Escaping Atom Types in Force Fields Using Direct Chemical Perception.
Escaping Atom Types in Force Fields Using Direct Chemical Perception.
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DOI：
10.1021/acs.jctc.8b00640
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发表时间：
2018-11-13
影响因子：
5.5
通讯作者：
Eastman PK
中科院分区：
文献类型：
--
作者：
Mobley DL;Bannan CC;Rizzi A;Bayly CI;Chodera JD;Lim VT;Lim NM;Beauchamp KA;Slochower DR;Shirts MR;Gilson MK;Eastman PK
指定分子力学力场的传统方法是将指定力场参数所需的所有信息编码为一组离散的原子类型。这相当于由一组顶点组成的分子图的表示，这些顶点表示按原子类型标记的原子，而未标记的边缘表示化学键。然后，通过在参数表中查找原子类型的成键对、三联体和四联体来分配价项，并使用原子类型本身来分配非成键参数，从而分配键的拉伸、角弯曲和二面体参数。这种方法（我们称之为间接化学感知，因为它在原子类型节点的中间图上操作）产生了许多技术问题。例如，原子类型必须足够复杂，以编码有关分子环境的所有必要信息，这使得很难扩展以这种方式编码的力场。原子类型化还会导致应用于化学等价的价项类的冗余参数激增，从而不必要地增加了力场的复杂性。在这里，我们描述了一种新的方法来分配力场参数项直接化学感知，避免了这些问题，称为SMIRKS原生开放力场（SMIRNOFF）格式。直接化学感知不是通过原子型图的中介来工作，而是直接在未修改的分子化学图上操作来分配参数。特别地，参数被分配到每种类型的力场项，例如：通过行业标准的SMARTS化学感知语言实现标准化学子结构查询，使用SMIRKS扩展，允许在化学模式中标记特定原子，从而实现键拉伸、角度弯曲、扭转和lennard - jones。我们使用特定分子的例子来展示这种方法的力量和通用性，这些分子会给间接化学感知带来问题，并构建和验证一个极简但非常通用的力场，smirnoff99frost。我们发现，只有300行左右长的参数定义文件提供了500万分子药物样测试集的所有覆盖率，但<0.02%。尽管简单，smirnoff99frost对于小分子水化自由能和纯有机液体的选定性质的准确性与通用琥珀力场（GAFF）相似，后者的规格需要数千个参数。该力场为后续的进一步优化和改装工作提供了一个起点。
Traditional approaches to specifying a molecular mechanics force field encode all the information needed to assign force field parameters to a given molecule into a discrete set of atom types. This is equivalent to a representation consisting of a molecular graph comprising a set of vertices, which represent atoms labeled by atom type, and unlabeled edges, which represent chemical bonds. Bond stretch, angle bend, and dihedral parameters are then assigned by looking up bonded pairs, triplets, and quartets of atom types in parameter tables to assign valence terms, and using the atom types themselves to assign nonbonded parameters. This approach, which we call indirect chemical perception because it operates on the intermediate graph of atom-typed nodes, creates a number of technical problems. For example, atom types must be sufficiently complex to encode all necessary information about the molecular environment, making it difficult to extend force fields encoded this way. Atom typing also results in a proliferation of redundant parameters applied to chemically equivalent classes of valence terms, needlessly increasing force field complexity. Here, we describe a new approach to assigning force field parameters terms direct chemical perception that avoids these problems, called the SMIRKS Native Open Force Field (SMIRNOFF) format. Rather than working through the intermediary of the atomtyped graph, direct chemical perception operates directly on the unmodified chemical graph of the molecule to assign parameters. In particular, parameters are assigned to each type of force field term—e.g., bond stretch, angle bend, torsion, and Lennard-Jones—based on standard chemical substructure queries implemented via the industry-standard SMARTS chemical perception language, using SMIRKS extensions that permit labeling of specific atoms within a chemical pattern. We demonstrate the power and generality of this approach using examples of specific molecules that pose problems for indirect chemical perception, and construct and validate a minimalist yet very general force field, SMIRNOFF99Frosst. We find that a parameter definition file only ~300 lines long provides coverage of all but <0.02% of a five million molecule drug-like test set. Despite its simplicity, the accuracy of SMIRNOFF99Frosst for small molecule hydration free energies and selected properties of pure organic liquids, is similar to that of the General Amber Force Field (GAFF), whose specification requires thousands of parameters. This force field provides a starting point for further optimization and refitting work to follow.
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影响因子：
5.5
作者：
Caleman, Carl;van Maaren, Paul J.;Hong, Minyan;Hub, Jochen S.;Costa, Luciano T.;van der Spoel, David
通讯作者：
van der Spoel, David
影响因子：
3.3
作者：
Beauchamp, Kyle A.;Behr, Julie M.;Chodera, John D.
通讯作者：
Chodera, John D.
影响因子：
4.3
作者：
Eastman P;Swails J;Chodera JD;McGibbon RT;Zhao Y;Beauchamp KA;Wang LP;Simmonett AC;Harrigan MP;Stern CD;Wiewiora RP;Brooks BR;Pande VS
通讯作者：
Pande VS
影响因子：
3.5
作者：
Bannan, Caitlin C.;Burley, Kalistyn H.;Chiu, Michael;Shirts, Michael R.;Gilson, Michael K.;Mobley, David L.
通讯作者：
Mobley, David L.
DOI：
10.1021/jp411529h
发表时间：
2014-06-19
期刊：
The journal of physical chemistry. B
影响因子：
--
作者：
Fennell CJ;Wymer KL;Mobley DL
通讯作者：
Mobley DL