Conformational Preferences and Benchmarking of Computational Methods for Piperazine-Based Ligands.

Area of Science:

• Computational Chemistry
• Medicinal Chemistry
• Drug Design

Background:

• Piperazine scaffolds are vital in drug discovery.
• Their conformational preferences and computational modeling are not well understood.

Purpose of the Study:

• To systematically benchmark computational methods for piperazine conformation.
• To provide guidance for modeling piperazine-containing ligands.

Main Methods:

• Systematic benchmark of N-phenylpiperazine and derivatives.
• Used DLPNO-CCSD-(T)/CBS-(3,4) as reference energies.
• Evaluated semiempirical, MP2, and various DFT functionals.

Main Results:

• Identified two dominant orientations (straight, bent) and three pucker preferences (chair, boat, twisted-boat).
• Chair conformation is strongly favored across experimental and computational data.
• M06-2X/cc-pVDZ (DFT) showed best accuracy/efficiency (MAE < 0.5 kcal/mol); MP2/cc-pVDZ is a viable ab initio option.

Conclusions:

• Modern DFT functionals provide accurate and efficient modeling of piperazine conformations.
• Established a transferable benchmarking framework for conformational studies of drug-like molecules.