Liliana Gallegos

Liliana Gallegos
Colorado State University | CSU · Department of Chemistry

About

8
Publications
370
Reads
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53
Citations
Citations since 2016
8 Research Items
53 Citations
201620172018201920202021202205101520253035
201620172018201920202021202205101520253035
201620172018201920202021202205101520253035
201620172018201920202021202205101520253035

Publications

Publications (8)
Article
Full-text available
The importance of modified peptides and proteins for applications in drug discovery, and for illuminating biological processes at the molecular level, is fueling a demand for efficient methods that facilitate the precise modification of these biomolecules. Herein, we describe the development of a photocatalytic method for the rapid and efficient di...
Article
We report that O-selective arylation of 2- and 4-pyridones with arylboronic acids is affected by a modular, bismacycle-based system. The utility of this umpolung approach to pyridyl ethers, which is complementary to conventional methods based on S N Ar or cross-coupling, is demonstrated through the concise synthesis of Ki6783 and picolinafen, and t...
Article
We report that O‐selective arylation of 2‐ and 4‐pyridones with arylboronic acids is affected by a modular, bismacycle‐based system. The utility of this umpolung approach to pyridyl ethers, which is complementary to conventional methods based on S N Ar or cross‐coupling, is demonstrated through the concise synthesis of Ki6783 and picolinafen, and t...
Article
The catalytic anti-Markovnikov addition of alcohols to simple alkenes is a longstanding synthetic challenge. We recently disclosed the use of organic superbase catalysis for the nucleophilic addition of alcohols to activated styrene derivatives. This article describes mechanistic studies on this reversible reaction, including thermodynamic and kine...
Article
Full-text available
From quantum chemical and experimental NMR data, a 3D graph neural network, CASCADE, has been developed to predict carbon and proton chemical shifts. Stereoisomers and conformers of organic molecules can be correctly distinguished.
Preprint
Full-text available
The computational prediction of NMR chemical shifts using quantum mechanical calculations is now commonplace in aiding organic structural assignment since spectra can be computed for several candidate structures and then compared with experimental values to find the best possible match. However, the computational demands of calculating multiple str...
Preprint
The computational prediction of NMR chemical shifts using quantum mechanical calculations is now commonplace in aiding organic structural assignment since spectra can be computed for several candidate structures and then compared with experimental values to find the best possible match. However, the computational demands of calculating multiple str...
Article
ConspectusMachine-readable chemical structure representations are foundational in all attempts to harness machine learning for the prediction of reactivities, selectivities, and chemical properties directly from molecular structure. The featurization of discrete chemical structures into a continuous vector space is a critical phase undertaken befor...

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