Vianello Robert, Domene Carmen, Mavri Janez
Computational Organic Chemistry and Biochemistry Group, Ruđer Bošković Institute Zagreb, Croatia.
Department of Chemistry, King's College LondonLondon, UK; Chemistry Research Laboratory, University of OxfordOxford, UK.
Front Neurosci. 2016 Jul 15;10:327. doi: 10.3389/fnins.2016.00327. eCollection 2016.
HIGHLIGHTS Computational techniques provide accurate descriptions of the structure and dynamics of biological systems, contributing to their understanding at an atomic level.Classical MD simulations are a precious computational tool for the processes where no chemical reactions take place.QM calculations provide valuable information about the enzyme activity, being able to distinguish among several mechanistic pathways, provided a carefully selected cluster model of the enzyme is considered.Multiscale QM/MM simulation is the method of choice for the computational treatment of enzyme reactions offering quantitative agreement with experimentally determined reaction parameters.Molecular simulation provide insight into the mechanism of both the catalytic activity and inhibition of monoamine oxidases, thus aiding in the rational design of their inhibitors that are all employed and antidepressants and antiparkinsonian drugs. Aging society and therewith associated neurodegenerative and neuropsychiatric diseases, including depression, Alzheimer's disease, obsessive disorders, and Parkinson's disease, urgently require novel drug candidates. Targets include monoamine oxidases A and B (MAOs), acetylcholinesterase (AChE), butyrylcholinesterase (BChE), and various receptors and transporters. For rational drug design it is particularly important to combine experimental synthetic, kinetic, toxicological, and pharmacological information with structural and computational work. This paper describes the application of various modern computational biochemistry methods in order to improve the understanding of a relationship between the structure and function of large biological systems including ion channels, transporters, receptors, and metabolic enzymes. The methods covered stem from classical molecular dynamics simulations to understand the physical basis and the time evolution of the structures, to combined QM, and QM/MM approaches to probe the chemical mechanisms of enzymatic activities and their inhibition. As an illustrative example, the later will focus on the monoamine oxidase family of enzymes, which catalyze the degradation of amine neurotransmitters in various parts of the brain, the imbalance of which is associated with the development and progression of a range of neurodegenerative disorders. Inhibitors that act mainly on MAO A are used in the treatment of depression, due to their ability to raise serotonin concentrations, while MAO B inhibitors decrease dopamine degradation and improve motor control in patients with Parkinson disease. Our results give strong support that both MAO isoforms, A and B, operate through the hydride transfer mechanism. Relevance of MAO catalyzed reactions and MAO inhibition in the context of neurodegeneration will be discussed.
计算技术能够精确描述生物系统的结构和动力学,有助于在原子水平上理解这些系统。经典分子动力学模拟是研究无化学反应过程的宝贵计算工具。量子力学计算能提供有关酶活性的有价值信息,若考虑精心挑选的酶簇模型,就能区分几种反应机理途径。多尺度量子力学/分子力学模拟是计算处理酶反应的首选方法,能与实验测定的反应参数达成定量一致。分子模拟有助于深入了解单胺氧化酶的催化活性和抑制机制,从而辅助合理设计其抑制剂,这些抑制剂被用作抗抑郁药和抗帕金森病药物。老龄化社会以及与之相关的神经退行性和神经精神疾病,包括抑郁症、阿尔茨海默病、强迫症和帕金森病,迫切需要新型候选药物。靶点包括单胺氧化酶A和B(MAOs)、乙酰胆碱酯酶(AChE)、丁酰胆碱酯酶(BChE)以及各种受体和转运蛋白。为了合理进行药物设计,将实验性的合成、动力学、毒理学和药理学信息与结构和计算工作相结合尤为重要。本文描述了各种现代计算生物化学方法的应用,以增进对包括离子通道、转运蛋白、受体和代谢酶在内的大型生物系统结构与功能关系的理解。所涵盖的方法从用于理解结构的物理基础和时间演化的经典分子动力学模拟,到用于探究酶活性及其抑制的化学机制的量子力学以及量子力学/分子力学相结合的方法。作为一个示例,后文将聚焦于单胺氧化酶家族的酶,它们催化大脑不同部位胺类神经递质的降解,其失衡与一系列神经退行性疾病的发生和发展相关。主要作用于MAO A的抑制剂因其能够提高血清素浓度而用于治疗抑郁症,而MAO B抑制剂可减少帕金森病患者体内多巴胺的降解并改善运动控制。我们的结果有力地支持了MAO的两种同工型A和B均通过氢化物转移机制发挥作用。将讨论MAO催化反应及MAO抑制在神经退行性变背景下的相关性。