Tools for Prediction of Alkyne p K a Values: Calculation of Hydrogen Exchange Barriers and NMR Chemical Shifts
- 1University of Zagreb , , Ante Kovačića 1 , ,
- 2University of Rijeka , , Radmile Matejčić 2 , ,
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.
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BibTeX
@article{ljulj2026tools,
title = {{Tools for Prediction of Alkyne p K a Values: Calculation of Hydrogen Exchange Barriers and NMR Chemical Shifts}},
author = {Antonio Ljulj and Lea Malezan and Maria Kolympadi Marković and Dean Marković and Davor Šakić and Valerije Vrček},
journal = {ACS Omega},
year = {2026},
month = nov,
doi = {10.1021/acsomega.6c05360},
url = {https://pubs.acs.org/acsodf/article/doi/10.1021/acsomega.6c05360/5462643/Tools-for-Prediction-of-Alkyne-pKa-Values},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Tools for Prediction of Alkyne p K a Values: Calculation of Hydrogen Exchange Barriers and NMR Chemical Shifts
AU - Antonio Ljulj
AU - Lea Malezan
AU - Maria Kolympadi Marković
AU - Dean Marković
AU - Davor Šakić
AU - Valerije Vrček
PY - 2026
DA - 2026/11/03
JO - ACS Omega
DO - 10.1021/acsomega.6c05360
UR - https://pubs.acs.org/acsodf/article/doi/10.1021/acsomega.6c05360/5462643/Tools-for-Prediction-of-Alkyne-pKa-Values
AB - 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.
SN - 2470-1343
ER -