Ligand-Binding Affinity Estimates Supported by Quantum-Mechanical Methods | JoVE Visualize

Area of Science:

Computational chemistry
Drug discovery
Molecular modeling

Background:

Accurate calculation of binding free energies for small molecules to macromolecules is a significant challenge in computational chemistry.
Standard molecular mechanics force fields often lack the required accuracy for these predictions.
Quantum-mechanical (QM) methods offer a promising avenue for improving the accuracy of binding affinity estimates.

Purpose of the Study:

To review various approaches that utilize explicit quantum-mechanical (QM) energies for calculating binding affinities.
To focus on the methodologies rather than specific applications in drug development.
To highlight the advancements and considerations in applying QM methods to receptor-ligand binding.

Main Methods:

Exploration of diverse QM methods, including semiempirical calculations, density-functional theory, and coupled-cluster methods.
Discussion of the necessity for dispersion and empirical corrections in approximate QM methods.
Consideration of basis set requirements for high-level QM calculations.
Analysis of different QM/MM (Quantum Mechanics/Molecular Mechanics) embedding strategies, varying the size of the QM region from the ligand alone to the entire complex.
Review of simulation approaches, such as minimized structures, end-state simulations, and full free-energy simulations.

Main Results:

Various QM methods, from semiempirical to coupled-cluster, have been applied to binding affinity calculations.
Empirical corrections and large basis sets are essential for achieving accurate results with approximate and high-level QM methods, respectively.
Different QM embedding strategies, including focusing QM on the ligand, nearby groups, or the entire complex (up to 1000 atoms), have been tested.
Effective QM embedding may only require including atoms within approximately 6 Å of the ligand.
All tested simulation approaches, including minimized structures, end-state, and free-energy simulations, have been evaluated.

Conclusions:

Quantum-mechanical methods, when properly applied with necessary corrections and appropriate embedding strategies, can significantly improve the accuracy of binding free energy calculations compared to traditional molecular mechanics.
The choice of QM method, basis set, and the extent of QM/MM embedding are critical factors influencing the accuracy and computational cost.
Further development and application of these QM-based approaches hold great potential for accelerating drug discovery and development by providing more reliable predictions of molecular interactions.