cα-NH之间J耦合常数,Cβ-NH之间J耦合常数和alpha HNH之间J耦合常数,分别用Jnhc、Jnhb和Jnha表示)。首先通过对不同的体系轨迹间的结构数据进行比对来发现结构发生明显变化(如翻转、侧链变动)的氨基酸残基(称为关键残基),再对这些关键残基构成的互作网络进行分析,研究残基间互作关系的变化,以找到引起残基构象变化的驱动力,从而对蛋白受体构象变化的分子机制以及信息传递途径进行研究和阐述。为了验证DIRN方法的准确性及可靠性,本文使用丙酮酸激酶PKM2以及G蛋白偶联受体家族的毒蕈碱乙酰胆碱受体M2和阿片受体κ进行验证,结果显示DIRN方法具有较高的灵敏度和特异度,同时具有可靠性和鲁棒性,可以作为蛋白质关键残基的预测方法。更多还原

【Abstract】 Protein functions are mostly determined by their three-dimensional structures which linked to conformational changes.Proteins can switch their functional roles among different conformations in response to various environments.Comformation change always companied with the functional process when protein binding agonist or antagonist.Therefore we need to answer two questions in order to undstand the allosteric mechanism,how and why the conformational changes happen.Protein as a macromolecule with diverse spatial structure can undergo flexible and complex conformation change under the force by the interactions from internal residues or external molecules.Protein conformational changes may be caused by reorientations of some residues and torsional changes in the main chain,the changes in torsional angles may induce localized changes or large scale domain motions.Aim to this,we need to investigate the key residues which are responsible for conformational changes and driven forces.First,we found protein conformational changes induced by the character changes of some residues in main chain torsional angles and side chain orientations.Tracing these changes is important for understanding the way of these proteins function.To answer the mentioned question,many computational methods that trace and simulate conformational changes in proteins include Molecular Dynamics(MD),Monte Carlo(MC)and their variants have been released.Additional efficient methods focusing on conformational changes in the protein structures are also employed such as Torsion angle dynamics(TAD),Bee Algorithm,Structured Intuitive Move Selector(SIMS)and Comparison with a classification based on normalized Bfactors.However,traditional biophysics-based conformational search methods require a large number of calculations and are hard to apply to large-scale conformational motions.Here we use Dynamical Importnt Residues Network(DIRN)to identify the character of structural data including Secondary Structure(DSSP),Dihedrals(Dih),Angles of three consecutive amino acids(T-ang),Chi1 torsions(Chi1),Chi2 torsions(Chi2),Chi3 torsions(Chi3),Chi4 torsions(Chi4),Omega torsions(Omega),as well as NMR data such as Scalar Coupling between HN and C_prime(Jnhc),Scalar Coupling between HN and C_beta(Jnhb),Scalar Coupling between HN and H_alpha(Jnha).Second,we study the interactions including hydrogen bond and hydrophobic interaction for these key residues distributing in conformation changing area,finding an obvious interaction network,was mapped on these residues covering global proteins,so we propose a hypothesis that conformational changes are initiated by the variation of interactions through a network comparison of a series key residues and this can also help us undstanding the signaling pathway.Human M2 muscarinic acetylcholine receptor(M2)and opioid receptor kappa(κOR)protein were used to validate this approach.更多还原