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

Area of Science:

• Computational chemistry
• Cheminformatics
• Drug design

Background:

• Accurate description of intermolecular interactions is vital for computational drug design.
• Assigning partial atomic charges is a critical step in molecular modeling.
• Existing methods can be time-consuming and computationally intensive.

Purpose of the Study:

• To develop an efficient, reliable, and automated procedure for assigning partial atomic charges.
• To address the molecular charge assignment problem using database distributions.
• To reduce the computational time for charge calculations in drug design.

Main Methods:

• Formal introduction of the molecular charge assignment problem.
• Utilizing a database of parameterized molecules and their chemical environments.
• Applying Integer Linear Programming and Dynamic Programming algorithms.
• Solving a variant of the multiple-choice knapsack problem.

Main Results:

• Developed a procedure for efficient and automatic partial atomic charge assignment.
• Demonstrated comparable accuracy to explicit charge calculations for novel molecules.
• Reduced charge determination time from hours/days to under a second.
• The problem is shown to be weakly NP-complete.

Conclusions:

• The proposed method offers a significant speed-up for partial atomic charge assignment.
• This automation enhances the reliability and efficiency of computational drug design workflows.
• Openly available software facilitates broader adoption and application.