GROMACS中FMM静电恒pH模拟。(B) GPU加速哈密顿插值。

IF 5.5 1区 化学 Q2 CHEMISTRY, PHYSICAL Journal of Chemical Theory and Computation Pub Date : 2025-02-25 Epub Date: 2025-02-07 DOI:10.1021/acs.jctc.4c01319
Bartosz Kohnke, Eliane Briand, Carsten Kutzner, Helmut Grubmüller
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引用次数: 0

摘要

生物大分子(如蛋白质、DNA/RNA或其复合物)的结构动力学受到其典型的许多可滴定基团的质子化变化的强烈影响,这解释了它们的pH敏感性。相反,生物分子的构象和环境变化会影响这些基团的质子化状态。除了少数例外,传统的基于力场的分子动力学(MD)模拟不能考虑这些影响,也不允许与pH缓冲液耦合。λ动力学方法实现了这种耦合,从而允许恒定ph下的MD模拟。它使用单独的哈密顿量来表示每个可滴定基团的质子化和去质子化状态,并在它们之间连续插入动态λ变量。然而,当使用粒子网格Ewald (PME)时,严格实现哈密顿插值(HI) λ动力学对于典型数量的站点来说是非常缓慢的。为了避免这个问题,最近有人提出用电荷(QI)来代替哈密顿量。在本文的第二篇论文中,我们提出了一种严格而高效的多极加速哈密顿插值(MAHI)方法来执行GROMACS中的λ动力学。从电荷尺度的哈密顿量开始,用快速多极方法(FMM)预先计算,计算出正确的HI力,计算开销可以忽略不计。然而,其他的静电求解器,如PME,也可以用于预计算。我们将哈密顿插值与电荷插值进行了比较,并表明HI导致质子化态之间更频繁的转换,从而获得更好的采样和精度。我们的准确性和性能基准测试表明,与常规的基于fmm的模拟相比,在100万原子的MD系统中引入512个可滴定位点,可增加不到20%的运行时间。我们已经将该方案集成到模拟软件GROMACS的gpu加速FMM代码中,允许从标准力场模拟轻松过渡到恒定pH模拟。
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Constant pH Simulation with FMM Electrostatics in GROMACS. (B) GPU Accelerated Hamiltonian Interpolation.

The structural dynamics of biological macromolecules, such as proteins, DNA/RNA, or their complexes, are strongly influenced by protonation changes of their typically many titratable groups, which explains their pH sensitivity. Conversely, conformational and environmental changes in the biomolecule affect the protonation state of these groups. With a few exceptions, conventional force field-based molecular dynamics (MD) simulations do not account for these effects, nor do they allow for coupling to a pH buffer. The λ-dynamics method implements this coupling and thus allows for MD simulations at constant pH. It uses separate Hamiltonians for the protonated and deprotonated states of each titratable group, with a dynamic λ variable that continuously interpolates between them. However, rigorous implementations of Hamiltonian Interpolation (HI) λ-dynamics are prohibitively slow for typical numbers of sites when used with particle mesh Ewald (PME). To circumvent this problem, it has recently been proposed to interpolate the charges (QI) instead of the Hamiltonians. Here, in the second of two companion papers, we propose a rigorous yet efficient Multipole-Accelerated Hamiltonian Interpolation (MAHI) method to perform λ-dynamics in GROMACS. Starting from a charge-scaled Hamiltonian, precomputed with the Fast Multipole Method (FMM), the correct HI forces are calculated with negligible computational overhead. However, other electrostatic solvers, such as PME, can also be used for the precomputation. We compare Hamiltonian interpolation with charge interpolation and show that HI leads to more frequent transitions between protonation states, resulting in better sampling and accuracy. Our accuracy and performance benchmarks show that introducing, e.g., 512 titratable sites to a one million atom MD system increases runtime by less than 20% compared to a regular FMM-based simulation. We have integrated the scheme into our GPU-accelerated FMM code for the simulation software GROMACS, allowing easy and effortless transitions from standard force field simulations to constant pH simulations.

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来源期刊
Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation 化学-物理:原子、分子和化学物理
CiteScore
9.90
自引率
16.40%
发文量
568
审稿时长
1 months
期刊介绍: The Journal of Chemical Theory and Computation invites new and original contributions with the understanding that, if accepted, they will not be published elsewhere. Papers reporting new theories, methodology, and/or important applications in quantum electronic structure, molecular dynamics, and statistical mechanics are appropriate for submission to this Journal. Specific topics include advances in or applications of ab initio quantum mechanics, density functional theory, design and properties of new materials, surface science, Monte Carlo simulations, solvation models, QM/MM calculations, biomolecular structure prediction, and molecular dynamics in the broadest sense including gas-phase dynamics, ab initio dynamics, biomolecular dynamics, and protein folding. The Journal does not consider papers that are straightforward applications of known methods including DFT and molecular dynamics. The Journal favors submissions that include advances in theory or methodology with applications to compelling problems.
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