Model for the fast estimation of basis set superposition error in biomolecular systems

Area of Science:

• Computational chemistry
• Quantum mechanics
• Biomolecular modeling

Background:

• Basis set superposition error (BSSE) is a major source of inaccuracy in quantum chemical energy calculations.
• This error is particularly pronounced in large, complex systems like proteins and protein-ligand complexes.
• Existing methods for correcting intramolecular BSSE are computationally expensive, requiring numerous additional quantum calculations.

Purpose of the Study:

• To develop a computationally efficient method for estimating both intermolecular and intramolecular Basis set superposition error (BSSE).
• To reduce the computational cost associated with correcting BSSE in large biomolecular systems.
• To provide a rapid assessment of BSSE magnitudes without performing additional quantum computations.

Main Methods:

• Systematically dividing complex molecules into interacting fragments.
• Employing a statistical model to estimate the contribution of each fragment to the overall BSSE.
• Propagating fragment-wise BSSE estimates throughout the entire molecular system.
• Analyzing the interacting fragments within the system to predict BSSE.

Main Results:

• The proposed method accurately estimates BSSE magnitudes for various molecular systems.
• The approach was successfully applied to protein-ligand complexes, helical proteins, and protein folds.
• The method significantly reduces the computational overhead compared to traditional counterpoise correction techniques.

Conclusions:

• A novel, computationally inexpensive statistical method for estimating BSSE has been developed.
• This approach offers a rapid and effective way to account for BSSE in large biomolecular systems.
• The findings have significant implications for improving the accuracy of quantum-based energy functions in drug discovery and structural biology.