A key factor in computational drug design is the consistency and reliability with which intermolecular interactions between a wide variety of molecules can be described. Here we present a procedure to efficiently, reliably and automatically assign partial atomic charges to atoms based on known distributions. We formally introduce the molecular charge assignment problem, where the task is to select a charge from a set of candidate charges for every atom of a given query molecule. Charges are accompanied by a score that depends on their observed frequency in similar neighbourhoods (chemical environments) in a database of previously parameterised molecules. The aim is to assign the charges such that the total charge equals a known target charge within a margin of error while maximizing the sum of the charge scores. We show that the problem is a variant of the well-studied multiple-choice knapsack problem and thus weakly NP -complete. We propose solutions based on Integer Linear Programming and a pseudo-polynomial time Dynamic Programming algorithm. We demonstrate that the results obtained for novel molecules not included in the database are comparable to the ones obtained performing explicit charge calculations while decreasing the time to determine partial charges for a molecule from hours or even days to below a second. Our software is openly available.

中文翻译：

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药物类分子的自动部分原子电荷分配：快速背包方法。

计算药物设计中的一个关键因素是一致性和可靠性，可以用来描述各种分子之间的分子间相互作用。在这里，我们提出一种程序，可以根据已知分布有效，可靠和自动地将部分原子电荷分配给原子。我们正式介绍分子电荷分配问题，其中的任务是为给定查询分子的每个原子从一组候选电荷中选择一个电荷。电荷伴随着一个分数，该分数取决于它们在先前参数化的分子的数据库中在相似邻域（化学环境）中观察到的频率。目的是分配电荷，以使总电荷等于误差范围内的已知目标电荷，同时使电荷得分的总和最大化。我们表明，该问题是经过充分研究的多项选择背包问题的变体，因此NP弱。我们提出了基于整数线性规划和伪多项式时间动态规划算法的解决方案。我们证明，未包含在数据库中的新型分子所获得的结果与执行显式电荷计算所获得的结果具有可比性，同时将确定分子的部分电荷的时间从数小时甚至数天缩短至一秒以下。我们的软件是公开可用的。我们证明，未包含在数据库中的新型分子所获得的结果与执行显式电荷计算所获得的结果具有可比性，同时将确定分子的部分电荷的时间从数小时甚至数天缩短至一秒以下。我们的软件是公开可用的。我们证明，未包含在数据库中的新型分子所获得的结果与执行显式电荷计算所获得的结果具有可比性，同时将确定分子的部分电荷的时间从数小时甚至数天缩短至一秒以下。我们的软件是公开可用的。