Molecular Structure

Molecular structure research focuses on understanding and manipulating the arrangement of atoms within molecules, primarily to design molecules with specific properties for applications like drug discovery and materials science. Current research heavily utilizes machine learning, employing architectures like transformers, convolutional neural networks, and generative flow networks to predict molecular structures from spectral data, generate novel molecules, and optimize existing ones based on desired properties. These advancements are significantly impacting chemical and biological sciences by accelerating the design and discovery of new molecules, improving the efficiency of experimental workflows, and providing deeper insights into structure-property relationships.