An Assessment of Dispersion-Corrected DFT Methods for Modeling Nonbonded Interactions in Protein Kinase Inhibitor...

Area of Science:

• Computational chemistry
• Drug discovery
• Structural biology

Background:

• Accurate modeling of nonbonded interactions between protein kinases and inhibitors is crucial for structure-based drug design.
• Density functional theory (DFT) methods are promising for quantifying these protein-ligand interactions, but accuracy varies with functionals and basis sets.

Purpose of the Study:

• To benchmark nine widely used DFT methods for modeling nonbonded interactions in protein kinase inhibitors.
• To identify an optimal DFT approach balancing accuracy and computational efficiency.

Main Methods:

• Benchmarking of nine DFT functionals (BLYP, TPSS, B97, ωB97X, B3LYP, M062X, PW6B95, B2PLYP, PWPB95) with D3BJ dispersion correction and def2-SVP, def2-TZVP, def2-QZVP basis sets.
• Calculation of nonbonded interaction energies for 49 motifs from 2139 kinase-inhibitor structures at the CCSD(T)/CBS level of theory as reference.
• Application of RI, RIJK, and RIJCOSX approximations for selected functionals.

Main Results:

• B3LYP/def2-TZVP and RIJK RI-B2PLYP/def2-QZVP methods demonstrated the best performance.
• These methods provide an optimal combination of accuracy and computational efficiency for modeling nonbonded interactions.

Conclusions:

• B3LYP/def2-TZVP and RIJK RI-B2PLYP/def2-QZVP are well-suited for efficient modeling of nonbonded interactions in protein kinase inhibitor recognition.
• This study provides guidance for selecting appropriate DFT methods in structure-based drug design.