Density Functional Theory and Its Applications

This chapter discusses the role of density functional theory (DFT) as a quantum mechanical approach in computer-aided drug design. Rapid hardware advances coupled with robust functionals, especially the hybrid B3LYP, have made DFT practical for the routine evaluation of geometry, energetics, and electronic properties at near-chemical accuracy. This chapter compares DFT with Hartree–Fock (HF) and costly post-HF methods, highlighting how explicit treatment of electron correlation enables reliable prediction of bond lengths, conformational energies, ionization potentials, and non-covalent binding energies within 1–2 kcal/mol. Case studies illustrate the translation of these calculations to modeling drug–receptor interactions, metal–ligand coordination, and protein secondary structure stabilization. A catalogue of open-source and commercial packages—Gaussian, ORCA, Q-Chem, CP2K, PSI4, and others—demonstrates the breadth of the available platforms, each optimized for specific system sizes or time-dependent phenomena. Practical guidelines are provided for selecting functionals, interpreting highest occupied molecular orbital/lowest unoccupied molecular orbital (HOMO/LUMO) gaps, and integrating DFT outputs with quantitative structure–activity relationship (QSAR) or machine learning pipelines. Limitations such as basis set dependence, dispersion treatment, and computational cost scaling are also examined, alongside emerging linear scaling algorithms and GPU acceleration that progressively extend DFT’s applicability to thousand-atom biomolecular systems.