Do molecular dynamics force fields accurately model Ramachandran distributions of amino acid residues in water?
Do molecular dynamics force fields accurately model Ramachandran distributions of amino acid residues in water?
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DOI：
10.1039/d1cp05069a
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发表时间：
2022-01-06
影响因子：
3.3
通讯作者：
Urbanc, Brigita
中科院分区：
文献类型：
--
作者：
Andrews, Brian;Guerra, Jose;Urbanc, Brigita
分子动力学（MD）是研究内在无序蛋白质的有力工具，但其可靠性依赖于力场的准确性。我们评估Amber ff 19 SB、Amber ff14 SB、OPLS-AA/M和CHARMM 36 m在水中捕获GxG肽中14个客体残基x（=G、A、L、V、I、F、Y、D-P、E-P、R、C、N、S、T）的内在构象动力学的能力。每个客体残基的MD衍生的Ramachandran分布用于计算5个J-偶联常数和酰胺I '带谱，以便于通过简化的chi（2）函数与光谱数据进行比较。我们表明，高斯模型，优化以最好地拟合实验数据，优于所有MD力场的数量级。MD力场的弱点是：（i）客体残基中聚脯氨酸II（pPII）群体的可变性不足;（ii）以过渡β链区域为代价的反平行的过采样;（iii）可电离和极性残基的转角形成构象的采样不足;以及（iv）Ramachandran分布的客体残基特异性不足。尽管Amber ff 19 SB在chi（2）值方面比其他三个力场表现更差，但它比其他三个力场更好地解释了残留物特异性pPII含量。残基特异性RSFF 1和Amber ff14 SB与TIP 4P/2005组合对六个客体残基x（=A、I、F、D-P、R、S）的额外测试揭示，单独来自蛋白质卷曲文库或改进的水模型的残基特异性不会导致显著较低的chi（2）值。
Molecular dynamics (MD) is a powerful tool for studying intrinsically disordered proteins, however, its reliability depends on the accuracy of the force field. We assess Amber ff19SB, Amber ff14SB, OPLS-AA/M, and CHARMM36m with respect to their capacity to capture intrinsic conformational dynamics of 14 guest residues x (=G, A, L, V, I, F, Y, D-P, E-P, R, C, N, S, T) in GxG peptides in water. The MD-derived Ramachandran distribution of each guest residue is used to calculate 5 J-coupling constants and amide I ' band profiles to facilitate a comparison to spectroscopic data through reduced chi(2) functions. We show that the Gaussian model, optimized to best fit the experimental data, outperforms all MD force fields by an order of magnitude. The weaknesses of the MD force fields are: (i) insufficient variability of the polyproline II (pPII) population among the guest residues; (ii) oversampling of antiparallel at the expense of transitional beta-strand region; (iii) inadequate sampling of turn-forming conformations for ionizable and polar residues; and (iv) insufficient guest residue-specificity of the Ramachandran distributions. Whereas Amber ff19SB performs worse than the other three force fields with respect to chi(2) values, it accounts for residue-specific pPII content better than the other three force fields. Additional testing of residue-specific RSFF1 and Amber ff14SB combined with TIP4P/2005 on six guest residues x (=A, I, F, D-P, R, S) reveals that residue specificity derived from protein coil libraries or an improved water model alone do not result in significantly lower chi(2) values.