Chemical Structure

Chemical structure research focuses on representing and understanding the arrangement of atoms in molecules and materials to predict their properties and design new compounds. Current efforts leverage graph-theoretic descriptors, graph neural networks (GNNs), and other machine learning models like linear regression and convolutional neural networks (CNNs) to analyze these structures, often incorporating 3D representations for enhanced accuracy. This work is crucial for accelerating drug discovery, materials science, and nanotoxicology by enabling faster, more accurate prediction of physicochemical properties and facilitating the design of molecules with desired characteristics, reducing reliance on expensive and time-consuming experimental methods.