AIMS: Artificial Intelligence for Molecular Sciences
The material world is made of atoms and molecules. Hence, the study of molecules, or molecular sciences, is fundamentally important. The application of molecular sciences has been driving the progress of almost every field in natural science. In the past few decades, data and computation have become a powerful engine (known as in silico) for advancing molecular sciences. AIMS is IFI's innovative Web-based software solution that aims at the strategic intersection between artificial intelligence and molecular sciences or, in layman's terms, to connect bits and atoms. AIMS currently supports two types of projects, introduced as follows. Molecular ModelingInteractive molecular dynamics allows users to design and perform computational experiments to test their own hypotheses. Play with a molecular dynamics simulation below to experience the power of computation in the browser! Live model above (view in full screen) — Chrome or Edge recommended With the visual analytics supported by techniques such as brushing and linking built in AIMS, users can explore quantitative structure–activity/property relationships (QSAR/QSPR) of molecules that they have collected. A well-known QSPR is the relationship between the boiling points and the carbon atom counts of alkanes (see this case study based on AIMS). Drug DiscoverySmall molecules represent an important type of drugs — 90% of all drugs sold on the global market are small molecules. The following example shows the process of screening an inhibitor to an HIV protease from a collection of small molecules using AIMS. Interactive molecular docking, currently under development, will allow users to validate a candidate molecule selected based on data science principles. For example, Lipinski's Rule of Five is implemented in AIMS as filters in the hyperspace of molecular properties as shown below. Live model above (view in full screen) — Chrome or Edge recommended |
Entrance
Tutorials
Features
Molecular dynamics
Taming chemical data
Adventure in Drug Discovery
Privacy Policy
This project is supported by the National Institutes of Health (NIH) under grant number R25GM150143 and the National Science Foundation (NSF) under grant number #2300976 Any opinions, findings, and conclusions or recommendations expressed in this material, however, are those of the authors and do not necessarily reflect the views of NIH and NSF. We thank EPAM Systems for providing the open-source Miew molecular viewer.
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