Being a computational research lab, we develop an increasingly diverse portfolio of software tools. On this page, you will find a selection of our most popular open source projects. For an exhaustive list, make sure to visit our GitHub organization!
- TeachOpenCADD for Jupyter · Jupyter notebooks on computer-aided drug design tasks using open resources
- TeachOpenCADD for KNIME · KNIME workflows on computer-aided drug design tasks using open resources
TeachOpenCADD is a teaching platform offering tutorials on central topics in cheminformatics and structural bioinformatics. The tutorials contain theoretical background and practical implementations using open source data and software. Implementations are available in two formats: Python-based Jupyter notebooks and GUI-based KNIME workflows.
In this project, we aim to combine structure-enabled machine learning and alchemical free energy calculations to develop a predictive quantitative model to rapidly assess kinase inhibitor affinity and selectivity, design ligands with desired selectivity profiles and assess the impact of clinical point mutations on inhibitor binding.
- KinFragLib · A kinase-focused fragment library
The KinFragLib project allows to explore and extend the chemical space of kinase inhibitors using data-driven fragmentation and recombination, built on available structural kinome data from the KLIFS database for over 2,500 kinase complexes. The computational fragmentation method splits known non-covalent kinase inhibitors into fragments with respect to their 3D proximity to six predefined subpockets relevant for binding.