Minimalist models for proteins: a comparative analysis
Minimalist models for proteins: a comparative analysis
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DOI：
10.1017/s0033583510000132
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发表时间：
2010-08
影响因子：
6.1
通讯作者：
V. Tozzini
中科院分区：
文献类型：
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作者：
V. Tozzini
摘要在过去的十年里，人们对生物聚合物的粗粒度（CG）模型重新产生了兴趣，这也是现代分子生物学的需要所激发的，它涉及纳米到微米尺寸的生物分子系统和大于微秒的时间尺度。事实上，这种规模和时间尺度的组合很难通过基于原子的模拟来访问。粗粒化系统是克服这些限制的一条途径，但是实际实现它的方法很多而且不同，使得CG模型的景观非常庞大和复杂。本文对CG模型进行了综述，并对它们的特点、应用和性能进行了比较。这种分析，仅限于蛋白质，侧重于最低限度的模型，即那些减少在最低限度的自由度，而不失去明确描述二级结构的可能性。这一类包括使用单个或几个相互作用的中心（珠）为每个氨基酸的模型。从这一分析中，出现了几个问题。建立这些模型的困难在于需要将可转移性/预测能力与准确复制结构的能力相结合。结果表明，这些方面可以通过准确地选择力场（FF）的条款和功能的形式，并结合不同的参数化程序进行优化。此外，尽管极简模型多种多样，但在参数值和FF项中可以找到不确定性。这些概述和示意性地提出了一个通用的参数空间中的多肽的相图的帮助下，并希望，可以作为指导方针的最低限度的模型，将最大可能的水平的预测能力和结构的准确性。
Abstract The last decade has witnessed a renewed interest in the coarse-grained (CG) models for biopolymers, also stimulated by the needs of modern molecular biology, dealing with nano- to micro-sized bio-molecular systems and larger than microsecond timescale. This combination of size and timescale is, in fact, hard to access by atomic-based simulations. Coarse graining the system is a route to be followed to overcome these limits, but the ways of practically implementing it are many and different, making the landscape of CG models very vast and complex. In this paper, the CG models are reviewed and their features, applications and performances compared. This analysis, restricted to proteins, focuses on the minimalist models, namely those reducing at minimum the number of degrees of freedom without losing the possibility of explicitly describing the secondary structures. This class includes models using a single or a few interacting centers (beads) for each amino acid. From this analysis several issues emerge. The difficulty in building these models resides in the need for combining transferability/predictive power with the capability of accurately reproducing the structures. It is shown that these aspects could be optimized by accurately choosing the force field (FF) terms and functional forms, and combining different parameterization procedures. In addition, in spite of the variety of the minimalist models, regularities can be found in the parameters values and in FF terms. These are outlined and schematically presented with the aid of a generic phase diagram of the polypeptide in the parameter space and, hopefully, could serve as guidelines for the development of minimalist models incorporating the maximum possible level of predictive power and structural accuracy.