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Monte Carlo simulations of antibody adsorption and orientation on charged surfaces.抗体在带电表面吸附和取向的蒙特卡洛模拟。
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General model for estimation of the inhibition of protein kinases using Monte Carlo simulations.使用蒙特卡罗模拟估算蛋白激酶抑制作用的通用模型。
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随机数生成器的质量对有机和生物系统的蒙特卡罗模拟结果有显著影响。

Quality of random number generators significantly affects results of Monte Carlo simulations for organic and biological systems.

机构信息

Department of Chemistry and Biochemistry, Worcester Polytechnic Institute, Worcester, Massachusetts 01609, USA.

出版信息

J Comput Chem. 2011 Feb;32(3):513-24. doi: 10.1002/jcc.21638. Epub 2010 Aug 23.

DOI:10.1002/jcc.21638
PMID:20734313
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2992609/
Abstract

We have simulated pure liquid butane, methanol, and hydrated alanine polypeptide with the Monte Carlo technique using three kinds of random number generators (RNG's)-the standard Linear Congruential Generator (LCG), a modification of the LCG with additional randomization used in the BOSS software, and the "Mersenne Twister" generator by Matsumoto and Nishimura. While using the latter two RNG's leads to reasonably similar physical features, the LCG produces significant different results. For the pure fluids, a noticeable expansion occurs. Using the original LCG on butane yields, a molecular volume of 171.4 Å(3) per molecule compared to about 163.6-163.9 Å(3) for the other two generators, a deviation of about 5%. For methanol, the LCG produces an average volume of 86.3 Å(3) per molecule, which is about 24% higher than the 68.8-70.2 Å(3) obtained with the RNG's in BOSS and the generator by Matsumoto and Nishimura. In case of the hydrated tridecaalanine peptide, the volume and energy tend to be noticeably greater with the LCG than with the BOSS (modified LCG) RNG's. For the simulated hydrated extended conformation of tridecaalanine, the difference in volume reached about 87%. The uniformity and periodicity of the generators do not seem to play the crucial role in these phenomena. We conclude that, it is important to test a RNG's by modeling a system such as the pure liquid methanol with a well-established force field before routinely employing it in Monte Carlo simulations.

摘要

我们使用蒙特卡罗技术,使用三种随机数生成器(RNG)模拟了纯液态丁烷、甲醇和水合丙氨酸多肽:标准线性同余生成器(LCG)、BOSS 软件中使用的附加随机化的 LCG 修正版,以及松本和西村的“Mersenne Twister”生成器。虽然使用后两种 RNG 会导致相当相似的物理特征,但 LCG 会产生明显不同的结果。对于纯流体,会发生明显的膨胀。在丁烷上使用原始 LCG 会导致每个分子的分子体积为 171.4 Å(3),而其他两种生成器的分子体积约为 163.6-163.9 Å(3),偏差约为 5%。对于甲醇,LCG 产生的平均分子体积为 86.3 Å(3),比 BOSS(修改后的 LCG)RNG 和松本和西村的生成器获得的 68.8-70.2 Å(3)高约 24%。在水合十三肽的情况下,LCG 产生的体积和能量明显大于 BOSS(修改后的 LCG)RNG。对于模拟的水合伸展构象的十三肽,体积差异达到约 87%。生成器的均匀性和周期性似乎在这些现象中没有起到关键作用。我们得出结论,在常规地将其用于蒙特卡罗模拟之前,通过模拟具有良好确立力场的纯液态甲醇等系统来测试 RNG 非常重要。