Predicting pK _a of flexible polybasic tetra-aza macrocycles

Area of Science:

• Computational chemistry
• Physical organic chemistry

Background:

• Tetra-aza macrocycles are flexible, polybasic molecules.
• Their complex electronic structures and tautomerism pose challenges for accurate pKa prediction.

Purpose of the Study:

• To develop and validate a physics-based computational protocol for predicting the acidity constants (pKa) of tetra-aza macrocycles.
• To apply this protocol to predict pKa values for novel tetra-aza macrocycles.

Main Methods:

• Conformational sampling using CREST/xTB.
• Density functional theory (DFT) calculations with continuum solvent refinement.
• Linear empirical correction (LEC) for pKa prediction.

Main Results:

• The computational protocol achieved a root-mean-square deviation of 1.2 log units for known tetra-aza macrocycle pKa values.
• The method accurately predicted the most stable protomers across a range of pH conditions.
• Predicted pKa values for four new tetra-aza macrocycles were generated.

Conclusions:

• The presented physics-based protocol offers a reliable method for predicting pKa values of tetra-aza macrocycles.
• This work provides valuable insights into the acid-base properties of these molecules.
• The predictions serve as a guide for the synthesis and experimental investigation of novel tetra-aza macrocycles.