Efficient evaluation of electrostatic potential with computerized optimized code.

Area of Science:

• Computational Chemistry
• Quantum Chemistry
• Molecular Modeling

Background:

• Evaluating molecular electrostatic potential (ESP) is computationally intensive, hindering tasks like charge fitting and QM/MM simulations.
• Existing methods face performance bottlenecks, especially for large molecular systems.

Purpose of the Study:

• To develop and present an efficient algorithm for calculating molecular electrostatic potential (ESP).
• To improve the performance of computational chemical tasks reliant on ESP evaluation.

Main Methods:

• Developed a novel algorithm that regroups ESP calculation terms based on Gaussian type orbitals (GTOs) and nuclear centers.
• Implemented the algorithm within the Multiwfn software package.
• Tested the algorithm's performance on diverse systems, including small molecules (dopamine, remdesivir) and a large metal-organic framework (MOF-5).

Main Results:

• The new algorithm demonstrated performance comparable to or exceeding state-of-the-art codes for dopamine and remdesivir.
• For a large MOF-5 system, the evaluation was completed in 1874 seconds on standard hardware.
• The algorithm shows excellent parallelization scaling, indicating efficiency on multi-core systems.

Conclusions:

• The proposed efficient ESP evaluation algorithm significantly reduces computational bottlenecks.
• The freely available source code offers a valuable tool for computational chemists, enhancing simulation efficiency.
• This advancement supports more complex and larger-scale molecular simulations in computational chemistry.