Best Robert B, Zhu Xiao, Shim Jihyun, Lopes Pedro E M, Mittal Jeetain, Feig Michael, Mackerell Alexander D
University of Cambridge, Department of Chemistry, Lensfield Road, Cambridge CB2 1EW.
J Chem Theory Comput. 2012 Sep 11;8(9):3257-3273. doi: 10.1021/ct300400x. Epub 2012 Jul 18.
While the quality of the current CHARMM22/CMAP additive force field for proteins has been demonstrated in a large number of applications, limitations in the model with respect to the equilibrium between the sampling of helical and extended conformations in folding simulations have been noted. To overcome this, as well as make other improvements in the model, we present a combination of refinements that should result in enhanced accuracy in simulations of proteins. The common (non Gly, Pro) backbone CMAP potential has been refined against experimental solution NMR data for weakly structured peptides, resulting in a rebalancing of the energies of the α-helix and extended regions of the Ramachandran map, correcting the α-helical bias of CHARMM22/CMAP. The Gly and Pro CMAPs have been refitted to more accurate quantum-mechanical energy surfaces. Side-chain torsion parameters have been optimized by fitting to backbone-dependent quantum-mechanical energy surfaces, followed by additional empirical optimization targeting NMR scalar couplings for unfolded proteins. A comprehensive validation of the revised force field was then performed against data not used to guide parametrization: (i) comparison of simulations of eight proteins in their crystal environments with crystal structures; (ii) comparison with backbone scalar couplings for weakly structured peptides; (iii) comparison with NMR residual dipolar couplings and scalar couplings for both backbone and side-chains in folded proteins; (iv) equilibrium folding of mini-proteins. The results indicate that the revised CHARMM 36 parameters represent an improved model for the modeling and simulation studies of proteins, including studies of protein folding, assembly and functionally relevant conformational changes.
虽然目前用于蛋白质的CHARMM22/CMAP加和力场的质量已在大量应用中得到验证,但在折叠模拟中,该模型在螺旋构象和伸展构象采样平衡方面存在局限性。为克服这一问题并对模型进行其他改进,我们提出了一系列优化方法,有望提高蛋白质模拟的准确性。针对弱结构肽的实验溶液核磁共振数据,对常见(非甘氨酸、脯氨酸)主链CMAP势进行了优化,从而重新平衡了拉氏图中α螺旋区和伸展区的能量,纠正了CHARMM22/CMAP的α螺旋偏差。对甘氨酸和脯氨酸的CMAP进行了重新拟合,使其更符合精确的量子力学能量表面。通过拟合依赖于主链的量子力学能量表面来优化侧链扭转参数,随后针对未折叠蛋白质的核磁共振标量耦合进行额外的经验优化。然后,针对未用于指导参数化的数据,对修订后的力场进行了全面验证:(i)将八种蛋白质在晶体环境中的模拟结果与晶体结构进行比较;(ii)与弱结构肽的主链标量耦合进行比较;(iii)与折叠蛋白质中主链和侧链的核磁共振剩余偶极耦合和标量耦合进行比较;(iv)微型蛋白质的平衡折叠。结果表明,修订后的CHARMM 36参数为蛋白质的建模和模拟研究提供了一个改进的模型,包括蛋白质折叠、组装和功能相关构象变化的研究。