Joined March 2021
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We're happy to be the #ChemSciPicks of week from @ChemicalScience
This week's #ChemSciPicks comes from Sereina Riniker (@rinikerlab) at ETH Zürich (@ETH_DCHAB) and looks at a general graph neural network based implicit solvation model for organic molecules in water. Read it here: doi.org/10.1039/D4SC02432J
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Our latest preprint introduces and validates a new hybrid classical/ML force field for working with condensed phase systems. It's now up on arXiv: arxiv.org/abs/2308.08984

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We are really happy to announce that @linker_phi's paper on membrane permeability of cyclic peptides has won the @RoySocChem's Outstanding Student Paper award in computational and theoretical chemistry for 2022!
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Our most recent preprint shares an efficient approach for assigning partial charges to atoms in molecules. The method uses a hierarchy created from attention values from a GNN trained on QM data. arxiv.org/abs/2305.15981 It's all #opensource and #opendata, of course.
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Our second paper that came out today describes @AnnaKamenik's collaboration with the Zenobi group combining experimental and computational techniques to help understand the structures of peptides in the gas phase. nature.com/articles/s41467-0…

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In our most recent publication we use a graph neural network to develop a model for implicit solvation in molecular dynamics simulations of peptides. The code is open source and the model is freely downloadable. pubs.aip.org/aip/jcp/article…
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Escape from the curse of dimensionality: Our newest preprint introduces an energy-based clustering algorithm that allows you to avoid common problems with estimated densities. The code is, of course, #opensource arxiv.org/abs/2303.01104 github.com/rinikerlab/Energy…

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Do you want a small sneak peak? Here is an unbiased MD simulation of a cyclic peptide crossing the membrane
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We are very happy to be starting this multi-year project with our collaborators at @NovartisScience.
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Congratulations to Sereina Riniker @rinikerlab who is among the recipients of the 2022 NIBR Global Scholars Program @NovartisScience !Each Scholar will receive up to 1 mil USD funding over 3 years along with drug-hunting expertise from #NIBR collaborators. novartis.com/research-develo…
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Great teamwork and discussions with academic and industry colleagues lead to this perspective looking at machine learning for small-molecule drug discovery. sciencedirect.com/science/ar…

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Hot off the press. We improved our IR spectra alignment algorithm that helps you determining the relative stereochemistry of organic molecules. It compares theoretical and experimental IR spectra of all isomers and finds the best match. Check it out here: pubs.rsc.org/en/content/arti…
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