Energetics of Protein Nucleation on Rough Polymeric Surfaces
Energetics of Protein Nucleation on Rough Polymeric Surfaces
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DOI：
10.1021/jp106349d
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发表时间：
2010-11-04
影响因子：
3.3
通讯作者：
Drioli, Enrico
中科院分区：
文献类型：
--
作者：
Curcio, Efrem;Curcio, Valerio;Drioli, Enrico
采用二维伊辛模型的Metropolis蒙特卡罗(MC)算法研究蛋白质晶体在粗糙的聚合物表面上的非均相成核。将理论结果与经典成核理论(CNT)以及蛋白质模型蛋清溶菌酶(HEWL)在聚偏氟乙烯(PVDF)、聚二甲基硅氧烷(PVDF)、聚二甲基硅氧烷(PDMS)和海氟隆(Hyflon)自制膜上结晶的实验数据进行了比较。随着表面粗糙度的增加，聚合物膜上成核过程的活化能降低，导致成核动力学比均相快许多个数量级。总而言之，MC随机动力学提供了一个独特的机会来研究在位置水平上的集体分子聚集对成核速率的影响，从而允许识别最优的聚合物膜的形态和结构属性，从而精细地控制结晶动力学。
Metropolis Monte Carlo (MC) algorithm of the two-dimensional Ising model is used to study the heterogeneous nucleation of protein crystals on rough polymeric surfaces. The theoretical findings are compared to those obtained from classical nucleation theory (CNT), and to experimental data from protein model hen egg white lysozyme (HEWL) crystallized on poly(vinylidene fluoride) or PVDF, poly(dimethylsiloxane) or PDMS and Hyflon homemade membranes. The reduction of the activation energy for the nucleation process on polymeric membranes, predicted to occur at increasing surface roughness, results in a nucleation kinetics that is many orders of magnitude faster than in homogeneous phase. In general, MC stochastic dynamics offers the unique opportunity to investigate the effects of collective molecular aggregation at site level on the nucleation rate and, consequently, allows to identify optimal morphological and structural properties of polymeric membranes for a fine control of the crystallization kinetics.