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Algorithms Mol Biol. 2019 Feb 5;14:1. doi: 10.1186/s13015-019-0138-7. eCollection 2019.

Automated partial atomic charge assignment for drug-like molecules: a fast knapsack approach.

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1Algorithmic Bioinformatics, Heinrich Heine University, Universitätsstr. 1, 40225 Düsseldorf, Germany.
2Life Sciences and Health Group, Centrum Wiskunde & Informatica, Science Park 123, 1098 XG Amsterdam, The Netherlands.
3School of Chemistry & Molecular Biosciences, The University of Queensland, Brisbane, QLD 4072 Australia.
4Netherlands eScience Center, Science Park 140, 1098 XG Amsterdam, The Netherlands.
5AIMMS Division of Molecular and Computational Toxicology, Vrije Universiteit, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands.


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.


Integer Linear Programming; Molecular dynamics simulations; Multiple-choice knapsack; Partial charge assignment; Pseudo-polynomial Dynamic Programming

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