Transferable scoring function based on semiempirical quantum mechanical PM6-DH2 method: CDK2 with 15 structurally...

Area of Science:

• Computational Chemistry
• Drug Design
• Molecular Modeling

Background:

• Accurate scoring functions are crucial for predicting protein-ligand binding affinity in drug discovery.
• Existing methods often struggle to consistently capture key interactions like dispersion and hydrogen bonding.
• Cyclin-dependent kinase 2 (CDK2) inhibitors are important targets in cancer therapy.

Purpose of the Study:

• To develop and validate a novel scoring function for estimating binding free energy of CDK2 inhibitors.
• To assess the performance of the semiempirical PM6-DH2 quantum mechanical method in scoring diverse inhibitors.
• To compare the new scoring function with existing computational approaches.

Main Methods:

• Utilized the PM6-DH2 semiempirical quantum mechanical method to score fifteen diverse CDK2 inhibitors.
• Reoptimized complex geometries from X-ray structures in continuum water.
• Constructed a scoring function based on interaction enthalpy, entropy, and desolvation/deformation energy corrections.

Main Results:

• The PM6-DH2 method demonstrated accurate scoring, with the best correlation (r²=0.87) found for bare interaction enthalpy.
• Interaction enthalpy corrected for desolvation and deformation energies also showed good correlation (r²=0.77).
• The developed scoring function outperformed previously published methods, though robustness is limited by data size.

Conclusions:

• The PM6-DH2-based scoring function provides a thermodynamically sound and parameter-free approach for estimating binding free energy.
• This method shows potential for ranking diverse protein-ligand complexes in drug design, as suggested by similar results for HIV-1 protease.
• Further validation with larger datasets is recommended to confirm the robustness and broad applicability of the scoring function.