AIMSim: An Accessible Cheminformatics Platform for Similarity Operations on Chemicals Datasets [post]

Himaghna Bhattacharjee, Jackson Burns, Dionisios Vlachos
2022 unpublished
The recent advances in deep learning, generative modeling, and statistical learning have ushered in a renewed interest in traditional cheminformatics tools and methods. Quantifying molecular similarity is essential in molecular generative modeling, exploratory molecular synthesis campaigns, and drug-discovery applications to assess how new molecules differ from existing ones. Most tools target advanced users and lack general implementations accessible to the larger community. In this work, we
more » ... troduce Artificial Intelligence Molecular Similarity (AIMSim), an accessible cheminformatics platform for performing similarity operations on collections of molecules called molecular datasets. AIMSim provides a unified platform to perform similarity-based tasks on molecular datasets, such as diversity quantification, outlier and novelty analysis, clustering, dimensionality reduction, and inter-molecular comparisons. AIMSim implements all major binary similarity metrics and molecular fingerprints and is provided as a Python package that includes support for command-line use as well as a fully functional Graphical User Interface for code-free utilization with fully interactive plots.
doi:10.26434/chemrxiv-2022-nw6f5-v5 fatcat:ntpwimor2jd7fmfxdseoxcukv4