Modelling the Correlation Between Molecular Electrostatic Potential and pKa on Sets of Carboxylic Acids, Phenols and Anilines

Pd-Catalyzed intermolecular C-H bond arylation reactions: effect of bulkiness of carboxylate ligands

A bulky carboxylic acid bearing one 1-adamantylmethyl and two methyl substituents at the α-position is demonstrated to work as an efficient carboxylate ligand source in Pd-catalyzed intermolecular C(sp²)-H bond arylation reactions. The reactions proceeded smoothly under mild conditions, taking advantage of the steric bulk of the carboxylate ligands.

Practical High-Quality Electrostatic Potential Surfaces for Drug Discovery Using a Graph-Convolutional Deep Neural Network

Inspecting protein and ligand electrostatic potential (ESP) surfaces in order to optimize electrostatic complementarity is a key activity in drug design. These ESP surfaces need to reflect the true electrostatic nature of the molecules, which typically means time-consuming high-level quantum mechanics (QM) calculations are required. For interactive design much faster alternative methods are required. Here, we present a graph convolutional deep neural network (DNN) model, trained on ESP surfaces derived from high quality QM calculations, that generates ESP surfaces for ligands in a fraction of a second. Additionally, we describe a method for constructing fast QM-trained ESP surfaces for proteins. We show that the DNN model generates ESP surfaces that are in good agreement with QM and that the ESP values correlate well with experimental properties relevant to medicinal chemistry. We believe that these high-quality, interactive ESP surfaces form a powerful tool for driving drug discovery programs forward. The trained model and associated code are available from https://github.com/AstexUK/ESP_DNN.

Calculation of VS,max and Its Use as a Descriptor for the Theoretical Calculation of pKa Values for Carboxylic Acids

The theoretical calculation of pKa values for Brønsted acids is a challenging task that involves sophisticated and time-consuming methods. Therefore, heuristic approaches are efficient and appealing methodologies to approximate these values. Herein, we used the maximum surface electrostatic potential (V_S,max) on the acidic hydrogen atoms of carboxylic acids to describe the H-bond interaction with water (the same descriptor that is used to characterize σ-bonded complexes) and correlate the results with experimental pKa values to obtain a predictive model for other carboxylic acids. We benchmarked six different methods, all including an implicit solvation model (water): Five density functionals and the Møller–Plesset second order perturbation theory in combination with six different basis sets for a total of thirty-six levels of theory. The ωB97X-D/cc-pVDZ level of theory stood out as the best one for consistently reproducing the reported pKa values, with a predictive power of 98% correlation in a test set of ten other carboxylic acids.

Steric Effect of Carboxylate Ligands on Pd-Catalyzed Intramolecular C(sp2 )-H and C(sp3 )-H Arylation Reactions

A bulky carboxylic acid bearing three cyclohexylmethyl substituents at the α-position, namely, tri(cyclohexylmethyl)acetic acid, is demonstrated to act as an efficient ligand source in Pd-catalyzed intramolecular C(sp² )-H and C(sp³ )-H arylation reactions. The reactions proceed smoothly under mild reaction conditions, even at room temperature due to the steric bulk of the carboxylate ligands, which accelerates the rate-determining C-H bond activation step in the catalytic cycle.