Tools for Prediction of Alkyne p K a Values: Calculation of Hydrogen Exchange Barriers and NMR Chemical Shifts

Abstract Accurate prediction of acidity in terminal alkynes is critical for understanding their chemical behavior in isotope labeling, synthesis design, and drug development. In this study, we evaluate multiple quantum-chemical strategies to identify a reliable and simple computational approach for estimating alkyne acidities. A range of descriptors, including thermodynamic proton and hydrogen atom transfers, reaction energy profiles, vibrational and magnetic properties, and atomic charge distributions, were assessed across a representative set of alkynes. Only two approaches demonstrated predictive performance aligned with experimental data. The first involves calculation of energy barriers for hydrogen exchange, which shows a linear correlation with known pKa values and offers applicability across alkyl-, aryl-, and fluoro-substituted alkynes. The second leverages computed acetylenic proton chemical shifts, which provide valid predictions for a limited subset of alkynes. In contrast, descriptors such as IR frequencies, 13C NMR shifts, and atomic charges failed to yield accurate estimates. We extended our predictions to pharmaceuticals with terminal alkyne groups─such as ethynylestradiol, deprenyl, and 5-ethynyluracil─for which experimental acidity data are currently unavailable. The proposed workflow combines computational efficiency with mechanistic relevance and may serve as a practical tool for chemists seeking to assess the acid–base properties of terminal alkynes in silico.