Our collaborative work with the BfR - combining in vitro with in silico predictions - is now published in the Environment International Journal:
“Quantitative high-throughput phenotypic screening for environmental estrogens using the E-Morph Screening Assay in combination with in silico predictions”
(DOI: 10.1016/j.envint.2021.106947).
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Have a look at our PLIPify work (WIP)!
PLIPify provides a wrapper around PLIP, which allows to digest multiple structures at once, performs the mapping of the individual profiles to fingerprints and reports protein-ligand interaction frequencies.
It has recently been applied to detect the main interaction within a set of roughly 400 MPro complex structures (large crystal-based fragment screen by Diamond Light Source) in the broader scope of the COVID Moonshot initiative.
Check out the results in the latest COVID Moonshot preprint: “Open Science Discovery of Oral Non-Covalent SARS-CoV-2 Main Protease Inhibitor Therapeutics” (DOI: 10.1101/2020.10.29.339317v2).
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Save the date (Thu. 9. September 2021, 4pm - 5:30pm CET) for an upcoming virtual seminar series, Digital Science for Drug Discovery.
Focused on the Berlin region, the series aims to facilitate and enmesh relationships between researchers working within both academia and industry. The over-arching theme? Making efficient and creative use of the wealth of available and growing chemical and biological data combined with powerful computational means at our disposal.
Confirmed speakers for the next series include Dr. Mohammed AlQuraishi of Columbia University and Dr. Patrick Walters of Relay Therapeutics.
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Interested in the new developments of deep learning in virtual screening ? Check out our review Kimber, 2021.
We discuss
- ligand, protein and complex encodings,
- deep learning models,
- data sets, and
- recent studies.
If you want to generate different encodings for your figures, have a look at the GitHub repository!
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The new edition of the “Structural Alignment and Superposition” internship is now open for registration!
In this internship, an open-source structural alignment Python package for biopolymers, i.e. proteins and ligands, that we started implementing in 2020 will be further developed and released. While diverse structural alignment implementations can be found in visualization software such as PyMol, VMD or UCSF Chimera, a standalone package is currently missing in the Python ecosystem. We have started filling that gap with a modern Python package designed under the current best practices for development, testing and deployment.
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Our KinFragLib project is now published in the Journal of Chemical Modeling
and Information:
“KinFragLib: Exploring the Kinase Inhibitor Space Using Subpocket-Focused
Fragmentation and Recombination”
(DOI: 10.1021/acs.jcim.0c00839).
Kinases are one of the most studied drug targets, resulting in an amount of
available data too large to be analyzed manually. In the KinFragLib project,
a precise cartography of the ATP-binding site guides the fragmentation of
cocrystallized kinase ligands by subpockets.
The resulting kinase-focused fragment library allows the analysis of the
chemical space by subpocket and is a rich source of inspiration for building
novel kinase inhibitors.
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We are happy to present the results of our KinFragLib project. Aiming to explore and extend the chemical space of kinase inhibitors, we propose a novel subpocket-guided fragmentation and recombination strategy.
Take a look at our preprint on ChemRxiv to find our more:
“KinFragLib: Exploring the kinase inhibitor space using subpocket-focused fragmentation and recombination”. You can find the reported fragment and combinatorial libraries including all analyses notebooks on our GitHub repository.
Thanks to all co-authors for working together on this project with such enthusiasm: Dominique Sydow, Paula Schmiel, Jérémie Mortier, and Andrea Volkamer.
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For obvious reasons, this edition will be online. It will take place on 2020.07.23. Check the struc2drug section for more details!
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We have been working on our new website for a few months and we can finally say that we are happy to announce we are going live! Special thanks to Jaime Rodríguez-Guerra for putting this together!
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Join us in our collective effort to better understand CoViD-19.
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