Chemical Similarity Search

Chemical similarity search aims to rapidly identify molecules with similar properties within vast databases, a crucial task in drug discovery and materials science. Recent research emphasizes developing faster search algorithms, often employing low-dimensional molecular embeddings and efficient data structures like k-d trees, to overcome the computational limitations of traditional brute-force methods. Furthermore, research explores the use of transformer-based language models and prompt engineering techniques to capture functional similarity beyond simple structural comparisons, potentially uncovering novel molecules with desired properties. These advancements significantly accelerate the search process and broaden the scope of chemical similarity analysis, leading to more efficient drug design and materials development.