Introducing KICK-MEP: exploring potential energy surfaces in systems with significant non-covalent interactions

Area of Science:

• Computational Chemistry
• Theoretical Chemistry
• Molecular Modeling

Background:

• Exploring potential energy surfaces (PES) is crucial for understanding molecular energy, geometry, and reactivity.
• Non-covalent interactions significantly influence the PES of atomic and molecular clusters.
• Accurate identification of low-energy structures is essential for predicting molecular behavior.

Purpose of the Study:

• Introduce Kick-MEP, a hybrid computational method for efficient PES exploration.
• Develop a method to estimate interaction energies and identify low-energy configurations at reduced cost.
• Validate Kick-MEP's effectiveness across diverse molecular systems.

Main Methods:

• Kick-MEP utilizes a stochastic Kick algorithm to generate initial molecular structures.
• It computes the Coulomb integral between maximum and minimum molecular electrostatic potential (MEP) values on an electron density isosurface.
• Selected low-energy structures are refined using gradient-based optimization and DFT calculations (PBE0-D3/Def2-TZVP).

Main Results:

• Kick-MEP successfully identified the lowest energy structures, including global minima, in silicon-lithium clusters, water clusters, and a thymol-Cucurbit[7]uril complex.
• The method demonstrated efficiency in estimating interaction energies and selecting relevant configurations.
• Benchmarking with molecular docking confirmed Kick-MEP's reliability.

Conclusions:

• Kick-MEP provides an efficient and accurate approach for exploring potential energy surfaces.
• The method is particularly effective for systems dominated by non-covalent interactions.
• Kick-MEP facilitates the discovery of global and local minima in molecular clusters.