The field of computational chemistry has seen a significant increase in the integration of
machine learning concepts and algorithms. In this Perspective, we surveyed 179 open …

Accurate prediction of micro-p K a values is crucial for understanding and modulating the
acidity and basicity of organic molecules, with applications in drug discovery, materials …

Accurately determining the global minima of a molecular structure is important in diverse
scientific fields, including drug design, materials science, and chemical synthesis …

Fragment growing is an important ligand design strategy in drug discovery. In this study, we
present FragGrow, a web server that facilitates structure-based drug design by fragment …

Guanidine-containing molecules are an interesting class of compounds within both
medicinal and material sciences. Having knowledge of their tautomerism is key in designing …

The rapid advancement of machine learning, particularly deep learning, has propelled
significant strides in drug discovery, offering novel methodologies for molecular property …

In the past, the discovery process of new materials was done mainly through trial and error,
which was time-consuming and expensive. However, computational simulations and models …