At the American Chemical Society Spring National Meeting & Expo, Atomwise members were selected to present their research and work. Learn what our Atoms have been working on below and visit Atomwise at ACS Fall 2022 National Meeting for other presentation sessions.  ..read more

At the American Chemical Society Fall 2022 National Meeting & Expo, Atomwise members were selected to present their research and work. Learn what our Atoms have been working on below and visit Atomwise at ACS Fall 2022 National Meeting for other presentation sessions.  ..read more

Atomwise scientists are using machine learning to help University of Alberta researchers find compounds that have the potential to regrow damaged nerves. Nerve damage is a common problem following injury in neurological disorders, but regrowing damaged nerves is difficult — especially if the underlying condition has been around for a long time. Even if the underlying disease is curable, nerve damage can still persist ..read more

Our scientists developed AtomNet® PoseRanker to improve our technology’s ability to rank poses for protein-ligand interactions with potential drug compounds Identifying the highest-quality protein-ligand poses generated from structure-based virtual high-throughput screening (vHTS) approaches is a major challenge for drug discovery. These methods typically use a physics-based scoring function to generate ranked lists of plausible poses, which are models of physical interactions between small molecules and protein targets. They are often effective at suggesting good poses, but the best ones are ..read more

Our scientists have developed a set of chemical benchmarks to better understand exactly what our computational models are learning. At Atomwise, AtomNet® structure-based models can quickly identify active compounds for protein targets from large chemical libraries for drug discovery projects. Understanding how models recognize features of molecular activity can shed light on, for example, important receptor-ligand interactions, biases toward particular functional groups, or target selectivity of compounds. However, it is still challenging to understand exactly what deep learning models are pi ..read more

At the American Chemical Society Spring National Meeting & Expo, Atomwise members were selected to present their research and work. Learn what our Atoms have been working on below and visit Atomwise at ACS Spring 2022 National Meeting for other presentation sessions.  ..read more

 Atomwise scientists are adapting machine learning models to make predictions about a class of drug compounds that has been challenging to study ..read more

At the American Chemical Society Spring National Meeting & Expo, Atomwise members were selected to present their research and work. Learn what our Atoms have been working on below and visit Atomwise at ACS Spring 2022 National Meeting for other presentation sessions.  ..read more

At the American Chemical Society Spring National Meeting & Expo, Atomwise members were selected to present their research and work. Learn what our Atoms have been working on below and visit Atomwise at ACS Spring 2022 National Meeting for other presentation sessions.  ..read more