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分子建模

實物作成的分子模型。
電腦軟體製作的分子模型。
實物作成的脯胺酸分子模型。

分子建模(英語:Molecular modelling)或稱分子模擬,是指利用理論方法與計算技術,模擬出化學分子的外觀或性質,屬於計算化學計算生物學領域的研究對象。並且是化學生物學上,如結構生物學等學門所應用的研究方法。

分类

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分子建模中最理想化即为量子力学(quantum mechanics,QM),包括从头算(ab initio)、密度泛函理论(density functional theory)等,原则上任何系统皆可得到优良结果,而无需特意进行参数化。虽然QM理论性强,但是成本极高,仅可用于小模型系统中分析电子分布及转移过程,更大尺度下的建模方法则由全原子分子动力学(all atom molecular dynamics,AAMD)取代。诸如AAMD这样的分子力学(molecular mechanics,MM)通过力场(force field)定义模拟过程中分子内内外相互作用力,根据原子间距离、键角等几何关系计算势能,而力场参数则通过首先通过QM计算得到。若结合QM精确性及MM快速性,在电子重排区域较为局限时,可使用混合QM/MM(hybrid QM/MM)方法,小部分关键活性位点由QM描述,而剩余大部分则由力场描述。若需要在更大尺度进行模拟,则需要通过粗粒化(coarse-grained,CG)将多个相邻原子视为单个CG珠子,珠子间相互作用再描述以参数化势能函数进行模拟,然而CG会丢失原子本身信息,降低系统模拟准确性[1][2]

历史

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分子聚合物与核酸的相互作用研究,由于现今仪器分辨率所限而无法更深入进行探索,可通过分子建模填补此中空白。通过计算机模拟,可获得原子或分子运动状态,从中分析相互作用,自1977年James Andrew McCammon等人首次模拟生物大分子以来,分子建模已成为生物系统的独特分析工具,其中模拟方法也不断发展。生物大分子结构多样,单一尺度下无法良好模拟,因此近年来已发展出诸多分子建模方法,涵盖多种不同尺度[3]

AMBER力场中,1999年Peter Andrew Kollman团队提出parm99力场,可以很好描述核酸模型[4],但随着模拟时长延长至100 ns尺度,则逐渐产生问题。2007年Modesto Orozco等人基于parm99改进了DNA在α/γ协同扭转方面的描述,提出了parmbsc0力场,解决了100 ns时间尺度内的核酸结构精确性[5],2016年该团队再提出parmbsc1,使DNA在μs尺度下维持模拟过程结构精确性[6]。AMBER 力场主要描述蛋白质以及核酸系统,对有机分子则力所不及,因此聚合物与DNA结合模拟中,仍需援引其他力场共同协助。2004年David A. Case等人提出GAFF(general AMBER force field),形式及参数化与AMBER力场一致,将力场范围扩展至各种带氢、碳、氮、氧、硫、磷以及卤素原子的有机分子。基于原子类型、电荷、键长、键角和扭转角等进行参数化,并不描述不同原子类型组合,而是根据键合拓扑结构及几何形状定义给定的有机分子[7]

分子建模軟體

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虽然AAMD当前仅能在μs尺度以内模拟106个原子,但随着算力不断提升,以及力场参数不断优化下不断发展。对于MD,其准确性极大取决于力场选择,不同力场专注于描述不同分子,选择不良力场易导致结果偏差。MD所用力场中,AMBER(assisted model building with energy refinement)和CHARMM(chemistry at Harvard macromolecular mechanics)使用最为广泛。目前MD领域,模拟常用程序包主要有CHARMM、AMBER、GROMACS(Groningen machine for chemical simulations)以及NAMD(nanoscale molecular dynamics)。各程序包基础功能类似,但也各有特色,CHARMM分析范围广泛,但是学习曲线较陡,需掌握其复杂脚本语言,且并行能力较差;NAMD简单易用,但其功能有所削减,仅有AAMD基本功能。AMBER与GROMACS功能近似NAMD,其中GROMACS无需使用脚本语言,拥有大量轨迹分析工具,其开源特性也独一于上述四种程序包,应用广泛[8]

一些常用软件参见

參見

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外部連結

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參考文獻

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  • A. R. Leach, Molecular Modelling: Principles and Applications, 2001, ISBN 0-582-38210-6
  • D. Frenkel, B. Smit, Understanding Molecular Simulation: From Algorithms to Applications, 1996, ISBN 0-12-267370-0
  • D. C. Rapaport, The Art of Molecular Dynamics Simulation, 2004, ISBN 0-521-82586-7
  • R. J. Sadus, Molecular Simulation of Fluids: Theory, Algorithms and Object-Orientation, 2002, ISBN 0-444-51082-6


  1. ^ Meneksedag-Erol, Deniz; Tang, Tian; Uludağ, Hasan. Molecular modeling of polynucleotide complexes. Biomaterials. 2014-08, 35 (25). ISSN 0142-9612. doi:10.1016/j.biomaterials.2014.04.103. 
  2. ^ Dans, Pablo D; Walther, Jürgen; Gómez, Hansel; Orozco, Modesto. Multiscale simulation of DNA. Current Opinion in Structural Biology. 2016-04, 37. ISSN 0959-440X. doi:10.1016/j.sbi.2015.11.011. 
  3. ^ McCammon, J. Andrew; Gelin, Bruce R.; Karplus, Martin. Dynamics of folded proteins. Nature. 1977-06, 267 (5612). ISSN 0028-0836. doi:10.1038/267585a0. 
  4. ^ Cheatham, Thomas E.; Cieplak, Piotr; Kollman, Peter A. A Modified Version of the Cornellet al.Force Field with Improved Sugar Pucker Phases and Helical Repeat. Journal of Biomolecular Structure and Dynamics. 1999-02, 16 (4). ISSN 0739-1102. doi:10.1080/07391102.1999.10508297. 
  5. ^ Pérez, Alberto; Marchán, Iván; Svozil, Daniel; Sponer, Jiri; Cheatham, Thomas E.; Laughton, Charles A.; Orozco, Modesto. Refinement of the AMBER Force Field for Nucleic Acids: Improving the Description of α/γ Conformers. Biophysical Journal. 2007-06, 92 (11). ISSN 0006-3495. doi:10.1529/biophysj.106.097782. 
  6. ^ Ivani, Ivan; Dans, Pablo D; Noy, Agnes; Pérez, Alberto; Faustino, Ignacio; Hospital, Adam; Walther, Jürgen; Andrio, Pau; Goñi, Ramon; Balaceanu, Alexandra; Portella, Guillem. Parmbsc1: a refined force field for DNA simulations. Nature Methods. 2015-11-16, 13 (1). ISSN 1548-7091. doi:10.1038/nmeth.3658. 
  7. ^ Wang, Junmei; Wolf, Romain M.; Caldwell, James W.; Kollman, Peter A.; Case, David A. Development and testing of a general amber force field. Journal of Computational Chemistry. 2004, 25 (9). ISSN 0192-8651. doi:10.1002/jcc.20035. 
  8. ^ Salsbury Jr, Freddie R. Molecular dynamics simulations of protein dynamics and their relevance to drug discovery. Current Opinion in Pharmacology. 2010-12, 10 (6). ISSN 1471-4892. doi:10.1016/j.coph.2010.09.016. 
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分子建模
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